2019-05-19 20:08:55 +08:00
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// SPDX-License-Identifier: GPL-2.0-only
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2005-04-17 06:20:36 +08:00
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/*
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* mm/readahead.c - address_space-level file readahead.
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*
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* Copyright (C) 2002, Linus Torvalds
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*
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2008-10-16 13:01:59 +08:00
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* 09Apr2002 Andrew Morton
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2005-04-17 06:20:36 +08:00
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* Initial version.
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*/
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#include <linux/kernel.h>
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2016-08-26 06:17:17 +08:00
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#include <linux/dax.h>
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include cleanup: Update gfp.h and slab.h includes to prepare for breaking implicit slab.h inclusion from percpu.h
percpu.h is included by sched.h and module.h and thus ends up being
included when building most .c files. percpu.h includes slab.h which
in turn includes gfp.h making everything defined by the two files
universally available and complicating inclusion dependencies.
percpu.h -> slab.h dependency is about to be removed. Prepare for
this change by updating users of gfp and slab facilities include those
headers directly instead of assuming availability. As this conversion
needs to touch large number of source files, the following script is
used as the basis of conversion.
http://userweb.kernel.org/~tj/misc/slabh-sweep.py
The script does the followings.
* Scan files for gfp and slab usages and update includes such that
only the necessary includes are there. ie. if only gfp is used,
gfp.h, if slab is used, slab.h.
* When the script inserts a new include, it looks at the include
blocks and try to put the new include such that its order conforms
to its surrounding. It's put in the include block which contains
core kernel includes, in the same order that the rest are ordered -
alphabetical, Christmas tree, rev-Xmas-tree or at the end if there
doesn't seem to be any matching order.
* If the script can't find a place to put a new include (mostly
because the file doesn't have fitting include block), it prints out
an error message indicating which .h file needs to be added to the
file.
The conversion was done in the following steps.
1. The initial automatic conversion of all .c files updated slightly
over 4000 files, deleting around 700 includes and adding ~480 gfp.h
and ~3000 slab.h inclusions. The script emitted errors for ~400
files.
2. Each error was manually checked. Some didn't need the inclusion,
some needed manual addition while adding it to implementation .h or
embedding .c file was more appropriate for others. This step added
inclusions to around 150 files.
3. The script was run again and the output was compared to the edits
from #2 to make sure no file was left behind.
4. Several build tests were done and a couple of problems were fixed.
e.g. lib/decompress_*.c used malloc/free() wrappers around slab
APIs requiring slab.h to be added manually.
5. The script was run on all .h files but without automatically
editing them as sprinkling gfp.h and slab.h inclusions around .h
files could easily lead to inclusion dependency hell. Most gfp.h
inclusion directives were ignored as stuff from gfp.h was usually
wildly available and often used in preprocessor macros. Each
slab.h inclusion directive was examined and added manually as
necessary.
6. percpu.h was updated not to include slab.h.
7. Build test were done on the following configurations and failures
were fixed. CONFIG_GCOV_KERNEL was turned off for all tests (as my
distributed build env didn't work with gcov compiles) and a few
more options had to be turned off depending on archs to make things
build (like ipr on powerpc/64 which failed due to missing writeq).
* x86 and x86_64 UP and SMP allmodconfig and a custom test config.
* powerpc and powerpc64 SMP allmodconfig
* sparc and sparc64 SMP allmodconfig
* ia64 SMP allmodconfig
* s390 SMP allmodconfig
* alpha SMP allmodconfig
* um on x86_64 SMP allmodconfig
8. percpu.h modifications were reverted so that it could be applied as
a separate patch and serve as bisection point.
Given the fact that I had only a couple of failures from tests on step
6, I'm fairly confident about the coverage of this conversion patch.
If there is a breakage, it's likely to be something in one of the arch
headers which should be easily discoverable easily on most builds of
the specific arch.
Signed-off-by: Tejun Heo <tj@kernel.org>
Guess-its-ok-by: Christoph Lameter <cl@linux-foundation.org>
Cc: Ingo Molnar <mingo@redhat.com>
Cc: Lee Schermerhorn <Lee.Schermerhorn@hp.com>
2010-03-24 16:04:11 +08:00
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#include <linux/gfp.h>
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2011-10-16 14:01:52 +08:00
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#include <linux/export.h>
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2005-04-17 06:20:36 +08:00
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#include <linux/blkdev.h>
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#include <linux/backing-dev.h>
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2006-12-10 18:19:40 +08:00
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#include <linux/task_io_accounting_ops.h>
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2005-04-17 06:20:36 +08:00
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#include <linux/pagevec.h>
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2007-09-21 15:19:54 +08:00
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#include <linux/pagemap.h>
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2012-05-30 06:06:43 +08:00
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#include <linux/syscalls.h>
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#include <linux/file.h>
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2016-01-15 07:22:01 +08:00
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#include <linux/mm_inline.h>
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2018-07-03 23:15:03 +08:00
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#include <linux/blk-cgroup.h>
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2018-08-29 13:41:29 +08:00
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#include <linux/fadvise.h>
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2005-04-17 06:20:36 +08:00
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2014-04-08 06:37:55 +08:00
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#include "internal.h"
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2005-04-17 06:20:36 +08:00
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/*
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* Initialise a struct file's readahead state. Assumes that the caller has
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* memset *ra to zero.
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*/
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void
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file_ra_state_init(struct file_ra_state *ra, struct address_space *mapping)
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{
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2015-01-14 17:42:36 +08:00
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ra->ra_pages = inode_to_bdi(mapping->host)->ra_pages;
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2007-10-16 16:24:33 +08:00
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ra->prev_pos = -1;
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2005-04-17 06:20:36 +08:00
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}
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2006-01-30 16:53:33 +08:00
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EXPORT_SYMBOL_GPL(file_ra_state_init);
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2005-04-17 06:20:36 +08:00
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2009-04-03 23:42:35 +08:00
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/*
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* see if a page needs releasing upon read_cache_pages() failure
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2009-04-03 23:42:36 +08:00
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* - the caller of read_cache_pages() may have set PG_private or PG_fscache
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* before calling, such as the NFS fs marking pages that are cached locally
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* on disk, thus we need to give the fs a chance to clean up in the event of
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* an error
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2009-04-03 23:42:35 +08:00
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*/
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static void read_cache_pages_invalidate_page(struct address_space *mapping,
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struct page *page)
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{
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2009-04-03 23:42:36 +08:00
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if (page_has_private(page)) {
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2009-04-03 23:42:35 +08:00
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if (!trylock_page(page))
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BUG();
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page->mapping = mapping;
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mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
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do_invalidatepage(page, 0, PAGE_SIZE);
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2009-04-03 23:42:35 +08:00
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page->mapping = NULL;
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unlock_page(page);
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}
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mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
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put_page(page);
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2009-04-03 23:42:35 +08:00
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}
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/*
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* release a list of pages, invalidating them first if need be
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*/
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static void read_cache_pages_invalidate_pages(struct address_space *mapping,
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struct list_head *pages)
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{
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struct page *victim;
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while (!list_empty(pages)) {
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2016-01-15 07:20:51 +08:00
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victim = lru_to_page(pages);
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2009-04-03 23:42:35 +08:00
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list_del(&victim->lru);
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read_cache_pages_invalidate_page(mapping, victim);
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}
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}
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2005-04-17 06:20:36 +08:00
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/**
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2006-06-25 20:48:08 +08:00
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* read_cache_pages - populate an address space with some pages & start reads against them
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2005-04-17 06:20:36 +08:00
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* @mapping: the address_space
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* @pages: The address of a list_head which contains the target pages. These
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* pages have their ->index populated and are otherwise uninitialised.
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* @filler: callback routine for filling a single page.
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* @data: private data for the callback routine.
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*
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* Hides the details of the LRU cache etc from the filesystems.
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2019-03-06 07:48:42 +08:00
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*
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* Returns: %0 on success, error return by @filler otherwise
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2005-04-17 06:20:36 +08:00
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*/
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int read_cache_pages(struct address_space *mapping, struct list_head *pages,
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int (*filler)(void *, struct page *), void *data)
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{
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struct page *page;
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int ret = 0;
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while (!list_empty(pages)) {
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2016-01-15 07:20:51 +08:00
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page = lru_to_page(pages);
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2005-04-17 06:20:36 +08:00
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list_del(&page->lru);
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mm, fs: obey gfp_mapping for add_to_page_cache()
Commit 6afdb859b710 ("mm: do not ignore mapping_gfp_mask in page cache
allocation paths") has caught some users of hardcoded GFP_KERNEL used in
the page cache allocation paths. This, however, wasn't complete and
there were others which went unnoticed.
Dave Chinner has reported the following deadlock for xfs on loop device:
: With the recent merge of the loop device changes, I'm now seeing
: XFS deadlock on my single CPU, 1GB RAM VM running xfs/073.
:
: The deadlocked is as follows:
:
: kloopd1: loop_queue_read_work
: xfs_file_iter_read
: lock XFS inode XFS_IOLOCK_SHARED (on image file)
: page cache read (GFP_KERNEL)
: radix tree alloc
: memory reclaim
: reclaim XFS inodes
: log force to unpin inodes
: <wait for log IO completion>
:
: xfs-cil/loop1: <does log force IO work>
: xlog_cil_push
: xlog_write
: <loop issuing log writes>
: xlog_state_get_iclog_space()
: <blocks due to all log buffers under write io>
: <waits for IO completion>
:
: kloopd1: loop_queue_write_work
: xfs_file_write_iter
: lock XFS inode XFS_IOLOCK_EXCL (on image file)
: <wait for inode to be unlocked>
:
: i.e. the kloopd, with it's split read and write work queues, has
: introduced a dependency through memory reclaim. i.e. that writes
: need to be able to progress for reads make progress.
:
: The problem, fundamentally, is that mpage_readpages() does a
: GFP_KERNEL allocation, rather than paying attention to the inode's
: mapping gfp mask, which is set to GFP_NOFS.
:
: The didn't used to happen, because the loop device used to issue
: reads through the splice path and that does:
:
: error = add_to_page_cache_lru(page, mapping, index,
: GFP_KERNEL & mapping_gfp_mask(mapping));
This has changed by commit aa4d86163e4 ("block: loop: switch to VFS
ITER_BVEC").
This patch changes mpage_readpage{s} to follow gfp mask set for the
mapping. There are, however, other places which are doing basically the
same.
lustre:ll_dir_filler is doing GFP_KERNEL from the function which
apparently uses GFP_NOFS for other allocations so let's make this
consistent.
cifs:readpages_get_pages is called from cifs_readpages and
__cifs_readpages_from_fscache called from the same path obeys mapping
gfp.
ramfs_nommu_expand_for_mapping is hardcoding GFP_KERNEL as well
regardless it uses mapping_gfp_mask for the page allocation.
ext4_mpage_readpages is the called from the page cache allocation path
same as read_pages and read_cache_pages
As I've noticed in my previous post I cannot say I would be happy about
sprinkling mapping_gfp_mask all over the place and it sounds like we
should drop gfp_mask argument altogether and use it internally in
__add_to_page_cache_locked that would require all the filesystems to use
mapping gfp consistently which I am not sure is the case here. From a
quick glance it seems that some file system use it all the time while
others are selective.
Signed-off-by: Michal Hocko <mhocko@suse.com>
Reported-by: Dave Chinner <david@fromorbit.com>
Cc: "Theodore Ts'o" <tytso@mit.edu>
Cc: Ming Lei <ming.lei@canonical.com>
Cc: Andreas Dilger <andreas.dilger@intel.com>
Cc: Oleg Drokin <oleg.drokin@intel.com>
Cc: Al Viro <viro@zeniv.linux.org.uk>
Cc: Christoph Hellwig <hch@lst.de>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2015-10-16 06:28:24 +08:00
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if (add_to_page_cache_lru(page, mapping, page->index,
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2016-07-27 06:24:53 +08:00
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readahead_gfp_mask(mapping))) {
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2009-04-03 23:42:35 +08:00
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read_cache_pages_invalidate_page(mapping, page);
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2005-04-17 06:20:36 +08:00
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continue;
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}
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mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
|
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put_page(page);
|
2007-10-16 16:24:57 +08:00
|
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2005-04-17 06:20:36 +08:00
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ret = filler(data, page);
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2007-10-16 16:24:57 +08:00
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if (unlikely(ret)) {
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2009-04-03 23:42:35 +08:00
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read_cache_pages_invalidate_pages(mapping, pages);
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2005-04-17 06:20:36 +08:00
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break;
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|
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}
|
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
|
|
|
task_io_account_read(PAGE_SIZE);
|
2005-04-17 06:20:36 +08:00
|
|
|
}
|
|
|
|
return ret;
|
|
|
|
}
|
|
|
|
|
|
|
|
EXPORT_SYMBOL(read_cache_pages);
|
|
|
|
|
2020-06-02 12:46:25 +08:00
|
|
|
static void read_pages(struct readahead_control *rac, struct list_head *pages,
|
|
|
|
gfp_t gfp)
|
2005-04-17 06:20:36 +08:00
|
|
|
{
|
2020-06-02 12:46:25 +08:00
|
|
|
const struct address_space_operations *aops = rac->mapping->a_ops;
|
2010-04-19 16:04:38 +08:00
|
|
|
struct blk_plug plug;
|
2005-04-17 06:20:36 +08:00
|
|
|
unsigned page_idx;
|
|
|
|
|
2020-06-02 12:46:25 +08:00
|
|
|
if (!readahead_count(rac))
|
2020-06-02 12:46:18 +08:00
|
|
|
return;
|
|
|
|
|
2010-04-19 16:04:38 +08:00
|
|
|
blk_start_plug(&plug);
|
|
|
|
|
2020-06-02 12:46:25 +08:00
|
|
|
if (aops->readpages) {
|
|
|
|
aops->readpages(rac->file, rac->mapping, pages,
|
|
|
|
readahead_count(rac));
|
2006-11-03 14:07:06 +08:00
|
|
|
/* Clean up the remaining pages */
|
|
|
|
put_pages_list(pages);
|
2005-04-17 06:20:36 +08:00
|
|
|
goto out;
|
|
|
|
}
|
|
|
|
|
2020-06-02 12:46:25 +08:00
|
|
|
for (page_idx = 0; page_idx < readahead_count(rac); page_idx++) {
|
2016-01-15 07:20:51 +08:00
|
|
|
struct page *page = lru_to_page(pages);
|
2005-04-17 06:20:36 +08:00
|
|
|
list_del(&page->lru);
|
2020-06-02 12:46:25 +08:00
|
|
|
if (!add_to_page_cache_lru(page, rac->mapping, page->index,
|
|
|
|
gfp))
|
|
|
|
aops->readpage(rac->file, page);
|
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
|
|
|
put_page(page);
|
2005-04-17 06:20:36 +08:00
|
|
|
}
|
2010-04-19 16:04:38 +08:00
|
|
|
|
2005-04-17 06:20:36 +08:00
|
|
|
out:
|
2010-04-19 16:04:38 +08:00
|
|
|
blk_finish_plug(&plug);
|
2020-06-02 12:46:18 +08:00
|
|
|
|
|
|
|
BUG_ON(!list_empty(pages));
|
2020-06-02 12:46:25 +08:00
|
|
|
rac->_nr_pages = 0;
|
2005-04-17 06:20:36 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
2018-06-02 00:03:06 +08:00
|
|
|
* __do_page_cache_readahead() actually reads a chunk of disk. It allocates
|
|
|
|
* the pages first, then submits them for I/O. This avoids the very bad
|
2005-04-17 06:20:36 +08:00
|
|
|
* behaviour which would occur if page allocations are causing VM writeback.
|
|
|
|
* We really don't want to intermingle reads and writes like that.
|
|
|
|
*/
|
2020-06-02 12:46:10 +08:00
|
|
|
void __do_page_cache_readahead(struct address_space *mapping,
|
2020-06-02 12:46:29 +08:00
|
|
|
struct file *filp, pgoff_t index, unsigned long nr_to_read,
|
2018-06-02 00:03:05 +08:00
|
|
|
unsigned long lookahead_size)
|
2005-04-17 06:20:36 +08:00
|
|
|
{
|
|
|
|
struct inode *inode = mapping->host;
|
|
|
|
struct page *page;
|
|
|
|
unsigned long end_index; /* The last page we want to read */
|
|
|
|
LIST_HEAD(page_pool);
|
|
|
|
int page_idx;
|
|
|
|
loff_t isize = i_size_read(inode);
|
2016-07-27 06:24:53 +08:00
|
|
|
gfp_t gfp_mask = readahead_gfp_mask(mapping);
|
2020-06-02 12:46:25 +08:00
|
|
|
struct readahead_control rac = {
|
|
|
|
.mapping = mapping,
|
|
|
|
.file = filp,
|
|
|
|
};
|
2005-04-17 06:20:36 +08:00
|
|
|
|
|
|
|
if (isize == 0)
|
2020-06-02 12:46:10 +08:00
|
|
|
return;
|
2005-04-17 06:20:36 +08:00
|
|
|
|
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
|
|
|
end_index = ((isize - 1) >> PAGE_SHIFT);
|
2005-04-17 06:20:36 +08:00
|
|
|
|
|
|
|
/*
|
|
|
|
* Preallocate as many pages as we will need.
|
|
|
|
*/
|
|
|
|
for (page_idx = 0; page_idx < nr_to_read; page_idx++) {
|
2020-06-02 12:46:29 +08:00
|
|
|
pgoff_t page_offset = index + page_idx;
|
2007-07-19 16:48:04 +08:00
|
|
|
|
2005-04-17 06:20:36 +08:00
|
|
|
if (page_offset > end_index)
|
|
|
|
break;
|
|
|
|
|
2017-12-04 17:30:18 +08:00
|
|
|
page = xa_load(&mapping->i_pages, page_offset);
|
2017-11-04 01:30:42 +08:00
|
|
|
if (page && !xa_is_value(page)) {
|
2018-06-02 00:03:06 +08:00
|
|
|
/*
|
|
|
|
* Page already present? Kick off the current batch of
|
|
|
|
* contiguous pages before continuing with the next
|
|
|
|
* batch.
|
|
|
|
*/
|
2020-06-02 12:46:25 +08:00
|
|
|
read_pages(&rac, &page_pool, gfp_mask);
|
2005-04-17 06:20:36 +08:00
|
|
|
continue;
|
2018-06-02 00:03:06 +08:00
|
|
|
}
|
2005-04-17 06:20:36 +08:00
|
|
|
|
2016-07-27 06:24:53 +08:00
|
|
|
page = __page_cache_alloc(gfp_mask);
|
2005-04-17 06:20:36 +08:00
|
|
|
if (!page)
|
|
|
|
break;
|
|
|
|
page->index = page_offset;
|
|
|
|
list_add(&page->lru, &page_pool);
|
2007-07-19 16:47:57 +08:00
|
|
|
if (page_idx == nr_to_read - lookahead_size)
|
|
|
|
SetPageReadahead(page);
|
2020-06-02 12:46:25 +08:00
|
|
|
rac._nr_pages++;
|
2005-04-17 06:20:36 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
|
|
|
* Now start the IO. We ignore I/O errors - if the page is not
|
|
|
|
* uptodate then the caller will launch readpage again, and
|
|
|
|
* will then handle the error.
|
|
|
|
*/
|
2020-06-02 12:46:25 +08:00
|
|
|
read_pages(&rac, &page_pool, gfp_mask);
|
2005-04-17 06:20:36 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
|
|
|
* Chunk the readahead into 2 megabyte units, so that we don't pin too much
|
|
|
|
* memory at once.
|
|
|
|
*/
|
2020-06-02 12:46:10 +08:00
|
|
|
void force_page_cache_readahead(struct address_space *mapping,
|
2020-06-02 12:46:29 +08:00
|
|
|
struct file *filp, pgoff_t index, unsigned long nr_to_read)
|
2005-04-17 06:20:36 +08:00
|
|
|
{
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
struct backing_dev_info *bdi = inode_to_bdi(mapping->host);
|
|
|
|
struct file_ra_state *ra = &filp->f_ra;
|
|
|
|
unsigned long max_pages;
|
|
|
|
|
2005-04-17 06:20:36 +08:00
|
|
|
if (unlikely(!mapping->a_ops->readpage && !mapping->a_ops->readpages))
|
2020-06-02 12:46:10 +08:00
|
|
|
return;
|
2005-04-17 06:20:36 +08:00
|
|
|
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
/*
|
|
|
|
* If the request exceeds the readahead window, allow the read to
|
|
|
|
* be up to the optimal hardware IO size
|
|
|
|
*/
|
|
|
|
max_pages = max_t(unsigned long, bdi->io_pages, ra->ra_pages);
|
|
|
|
nr_to_read = min(nr_to_read, max_pages);
|
2005-04-17 06:20:36 +08:00
|
|
|
while (nr_to_read) {
|
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
|
|
|
unsigned long this_chunk = (2 * 1024 * 1024) / PAGE_SIZE;
|
2005-04-17 06:20:36 +08:00
|
|
|
|
|
|
|
if (this_chunk > nr_to_read)
|
|
|
|
this_chunk = nr_to_read;
|
2020-06-02 12:46:29 +08:00
|
|
|
__do_page_cache_readahead(mapping, filp, index, this_chunk, 0);
|
2014-01-30 06:05:51 +08:00
|
|
|
|
2020-06-02 12:46:29 +08:00
|
|
|
index += this_chunk;
|
2005-04-17 06:20:36 +08:00
|
|
|
nr_to_read -= this_chunk;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2007-07-19 16:48:04 +08:00
|
|
|
/*
|
|
|
|
* Set the initial window size, round to next power of 2 and square
|
|
|
|
* for small size, x 4 for medium, and x 2 for large
|
|
|
|
* for 128k (32 page) max ra
|
|
|
|
* 1-8 page = 32k initial, > 8 page = 128k initial
|
|
|
|
*/
|
|
|
|
static unsigned long get_init_ra_size(unsigned long size, unsigned long max)
|
|
|
|
{
|
|
|
|
unsigned long newsize = roundup_pow_of_two(size);
|
|
|
|
|
|
|
|
if (newsize <= max / 32)
|
|
|
|
newsize = newsize * 4;
|
|
|
|
else if (newsize <= max / 4)
|
|
|
|
newsize = newsize * 2;
|
|
|
|
else
|
|
|
|
newsize = max;
|
|
|
|
|
|
|
|
return newsize;
|
|
|
|
}
|
|
|
|
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
/*
|
|
|
|
* Get the previous window size, ramp it up, and
|
|
|
|
* return it as the new window size.
|
|
|
|
*/
|
2007-07-19 16:48:04 +08:00
|
|
|
static unsigned long get_next_ra_size(struct file_ra_state *ra,
|
2018-12-28 16:33:34 +08:00
|
|
|
unsigned long max)
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
{
|
2007-07-19 16:48:08 +08:00
|
|
|
unsigned long cur = ra->size;
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
|
|
|
|
if (cur < max / 16)
|
2018-12-28 16:33:34 +08:00
|
|
|
return 4 * cur;
|
|
|
|
if (cur <= max / 2)
|
|
|
|
return 2 * cur;
|
|
|
|
return max;
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
|
|
|
* On-demand readahead design.
|
|
|
|
*
|
|
|
|
* The fields in struct file_ra_state represent the most-recently-executed
|
|
|
|
* readahead attempt:
|
|
|
|
*
|
2007-07-19 16:48:08 +08:00
|
|
|
* |<----- async_size ---------|
|
|
|
|
* |------------------- size -------------------->|
|
|
|
|
* |==================#===========================|
|
|
|
|
* ^start ^page marked with PG_readahead
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
*
|
|
|
|
* To overlap application thinking time and disk I/O time, we do
|
|
|
|
* `readahead pipelining': Do not wait until the application consumed all
|
|
|
|
* readahead pages and stalled on the missing page at readahead_index;
|
2007-07-19 16:48:08 +08:00
|
|
|
* Instead, submit an asynchronous readahead I/O as soon as there are
|
|
|
|
* only async_size pages left in the readahead window. Normally async_size
|
|
|
|
* will be equal to size, for maximum pipelining.
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
*
|
|
|
|
* In interleaved sequential reads, concurrent streams on the same fd can
|
|
|
|
* be invalidating each other's readahead state. So we flag the new readahead
|
2007-07-19 16:48:08 +08:00
|
|
|
* page at (start+size-async_size) with PG_readahead, and use it as readahead
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
* indicator. The flag won't be set on already cached pages, to avoid the
|
|
|
|
* readahead-for-nothing fuss, saving pointless page cache lookups.
|
|
|
|
*
|
2007-10-16 16:24:33 +08:00
|
|
|
* prev_pos tracks the last visited byte in the _previous_ read request.
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
* It should be maintained by the caller, and will be used for detecting
|
|
|
|
* small random reads. Note that the readahead algorithm checks loosely
|
|
|
|
* for sequential patterns. Hence interleaved reads might be served as
|
|
|
|
* sequential ones.
|
|
|
|
*
|
|
|
|
* There is a special-case: if the first page which the application tries to
|
|
|
|
* read happens to be the first page of the file, it is assumed that a linear
|
|
|
|
* read is about to happen and the window is immediately set to the initial size
|
|
|
|
* based on I/O request size and the max_readahead.
|
|
|
|
*
|
|
|
|
* The code ramps up the readahead size aggressively at first, but slow down as
|
|
|
|
* it approaches max_readhead.
|
|
|
|
*/
|
|
|
|
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
/*
|
2020-06-02 12:46:29 +08:00
|
|
|
* Count contiguously cached pages from @index-1 to @index-@max,
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
* this count is a conservative estimation of
|
|
|
|
* - length of the sequential read sequence, or
|
|
|
|
* - thrashing threshold in memory tight systems
|
|
|
|
*/
|
|
|
|
static pgoff_t count_history_pages(struct address_space *mapping,
|
2020-06-02 12:46:29 +08:00
|
|
|
pgoff_t index, unsigned long max)
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
{
|
|
|
|
pgoff_t head;
|
|
|
|
|
|
|
|
rcu_read_lock();
|
2020-06-02 12:46:29 +08:00
|
|
|
head = page_cache_prev_miss(mapping, index - 1, max);
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
rcu_read_unlock();
|
|
|
|
|
2020-06-02 12:46:29 +08:00
|
|
|
return index - 1 - head;
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
|
|
|
* page cache context based read-ahead
|
|
|
|
*/
|
|
|
|
static int try_context_readahead(struct address_space *mapping,
|
|
|
|
struct file_ra_state *ra,
|
2020-06-02 12:46:29 +08:00
|
|
|
pgoff_t index,
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
unsigned long req_size,
|
|
|
|
unsigned long max)
|
|
|
|
{
|
|
|
|
pgoff_t size;
|
|
|
|
|
2020-06-02 12:46:29 +08:00
|
|
|
size = count_history_pages(mapping, index, max);
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
|
|
|
|
/*
|
2013-09-12 05:21:47 +08:00
|
|
|
* not enough history pages:
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
* it could be a random read
|
|
|
|
*/
|
2013-09-12 05:21:47 +08:00
|
|
|
if (size <= req_size)
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
return 0;
|
|
|
|
|
|
|
|
/*
|
|
|
|
* starts from beginning of file:
|
|
|
|
* it is a strong indication of long-run stream (or whole-file-read)
|
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
if (size >= index)
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
size *= 2;
|
|
|
|
|
2020-06-02 12:46:29 +08:00
|
|
|
ra->start = index;
|
2013-09-12 05:21:47 +08:00
|
|
|
ra->size = min(size + req_size, max);
|
|
|
|
ra->async_size = 1;
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
|
|
|
|
return 1;
|
|
|
|
}
|
|
|
|
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
/*
|
|
|
|
* A minimal readahead algorithm for trivial sequential/random reads.
|
|
|
|
*/
|
2020-06-02 12:46:10 +08:00
|
|
|
static void ondemand_readahead(struct address_space *mapping,
|
|
|
|
struct file_ra_state *ra, struct file *filp,
|
2020-06-02 12:46:29 +08:00
|
|
|
bool hit_readahead_marker, pgoff_t index,
|
2020-06-02 12:46:10 +08:00
|
|
|
unsigned long req_size)
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
{
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
struct backing_dev_info *bdi = inode_to_bdi(mapping->host);
|
|
|
|
unsigned long max_pages = ra->ra_pages;
|
2018-07-27 23:09:53 +08:00
|
|
|
unsigned long add_pages;
|
2020-06-02 12:46:29 +08:00
|
|
|
pgoff_t prev_index;
|
2009-06-17 06:31:33 +08:00
|
|
|
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
/*
|
|
|
|
* If the request exceeds the readahead window, allow the read to
|
|
|
|
* be up to the optimal hardware IO size
|
|
|
|
*/
|
|
|
|
if (req_size > max_pages && bdi->io_pages > max_pages)
|
|
|
|
max_pages = min(req_size, bdi->io_pages);
|
|
|
|
|
2009-06-17 06:31:33 +08:00
|
|
|
/*
|
|
|
|
* start of file
|
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
if (!index)
|
2009-06-17 06:31:33 +08:00
|
|
|
goto initial_readahead;
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
|
|
|
|
/*
|
2020-06-02 12:46:29 +08:00
|
|
|
* It's the expected callback index, assume sequential access.
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
* Ramp up sizes, and push forward the readahead window.
|
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
if ((index == (ra->start + ra->size - ra->async_size) ||
|
|
|
|
index == (ra->start + ra->size))) {
|
2007-07-19 16:48:08 +08:00
|
|
|
ra->start += ra->size;
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
ra->size = get_next_ra_size(ra, max_pages);
|
2007-07-19 16:48:08 +08:00
|
|
|
ra->async_size = ra->size;
|
|
|
|
goto readit;
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
}
|
|
|
|
|
2007-10-16 16:24:34 +08:00
|
|
|
/*
|
|
|
|
* Hit a marked page without valid readahead state.
|
|
|
|
* E.g. interleaved reads.
|
|
|
|
* Query the pagecache for async_size, which normally equals to
|
|
|
|
* readahead size. Ramp it up and use it as the new readahead size.
|
|
|
|
*/
|
|
|
|
if (hit_readahead_marker) {
|
|
|
|
pgoff_t start;
|
|
|
|
|
2008-07-26 10:45:28 +08:00
|
|
|
rcu_read_lock();
|
2020-06-02 12:46:29 +08:00
|
|
|
start = page_cache_next_miss(mapping, index + 1, max_pages);
|
2008-07-26 10:45:28 +08:00
|
|
|
rcu_read_unlock();
|
2007-10-16 16:24:34 +08:00
|
|
|
|
2020-06-02 12:46:29 +08:00
|
|
|
if (!start || start - index > max_pages)
|
2020-06-02 12:46:10 +08:00
|
|
|
return;
|
2007-10-16 16:24:34 +08:00
|
|
|
|
|
|
|
ra->start = start;
|
2020-06-02 12:46:29 +08:00
|
|
|
ra->size = start - index; /* old async_size */
|
2009-06-17 06:31:23 +08:00
|
|
|
ra->size += req_size;
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
ra->size = get_next_ra_size(ra, max_pages);
|
2007-10-16 16:24:34 +08:00
|
|
|
ra->async_size = ra->size;
|
|
|
|
goto readit;
|
|
|
|
}
|
|
|
|
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
/*
|
2009-06-17 06:31:33 +08:00
|
|
|
* oversize read
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
*/
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
if (req_size > max_pages)
|
2009-06-17 06:31:33 +08:00
|
|
|
goto initial_readahead;
|
|
|
|
|
|
|
|
/*
|
|
|
|
* sequential cache miss
|
2020-06-02 12:46:29 +08:00
|
|
|
* trivial case: (index - prev_index) == 1
|
|
|
|
* unaligned reads: (index - prev_index) == 0
|
2009-06-17 06:31:33 +08:00
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
prev_index = (unsigned long long)ra->prev_pos >> PAGE_SHIFT;
|
|
|
|
if (index - prev_index <= 1UL)
|
2009-06-17 06:31:33 +08:00
|
|
|
goto initial_readahead;
|
|
|
|
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
/*
|
|
|
|
* Query the page cache and look for the traces(cached history pages)
|
|
|
|
* that a sequential stream would leave behind.
|
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
if (try_context_readahead(mapping, ra, index, req_size, max_pages))
|
readahead: introduce context readahead algorithm
Introduce page cache context based readahead algorithm.
This is to better support concurrent read streams in general.
RATIONALE
---------
The current readahead algorithm detects interleaved reads in a _passive_ way.
Given a sequence of interleaved streams 1,1001,2,1002,3,4,1003,5,1004,1005,6,...
By checking for (offset == prev_offset + 1), it will discover the sequentialness
between 3,4 and between 1004,1005, and start doing sequential readahead for the
individual streams since page 4 and page 1005.
The context readahead algorithm guarantees to discover the sequentialness no
matter how the streams are interleaved. For the above example, it will start
sequential readahead since page 2 and 1002.
The trick is to poke for page @offset-1 in the page cache when it has no other
clues on the sequentialness of request @offset: if the current requenst belongs
to a sequential stream, that stream must have accessed page @offset-1 recently,
and the page will still be cached now. So if page @offset-1 is there, we can
take request @offset as a sequential access.
BENEFICIARIES
-------------
- strictly interleaved reads i.e. 1,1001,2,1002,3,1003,...
the current readahead will take them as silly random reads;
the context readahead will take them as two sequential streams.
- cooperative IO processes i.e. NFS and SCST
They create a thread pool, farming off (sequential) IO requests to different
threads which will be performing interleaved IO.
It was not easy(or possible) to reliably tell from file->f_ra all those
cooperative processes working on the same sequential stream, since they will
have different file->f_ra instances. And NFSD's file->f_ra is particularly
unusable, since their file objects are dynamically created for each request.
The nfsd does have code trying to restore the f_ra bits, but not satisfactory.
The new scheme is to detect the sequential pattern via looking up the page
cache, which provides one single and consistent view of the pages recently
accessed. That makes sequential detection for cooperative processes possible.
USER REPORT
-----------
Vladislav recommends the addition of context readahead as a result of his SCST
benchmarks. It leads to 6%~40% performance gains in various cases and achieves
equal performance in others. http://lkml.org/lkml/2009/3/19/239
OVERHEADS
---------
In theory, it introduces one extra page cache lookup per random read. However
the below benchmark shows context readahead to be slightly faster, wondering..
Randomly reading 200MB amount of data on a sparse file, repeat 20 times for
each block size. The average throughputs are:
original ra context ra gain
4K random reads: 65.561MB/s 65.648MB/s +0.1%
16K random reads: 124.767MB/s 124.951MB/s +0.1%
64K random reads: 162.123MB/s 162.278MB/s +0.1%
Cc: Jens Axboe <jens.axboe@oracle.com>
Cc: Jeff Moyer <jmoyer@redhat.com>
Tested-by: Vladislav Bolkhovitin <vst@vlnb.net>
Signed-off-by: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-06-17 06:31:36 +08:00
|
|
|
goto readit;
|
|
|
|
|
2009-06-17 06:31:33 +08:00
|
|
|
/*
|
|
|
|
* standalone, small random read
|
|
|
|
* Read as is, and do not pollute the readahead state.
|
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
__do_page_cache_readahead(mapping, filp, index, req_size, 0);
|
2020-06-02 12:46:10 +08:00
|
|
|
return;
|
2009-06-17 06:31:33 +08:00
|
|
|
|
|
|
|
initial_readahead:
|
2020-06-02 12:46:29 +08:00
|
|
|
ra->start = index;
|
mm: don't cap request size based on read-ahead setting
We ran into a funky issue, where someone doing 256K buffered reads saw
128K requests at the device level. Turns out it is read-ahead capping
the request size, since we use 128K as the default setting. This
doesn't make a lot of sense - if someone is issuing 256K reads, they
should see 256K reads, regardless of the read-ahead setting, if the
underlying device can support a 256K read in a single command.
This patch introduces a bdi hint, io_pages. This is the soft max IO
size for the lower level, I've hooked it up to the bdev settings here.
Read-ahead is modified to issue the maximum of the user request size,
and the read-ahead max size, but capped to the max request size on the
device side. The latter is done to avoid reading ahead too much, if the
application asks for a huge read. With this patch, the kernel behaves
like the application expects.
Link: http://lkml.kernel.org/r/1479498073-8657-1-git-send-email-axboe@fb.com
Signed-off-by: Jens Axboe <axboe@fb.com>
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-12-13 08:43:26 +08:00
|
|
|
ra->size = get_init_ra_size(req_size, max_pages);
|
2007-07-19 16:48:08 +08:00
|
|
|
ra->async_size = ra->size > req_size ? ra->size - req_size : ra->size;
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
|
2007-07-19 16:48:08 +08:00
|
|
|
readit:
|
2009-06-17 06:31:24 +08:00
|
|
|
/*
|
|
|
|
* Will this read hit the readahead marker made by itself?
|
|
|
|
* If so, trigger the readahead marker hit now, and merge
|
|
|
|
* the resulted next readahead window into the current one.
|
2018-07-27 23:09:53 +08:00
|
|
|
* Take care of maximum IO pages as above.
|
2009-06-17 06:31:24 +08:00
|
|
|
*/
|
2020-06-02 12:46:29 +08:00
|
|
|
if (index == ra->start && ra->size == ra->async_size) {
|
2018-07-27 23:09:53 +08:00
|
|
|
add_pages = get_next_ra_size(ra, max_pages);
|
|
|
|
if (ra->size + add_pages <= max_pages) {
|
|
|
|
ra->async_size = add_pages;
|
|
|
|
ra->size += add_pages;
|
|
|
|
} else {
|
|
|
|
ra->size = max_pages;
|
|
|
|
ra->async_size = max_pages >> 1;
|
|
|
|
}
|
2009-06-17 06:31:24 +08:00
|
|
|
}
|
|
|
|
|
2020-06-02 12:46:10 +08:00
|
|
|
ra_submit(ra, mapping, filp);
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
/**
|
2007-07-19 16:48:08 +08:00
|
|
|
* page_cache_sync_readahead - generic file readahead
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
* @mapping: address_space which holds the pagecache and I/O vectors
|
|
|
|
* @ra: file_ra_state which holds the readahead state
|
|
|
|
* @filp: passed on to ->readpage() and ->readpages()
|
2020-06-02 12:46:29 +08:00
|
|
|
* @index: Index of first page to be read.
|
|
|
|
* @req_count: Total number of pages being read by the caller.
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
*
|
2007-07-19 16:48:08 +08:00
|
|
|
* page_cache_sync_readahead() should be called when a cache miss happened:
|
|
|
|
* it will submit the read. The readahead logic may decide to piggyback more
|
|
|
|
* pages onto the read request if access patterns suggest it will improve
|
|
|
|
* performance.
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
*/
|
2007-07-19 16:48:08 +08:00
|
|
|
void page_cache_sync_readahead(struct address_space *mapping,
|
|
|
|
struct file_ra_state *ra, struct file *filp,
|
2020-06-02 12:46:29 +08:00
|
|
|
pgoff_t index, unsigned long req_count)
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
{
|
|
|
|
/* no read-ahead */
|
|
|
|
if (!ra->ra_pages)
|
2007-07-19 16:48:08 +08:00
|
|
|
return;
|
|
|
|
|
2018-07-03 23:15:03 +08:00
|
|
|
if (blk_cgroup_congested())
|
|
|
|
return;
|
|
|
|
|
2010-03-06 05:42:03 +08:00
|
|
|
/* be dumb */
|
2010-04-07 05:34:53 +08:00
|
|
|
if (filp && (filp->f_mode & FMODE_RANDOM)) {
|
2020-06-02 12:46:29 +08:00
|
|
|
force_page_cache_readahead(mapping, filp, index, req_count);
|
2010-03-06 05:42:03 +08:00
|
|
|
return;
|
|
|
|
}
|
|
|
|
|
2007-07-19 16:48:08 +08:00
|
|
|
/* do read-ahead */
|
2020-06-02 12:46:29 +08:00
|
|
|
ondemand_readahead(mapping, ra, filp, false, index, req_count);
|
2007-07-19 16:48:08 +08:00
|
|
|
}
|
|
|
|
EXPORT_SYMBOL_GPL(page_cache_sync_readahead);
|
|
|
|
|
|
|
|
/**
|
|
|
|
* page_cache_async_readahead - file readahead for marked pages
|
|
|
|
* @mapping: address_space which holds the pagecache and I/O vectors
|
|
|
|
* @ra: file_ra_state which holds the readahead state
|
|
|
|
* @filp: passed on to ->readpage() and ->readpages()
|
2020-06-02 12:46:29 +08:00
|
|
|
* @page: The page at @index which triggered the readahead call.
|
|
|
|
* @index: Index of first page to be read.
|
|
|
|
* @req_count: Total number of pages being read by the caller.
|
2007-07-19 16:48:08 +08:00
|
|
|
*
|
2010-05-25 05:32:36 +08:00
|
|
|
* page_cache_async_readahead() should be called when a page is used which
|
2020-06-02 12:46:29 +08:00
|
|
|
* is marked as PageReadahead; this is a marker to suggest that the application
|
2007-07-19 16:48:08 +08:00
|
|
|
* has used up enough of the readahead window that we should start pulling in
|
2008-03-20 08:01:02 +08:00
|
|
|
* more pages.
|
|
|
|
*/
|
2007-07-19 16:48:08 +08:00
|
|
|
void
|
|
|
|
page_cache_async_readahead(struct address_space *mapping,
|
|
|
|
struct file_ra_state *ra, struct file *filp,
|
2020-06-02 12:46:29 +08:00
|
|
|
struct page *page, pgoff_t index,
|
|
|
|
unsigned long req_count)
|
2007-07-19 16:48:08 +08:00
|
|
|
{
|
|
|
|
/* no read-ahead */
|
|
|
|
if (!ra->ra_pages)
|
|
|
|
return;
|
|
|
|
|
|
|
|
/*
|
|
|
|
* Same bit is used for PG_readahead and PG_reclaim.
|
|
|
|
*/
|
|
|
|
if (PageWriteback(page))
|
|
|
|
return;
|
|
|
|
|
|
|
|
ClearPageReadahead(page);
|
|
|
|
|
|
|
|
/*
|
|
|
|
* Defer asynchronous read-ahead on IO congestion.
|
|
|
|
*/
|
2015-05-23 05:13:44 +08:00
|
|
|
if (inode_read_congested(mapping->host))
|
2007-07-19 16:48:08 +08:00
|
|
|
return;
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
|
2018-07-03 23:15:03 +08:00
|
|
|
if (blk_cgroup_congested())
|
|
|
|
return;
|
|
|
|
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
/* do read-ahead */
|
2020-06-02 12:46:29 +08:00
|
|
|
ondemand_readahead(mapping, ra, filp, true, index, req_count);
|
readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2007-07-19 16:48:01 +08:00
|
|
|
}
|
2007-07-19 16:48:08 +08:00
|
|
|
EXPORT_SYMBOL_GPL(page_cache_async_readahead);
|
2012-05-30 06:06:43 +08:00
|
|
|
|
2018-03-20 00:51:36 +08:00
|
|
|
ssize_t ksys_readahead(int fd, loff_t offset, size_t count)
|
2012-05-30 06:06:43 +08:00
|
|
|
{
|
|
|
|
ssize_t ret;
|
2012-08-29 00:52:22 +08:00
|
|
|
struct fd f;
|
2012-05-30 06:06:43 +08:00
|
|
|
|
|
|
|
ret = -EBADF;
|
2012-08-29 00:52:22 +08:00
|
|
|
f = fdget(fd);
|
2018-08-29 13:41:29 +08:00
|
|
|
if (!f.file || !(f.file->f_mode & FMODE_READ))
|
|
|
|
goto out;
|
|
|
|
|
|
|
|
/*
|
|
|
|
* The readahead() syscall is intended to run only on files
|
|
|
|
* that can execute readahead. If readahead is not possible
|
|
|
|
* on this file, then we must return -EINVAL.
|
|
|
|
*/
|
|
|
|
ret = -EINVAL;
|
|
|
|
if (!f.file->f_mapping || !f.file->f_mapping->a_ops ||
|
|
|
|
!S_ISREG(file_inode(f.file)->i_mode))
|
|
|
|
goto out;
|
|
|
|
|
|
|
|
ret = vfs_fadvise(f.file, offset, count, POSIX_FADV_WILLNEED);
|
|
|
|
out:
|
|
|
|
fdput(f);
|
2012-05-30 06:06:43 +08:00
|
|
|
return ret;
|
|
|
|
}
|
2018-03-20 00:51:36 +08:00
|
|
|
|
|
|
|
SYSCALL_DEFINE3(readahead, int, fd, loff_t, offset, size_t, count)
|
|
|
|
{
|
|
|
|
return ksys_readahead(fd, offset, count);
|
|
|
|
}
|