mirror of https://mirror.osredm.com/root/redis.git
13 Commits
| Author | SHA1 | Message | Date |
|---|---|---|---|
Yuan Wang
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64a40b20d9
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Async IO Threads (#13695)
## Introduction
Redis introduced IO Thread in 6.0, allowing IO threads to handle client
request reading, command parsing and reply writing, thereby improving
performance. The current IO thread implementation has a few drawbacks.
- The main thread is blocked during IO thread read/write operations and
must wait for all IO threads to complete their current tasks before it
can continue execution. In other words, the entire process is
synchronous. This prevents the efficient utilization of multi-core CPUs
for parallel processing.
- When the number of clients and requests increases moderately, it
causes all IO threads to reach full CPU utilization due to the busy wait
mechanism used by the IO threads. This makes it challenging for us to
determine which part of Redis has reached its bottleneck.
- When IO threads are enabled with TLS and io-threads-do-reads, a
disconnection of a connection with pending data may result in it being
assigned to multiple IO threads simultaneously. This can cause race
conditions and trigger assertion failures. Related issue:
redis#12540
Therefore, we designed an asynchronous IO threads solution. The IO
threads adopt an event-driven model, with the main thread dedicated to
command processing, meanwhile, the IO threads handle client read and
write operations in parallel.
## Implementation
### Overall
As before, we did not change the fact that all client commands must be
executed on the main thread, because Redis was originally designed to be
single-threaded, and processing commands in a multi-threaded manner
would inevitably introduce numerous race and synchronization issues. But
now each IO thread has independent event loop, therefore, IO threads can
use a multiplexing approach to handle client read and write operations,
eliminating the CPU overhead caused by busy-waiting.
the execution process can be briefly described as follows:
the main thread assigns clients to IO threads after accepting
connections, IO threads will notify the main thread when clients
finish reading and parsing queries, then the main thread processes
queries from IO threads and generates replies, IO threads handle
writing reply to clients after receiving clients list from main thread,
and then continue to handle client read and write events.
### Each IO thread has independent event loop
We now assign each IO thread its own event loop. This approach
eliminates the need for the main thread to perform the costly
`epoll_wait` operation for handling connections (except for specific
ones). Instead, the main thread processes requests from the IO threads
and hands them back once completed, fully offloading read and write
events to the IO threads.
Additionally, all TLS operations, including handling pending data, have
been moved entirely to the IO threads. This resolves the issue where
io-threads-do-reads could not be used with TLS.
### Event-notified client queue
To facilitate communication between the IO threads and the main thread,
we designed an event-notified client queue. Each IO thread and the main
thread have two such queues to store clients waiting to be processed.
These queues are also integrated with the event loop to enable handling.
We use pthread_mutex to ensure the safety of queue operations, as well
as data visibility and ordering, and race conditions are minimized, as
each IO thread and the main thread operate on independent queues,
avoiding thread suspension due to lock contention. And we implemented an
event notifier based on `eventfd` or `pipe` to support event-driven
handling.
### Thread safety
Since the main thread and IO threads can execute in parallel, we must
handle data race issues carefully.
**client->flags**
The primary tasks of IO threads are reading and writing, i.e.
`readQueryFromClient` and `writeToClient`. However, IO threads and the
main thread may concurrently modify or access `client->flags`, leading
to potential race conditions. To address this, we introduced an io-flags
variable to record operations performed by IO threads, thereby avoiding
race conditions on `client->flags`.
**Pause IO thread**
In the main thread, we may want to operate data of IO threads, maybe
uninstall event handler, access or operate query/output buffer or resize
event loop, we need a clean and safe context to do that. We pause IO
thread in `IOThreadBeforeSleep`, do some jobs and then resume it. To
avoid thread suspended, we use busy waiting to confirm the target
status. Besides we use atomic variable to make sure memory visibility
and ordering. We introduce these functions to pause/resume IO Threads as
below.
```
pauseIOThread, resumeIOThread
pauseAllIOThreads, resumeAllIOThreads
pauseIOThreadsRange, resumeIOThreadsRange
```
Testing has shown that `pauseIOThread` is highly efficient, allowing the
main thread to execute nearly 200,000 operations per second during
stress tests. Similarly, `pauseAllIOThreads` with 8 IO threads can
handle up to nearly 56,000 operations per second. But operations
performed between pausing and resuming IO threads must be quick;
otherwise, they could cause the IO threads to reach full CPU
utilization.
**freeClient and freeClientAsync**
The main thread may need to terminate a client currently running on an
IO thread, for example, due to ACL rule changes, reaching the output
buffer limit, or evicting a client. In such cases, we need to pause the
IO thread to safely operate on the client.
**maxclients and maxmemory-clients updating**
When adjusting `maxclients`, we need to resize the event loop for all IO
threads. Similarly, when modifying `maxmemory-clients`, we need to
traverse all clients to calculate their memory usage. To ensure safe
operations, we pause all IO threads during these adjustments.
**Client info reading**
The main thread may need to read a client’s fields to generate a
descriptive string, such as for the `CLIENT LIST` command or logging
purposes. In such cases, we need to pause the IO thread handling that
client. If information for all clients needs to be displayed, all IO
threads must be paused.
**Tracking redirect**
Redis supports the tracking feature and can even send invalidation
messages to a connection with a specified ID. But the target client may
be running on IO thread, directly manipulating the client’s output
buffer is not thread-safe, and the IO thread may not be aware that the
client requires a response. In such cases, we pause the IO thread
handling the client, modify the output buffer, and install a write event
handler to ensure proper handling.
**clientsCron**
In the `clientsCron` function, the main thread needs to traverse all
clients to perform operations such as timeout checks, verifying whether
they have reached the soft output buffer limit, resizing the
output/query buffer, or updating memory usage. To safely operate on a
client, the IO thread handling that client must be paused.
If we were to pause the IO thread for each client individually, the
efficiency would be very low. Conversely, pausing all IO threads
simultaneously would be costly, especially when there are many IO
threads, as clientsCron is invoked relatively frequently.
To address this, we adopted a batched approach for pausing IO threads.
At most, 8 IO threads are paused at a time. The operations mentioned
above are only performed on clients running in the paused IO threads,
significantly reducing overhead while maintaining safety.
### Observability
In the current design, the main thread always assigns clients to the IO
thread with the least clients. To clearly observe the number of clients
handled by each IO thread, we added the new section in INFO output. The
`INFO THREADS` section can show the client count for each IO thread.
```
# Threads
io_thread_0:clients=0
io_thread_1:clients=2
io_thread_2:clients=2
```
Additionally, in the `CLIENT LIST` output, we also added a field to
indicate the thread to which each client is assigned.
`id=244 addr=127.0.0.1:41870 laddr=127.0.0.1:6379 ... resp=2 lib-name=
lib-ver= io-thread=1`
## Trade-off
### Special Clients
For certain special types of clients, keeping them running on IO threads
would result in severe race issues that are difficult to resolve.
Therefore, we chose not to offload these clients to the IO threads.
For replica, monitor, subscribe, and tracking clients, main thread may
directly write them a reply when conditions are met. Race issues are
difficult to resolve, so we have them processed in the main thread. This
includes the Lua debug clients as well, since we may operate connection
directly.
For blocking client, after the IO thread reads and parses a command and
hands it over to the main thread, if the client is identified as a
blocking type, it will be remained in the main thread. Once the blocking
operation completes and the reply is generated, the client is
transferred back to the IO thread to send the reply and wait for event
triggers.
### Clients Eviction
To support client eviction, it is necessary to update each client’s
memory usage promptly during operations such as read, write, or command
execution. However, when a client operates on an IO thread, it is not
feasible to update the memory usage immediately due to the risk of data
races. As a result, memory usage can only be updated either in the main
thread while processing commands or in the `ClientsCron` periodically.
The downside of this approach is that updates might experience a delay
of up to one second, which could impact the precision of memory
management for eviction.
To avoid incorrectly evicting clients. We adopted a best-effort
compensation solution, when we decide to eviction a client, we update
its memory usage again before evicting, if the memory used by the client
does not decrease or memory usage bucket is not changed, then we will
evict it, otherwise, not evict it.
However, we have not completely solved this problem. Due to the delay in
memory usage updates, it may lead us to make incorrect decisions about
the need to evict clients.
### Defragment
In the majority of cases we do NOT use the data from argv directly in
the db.
1. key names
We store a copy that we allocate in the main thread, see `sdsdup()` in
`dbAdd()`.
2. hash key and value
We store key as hfield and store value as sds, see `hfieldNew()` and
`sdsdup()` in `hashTypeSet()`.
3. other datatypes
They don't even use SDS, so there is no reference issues.
But in some cases client the data from argv may be retain by the main
thread.
As a result, during fragmentation cleanup, we need to move allocations
from the IO thread’s arena to the main thread’s arena. We always
allocate new memory in the main thread’s arena, but the memory released
by IO threads may not yet have been reclaimed. This ultimately causes
the fragmentation rate to be higher compared to creating and allocating
entirely within a single thread.
The following cases below will lead to memory allocated by the IO thread
being kept by the main thread.
1. string related command: `append`, `getset`, `mset` and `set`.
If `tryObjectEncoding()` does not change argv, we will keep it directly
in the main thread, see the code in `tryObjectEncoding()`(specifically
`trimStringObjectIfNeeded()`)
2. block related command.
the key names will be kept in `c->db->blocking_keys`.
3. watch command
the key names will be kept in `c->db->watched_keys`.
4. [s]subscribe command
channel name will be kept in `serverPubSubChannels`.
5. script load command
script will be kept in `server.lua_scripts`.
7. some module API: `RM_RetainString`, `RM_HoldString`
Those issues will be handled in other PRs.
## Testing
### Functional Testing
The commit with enabling IO Threads has passed all TCL tests, but we did
some changes:
**Client query buffer**: In the original code, when using a reusable
query buffer, ownership of the query buffer would be released after the
command was processed. However, with IO threads enabled, the client
transitions from an IO thread to the main thread for processing. This
causes the ownership release to occur earlier than the command
execution. As a result, when IO threads are enabled, the client's
information will never indicate that a shared query buffer is in use.
Therefore, we skip the corresponding query buffer tests in this case.
**Defragment**: Add a new defragmentation test to verify the effect of
io threads on defragmentation.
**Command delay**: For deferred clients in TCL tests, due to clients
being assigned to different threads for execution, delays may occur. To
address this, we introduced conditional waiting: the process proceeds to
the next step only when the `client list` contains the corresponding
commands.
### Sanitizer Testing
The commit passed all TCL tests and reported no errors when compiled
with the `fsanitizer=thread` and `fsanitizer=address` options enabled.
But we made the following modifications: we suppressed the sanitizer
warnings for clients with watched keys when updating `client->flags`, we
think IO threads read `client->flags`, but never modify it or read the
`CLIENT_DIRTY_CAS` bit, main thread just only modifies this bit, so
there is no actual data race.
## Others
### IO thread number
In the new multi-threaded design, the main thread is primarily focused
on command processing to improve performance. Typically, the main thread
does not handle regular client I/O operations but is responsible for
clients such as replication and tracking clients. To avoid breaking
changes, we still consider the main thread as the first IO thread.
When the io-threads configuration is set to a low value (e.g., 2),
performance does not show a significant improvement compared to a
single-threaded setup for simple commands (such as SET or GET), as the
main thread does not consume much CPU for these simple operations. This
results in underutilized multi-core capacity. However, for more complex
commands, having a low number of IO threads may still be beneficial.
Therefore, it’s important to adjust the `io-threads` based on your own
performance tests.
Additionally, you can clearly monitor the CPU utilization of the main
thread and IO threads using `top -H -p $redis_pid`. This allows you to
easily identify where the bottleneck is. If the IO thread is the
bottleneck, increasing the `io-threads` will improve performance. If the
main thread is the bottleneck, the overall performance can only be
scaled by increasing the number of shards or replicas.
---------
Co-authored-by: debing.sun <debing.sun@redis.com>
Co-authored-by: oranagra <oran@redislabs.com>
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Oran Agra
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447ce11a64
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solve race conditions in tests (#13433)
[exception]: Executing test client: ERR FAILOVER target replica is not
online.. ERR FAILOVER target replica is not online.
while executing
"$node_0 failover to $node_1_host $node_1_port"
("uplevel" body line 16)
invoked from within
"uplevel 1 $code"
(procedure "test" line 58)
invoked from within
"test {failover command to specific replica works} {
[err]: client evicted due to percentage of maxmemory in
tests/unit/client-eviction.tcl
Expected 33622 >= 220200 && 33622 < 440401 (context: type eval line 17
cmd {assert {$tot_mem >= $n && $tot_mem < $maxmemory_clients_actual}}
proc ::test)
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Oran Agra
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997fa41e99
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Attempt to solve MacOS CI issues in GH Actions (#12013)
The MacOS CI in github actions often hangs without any logs. GH argues that it's due to resource utilization, either running out of disk space, memory, or CPU starvation, and thus the runner is terminated. This PR contains multiple attempts to resolve this: 1. introducing pause_process instead of SIGSTOP, which waits for the process to stop before resuming the test, possibly resolving race conditions in some tests, this was a suspect since there was one test that could result in an infinite loop in that case, in practice this didn't help, but still a good idea to keep. 2. disable the `save` config in many tests that don't need it, specifically ones that use heavy writes and could create large files. 3. change the `populate` proc to use short pipeline rather than an infinite one. 4. use `--clients 1` in the macos CI so that we don't risk running multiple resource demanding tests in parallel. 5. enable `--verbose` to be repeated to elevate verbosity and print more info to stdout when a test or a server starts. |
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guybe7
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4ba47d2d21
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Add reply_schema to command json files (internal for now) (#10273)
Work in progress towards implementing a reply schema as part of COMMAND DOCS, see #9845 Since ironing the details of the reply schema of each and every command can take a long time, we would like to merge this PR when the infrastructure is ready, and let this mature in the unstable branch. Meanwhile the changes of this PR are internal, they are part of the repo, but do not affect the produced build. ### Background In #9656 we add a lot of information about Redis commands, but we are missing information about the replies ### Motivation 1. Documentation. This is the primary goal. 2. It should be possible, based on the output of COMMAND, to be able to generate client code in typed languages. In order to do that, we need Redis to tell us, in detail, what each reply looks like. 3. We would like to build a fuzzer that verifies the reply structure (for now we use the existing testsuite, see the "Testing" section) ### Schema The idea is to supply some sort of schema for the various replies of each command. The schema will describe the conceptual structure of the reply (for generated clients), as defined in RESP3. Note that the reply structure itself may change, depending on the arguments (e.g. `XINFO STREAM`, with and without the `FULL` modifier) We decided to use the standard json-schema (see https://json-schema.org/) as the reply-schema. Example for `BZPOPMIN`: ``` "reply_schema": { "oneOf": [ { "description": "Timeout reached and no elements were popped.", "type": "null" }, { "description": "The keyname, popped member, and its score.", "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "description": "Keyname", "type": "string" }, { "description": "Member", "type": "string" }, { "description": "Score", "type": "number" } ] } ] } ``` #### Notes 1. It is ok that some commands' reply structure depends on the arguments and it's the caller's responsibility to know which is the relevant one. this comes after looking at other request-reply systems like OpenAPI, where the reply schema can also be oneOf and the caller is responsible to know which schema is the relevant one. 2. The reply schemas will describe RESP3 replies only. even though RESP3 is structured, we want to use reply schema for documentation (and possibly to create a fuzzer that validates the replies) 3. For documentation, the description field will include an explanation of the scenario in which the reply is sent, including any relation to arguments. for example, for `ZRANGE`'s two schemas we will need to state that one is with `WITHSCORES` and the other is without. 4. For documentation, there will be another optional field "notes" in which we will add a short description of the representation in RESP2, in case it's not trivial (RESP3's `ZRANGE`'s nested array vs. RESP2's flat array, for example) Given the above: 1. We can generate the "return" section of all commands in [redis-doc](https://redis.io/commands/) (given that "description" and "notes" are comprehensive enough) 2. We can generate a client in a strongly typed language (but the return type could be a conceptual `union` and the caller needs to know which schema is relevant). see the section below for RESP2 support. 3. We can create a fuzzer for RESP3. ### Limitations (because we are using the standard json-schema) The problem is that Redis' replies are more diverse than what the json format allows. This means that, when we convert the reply to a json (in order to validate the schema against it), we lose information (see the "Testing" section below). The other option would have been to extend the standard json-schema (and json format) to include stuff like sets, bulk-strings, error-string, etc. but that would mean also extending the schema-validator - and that seemed like too much work, so we decided to compromise. Examples: 1. We cannot tell the difference between an "array" and a "set" 2. We cannot tell the difference between simple-string and bulk-string 3. we cannot verify true uniqueness of items in commands like ZRANGE: json-schema doesn't cover the case of two identical members with different scores (e.g. `[["m1",6],["m1",7]]`) because `uniqueItems` compares (member,score) tuples and not just the member name. ### Testing This commit includes some changes inside Redis in order to verify the schemas (existing and future ones) are indeed correct (i.e. describe the actual response of Redis). To do that, we added a debugging feature to Redis that causes it to produce a log of all the commands it executed and their replies. For that, Redis needs to be compiled with `-DLOG_REQ_RES` and run with `--reg-res-logfile <file> --client-default-resp 3` (the testsuite already does that if you run it with `--log-req-res --force-resp3`) You should run the testsuite with the above args (and `--dont-clean`) in order to make Redis generate `.reqres` files (same dir as the `stdout` files) which contain request-response pairs. These files are later on processed by `./utils/req-res-log-validator.py` which does: 1. Goes over req-res files, generated by redis-servers, spawned by the testsuite (see logreqres.c) 2. For each request-response pair, it validates the response against the request's reply_schema (obtained from the extended COMMAND DOCS) 5. In order to get good coverage of the Redis commands, and all their different replies, we chose to use the existing redis test suite, rather than attempt to write a fuzzer. #### Notes about RESP2 1. We will not be able to use the testing tool to verify RESP2 replies (we are ok with that, it's time to accept RESP3 as the future RESP) 2. Since the majority of the test suite is using RESP2, and we want the server to reply with RESP3 so that we can validate it, we will need to know how to convert the actual reply to the one expected. - number and boolean are always strings in RESP2 so the conversion is easy - objects (maps) are always a flat array in RESP2 - others (nested array in RESP3's `ZRANGE` and others) will need some special per-command handling (so the client will not be totally auto-generated) Example for ZRANGE: ``` "reply_schema": { "anyOf": [ { "description": "A list of member elements", "type": "array", "uniqueItems": true, "items": { "type": "string" } }, { "description": "Members and their scores. Returned in case `WITHSCORES` was used.", "notes": "In RESP2 this is returned as a flat array", "type": "array", "uniqueItems": true, "items": { "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "description": "Member", "type": "string" }, { "description": "Score", "type": "number" } ] } } ] } ``` ### Other changes 1. Some tests that behave differently depending on the RESP are now being tested for both RESP, regardless of the special log-req-res mode ("Pub/Sub PING" for example) 2. Update the history field of CLIENT LIST 3. Added basic tests for commands that were not covered at all by the testsuite ### TODO - [x] (maybe a different PR) add a "condition" field to anyOf/oneOf schemas that refers to args. e.g. when `SET` return NULL, the condition is `arguments.get||arguments.condition`, for `OK` the condition is `!arguments.get`, and for `string` the condition is `arguments.get` - https://github.com/redis/redis/issues/11896 - [x] (maybe a different PR) also run `runtest-cluster` in the req-res logging mode - [x] add the new tests to GH actions (i.e. compile with `-DLOG_REQ_RES`, run the tests, and run the validator) - [x] (maybe a different PR) figure out a way to warn about (sub)schemas that are uncovered by the output of the tests - https://github.com/redis/redis/issues/11897 - [x] (probably a separate PR) add all missing schemas - [x] check why "SDOWN is triggered by misconfigured instance replying with errors" fails with --log-req-res - [x] move the response transformers to their own file (run both regular, cluster, and sentinel tests - need to fight with the tcl including mechanism a bit) - [x] issue: module API - https://github.com/redis/redis/issues/11898 - [x] (probably a separate PR): improve schemas: add `required` to `object`s - https://github.com/redis/redis/issues/11899 Co-authored-by: Ozan Tezcan <ozantezcan@gmail.com> Co-authored-by: Hanna Fadida <hanna.fadida@redislabs.com> Co-authored-by: Oran Agra <oran@redislabs.com> Co-authored-by: Shaya Potter <shaya@redislabs.com> |
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Oran Agra
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c8226ae378
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Try to solve valgrind CI test error with client-eviction test (#11822)
The test sporadically failed with valgrind trying to match `no client named obuf-client1 found*` in the log it looks like `obuf-client1` was indeed dropped, so i'm guessing it's because CLIENT LIST was processed first. |
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Binbin
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cd58af4d7f
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Speed up test: client evicted due to client tracking prefixes (#11823)
We noticed that `client evicted due to client tracking prefixes` takes over 200 seconds with valgrind. We combine three prefixes in each command, this will probably save us half the testing time. Before: normal: 3508ms, valgrind: 289503ms -> 290s With three prefixes, normal: 1500ms, valgrind: 135742ms -> 136s Since we did not actually count the memory usage of all prefixes, see getClientMemoryUsage, so we can not use larger prefixes to speed up the test here. Also this PR cleaned up some spaces (IDE jobs) and typos. |
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Harkrishn Patro
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c0267b3fa5
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Optimize client memory usage tracking operation while client eviction is disabled (#11348)
## Issue During the client input/output buffer processing, the memory usage is incrementally updated to keep track of clients going beyond a certain threshold `maxmemory-clients` to be evicted. However, this additional tracking activity leads to unnecessary CPU cycles wasted when no client-eviction is required. It is applicable in two cases. * `maxmemory-clients` is set to `0` which equates to no client eviction (applicable to all clients) * `CLIENT NO-EVICT` flag is set to `ON` which equates to a particular client not applicable for eviction. ## Solution * Disable client memory usage tracking during the read/write flow when `maxmemory-clients` is set to `0` or `client no-evict` is `on`. The memory usage is tracked only during the `clientCron` i.e. it gets periodically updated. * Cleanup the clients from the memory usage bucket when client eviction is disabled. * When the maxmemory-clients config is enabled or disabled at runtime, we immediately update the memory usage buckets for all clients (tested scanning 80000 took some 20ms) Benchmark shown that this can improve performance by about 5% in certain situations. Co-authored-by: Oran Agra <oran@redislabs.com> |
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Harkrishn Patro
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0ab885a685
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Account sharded pubsub channels memory consumption (#10925)
Account sharded pubsub channels memory consumption in client memory usage computation to accurately evict client based on the set threshold for `maxmemory-clients`. |
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ranshid
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9b15dd288e
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Introduce debug command to disable reply buffer resizing (#10360)
In order to resolve some flaky tests which hard rely on examine memory footprint. we introduce the following fixes: # Fix in client-eviction test - by @yoav-steinberg Sometime the libc allocator can use different size client struct allocations. this may cause unexpected memory calculations to fail the test. # Introduce new DEBUG command for disabling reply buffer resizing In order to eliminate reply buffer resizing during specific tests. we introduced the ability to disable (and enable) the resizing cron job Co-authored-by: yoav-steinberg yoav@redislabs.com |
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ranshid
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5860fa3d9c
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deflake client-eviction test "evict clients only until below limit" (#10354)
After introducing #9822 need to prevent client reply buffer shrink to maintain correct client memory math. add needs:debug missing one one test. Co-authored-by: Oran Agra <oran@redislabs.com> |
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ranshid
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47c51d0c78
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introduce dynamic client reply buffer size - save memory on idle clients (#9822)
Current implementation simple idle client which serves no traffic still
use ~17Kb of memory. this is mainly due to a fixed size reply buffer
currently set to 16kb.
We have encountered some cases in which the server operates in a low memory environments.
In such cases a user who wishes to create large connection pools to support potential burst period,
will exhaust a large amount of memory to maintain connected Idle clients.
Some users may choose to "sacrifice" performance in order to save memory.
This commit introduce a dynamic mechanism to shrink and expend the client reply buffer based on
periodic observed peak.
the algorithm works as follows:
1. each time a client reply buffer has been fully written, the last recorded peak is updated:
new peak = MAX( last peak, current written size)
2. during clients cron we check for each client if the last observed peak was:
a. matching the current buffer size - in which case we expend (resize) the buffer size by 100%
b. less than half the buffer size - in which case we shrink the buffer size by 50%
3. In any case we will **not** resize the buffer in case:
a. the current buffer peak is less then the current buffer usable size and higher than 1/2 the
current buffer usable size
b. the value of (current buffer usable size/2) is less than 1Kib
c. the value of (current buffer usable size*2) is larger than 16Kib
4. the peak value is reset to the current buffer position once every **5** seconds. we maintain a new
field in the client structure (buf_peak_last_reset_time) which is used to keep track of how long it
passed since the last buffer peak reset.
### **Interface changes:**
**CIENT LIST** - now contains 2 new extra fields:
rbs= < the current size in bytes of the client reply buffer >
rbp=< the current value in bytes of the last observed buffer peak position >
**INFO STATS** - now contains 2 new statistics:
reply_buffer_shrinks = < total number of buffer shrinks performed >
reply_buffer_expends = < total number of buffer expends performed >
Co-authored-by: Oran Agra <oran@redislabs.com>
Co-authored-by: Yoav Steinberg <yoav@redislabs.com>
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yoav-steinberg
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6600253046
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Client eviction ci issues (#9549)
Fixing CI test issues introduced in #8687 - valgrind warnings in readQueryFromClient when client was freed by processInputBuffer - adding DEBUG pause-cron for tests not to be time dependent. - skipping a test that depends on socket buffers / events not compatible with TLS - making sure client got subscribed by not using deferring client |
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yoav-steinberg
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2753429c99
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Client eviction (#8687)
### Description A mechanism for disconnecting clients when the sum of all connected clients is above a configured limit. This prevents eviction or OOM caused by accumulated used memory between all clients. It's a complimentary mechanism to the `client-output-buffer-limit` mechanism which takes into account not only a single client and not only output buffers but rather all memory used by all clients. #### Design The general design is as following: * We track memory usage of each client, taking into account all memory used by the client (query buffer, output buffer, parsed arguments, etc...). This is kept up to date after reading from the socket, after processing commands and after writing to the socket. * Based on the used memory we sort all clients into buckets. Each bucket contains all clients using up up to x2 memory of the clients in the bucket below it. For example up to 1m clients, up to 2m clients, up to 4m clients, ... * Before processing a command and before sleep we check if we're over the configured limit. If we are we start disconnecting clients from larger buckets downwards until we're under the limit. #### Config `maxmemory-clients` max memory all clients are allowed to consume, above this threshold we disconnect clients. This config can either be set to 0 (meaning no limit), a size in bytes (possibly with MB/GB suffix), or as a percentage of `maxmemory` by using the `%` suffix (e.g. setting it to `10%` would mean 10% of `maxmemory`). #### Important code changes * During the development I encountered yet more situations where our io-threads access global vars. And needed to fix them. I also had to handle keeps the clients sorted into the memory buckets (which are global) while their memory usage changes in the io-thread. To achieve this I decided to simplify how we check if we're in an io-thread and make it much more explicit. I removed the `CLIENT_PENDING_READ` flag used for checking if the client is in an io-thread (it wasn't used for anything else) and just used the global `io_threads_op` variable the same way to check during writes. * I optimized the cleanup of the client from the `clients_pending_read` list on client freeing. We now store a pointer in the `client` struct to this list so we don't need to search in it (`pending_read_list_node`). * Added `evicted_clients` stat to `INFO` command. * Added `CLIENT NO-EVICT ON|OFF` sub command to exclude a specific client from the client eviction mechanism. Added corrosponding 'e' flag in the client info string. * Added `multi-mem` field in the client info string to show how much memory is used up by buffered multi commands. * Client `tot-mem` now accounts for buffered multi-commands, pubsub patterns and channels (partially), tracking prefixes (partially). * CLIENT_CLOSE_ASAP flag is now handled in a new `beforeNextClient()` function so clients will be disconnected between processing different clients and not only before sleep. This new function can be used in the future for work we want to do outside the command processing loop but don't want to wait for all clients to be processed before we get to it. Specifically I wanted to handle output-buffer-limit related closing before we process client eviction in case the two race with each other. * Added a `DEBUG CLIENT-EVICTION` command to print out info about the client eviction buckets. * Each client now holds a pointer to the client eviction memory usage bucket it belongs to and listNode to itself in that bucket for quick removal. * Global `io_threads_op` variable now can contain a `IO_THREADS_OP_IDLE` value indicating no io-threading is currently being executed. * In order to track memory used by each clients in real-time we can't rely on updating these stats in `clientsCron()` alone anymore. So now I call `updateClientMemUsage()` (used to be `clientsCronTrackClientsMemUsage()`) after command processing, after writing data to pubsub clients, after writing the output buffer and after reading from the socket (and maybe other places too). The function is written to be fast. * Clients are evicted if needed (with appropriate log line) in `beforeSleep()` and before processing a command (before performing oom-checks and key-eviction). * All clients memory usage buckets are grouped as follows: * All clients using less than 64k. * 64K..128K * 128K..256K * ... * 2G..4G * All clients using 4g and up. * Added client-eviction.tcl with a bunch of tests for the new mechanism. * Extended maxmemory.tcl to test the interaction between maxmemory and maxmemory-clients settings. * Added an option to flag a numeric configuration variable as a "percent", this means that if we encounter a '%' after the number in the config file (or config set command) we consider it as valid. Such a number is store internally as a negative value. This way an integer value can be interpreted as either a percent (negative) or absolute value (positive). This is useful for example if some numeric configuration can optionally be set to a percentage of something else. Co-authored-by: Oran Agra <oran@redislabs.com> |