close#13709
Fix the index error of CRLF character for integer-encoded strings
in addReplyBulk function
---------
Co-authored-by: debing.sun <debing.sun@redis.com>
## 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>
The bug was introduced in #13558 .
When merging dense hll structures, `hllDenseCompress` writes to wrong
location and the result will be zero. The unit tests didn't cover this
case.
This PR
+ fixes the bug
+ adds `PFDEBUG SIMD (ON|OFF)` for unit tests
+ adds a new TCL test to cover the cases
Synchronized from https://github.com/valkey-io/valkey/pull/1293
---------
Signed-off-by: Xuyang Wang <xuyangwang@link.cuhk.edu.cn>
Co-authored-by: debing.sun <debing.sun@redis.com>
- Add empty string test for the new API
`RedisModule_ACLCheckKeyPrefixPermissions`.
- Fix order of checks: `(pattern[patternLen - 1] != '*' || patternLen ==
0)`
---------
Co-authored-by: debing.sun <debing.sun@redis.com>
This PR introduces API to query Expiration time of hash fields.
# New `RedisModule_HashFieldMinExpire()`
For a given hash, retrieves the minimum expiration time across all
fields. If no fields have expiration or if the key is not a hash then
return `REDISMODULE_NO_EXPIRE` (-1).
```
mstime_t RM_HashFieldMinExpire(RedisModuleKey *hash);
```
# Extension to `RedisModule_HashGet()`
Adds a new flag, `REDISMODULE_HASH_EXPIRE_TIME`, to retrieve the
expiration time of a specific hash field. If the field does not exist or
has no expiration, returns `REDISMODULE_NO_EXPIRE`. It is fully
backward-compatible (RM_HashGet retains its original behavior unless the
new flag is used).
Example:
```
mstime_t expiry1, expiry2;
RedisModule_HashGet(mykey, REDISMODULE_HASH_EXPIRE_TIME, "field1", &expiry1, NULL);
RedisModule_HashGet(mykey, REDISMODULE_HASH_EXPIRE_TIME, "field1", &expiry1, "field2", &expiry2, NULL);
```
This PR introduces a new API function to the Redis Module API:
```
int RedisModule_ACLCheckKeyPrefixPermissions(RedisModuleUser *user, RedisModuleString *prefix, int flags);
```
Purpose:
The function checks if a given user has access permissions to any key
that match a specific prefix. This validation is based on the user’s ACL
permissions and the specified flags.
Note, this prefix-based approach API may fail to detect prefixes that
are individually uncovered but collectively covered by the patterns. For
example the prefix `ID-*` is not fully included in pattern `ID-[0]*` and
is not fully included in pattern `ID-[^0]*` but it is fully included in
the set of patterns `{ID-[0]*, ID-[^0]*}`
Starting from https://github.com/redis/redis/pull/13133, we allocate a
jemalloc thread cache and use it for lua vm.
On certain cases, like `script flush` or `function flush` command, we
free the existing thread cache and create a new one.
Though, for `function flush`, we were not actually destroying the
existing thread cache itself. Each call creates a new thread cache on
jemalloc and we leak the previous thread cache instances. Jemalloc
allows maximum 4096 thread cache instances. If we reach this limit,
Redis prints "Failed creating the lua jemalloc tcache" log and abort.
There are other cases that can cause this memory leak, including
replication scenarios when emptyData() is called.
The implication is that it looks like redis `used_memory` is low, but
`allocator_allocated` and RSS remain high.
Co-authored-by: debing.sun <debing.sun@redis.com>
PR #10285 introduced support for modules to register four types of
configurations — Bool, Numeric, String, and Enum. Accessible through the
Redis config file and the CONFIG command.
With this PR, it will be possible to register configuration parameters
without automatically prefixing the parameter names. This provides
greater flexibility in configuration naming, enabling, for instance,
both `bf-initial-size` or `initial-size` to be defined in the module
without automatically prefixing with `<MODULE-NAME>.`. In addition it
will also be possible to create a single additional alias via the same
API. This brings us another step closer to integrate modules into redis
core.
**Example:** Register a configuration parameter `bf-initial-size` with
an alias `initial-size` without the automatic module name prefix, set
with new `REDISMODULE_CONFIG_UNPREFIXED` flag:
```
RedisModule_RegisterBoolConfig(ctx, "bf-initial-size|initial-size", default_val, optflags | REDISMODULE_CONFIG_UNPREFIXED, getfn, setfn, applyfn, privdata);
```
# API changes
Related functions that now support unprefixed configuration flag
(`REDISMODULE_CONFIG_UNPREFIXED`) along with optional alias:
```
RedisModule_RegisterBoolConfig
RedisModule_RegisterEnumConfig
RedisModule_RegisterNumericConfig
RedisModule_RegisterStringConfig
```
# Implementation Details:
`config.c`: On load server configuration, at function
`loadServerConfigFromString()`, it collects all unknown configurations
into `module_configs_queue` dictionary. These may include valid module
configurations or invalid ones. They will be validated later by
`loadModuleConfigs()` against the configurations declared by the loaded
module(s).
`Module.c:` The `ModuleConfig` structure has been modified to store now:
(1) Full configuration name (2) Alias (3) Unprefixed flag status -
ensuring that configurations retain their original registration format
when triggered in notifications.
Added error printout:
This change introduces an error printout for unresolved configurations,
detailing each unresolved parameter detected during startup. The last
line in the output existed prior to this change and has been retained to
systems relies on it:
```
595011:M 18 Nov 2024 08:26:23.616 # Unresolved Configuration(s) Detected:
595011:M 18 Nov 2024 08:26:23.616 # >>> 'bf-initiel-size 8'
595011:M 18 Nov 2024 08:26:23.616 # >>> 'search-sizex 32'
595011:M 18 Nov 2024 08:26:23.616 # Module Configuration detected without loadmodule directive or no ApplyConfig call: aborting
```
# Backward Compatibility:
Existing modules will function without modification, as the new
functionality only applies if REDISMODULE_CONFIG_UNPREFIXED is
explicitly set.
# Module vs. Core API Conflict Behavior
The new API allows to modules loading duplication of same configuration
name or same configuration alias, just like redis core configuration
allows (i.e. the users sets two configs with a different value, but
these two configs are actually the same one). Unlike redis core, given a
name and its alias, it doesn't allow have both configuration on load. To
implement it, it is required to modify DS `module_configs_queue` to
reflect the order of their loading and later on, during
`loadModuleConfigs()`, resolve pairs of names and aliases and which one
is the last one to apply. "Relaxing" this limitation can be deferred to
a future update if necessary, but for now, we error in this case.
Fix to https://github.com/redis/redis/issues/13650
providing an invalid config to a module with datatype crashes when redis
tries to unload the module due to the invalid config
---------
Co-authored-by: debing.sun <debing.sun@redis.com>
If `hide-user-data-from-log` config is enabled, we don't print client
argv in the crashlog to avoid leaking user info.
Though, debugging a crash becomes harder as we don't see the command
arguments causing the crash.
With this PR, we'll be printing command tokens to the log. As we have
command tokens defined in json schema for each command, using this data,
we can find tokens in the client argv.
e.g.
`SET key value GET EX 10` ---> we'll print `SET * * GET EX *` in the
log.
Modules should introduce their command structure via
`RM_SetCommandInfo()`.
Then, on a crash we'll able to know module command tokens.
This PR adds a new section to the `INFO` command output, called
`keysizes`. This section provides detailed statistics on the
distribution of key sizes for each data type (strings, lists, sets,
hashes and zsets) within the dataset. The distribution is tracked using
a base-2 logarithmic histogram.
# Motivation
Currently, Redis lacks a built-in feature to track key sizes and item
sizes per data type at a granular level. Understanding the distribution
of key sizes is critical for monitoring memory usage and optimizing
performance, particularly in large datasets. This enhancement will allow
users to inspect the size distribution of keys directly from the `INFO`
command, assisting with performance analysis and capacity planning.
# Changes
New Section in `INFO` Command: A new section called `keysizes` has been
added to the `INFO` command output. This section reports a per-database,
per-type histogram of key sizes. It provides insights into how many keys
fall into specific size ranges (represented in powers of 2).
**Example output:**
```
127.0.0.1:6379> INFO keysizes
# Keysizes
db0_distrib_strings_sizes:1=19,2=655,512=100899,1K=31,2K=29,4K=23,8K=16,16K=3,32K=2
db0_distrib_lists_items:1=5784492,32=3558,64=1047,128=676,256=533,512=218,4K=1,8K=42
db0_distrib_sets_items:1=735564=50612,8=21462,64=1365,128=974,2K=292,4K=154,8K=89,
db0_distrib_hashes_items:2=1,4=544,32=141169,64=207329,128=4349,256=136226,1K=1
```
## Future Use Cases:
The key size distribution is collected per slot as well, laying the
groundwork for future enhancements related to Redis Cluster.
From 7.4, Redis allows `GET` options in cluster mode when the pattern maps to
the same slot as the key, but GET # pattern that represents key itself is missed.
This commit resolves it, bug report #13607.
---------
Co-authored-by: Yuan Wang <yuan.wang@redis.com>
- Add a new 'EXPERIMENTAL' command flag, which causes the command
generator to skip over it and make the command to be unavailable for
execution
- Skip experimental tests by default
- Move the SFLUSH tests from the old framework to the new one
---------
Co-authored-by: YaacovHazan <yaacov.hazan@redislabs.com>
Test 1 - give more time for expiration
Test 2 - Evaluate expiration time boundaries [+1,+2] before setting expiration [+1]
Test 3 - Avoid race on test HFEs propagated to replica
The PR extends `RedisModule_OpenKey`'s flags to include
`REDISMODULE_OPEN_KEY_ACCESS_EXPIRED`, which allows to access expired
keys.
It also allows to access expired subkeys. Currently relevant only for
hash fields
and has its impact on `RM_HashGet` and `RM_Scan`.
If the hash previously had HFEs (hash-fields with expiration) but later no longer
does, the key ref in the hash might become outdated after a MOVE, COPY,
RENAME or RESTORE operation. These commands maintain the key ref only
if HFEs are present. That is, we can only be sure that key ref is valid as long as the
hash has HFEs.
When a client in no-touch mode issues a TOUCH command on a key, the
key’s access time should be updated, but in scripts, and module's
RM_Call, it isn’t updated.
Command proc should be matched to the executing client, not the current
client.
Co-authored-by: Udi Ron <udi@speedb.io>
#13495 introduced a change to reply -LOADING while flushing existing db on a replica. Some of our tests are
sensitive to this change and do no expect -LOADING reply.
Fixing a couple of tests that fail time to time.
This PR is based on the commits from PR
https://github.com/valkey-io/valkey/pull/258,
https://github.com/valkey-io/valkey/pull/593,
https://github.com/valkey-io/valkey/pull/639
This PR optimizes client query buffer handling in Redis by introducing
a reusable query buffer that is used by default for client reads. This
reduces memory usage by ~20KB per client by avoiding allocations for
most clients using short (<16KB) complete commands. For larger or
partial commands, the client still gets its own private buffer.
The primary changes are:
* Adding a reusable query buffer `thread_shared_qb` that clients use by
default.
* Modifying client querybuf initialization and reset logic.
* Freeing idle client query buffers when empty to allow reuse of the
reusable query buffer.
* Master client query buffers are kept private as their contents need to
be preserved for replication stream.
* When nested commands is executed, only the first user uses the reuse
buffer, and subsequent users will still use the private buffer.
In addition to the memory savings, this change shows a 3% improvement in
latency and throughput when running with 1000 active clients.
The memory reduction may also help reduce the need to evict clients when
reaching max memory limit, as the query buffer is the main memory
consumer per client.
This PR is different from https://github.com/valkey-io/valkey/pull/258
1. When a client is in the mid of requiring a reused buffer and
returning it, regardless of whether the query buffer has changed
(expanded), we do not update the reused query buffer in the middle, but
return the reused query buffer (expanded or with data remaining) or
reset it at the end.
2. Adding a new thread variable `thread_shared_qb_used` to avoid
multiple clients requiring the reusable query buffer at the same time.
---------
Signed-off-by: Uri Yagelnik <uriy@amazon.com>
Signed-off-by: Madelyn Olson <matolson@amazon.com>
Co-authored-by: Uri Yagelnik <uriy@amazon.com>
Co-authored-by: Madelyn Olson <madelyneolson@gmail.com>
Co-authored-by: oranagra <oran@redislabs.com>
RM_RdbLoad() disables AOF temporarily while loading RDB.
Later, it does not enable it back as it checks AOF state (disabled by then)
rather than AOF config parameter.
Added a change to restart AOF according to config parameter.
All the defrag allocations API expects to get a value and replace it, leaving the old value untouchable.
In some cases a value might be shared between multiple keys, in such cases we can not simply replace
it when the defrag callback is called.
To allow support such use cases, the PR adds two new API's to the defrag API:
1. `RM_DefragAllocRaw` - allocate memory base on a given size.
2. `RM_DefragFreeRaw` - Free the given pointer.
Those API's avoid using tcache so they operate just like `RM_DefragAlloc` but allows the user to split
the allocation and the memory free operations into two stages and control when those happen.
In addition the PR adds new API to allow the module to receive notifications when defrag start and end: `RM_RegisterDefragCallbacks`
Those callbacks are the same as `RM_RegisterDefragFunc` but promised to be called and the start
and the end of the defrag process.
Fixed the issue about GETRANGE and SUBSTR command
return unexpected result caused by the `start` and `end` out of
definition range of string.
---
## break change
Before this PR, when negative `end` was out of range (i.e., end <
-strlen), we would fix it to 0 to get the substring, which also resulted
in the first character still being returned for this kind of out of
range.
After this PR, we ensure that `GETRANGE` returns an empty bulk when the
negative end index is out of range.
Closes#11738
---------
Co-authored-by: debing.sun <debing.sun@redis.com>
Move the TYPE filtering to the scan callback so that avoided the
`lookupKey` operation. This is the follow-up to #12209 . In this thread
we introduced two breaking changes：
1. we will not attempt to do lazy expire (delete) a key that was
filtered by not matching the TYPE (like we already do for MATCH
pattern).
2. when the specified key TYPE filter is an unknown type, server will
reply a error immediately instead of doing a full scan that comes back
empty handed.
## Describe
When using the `XTRIM` command to trim a stream, it does not update the
maximal tombstone (`max_deleted_entry_id`). This leads to an issue where
the lag calculation incorrectly assumes that there are no tombstones
after the consumer group's last_id, resulting in an inaccurate lag.
The reason XTRIM doesn't need to update the maximal tombstone is that it
always trims from the beginning of the stream. This means that it
consistently changes the position of the first entry, leading to the
following scenarios:
1) First entry trimmed after maximal tombstone:
If the first entry is trimmed to a position after the maximal tombstone,
all tombstones will be before the first entry, so they won't affect the
consumer group's lag.
2) First entry trimmed before maximal tombstone:
If the first entry is trimmed to a position before the maximal
tombstone, the maximal tombstone will not be updated.
## Solution
Therefore, this PR optimizes the lag calculation by ensuring that when
both the consumer group's last_id and the maximal tombstone are behind
the first entry, the consumer group's lag is always equal to the number
of remaining elements in the stream.
Supplement to PR https://github.com/redis/redis/pull/13338
Hash field expiration is optimized to avoid frequent update global HFE DS for
each field deletion. Eventually active-expiration will run and update or remove
the hash from global HFE DS gracefully. Nevertheless, statistic "subexpiry"
might reflect wrong number of hashes with HFE to the user if HDEL deletes
the last field with expiration in hash (yet there are more fields without expiration).
Following this change, if HDEL the last field with expiration in the hash then
take care to remove the hash from global HFE DS as well.
This PR is based on the commits from PR
https://github.com/valkey-io/valkey/pull/52.
Ref: https://github.com/redis/redis/pull/12760
Close https://github.com/redis/redis/issues/13401
This PR will replace https://github.com/redis/redis/pull/13449
Fixes compatibilty of Redis cluster (7.2 - extensions enabled by
default) with older Redis cluster (< 7.0 - extensions not handled) .
With some of the extensions enabled by default in 7.2 version, new nodes
running 7.2 and above start sending out larger clusterbus message
payload including the ping extensions. This caused an incompatibility
with node running engine versions < 7.0. Old nodes (< 7.0) would receive
the payload from new nodes (> 7.2) would observe a payload length
(totlen) > (estlen) and would perform an early exit and won't process
the message.
This fix does the following things:
1. Always set `CLUSTERMSG_FLAG0_EXT_DATA`, because during the meet
phase, we do not know whether the connected node supports ext data, we
need to make sure that it knows and send back its ext data if it has.
2. If another node does not support ext data, we will not send it ext
data to avoid the handshake failure due to the incorrect payload length.
Note: A successful `PING`/`PONG` is required as a sender for a given
node to be marked as `CLUSTERMSG_FLAG0_EXT_DATA` and then extensions
message
will be sent to it. This could cause a slight delay in receiving the
extensions message(s).
---------
Signed-off-by: Harkrishn Patro <harkrisp@amazon.com>
Co-authored-by: Harkrishn Patro <harkrisp@amazon.com>
---------
Signed-off-by: Harkrishn Patro <harkrisp@amazon.com>
Co-authored-by: Harkrishn Patro <harkrisp@amazon.com>
1. Fix fuzzer test failure when the key was deleted due to expiration
before sending random traffic for the key.
After HFE, when all fields in a hash are expired, the hash might be
deleted due to expiration.
If the key was expired in the mid of `RESTORE` command and sending rand
trafic, `fuzzer` test will fail in the following code because the 'TYPE
key' will return `none` and then throw an exception because it cannot be
found in `$commands`
94b9072e44/tests/support/util.tcl (L712-L713)
This PR adds a `None` check for the reply of `KEY TYPE` command and adds
a print of `err` to avoid false positives in the future.
failed CI:
https://github.com/redis/redis/actions/runs/10127334121/job/28004985388
2. Fix the issue where key was deleted due to expiration before the
`scan.scan_key` command could execute, caused by premature enabling of
`set-active-expire`.
failed CI:
https://github.com/redis/redis/actions/runs/10153722715/job/28077610552
---------
Co-authored-by: oranagra <oran@redislabs.com>
Fix#13337
Ths PR fixes fixed two bugs that caused lag calculation errors.
1. When the latest tombstone is before the first entry, the tombstone
may stil be after the last id of consume group.
2. When a tombstone is after the last id of consume group, the group's
counter will be invalid, we should caculate the entries_read by using
estimates.
[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)
When the tests are run against an external server in this order:
`--single unit/introspection --single unit/moduleapi/blockonbackground
--single integration/redis-cli`
the test would hang when the "ASK redirect test" test attempts to create
a listening socket (it fails, and then redis-cli itself hangs waiting
for a non-responsive socket created by the introspection test).
the reasons are:
1. the blockedbackground test includes util.tcl and resets the
`::last_port_attempted` variable
2. the test in introspection didn't close the listening server, so it's
still alive.
3. find_available_port doesn't properly detect the busy port, and it
thinks that the port is free even though it's busy.
fixing all 3 of these problems, even though fixing just one would be
enough to let the test pass.
Nowdays we do not trigger LUA GC after loading lua script. This means
that when a large number of scripts are loaded, such as when functions
are propagating from the master to the replica, if the LUA scripts are
never touched on the replica, the garbage might remain there
indefinitely.
Before this PR, we would share a gc_count between scripts and functions.
This means that, under certain circumstances, the GC trigger for scripts
and functions was not fair.
For example, loading a large number of scripts followed by a small
number of functions could result in the functions triggering GC.
In this PR, we assign a unique `gc_count` to each of them, so the GC
triggers between them will no longer affect each other.
on the other hand, this PR will to bring regession for script loading
commands(`FUNCTION LOAD` and `SCRIPT LOAD`), but they are not hot path,
we can ignore it, and it will be replaced
https://github.com/redis/redis/pull/13375 in the future.
---------
Co-authored-by: Oran Agra <oran@redislabs.com>
If `config resetstat` is executed and a defrag is started after it, the
`total_active_defrag_time` will not be 0.
When we start the defrag again, we will skip the following steps:
1. waiting for the defrag to start. (s total_active_defrag_time is equal
0)
2. waiting for the test to complete. (active_defrag_running is euqal 0)
which result in the test failed.
---------
Co-authored-by: oranagra <oran@redislabs.com>
### Issue
The current implementation of `FUNCTION FLUSH` command uses
`lua_unref()` to unreference script closures in Lua vm. However,
invoking `lua_unref()` during lazy free (`ASYNC` argument) is risky
since it is not thread-safe.
Another issue is that using `lua_unref()` to unreference references does
not trigger GC, This can result in the Lua VM leaves a significant
amount of garbage, which may never be cleaned up if not properly GC.
### Solution
The proposed solution is to completely rebuild the engines, resulting in
a brand new Lua VM.
---------
Co-authored-by: meir <meir@redis.com>
* INFO command : rename `hashes_with_expiry_fields` to `subexpiry`
* INFO command : rename `expired_hash_fields` to `expired_subkeys`
* Fix statistic of `expired_subkeys` to count also lazy expired
* Remove TODOs comments leftover in TCL
* Fix potential flaky test of rdb load of hash-field-expiration
If we run FLUSHALL when the 'save' config is set, and there's a fork
child ding BGSAVE, there's a chance the child is already finished, and
the parent process is unaware of it. in that case the child will not get
the kill signal and will finish successfully, but the parent process
thinks it killed it and will reset the dirty counter to 0, then the
backgroundSaveDoneHandlerDisk method can set the dirty counter to a
negative value.
getKeysUsingKeySpece had the range check AFTER the allocation, of the
keys buffer, which could lead to an OOM panic when invalid arguments are
provided, leading to an overflow.
The allocated memory is only used after the range check, so there's no
risk of buffer overrun.
The OOM panic can happen on 32bit builds, or 64 builds running on
systems with less than 4GB of RAM, and is reachable via the COMMAND
GETKEYSANDFLAGS, and ACL key name validation.
There was wrong preliminary assumption that we can optionally provide
vector of arguments more than count.
This is error-prone approach that leaded to actual error in that case.
This PR enforce that vector of argument match count.
Also fixed flaky HRANDFIELD test.
In certain situations, we might generate a large number of propagates
(e.g., multi/exec, Lua script, or a single command generating tons of
propagations) within an event loop.
During the process of propagating to a replica, if the replica is
disconnected(marked as CLIENT_CLOSE_ASAP) due to exceeding the output
buffer limit, we should remove its reference to the global replication
buffer to avoid the global replication buffer being unable to be
properly trimmed due to being referenced.
---------
Co-authored-by: oranagra <oran@redislabs.com>
H(P)EXPIREAT command might delete fields in case the absolute time is in the
past. Those HDELs need to be propagated as well.
In general, as we need to propagate H(P)EXPIRE(AT) command to the replica, each
field that is mentioned in the command should be categorized into one of the four
options:
1. Managed to update field’s expiration time - propagate it to replica as part
of the HPEXPIREAT command.
2. Deleted the field because the time is in the past - propagate also HDEL command
to delete the field and remove the field from the propagated HPEXPIREAT.
3. Condition not met for the field - Remove the field from the propagated
HPEXPIREAT command.
4. Field does not exists - Remove the field from the propagated HPEXPIREAT command.
If none of the provided fields match option number 1, then avoid also propagating
the HPEXPIREAT command to the replica.
This approach is aligned with the EXPIRE command:
If a given key has already expired, then DEL will be propagated instead of
EXPIRE command. If condition not met, then command will be rejected. Otherwise,
EXPIRE command will be propagated for given key.
Considerations for the selected imp of HRANDFIELD & HFE feature:
HRANDFIELD might access any of the fields in the hash as some of them
might be expired. And so the Implementation of HRANDFIELD along with HFEs
might be one of the two options:
1. Expire hash-fields before diving into handling HRANDFIELD.
2. Refine HRANDFIELD cases to deal with expired fields.
Regarding the first option, as reference, the command RANDOMKEY also
declareson O(1) complexity, yet might be stuck on a very long (but not infinite)
loop trying to find non-expired keys. Furthermore RANDOMKEY also evicts expired
keys along the way even though it is categorized as a read-only command. Note
that the case of HRANDFIELD is more lightweight versus RANDOMKEY since
HFEs have much more effective and aggressive active-expiration for fields behind.
The second option introduces additional implementation complexity to HRANDFIELD.
We could further refine HRANDFIELD cases to differentiate between scenarios
with many expired fields versus few expired fields, and adjust based on the
percentage of expired fields. However, this approach could still lead to long
loops or necessitate expiring fields before selecting them. For the “lightweight”
cases it is also expected to have a lightweight expiration.
Considering the pros and cons, and the fact that HRANDFIELD is an infrequent
command (particularly with HFEs) and the fact we have effective active-expiration
behind for hash-fields, it is better to keep it simple and choose option number 1.
Other changes:
* Don't mark command dirty by internal hashTypeExpire(). It causes to read
only command of HRANDFIELD to be accidently propagated (This flag
should be indicated at higher level, by the command functions).
* Align `hashTypeExpireIfNeeded()` and `hashTypeGetValue()` to be more
aligned with `expireIfNeeded()` logic of keyspace.
Currently, HFE commands reply with empty array if the key does not
exist. Though, non-existing key and empty key is the same thing.
It means fields given in the command do not exist in the empty key.
So, replying with an array of 'no field' error codes (-2) suits better
to Redis logic. e.g. Similarly, `hmget` returns array of nulls if the
key does not exist.
After this PR:
```
127.0.0.1:6379> hpersist missingkey fields 2 a b
1) (integer) -2
2) (integer) -2
```
When the hash field expired, we will send a new `hexpired` notification.
It mainly includes the following three cases:
1. When field expired by active expiration.
2. When field expired by lazy expiration.
3. When the user uses the `h(p)expire(at)` command, the user will also
get a `hexpired` notification if the field expires during the command.
## Improvement
1. Now if more than one field expires in the hmget command, we will only
send a `hexpired` notification.
2. When a field with TTL is deleted by commands like hdel without
updating the global DS, active expire will not send a notification.
---------
Co-authored-by: Ozan Tezcan <ozantezcan@gmail.com>
Co-authored-by: Moti Cohen <moti.cohen@redis.com>
Reserve 2 bits out of hash-field expiration time (`EB_EXPIRE_TIME_MAX`)
for possible future lightweight indexing/categorizing of fields. It can
be achieved by hacking HFE as follows:
```
HPEXPIREAT key [ 2^47 + USER_INDEX ] FIELDS numfields field [field …]
```
Redis will also need to expose kind of `HEXPIRESCAN` and `HEXPIRECOUNT`
for this idea. Yet to be better defined.
`HFE_MAX_ABS_TIME_MSEC` constraint must be enforced only at API level.
Internally, the expiration time can be up to `EB_EXPIRE_TIME_MAX` for
future readiness.
raffertyyu