# Overview
Users utilize the `FLUSHDB SYNC` and `FLUSHALL SYNC` commands for a variety of
reasons. The main issue with this command is that if the database becomes
substantial in size, the server will be unresponsive for an extended period.
Other than freezing application traffic, this may also lead some clients making
incorrect judgments about the server's availability. For instance, a watchdog may
erroneously decide to terminate the process, resulting in potential adverse
outcomes. While a `FLUSH* ASYNC` can address these issues, it might not be used
for two reasons: firstly, it's not the default, and secondly, in some cases, the
client issuing the flush wants to wait for its completion before repopulating the
database.
Between the option of triggering FLUSH* asynchronously in the background without
indication for completion versus running it synchronously in the foreground by
the main thread, there is another more appealing option. We can block the
client that requested the flush, execute the flush command in the background, and
once done, unblock the client and return notification for completion. This approach
ensures the server remains responsive to other clients, and the blocked client
receives the expected response only after the flush operation has been successfully
carried out.
# Implementation details
Instead of defining yet another flavor to the flush command, we can modify
`FLUSHALL SYNC` and `FLUSHDB SYNC` always run in this new mode.
## Extending BIO Threads capabilities
Today jobs that are carried out by BIO threads don't have the capability to
indicate completion to the main thread. We can add this infrastructure by having
an additional dummy job, coined as completion-job, that eventually will be written
by BIO threads to a response-queue. The main thread will take care to consume items
from the response-queue and call the provided callback function of each
completion-job.
## FLUSH* SYNC to run as blocking ASYNC
Command `FLUSH* SYNC` will be modified to create one or more async jobs to flush
DB(s) and afterward will push additional completion-job request. By sending the
completion job request only at the end, the main thread will be called back only
after all the preceding jobs completed their task in the background. During that
time, the client of the command is suspended and marked as `BLOCKED_LAZYFREE`
whereas any other client will be able to communicate with the server without any
issue.
Users who abuse lua error_reply will generate a new error object on each
error call, which can make server.errors get bigger and bigger. This
will
cause the server to block when calling INFO (we also return errorstats
by
default).
To prevent the damage it can cause, when a misuse is detected, we will
print a warning log and disable the errorstats to avoid adding more new
errors. It can be re-enabled via CONFIG RESETSTAT.
Because server.errors may be very large (it may be better now since we
have the limit), config resetstat may block for a while. So in
resetErrorTableStats, we will try to lazyfree server.errors.
See the related discussion at the end of #8217.
After #13072, there is an use-after-free error. In expireScanCallback, we
will delete the dict, and then in dictScan we will continue to use the dict,
like we will doing `dictResumeRehashing(d)` in the end, this casued an error.
In this PR, in freeDictIfNeeded, if the dict's pauserehash is set, don't
delete the dict yet, and then when scan returns try to delete it again.
At the same time, we noticed that there will be similar problems in iterator.
We may also delete elements during the iteration process, causing the dict
to be deleted, so the part related to iter in the PR has also been modified.
dictResetIterator was also missing from the previous kvstoreIteratorNextDict,
we currently have no scenario that elements will be deleted in kvstoreIterator
process, deal with it together to avoid future problems. Added some simple
tests to verify the changes.
In addition, the modification in #13072 omitted initTempDb and emptyDbAsync,
and they were also added. This PR also remove the slow flag from the expire
test (consumes 1.3s) so that problems can be found in CI in the future.
In some cases, users will abuse lua eval. Each EVAL call generates
a new lua script, which is added to the lua interpreter and cached
to redis-server, consuming a large amount of memory over time.
Since EVAL is mostly the one that abuses the lua cache, and these
won't have pipeline issues (i.e. the script won't disappear
unexpectedly,
and cause errors like it would with SCRIPT LOAD and EVALSHA),
we implement a plain FIFO LRU eviction only for these (not for
scripts loaded with SCRIPT LOAD).
### Implementation notes:
When not abused we'll probably have less than 100 scripts, and when
abused we'll have many thousands. So we use a hard coded value of 500
scripts. And considering that we don't have many scripts, then unlike
keys, we don't need to worry about the memory usage of keeping a true
sorted LRU linked list. We compute the SHA of each script anyway,
and put the script in a dict, we can store a listNode there, and use
it for quick removal and re-insertion into an LRU list each time the
script is used.
### New interfaces:
At the same time, a new `evicted_scripts` field is added to
INFO, which represents the number of evicted eval scripts. Users
can check it to see if they are abusing EVAL.
### benchmark:
`./src/redis-benchmark -P 10 -n 1000000 -r 10000000000 eval "return
__rand_int__" 0`
The simple abuse of eval benchmark test that will create 1 million EVAL
scripts. The performance has been improved by 50%, and the max latency
has dropped from 500ms to 13ms (this may be caused by table expansion
inside Lua when the number of scripts is large). And in the INFO memory,
it used to consume 120MB (server cache) + 310MB (lua engine), but now
it only consumes 70KB (server cache) + 210KB (lua_engine) because of
the scripts eviction.
For non-abusive case of about 100 EVAL scripts, there's no noticeable
change in performance or memory usage.
### unlikely potentially breaking change:
in theory, a user can maybe load a
script with EVAL and then use EVALSHA to call it (by calculating the
SHA1 value on the client side), it could be that if we read the docs
carefully we'll realized it's a valid scenario, but we suppose it's
extremely rare. So it may happen that EVALSHA acts on a script created
by EVAL, and the script is evicted and EVALSHA returns a NOSCRIPT error.
that is if you have more than 500 scripts being used in the same
transaction / pipeline.
This solves the second point in #13102.
Even if we have SCRIPT FLUSH ASYNC now, when there are a lot of
lua scripts, SCRIPT FLUSH ASYNC will still block the main thread.
This is because lua_close is executed in the main thread, and lua
heap needs to release a lot of memory.
In this PR, we take the current lua instance on lctx.lua and call
lua_close on it in a background thread, to close it in async way.
This is MeirShpilraien's idea.
# Description
Gather most of the scattered `redisDb`-related code from the per-slot
dict PR (#11695) and turn it to a new data structure, `kvstore`. i.e.
it's a class that represents an array of dictionaries.
# Motivation
The main motivation is code cleanliness, the idea of using an array of
dictionaries is very well-suited to becoming a self-contained data
structure.
This allowed cleaning some ugly code, among others: loops that run twice
on the main dict and expires dict, and duplicate code for allocating and
releasing this data structure.
# Notes
1. This PR reverts the part of https://github.com/redis/redis/pull/12848
where the `rehashing` list is global (handling rehashing `dict`s is
under the responsibility of `kvstore`, and should not be managed by the
server)
2. This PR also replaces the type of `server.pubsubshard_channels` from
`dict**` to `kvstore` (original PR:
https://github.com/redis/redis/pull/12804). After that was done,
server.pubsub_channels was also chosen to be a `kvstore` (with only one
`dict`, which seems odd) just to make the code cleaner by making it the
same type as `server.pubsubshard_channels`, see
`pubsubtype.serverPubSubChannels`
3. the keys and expires kvstores are currenlty configured to allocate
the individual dicts only when the first key is added (unlike before, in
which they allocated them in advance), but they won't release them when
the last key is deleted.
Worth mentioning that due to the recent change the reply of DEBUG
HTSTATS changed, in case no keys were ever added to the db.
before:
```
127.0.0.1:6379> DEBUG htstats 9
[Dictionary HT]
Hash table 0 stats (main hash table):
No stats available for empty dictionaries
[Expires HT]
Hash table 0 stats (main hash table):
No stats available for empty dictionaries
```
after:
```
127.0.0.1:6379> DEBUG htstats 9
[Dictionary HT]
[Expires HT]
```
This PR did some cleanups around function:
- drop the comment about Libraries Ctx, since we do have comment
in functionsLibCtx, no need to maintain multiple copies.
- remove outdated comment about the dropped Library description.
- remove unused desc and code vars in functionExtractLibMetaData.
- fix engines_nemory typo, changed it to engines_memory.
- remove outdated comment about FUNCTION CREATE and FUNCTION INFO,
FUNCTION CREATE was renamed to FUNCTION LOAD.
- Check in initServer whether the return of functionsInit is OK.
After #11695, we added two functions `rehashingStarted` and
`rehashingCompleted` to the dict structure. We also registered two
handlers for the main database's dict and expire structures. This allows
the main database to record the dict in `rehashing` list when rehashing
starts. Later, in `serverCron`, the `incrementallyRehash` function is
continuously called to perform the rehashing operation. However,
currently, when rehashing is completed, `rehashingCompleted` does not
remove the dict from the `rehashing` list. This results in the
`rehashing` list containing many invalid dicts. Although subsequent cron
checks and removes dicts that don't require rehashing, it is still
inefficient.
This PR implements the functionality to remove the dict from the
`rehashing` list in `rehashingCompleted`. This is achieved by adding
`metadata` to the dict structure, which keeps track of its position in
the `rehashing` list, allowing for quick removal. This approach avoids
storing duplicate dicts in the `rehashing` list.
Additionally, there are other modifications:
1. Whether in standalone or cluster mode, the dict in database is
inserted into the rehashing linked list when rehashing starts. This
eliminates the need to distinguish between standalone and cluster mode
in `incrementallyRehash`. The function only needs to focus on the dicts
in the `rehashing` list that require rehashing.
2. `rehashing` list is moved from per-database to Redis server level.
This decouples `incrementallyRehash` from the database ID, and in
standalone mode, there is no need to iterate over all databases,
avoiding unnecessary access to databases that do not require rehashing.
In the future, even if unsharded-cluster mode supports multiple
databases, there will be no risk involved.
3. The insertion and removal operations of dict structures in the
`rehashing` list are decoupled from `activerehashing` config.
`activerehashing` only controls whether `incrementallyRehash` is
executed in serverCron. There is no need for additional steps when
modifying the `activerehashing` switch, as in #12705.
This is an implementation of https://github.com/redis/redis/issues/10589 that eliminates 16 bytes per entry in cluster mode, that are currently used to create a linked list between entries in the same slot. Main idea is splitting main dictionary into 16k smaller dictionaries (one per slot), so we can perform all slot specific operations, such as iteration, without any additional info in the `dictEntry`. For Redis cluster, the expectation is that there will be a larger number of keys, so the fixed overhead of 16k dictionaries will be The expire dictionary is also split up so that each slot is logically decoupled, so that in subsequent revisions we will be able to atomically flush a slot of data.
## Important changes
* Incremental rehashing - one big change here is that it's not one, but rather up to 16k dictionaries that can be rehashing at the same time, in order to keep track of them, we introduce a separate queue for dictionaries that are rehashing. Also instead of rehashing a single dictionary, cron job will now try to rehash as many as it can in 1ms.
* getRandomKey - now needs to not only select a random key, from the random bucket, but also needs to select a random dictionary. Fairness is a major concern here, as it's possible that keys can be unevenly distributed across the slots. In order to address this search we introduced binary index tree). With that data structure we are able to efficiently find a random slot using binary search in O(log^2(slot count)) time.
* Iteration efficiency - when iterating dictionary with a lot of empty slots, we want to skip them efficiently. We can do this using same binary index that is used for random key selection, this index allows us to find a slot for a specific key index. For example if there are 10 keys in the slot 0, then we can quickly find a slot that contains 11th key using binary search on top of the binary index tree.
* scan API - in order to perform a scan across the entire DB, the cursor now needs to not only save position within the dictionary but also the slot id. In this change we append slot id into LSB of the cursor so it can be passed around between client and the server. This has interesting side effect, now you'll be able to start scanning specific slot by simply providing slot id as a cursor value. The plan is to not document this as defined behavior, however. It's also worth nothing the SCAN API is now technically incompatible with previous versions, although practically we don't believe it's an issue.
* Checksum calculation optimizations - During command execution, we know that all of the keys are from the same slot (outside of a few notable exceptions such as cross slot scripts and modules). We don't want to compute the checksum multiple multiple times, hence we are relying on cached slot id in the client during the command executions. All operations that access random keys, either should pass in the known slot or recompute the slot.
* Slot info in RDB - in order to resize individual dictionaries correctly, while loading RDB, it's not enough to know total number of keys (of course we could approximate number of keys per slot, but it won't be precise). To address this issue, we've added additional metadata into RDB that contains number of keys in each slot, which can be used as a hint during loading.
* DB size - besides `DBSIZE` API, we need to know size of the DB in many places want, in order to avoid scanning all dictionaries and summing up their sizes in a loop, we've introduced a new field into `redisDb` that keeps track of `key_count`. This way we can keep DBSIZE operation O(1). This is also kept for O(1) expires computation as well.
## Performance
This change improves SET performance in cluster mode by ~5%, most of the gains come from us not having to maintain linked lists for keys in slot, non-cluster mode has same performance. For workloads that rely on evictions, the performance is similar because of the extra overhead for finding keys to evict.
RDB loading performance is slightly reduced, as the slot of each key needs to be computed during the load.
## Interface changes
* Removed `overhead.hashtable.slot-to-keys` to `MEMORY STATS`
* Scan API will now require 64 bits to store the cursor, even on 32 bit systems, as the slot information will be stored.
* New RDB version to support the new op code for SLOT information.
---------
Co-authored-by: Vitaly Arbuzov <arvit@amazon.com>
Co-authored-by: Harkrishn Patro <harkrisp@amazon.com>
Co-authored-by: Roshan Khatri <rvkhatri@amazon.com>
Co-authored-by: Madelyn Olson <madelyneolson@gmail.com>
Co-authored-by: Oran Agra <oran@redislabs.com>
Technically declaring a prototype with an empty declaration has been deprecated since the early days of C, but we never got a warning for it. C2x will apparently be introducing a breaking change if you are using this type of declarator, so Clang 15 has started issuing a warning with -pedantic. Although not apparently a problem for any of the compiler we build on, if feels like the right thing is to properly adhere to the C standard and use (void).
Improve memory efficiency of list keys
## Description of the feature
The new listpack encoding uses the old `list-max-listpack-size` config
to perform the conversion, which we can think it of as a node inside a
quicklist, but without 80 bytes overhead (internal fragmentation included)
of quicklist and quicklistNode structs.
For example, a list key with 5 items of 10 chars each, now takes 128 bytes
instead of 208 it used to take.
## Conversion rules
* Convert listpack to quicklist
When the listpack length or size reaches the `list-max-listpack-size` limit,
it will be converted to a quicklist.
* Convert quicklist to listpack
When a quicklist has only one node, and its length or size is reduced to half
of the `list-max-listpack-size` limit, it will be converted to a listpack.
This is done to avoid frequent conversions when we add or remove at the bounding size or length.
## Interface changes
1. add list entry param to listTypeSetIteratorDirection
When list encoding is listpack, `listTypeIterator->lpi` points to the next entry of current entry,
so when changing the direction, we need to use the current node (listTypeEntry->p) to
update `listTypeIterator->lpi` to the next node in the reverse direction.
## Benchmark
### Listpack VS Quicklist with one node
* LPUSH - roughly 0.3% improvement
* LRANGE - roughly 13% improvement
### Both are quicklist
* LRANGE - roughly 3% improvement
* LRANGE without pipeline - roughly 3% improvement
From the benchmark, as we can see from the results
1. When list is quicklist encoding, LRANGE improves performance by <5%.
2. When list is listpack encoding, LRANGE improves performance by ~13%,
the main enhancement is brought by `addListListpackRangeReply()`.
## Memory usage
1M lists(key:0~key:1000000) with 5 items of 10 chars ("hellohello") each.
shows memory usage down by 35.49%, from 214MB to 138MB.
## Note
1. Add conversion callback to support doing some work before conversion
Since the quicklist iterator decompresses the current node when it is released, we can
no longer decompress the quicklist after we convert the list.
# Redis Function Libraries
This PR implements Redis Functions Libraries as describe on: https://github.com/redis/redis/issues/9906.
Libraries purpose is to provide a better code sharing between functions by allowing to create multiple
functions in a single command. Functions that were created together can safely share code between
each other without worrying about compatibility issues and versioning.
Creating a new library is done using 'FUNCTION LOAD' command (full API is described below)
This PR introduces a new struct called libraryInfo, libraryInfo holds information about a library:
* name - name of the library
* engine - engine used to create the library
* code - library code
* description - library description
* functions - the functions exposed by the library
When Redis gets the `FUNCTION LOAD` command it creates a new empty libraryInfo.
Redis passes the `CODE` to the relevant engine alongside the empty libraryInfo.
As a result, the engine will create one or more functions by calling 'libraryCreateFunction'.
The new funcion will be added to the newly created libraryInfo. So far Everything is happening
locally on the libraryInfo so it is easy to abort the operation (in case of an error) by simply
freeing the libraryInfo. After the library info is fully constructed we start the joining phase by
which we will join the new library to the other libraries currently exist on Redis.
The joining phase make sure there is no function collision and add the library to the
librariesCtx (renamed from functionCtx). LibrariesCtx is used all around the code in the exact
same way as functionCtx was used (with respect to RDB loading, replicatio, ...).
The only difference is that apart from function dictionary (maps function name to functionInfo
object), the librariesCtx contains also a libraries dictionary that maps library name to libraryInfo object.
## New API
### FUNCTION LOAD
`FUNCTION LOAD <ENGINE> <LIBRARY NAME> [REPLACE] [DESCRIPTION <DESCRIPTION>] <CODE>`
Create a new library with the given parameters:
* ENGINE - REPLACE Engine name to use to create the library.
* LIBRARY NAME - The new library name.
* REPLACE - If the library already exists, replace it.
* DESCRIPTION - Library description.
* CODE - Library code.
Return "OK" on success, or error on the following cases:
* Library name already taken and REPLACE was not used
* Name collision with another existing library (even if replace was uses)
* Library registration failed by the engine (usually compilation error)
## Changed API
### FUNCTION LIST
`FUNCTION LIST [LIBRARYNAME <LIBRARY NAME PATTERN>] [WITHCODE]`
Command was modified to also allow getting libraries code (so `FUNCTION INFO` command is no longer
needed and removed). In addition the command gets an option argument, `LIBRARYNAME` allows you to
only get libraries that match the given `LIBRARYNAME` pattern. By default, it returns all libraries.
### INFO MEMORY
Added number of libraries to `INFO MEMORY`
### Commands flags
`DENYOOM` flag was set on `FUNCTION LOAD` and `FUNCTION RESTORE`. We consider those commands
as commands that add new data to the dateset (functions are data) and so we want to disallows
to run those commands on OOM.
## Removed API
* FUNCTION CREATE - Decided on https://github.com/redis/redis/issues/9906
* FUNCTION INFO - Decided on https://github.com/redis/redis/issues/9899
## Lua engine changes
When the Lua engine gets the code given on `FUNCTION LOAD` command, it immediately runs it, we call
this run the loading run. Loading run is not a usual script run, it is not possible to invoke any
Redis command from within the load run.
Instead there is a new API provided by `library` object. The new API's:
* `redis.log` - behave the same as `redis.log`
* `redis.register_function` - register a new function to the library
The loading run purpose is to register functions using the new `redis.register_function` API.
Any attempt to use any other API will result in an error. In addition, the load run is has a time
limit of 500ms, error is raise on timeout and the entire operation is aborted.
### `redis.register_function`
`redis.register_function(<function_name>, <callback>, [<description>])`
This new API allows users to register a new function that will be linked to the newly created library.
This API can only be called during the load run (see definition above). Any attempt to use it outside
of the load run will result in an error.
The parameters pass to the API are:
* function_name - Function name (must be a Lua string)
* callback - Lua function object that will be called when the function is invokes using fcall/fcall_ro
* description - Function description, optional (must be a Lua string).
### Example
The following example creates a library called `lib` with 2 functions, `f1` and `f1`, returns 1 and 2 respectively:
```
local function f1(keys, args)
return 1
end
local function f2(keys, args)
return 2
end
redis.register_function('f1', f1)
redis.register_function('f2', f2)
```
Notice: Unlike `eval`, functions inside a library get the KEYS and ARGV as arguments to the
functions and not as global.
### Technical Details
On the load run we only want the user to be able to call a white list on API's. This way, in
the future, if new API's will be added, the new API's will not be available to the load run
unless specifically added to this white list. We put the while list on the `library` object and
make sure the `library` object is only available to the load run by using [lua_setfenv](https://www.lua.org/manual/5.1/manual.html#lua_setfenv) API. This API allows us to set
the `globals` of a function (and all the function it creates). Before starting the load run we
create a new fresh Lua table (call it `g`) that only contains the `library` API (we make sure
to set global protection on this table just like the general global protection already exists
today), then we use [lua_setfenv](https://www.lua.org/manual/5.1/manual.html#lua_setfenv)
to set `g` as the global table of the load run. After the load run finished we update `g`
metatable and set `__index` and `__newindex` functions to be `_G` (Lua default globals),
we also pop out the `library` object as we do not need it anymore.
This way, any function that was created on the load run (and will be invoke using `fcall`) will
see the default globals as it expected to see them and will not have the `library` API anymore.
An important outcome of this new approach is that now we can achieve a distinct global table
for each library (it is not yet like that but it is very easy to achieve it now). In the future we can
decide to remove global protection because global on different libraries will not collide or we
can chose to give different API to different libraries base on some configuration or input.
Notice that this technique was meant to prevent errors and was not meant to prevent malicious
user from exploit it. For example, the load run can still save the `library` object on some local
variable and then using in `fcall` context. To prevent such a malicious use, the C code also make
sure it is running in the right context and if not raise an error.
Added `FUNCTION FLUSH` command. The new sub-command allows delete all the functions.
An optional `[SYNC|ASYNC]` argument can be given to control whether or not to flush the
functions synchronously or asynchronously. if not given the default flush mode is chosen by
`lazyfree-lazy-user-flush` configuration values.
Add the missing `functions.tcl` test to the list of tests that are executed in test_helper.tcl,
and call FUNCTION FLUSH in between servers in external mode
## Background
For redis master, one replica uses one copy of replication buffer, that is a big waste of memory,
more replicas more waste, and allocate/free memory for every reply list also cost much.
If we set client-output-buffer-limit small and write traffic is heavy, master may disconnect with
replicas and can't finish synchronization with replica. If we set client-output-buffer-limit big,
master may be OOM when there are many replicas that separately keep much memory.
Because replication buffers of different replica client are the same, one simple idea is that
all replicas only use one replication buffer, that will effectively save memory.
Since replication backlog content is the same as replicas' output buffer, now we
can discard replication backlog memory and use global shared replication buffer
to implement replication backlog mechanism.
## Implementation
I create one global "replication buffer" which contains content of replication stream.
The structure of "replication buffer" is similar to the reply list that exists in every client.
But the node of list is `replBufBlock`, which has `id, repl_offset, refcount` fields.
```c
/* Replication buffer blocks is the list of replBufBlock.
*
* +--------------+ +--------------+ +--------------+
* | refcount = 1 | ... | refcount = 0 | ... | refcount = 2 |
* +--------------+ +--------------+ +--------------+
* | / \
* | / \
* | / \
* Repl Backlog Replia_A Replia_B
*
* Each replica or replication backlog increments only the refcount of the
* 'ref_repl_buf_node' which it points to. So when replica walks to the next
* node, it should first increase the next node's refcount, and when we trim
* the replication buffer nodes, we remove node always from the head node which
* refcount is 0. If the refcount of the head node is not 0, we must stop
* trimming and never iterate the next node. */
/* Similar with 'clientReplyBlock', it is used for shared buffers between
* all replica clients and replication backlog. */
typedef struct replBufBlock {
int refcount; /* Number of replicas or repl backlog using. */
long long id; /* The unique incremental number. */
long long repl_offset; /* Start replication offset of the block. */
size_t size, used;
char buf[];
} replBufBlock;
```
So now when we feed replication stream into replication backlog and all replicas, we only need
to feed stream into replication buffer `feedReplicationBuffer`. In this function, we set some fields of
replication backlog and replicas to references of the global replication buffer blocks. And we also
need to check replicas' output buffer limit to free if exceeding `client-output-buffer-limit`, and trim
replication backlog if exceeding `repl-backlog-size`.
When sending reply to replicas, we also need to iterate replication buffer blocks and send its
content, when totally sending one block for replica, we decrease current node count and
increase the next current node count, and then free the block which reference is 0 from the
head of replication buffer blocks.
Since now we use linked list to manage replication backlog, it may cost much time for iterating
all linked list nodes to find corresponding replication buffer node. So we create a rax tree to
store some nodes for index, but to avoid rax tree occupying too much memory, i record
one per 64 nodes for index.
Currently, to make partial resynchronization as possible as much, we always let replication
backlog as the last reference of replication buffer blocks, backlog size may exceeds our setting
if slow replicas that reference vast replication buffer blocks, and this method doesn't increase
memory usage since they share replication buffer. To avoid freezing server for freeing unreferenced
replication buffer blocks when we need to trim backlog for exceeding backlog size setting,
we trim backlog incrementally (free 64 blocks per call now), and make it faster in
`beforeSleep` (free 640 blocks).
### Other changes
- `mem_total_replication_buffers`: we add this field in INFO command, it means the total
memory of replication buffers used.
- `mem_clients_slaves`: now even replica is slow to replicate, and its output buffer memory
is not 0, but it still may be 0, since replication backlog and replicas share one global replication
buffer, only if replication buffer memory is more than the repl backlog setting size, we consider
the excess as replicas' memory. Otherwise, we think replication buffer memory is the consumption
of repl backlog.
- Key eviction
Since all replicas and replication backlog share global replication buffer, we think only the
part of exceeding backlog size the extra separate consumption of replicas.
Because we trim backlog incrementally in the background, backlog size may exceeds our
setting if slow replicas that reference vast replication buffer blocks disconnect.
To avoid massive eviction loop, we don't count the delayed freed replication backlog into
used memory even if there are no replicas, i.e. we also regard this memory as replicas's memory.
- `client-output-buffer-limit` check for replica clients
It doesn't make sense to set the replica clients output buffer limit lower than the repl-backlog-size
config (partial sync will succeed and then replica will get disconnected). Such a configuration is
ignored (the size of repl-backlog-size will be used). This doesn't have memory consumption
implications since the replica client will share the backlog buffers memory.
- Drop replication backlog after loading data if needed
We always create replication backlog if server is a master, we need it because we put DELs in
it when loading expired keys in RDB, but if RDB doesn't have replication info or there is no rdb,
it is not possible to support partial resynchronization, to avoid extra memory of replication backlog,
we drop it.
- Multi IO threads
Since all replicas and replication backlog use global replication buffer, if I/O threads are enabled,
to guarantee data accessing thread safe, we must let main thread handle sending the output buffer
to all replicas. But before, other IO threads could handle sending output buffer of all replicas.
## Other optimizations
This solution resolve some other problem:
- When replicas disconnect with master since of out of output buffer limit, releasing the output
buffer of replicas may freeze server if we set big `client-output-buffer-limit` for replicas, but now,
it doesn't cause freezing.
- This implementation may mitigate reply list copy cost time(also freezes server) when one replication
has huge reply buffer and another replica can copy buffer for full synchronization. now, we just copy
reference info, it is very light.
- If we set replication backlog size big, it also may cost much time to copy replication backlog into
replica's output buffer. But this commit eliminates this problem.
- Resizing replication backlog size doesn't empty current replication backlog content.
* Enhance dict to support arbitrary metadata carried in dictEntry
Co-authored-by: Viktor Söderqvist <viktor.soderqvist@est.tech>
* Rewrite slot-to-keys mapping to linked lists using dict entry metadata
This is a memory enhancement for Redis Cluster.
The radix tree slots_to_keys (which duplicates all key names prefixed with their
slot number) is replaced with a linked list for each slot. The dict entries of
the same cluster slot form a linked list and the pointers are stored as metadata
in each dict entry of the main DB dict.
This commit also moves the slot-to-key API from db.c to cluster.c.
Co-authored-by: Jim Brunner <brunnerj@amazon.com>
Reduce dict struct memory overhead
on 64bit dict size goes down from jemalloc's 96 byte bin to its 56 byte bin.
summary of changes:
- Remove `privdata` from callbacks and dict creation. (this affects many files, see "Interface change" below).
- Meld `dictht` struct into the `dict` struct to eliminate struct padding. (this affects just dict.c and defrag.c)
- Eliminate the `sizemask` field, can be calculated from size when needed.
- Convert the `size` field into `size_exp` (exponent), utilizes one byte instead of 8.
Interface change: pass dict pointer to dict type call back functions.
This is instead of passing the removed privdata field. In the future if
we'd like to have private data in the callbacks we can extract it from
the dict type. We can extend dictType to include a custom dict struct
allocator and use it to allocate more data at the end of the dict
struct. This data can then be used to store private data later acccessed
by the callbacks.
Create new module type enhanced callbacks: mem_usage2, free_effort2, unlink2, copy2.
These will be given a context point from which the module can obtain the key name and database id.
In addition the digest and defrag context can now be used to obtain the key name and database id.
Without this fix, FLUSHALL ASYNC would have freed these in a background thread,
even if they didn't contain many elements (unlike how it works with other structures), which could be inefficient.
When estimating the effort for unlink, we try to compute the effort of
the first group and extrapolate.
If there's a groups rax that's empty, there'a an assertion.
reproduce:
xadd s * a b
xgroup create s bla $
xgroup destroy s bla
unlink s
* Adds ASYNC and SYNC arguments to SCRIPT FLUSH
* Adds SYNC argument to FLUSHDB and FLUSHALL
* Adds new config to control the default behavior of FLUSHDB, FLUSHALL and SCRIPT FLUASH.
the new behavior is as follows:
* FLUSH[ALL|DB],SCRIPT FLUSH: Determine sync or async according to the
value of lazyfree-lazy-user-flush.
* FLUSH[ALL|DB],SCRIPT FLUSH ASYNC: Always flushes the database in an async manner.
* FLUSH[ALL|DB],SCRIPT FLUSH SYNC: Always flushes the database in a sync manner.
As we know, redis may reject user's requests or evict some keys if
used memory is over maxmemory. Dictionaries expanding may make
things worse, some big dictionaries, such as main db and expires dict,
may eat huge memory at once for allocating a new big hash table and be
far more than maxmemory after expanding.
There are related issues: #4213#4583
More details, when expand dict in redis, we will allocate a new big
ht[1] that generally is double of ht[0], The size of ht[1] will be
very big if ht[0] already is big. For db dict, if we have more than
64 million keys, we need to cost 1GB for ht[1] when dict expands.
If the sum of used memory and new hash table of dict needed exceeds
maxmemory, we shouldn't allow the dict to expand. Because, if we
enable keys eviction, we still couldn't add much more keys after
eviction and rehashing, what's worse, redis will keep less keys when
redis only remains a little memory for storing new hash table instead
of users' data. Moreover users can't write data in redis if disable
keys eviction.
What this commit changed ?
Add a new member function expandAllowed for dict type, it provide a way
for caller to allow expand or not. We expose two parameters for this
function: more memory needed for expanding and dict current load factor,
users can implement a function to make a decision by them.
For main db dict and expires dict type, these dictionaries may be very
big and cost huge memory for expanding, so we implement a judgement
function: we can stop dict to expand provisionally if used memory will
be over maxmemory after dict expands, but to guarantee the performance
of redis, we still allow dict to expand if dict load factor exceeds the
safe load factor.
Add test cases to verify we don't allow main db to expand when left
memory is not enough, so that avoid keys eviction.
Other changes:
For new hash table size when expand. Before this commit, the size is
that double used of dict and later _dictNextPower. Actually we aim to
control a dict load factor between 0.5 and 1.0. Now we replace *2 with
+1, since the first check is that used >= size, the outcome of before
will usually be the same as _dictNextPower(used+1). The only case where
it'll differ is when dict_can_resize is false during fork, so that later
the _dictNextPower(used*2) will cause the dict to jump to *4 (i.e.
_dictNextPower(1025*2) will return 4096).
Fix rehash test cases due to changing algorithm of new hash table size
when expand.
When replica diskless-load type is swapdb in cluster mode, we didn't backup
keys to slots map, so we will lose keys to slots map if fail to sync.
Now we backup keys to slots map at first, and restore it properly when fail.
This commit includes a refactory/cleanup of the backups mechanism (moving it to db.c and re-structuring it a bit).
Co-authored-by: Oran Agra <oran@redislabs.com>
Add two optional callbacks to the RedisModuleTypeMethods structure, which is `free_effort`
and `unlink`. the `free_effort` callback indicates the effort required to free a module memory.
Currently, if the effort exceeds LAZYFREE_THRESHOLD, the module memory may be released
asynchronously. the `unlink` callback indicates the key has been removed from the DB by redis, and
may soon be freed by a background thread.
Add `lazyfreed_objects` info field, which represents the number of objects that have been
lazyfreed since redis was started.
Add `RM_GetTypeMethodVersion` API, which return the current redis-server runtime value of
`REDISMODULE_TYPE_METHOD_VERSION`. You can use that when calling `RM_CreateDataType` to know
which fields of RedisModuleTypeMethods are gonna be supported and which will be ignored.
Redis 6.0 introduces I/O threads, it is so cool and efficient, we use C11
_Atomic to establish inter-thread synchronization without mutex. But the
compiler that must supports C11 _Atomic can compile redis code, that brings a
lot of inconvenience since some common platforms can't support by default such
as CentOS7, so we want to implement redis atomic type to make it more portable.
We have implemented our atomic variable for redis that only has 'relaxed'
operations in src/atomicvar.h, so we implement some operations with
'sequentially-consistent', just like the default behavior of C11 _Atomic that
can establish inter-thread synchronization. And we replace all uses of C11
_Atomic with redis atomic variable.
Our implementation of redis atomic variable uses C11 _Atomic, __atomic or
__sync macros if available, it supports most common platforms, and we will
detect automatically which feature we use. In Makefile we use a dummy file to
detect if the compiler supports C11 _Atomic. Now for gcc, we can compile redis
code theoretically if your gcc version is not less than 4.1.2(starts to support
__sync_xxx operations). Otherwise, we remove use mutex fallback to implement
redis atomic variable for performance and test. You will get compiling errors
if your compiler doesn't support all features of above.
For cover redis atomic variable tests, we add other CI jobs that build redis on
CentOS6 and CentOS7 and workflow daily jobs that run the tests on them.
For them, we just install gcc by default in order to cover different compiler
versions, gcc is 4.4.7 by default installation on CentOS6 and 4.8.5 on CentOS7.
We restore the feature that we can test redis with Helgrind to find data race
errors. But you need install Valgrind in the default path configuration firstly
before running your tests, since we use macros in helgrind.h to tell Helgrind
inter-thread happens-before relationship explicitly for avoiding false positives.
Please open an issue on github if you find data race errors relate to this commit.
Unrelated:
- Fix redefinition of typedef 'RedisModuleUserChangedFunc'
For some old version compilers, they will report errors or warnings, if we
re-define function type.
Otherwise, it is treated as a single allocation and freed synchronously. The following logic is used for estimating the effort in constant-ish time complexity:
1. Check the number of nodes.
1. Add an allocation for each consumer group registered inside the stream.
1. Check the number of PELs in the first CG, and then add this count times the number of CGs.
1. Check the number of consumers in the first CG, and then add this count times the number of CGs.
Reloading of the RDB generated by
DEBUG POPULATE 5000000
SAVE
is now 25% faster.
This commit also prepares the ability to have more flexibility when
loading stuff from the RDB, since we no longer use dbAdd() but can
control exactly how things are added in the database.
Moti Cohen