mirror of
https://github.com/redis/redis.git
synced 2026-02-11 14:53:19 -05:00
## 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>
599 lines
21 KiB
Tcl
599 lines
21 KiB
Tcl
start_server {tags {"maxmemory" "external:skip"}} {
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r config set maxmemory 11mb
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r config set maxmemory-policy allkeys-lru
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set server_pid [s process_id]
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proc init_test {client_eviction} {
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r flushdb
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set prev_maxmemory_clients [r config get maxmemory-clients]
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if $client_eviction {
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r config set maxmemory-clients 3mb
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r client no-evict on
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} else {
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r config set maxmemory-clients 0
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}
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r config resetstat
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# fill 5mb using 50 keys of 100kb
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for {set j 0} {$j < 50} {incr j} {
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r setrange $j 100000 x
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}
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assert_equal [r dbsize] 50
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}
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# Return true if the eviction occurred (client or key) based on argument
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proc check_eviction_test {client_eviction} {
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set evicted_keys [s evicted_keys]
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set evicted_clients [s evicted_clients]
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set dbsize [r dbsize]
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if $client_eviction {
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if {[lindex [r config get io-threads] 1] == 1} {
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return [expr $evicted_clients > 0 && $evicted_keys == 0 && $dbsize == 50]
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} else {
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return [expr $evicted_clients >= 0 && $evicted_keys >= 0 && $dbsize <= 50]
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}
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} else {
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return [expr $evicted_clients == 0 && $evicted_keys > 0 && $dbsize < 50]
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}
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}
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# Assert the eviction test passed (and prints some debug info on verbose)
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proc verify_eviction_test {client_eviction} {
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set evicted_keys [s evicted_keys]
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set evicted_clients [s evicted_clients]
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set dbsize [r dbsize]
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if $::verbose {
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puts "evicted keys: $evicted_keys"
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puts "evicted clients: $evicted_clients"
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puts "dbsize: $dbsize"
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}
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assert [check_eviction_test $client_eviction]
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}
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foreach {client_eviction} {false true} {
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set clients {}
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test "eviction due to output buffers of many MGET clients, client eviction: $client_eviction" {
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init_test $client_eviction
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for {set j 0} {$j < 20} {incr j} {
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set rr [redis_deferring_client]
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lappend clients $rr
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}
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# Generate client output buffers via MGET until we can observe some effect on
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# keys / client eviction, or we time out.
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set t [clock seconds]
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while {![check_eviction_test $client_eviction] && [expr [clock seconds] - $t] < 20} {
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foreach rr $clients {
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if {[catch {
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$rr mget 1
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$rr flush
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} err]} {
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lremove clients $rr
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}
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}
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}
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verify_eviction_test $client_eviction
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}
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foreach rr $clients {
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$rr close
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}
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set clients {}
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test "eviction due to input buffer of a dead client, client eviction: $client_eviction" {
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init_test $client_eviction
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for {set j 0} {$j < 30} {incr j} {
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set rr [redis_deferring_client]
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lappend clients $rr
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}
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foreach rr $clients {
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if {[catch {
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$rr write "*250\r\n"
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for {set j 0} {$j < 249} {incr j} {
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$rr write "\$1000\r\n"
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$rr write [string repeat x 1000]
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$rr write "\r\n"
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$rr flush
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}
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}]} {
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lremove clients $rr
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}
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}
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verify_eviction_test $client_eviction
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}
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foreach rr $clients {
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$rr close
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}
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set clients {}
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test "eviction due to output buffers of pubsub, client eviction: $client_eviction" {
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init_test $client_eviction
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for {set j 0} {$j < 20} {incr j} {
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set rr [redis_client]
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lappend clients $rr
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}
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foreach rr $clients {
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$rr subscribe bla
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}
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# Generate client output buffers via PUBLISH until we can observe some effect on
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# keys / client eviction, or we time out.
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set bigstr [string repeat x 100000]
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set t [clock seconds]
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while {![check_eviction_test $client_eviction] && [expr [clock seconds] - $t] < 20} {
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if {[catch { r publish bla $bigstr } err]} {
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if $::verbose {
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puts "Error publishing: $err"
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}
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}
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}
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verify_eviction_test $client_eviction
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}
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foreach rr $clients {
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$rr close
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}
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}
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}
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start_server {tags {"maxmemory external:skip"}} {
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test "Without maxmemory small integers are shared" {
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r config set maxmemory 0
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r set a 1
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assert_refcount_morethan a 1
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}
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test "With maxmemory and non-LRU policy integers are still shared" {
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r config set maxmemory 1073741824
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r config set maxmemory-policy allkeys-random
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r set a 1
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assert_refcount_morethan a 1
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}
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test "With maxmemory and LRU policy integers are not shared" {
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r config set maxmemory 1073741824
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r config set maxmemory-policy allkeys-lru
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r set a 1
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r config set maxmemory-policy volatile-lru
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r set b 1
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assert_refcount 1 a
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assert_refcount 1 b
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r config set maxmemory 0
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}
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foreach policy {
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allkeys-random allkeys-lru allkeys-lfu volatile-lru volatile-lfu volatile-random volatile-ttl
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} {
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test "maxmemory - is the memory limit honoured? (policy $policy)" {
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# make sure to start with a blank instance
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r flushall
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# Get the current memory limit and calculate a new limit.
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# We just add 100k to the current memory size so that it is
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# fast for us to reach that limit.
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set used [s used_memory]
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set limit [expr {$used+100*1024}]
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r config set maxmemory $limit
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r config set maxmemory-policy $policy
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# Now add keys until the limit is almost reached.
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set numkeys 0
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while 1 {
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r setex [randomKey] 10000 x
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incr numkeys
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if {[s used_memory]+4096 > $limit} {
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assert {$numkeys > 10}
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break
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}
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}
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# If we add the same number of keys already added again, we
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# should still be under the limit.
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for {set j 0} {$j < $numkeys} {incr j} {
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r setex [randomKey] 10000 x
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}
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assert {[s used_memory] < ($limit+4096)}
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}
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}
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foreach policy {
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allkeys-random allkeys-lru volatile-lru volatile-random volatile-ttl
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} {
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test "maxmemory - only allkeys-* should remove non-volatile keys ($policy)" {
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# make sure to start with a blank instance
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r flushall
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# Get the current memory limit and calculate a new limit.
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# We just add 100k to the current memory size so that it is
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# fast for us to reach that limit.
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set used [s used_memory]
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set limit [expr {$used+100*1024}]
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r config set maxmemory $limit
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r config set maxmemory-policy $policy
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# Now add keys until the limit is almost reached.
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set numkeys 0
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while 1 {
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r set [randomKey] x
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incr numkeys
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if {[s used_memory]+4096 > $limit} {
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assert {$numkeys > 10}
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break
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}
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}
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# If we add the same number of keys already added again and
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# the policy is allkeys-* we should still be under the limit.
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# Otherwise we should see an error reported by Redis.
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set err 0
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for {set j 0} {$j < $numkeys} {incr j} {
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if {[catch {r set [randomKey] x} e]} {
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if {[string match {*used memory*} $e]} {
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set err 1
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}
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}
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}
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if {[string match allkeys-* $policy]} {
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assert {[s used_memory] < ($limit+4096)}
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} else {
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assert {$err == 1}
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}
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}
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}
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foreach policy {
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volatile-lru volatile-lfu volatile-random volatile-ttl
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} {
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test "maxmemory - policy $policy should only remove volatile keys." {
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# make sure to start with a blank instance
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r flushall
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# Get the current memory limit and calculate a new limit.
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# We just add 100k to the current memory size so that it is
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# fast for us to reach that limit.
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set used [s used_memory]
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set limit [expr {$used+100*1024}]
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r config set maxmemory $limit
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r config set maxmemory-policy $policy
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# Now add keys until the limit is almost reached.
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set numkeys 0
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while 1 {
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# Odd keys are volatile
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# Even keys are non volatile
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if {$numkeys % 2} {
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r setex "key:$numkeys" 10000 x
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} else {
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r set "key:$numkeys" x
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}
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if {[s used_memory]+4096 > $limit} {
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assert {$numkeys > 10}
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break
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}
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incr numkeys
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}
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# Now we add the same number of volatile keys already added.
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# We expect Redis to evict only volatile keys in order to make
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# space.
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set err 0
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for {set j 0} {$j < $numkeys} {incr j} {
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catch {r setex "foo:$j" 10000 x}
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}
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# We should still be under the limit.
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assert {[s used_memory] < ($limit+4096)}
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# However all our non volatile keys should be here.
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for {set j 0} {$j < $numkeys} {incr j 2} {
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assert {[r exists "key:$j"]}
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}
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}
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}
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}
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# Calculate query buffer memory of slave
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proc slave_query_buffer {srv} {
|
|
set clients [split [$srv client list] "\r\n"]
|
|
set c [lsearch -inline $clients *flags=S*]
|
|
if {[string length $c] > 0} {
|
|
assert {[regexp {qbuf=([0-9]+)} $c - qbuf]}
|
|
assert {[regexp {qbuf-free=([0-9]+)} $c - qbuf_free]}
|
|
return [expr $qbuf + $qbuf_free]
|
|
}
|
|
return 0
|
|
}
|
|
|
|
proc test_slave_buffers {test_name cmd_count payload_len limit_memory pipeline} {
|
|
start_server {tags {"maxmemory external:skip"}} {
|
|
start_server {} {
|
|
set slave_pid [s process_id]
|
|
test "$test_name" {
|
|
set slave [srv 0 client]
|
|
set slave_host [srv 0 host]
|
|
set slave_port [srv 0 port]
|
|
set master [srv -1 client]
|
|
set master_host [srv -1 host]
|
|
set master_port [srv -1 port]
|
|
|
|
# Disable slow log for master to avoid memory growth in slow env.
|
|
$master config set slowlog-log-slower-than -1
|
|
|
|
# add 100 keys of 100k (10MB total)
|
|
for {set j 0} {$j < 100} {incr j} {
|
|
$master setrange "key:$j" 100000 asdf
|
|
}
|
|
|
|
# make sure master doesn't disconnect slave because of timeout
|
|
$master config set repl-timeout 1200 ;# 20 minutes (for valgrind and slow machines)
|
|
$master config set maxmemory-policy allkeys-random
|
|
$master config set client-output-buffer-limit "replica 100000000 100000000 300"
|
|
$master config set repl-backlog-size [expr {10*1024}]
|
|
|
|
# disable latency tracking
|
|
$master config set latency-tracking no
|
|
$slave config set latency-tracking no
|
|
|
|
$slave slaveof $master_host $master_port
|
|
wait_for_condition 50 100 {
|
|
[s 0 master_link_status] eq {up}
|
|
} else {
|
|
fail "Replication not started."
|
|
}
|
|
|
|
# measure used memory after the slave connected and set maxmemory
|
|
set orig_used [s -1 used_memory]
|
|
set orig_client_buf [s -1 mem_clients_normal]
|
|
set orig_mem_not_counted_for_evict [s -1 mem_not_counted_for_evict]
|
|
set orig_used_no_repl [expr {$orig_used - $orig_mem_not_counted_for_evict}]
|
|
set limit [expr {$orig_used - $orig_mem_not_counted_for_evict + 32*1024}]
|
|
|
|
if {$limit_memory==1} {
|
|
$master config set maxmemory $limit
|
|
}
|
|
|
|
# put the slave to sleep
|
|
set rd_slave [redis_deferring_client]
|
|
pause_process $slave_pid
|
|
|
|
# send some 10mb worth of commands that don't increase the memory usage
|
|
if {$pipeline == 1} {
|
|
set rd_master [redis_deferring_client -1]
|
|
for {set k 0} {$k < $cmd_count} {incr k} {
|
|
$rd_master setrange key:0 0 [string repeat A $payload_len]
|
|
}
|
|
for {set k 0} {$k < $cmd_count} {incr k} {
|
|
$rd_master read
|
|
}
|
|
} else {
|
|
for {set k 0} {$k < $cmd_count} {incr k} {
|
|
$master setrange key:0 0 [string repeat A $payload_len]
|
|
}
|
|
}
|
|
|
|
set new_used [s -1 used_memory]
|
|
set slave_buf [s -1 mem_clients_slaves]
|
|
set client_buf [s -1 mem_clients_normal]
|
|
set mem_not_counted_for_evict [s -1 mem_not_counted_for_evict]
|
|
set used_no_repl [expr {$new_used - $mem_not_counted_for_evict - [slave_query_buffer $master]}]
|
|
# we need to exclude replies buffer and query buffer of replica from used memory.
|
|
# removing the replica (output) buffers is done so that we are able to measure any other
|
|
# changes to the used memory and see that they're insignificant (the test's purpose is to check that
|
|
# the replica buffers are counted correctly, so the used memory growth after deducting them
|
|
# should be nearly 0).
|
|
# we remove the query buffers because on slow test platforms, they can accumulate many ACKs.
|
|
set delta [expr {($used_no_repl - $client_buf) - ($orig_used_no_repl - $orig_client_buf)}]
|
|
|
|
assert {[$master dbsize] == 100}
|
|
assert {$slave_buf > 2*1024*1024} ;# some of the data may have been pushed to the OS buffers
|
|
set delta_max [expr {$cmd_count / 2}] ;# 1 byte unaccounted for, with 1M commands will consume some 1MB
|
|
assert {$delta < $delta_max && $delta > -$delta_max}
|
|
|
|
$master client kill type slave
|
|
set info_str [$master info memory]
|
|
set killed_used [getInfoProperty $info_str used_memory]
|
|
set killed_mem_not_counted_for_evict [getInfoProperty $info_str mem_not_counted_for_evict]
|
|
set killed_slave_buf [s -1 mem_clients_slaves]
|
|
# we need to exclude replies buffer and query buffer of slave from used memory after kill slave
|
|
set killed_used_no_repl [expr {$killed_used - $killed_mem_not_counted_for_evict - [slave_query_buffer $master]}]
|
|
set delta_no_repl [expr {$killed_used_no_repl - $used_no_repl}]
|
|
assert {[$master dbsize] == 100}
|
|
assert {$killed_slave_buf == 0}
|
|
assert {$delta_no_repl > -$delta_max && $delta_no_repl < $delta_max}
|
|
|
|
}
|
|
# unfreeze slave process (after the 'test' succeeded or failed, but before we attempt to terminate the server
|
|
resume_process $slave_pid
|
|
}
|
|
}
|
|
}
|
|
|
|
# test that slave buffer are counted correctly
|
|
# we wanna use many small commands, and we don't wanna wait long
|
|
# so we need to use a pipeline (redis_deferring_client)
|
|
# that may cause query buffer to fill and induce eviction, so we disable it
|
|
test_slave_buffers {slave buffer are counted correctly} 1000000 10 0 1
|
|
|
|
# test that slave buffer don't induce eviction
|
|
# test again with fewer (and bigger) commands without pipeline, but with eviction
|
|
test_slave_buffers "replica buffer don't induce eviction" 100000 100 1 0
|
|
|
|
start_server {tags {"maxmemory external:skip"}} {
|
|
test {Don't rehash if used memory exceeds maxmemory after rehash} {
|
|
r config set latency-tracking no
|
|
r config set maxmemory 0
|
|
r config set maxmemory-policy allkeys-random
|
|
|
|
# Next rehash size is 8192, that will eat 64k memory
|
|
populate 4095 "" 1
|
|
|
|
set used [s used_memory]
|
|
set limit [expr {$used + 10*1024}]
|
|
r config set maxmemory $limit
|
|
|
|
# Adding a key to meet the 1:1 radio.
|
|
r set k0 v0
|
|
# The dict has reached 4096, it can be resized in tryResizeHashTables in cron,
|
|
# or we add a key to let it check whether it can be resized.
|
|
r set k1 v1
|
|
# Next writing command will trigger evicting some keys if last
|
|
# command trigger DB dict rehash
|
|
r set k2 v2
|
|
# There must be 4098 keys because redis doesn't evict keys.
|
|
r dbsize
|
|
} {4098}
|
|
}
|
|
|
|
start_server {tags {"maxmemory external:skip"}} {
|
|
test {client tracking don't cause eviction feedback loop} {
|
|
r config set latency-tracking no
|
|
r config set maxmemory 0
|
|
r config set maxmemory-policy allkeys-lru
|
|
r config set maxmemory-eviction-tenacity 100
|
|
|
|
# 10 clients listening on tracking messages
|
|
set clients {}
|
|
for {set j 0} {$j < 10} {incr j} {
|
|
lappend clients [redis_deferring_client]
|
|
}
|
|
foreach rd $clients {
|
|
$rd HELLO 3
|
|
$rd read ; # Consume the HELLO reply
|
|
$rd CLIENT TRACKING on
|
|
$rd read ; # Consume the CLIENT reply
|
|
}
|
|
|
|
# populate 300 keys, with long key name and short value
|
|
for {set j 0} {$j < 300} {incr j} {
|
|
set key $j[string repeat x 1000]
|
|
r set $key x
|
|
|
|
# for each key, enable caching for this key
|
|
foreach rd $clients {
|
|
$rd get $key
|
|
$rd read
|
|
}
|
|
}
|
|
|
|
# we need to wait one second for the client querybuf excess memory to be
|
|
# trimmed by cron, otherwise the INFO used_memory and CONFIG maxmemory
|
|
# below (on slow machines) won't be "atomic" and won't trigger eviction.
|
|
after 1100
|
|
|
|
# set the memory limit which will cause a few keys to be evicted
|
|
# we need to make sure to evict keynames of a total size of more than
|
|
# 16kb since the (PROTO_REPLY_CHUNK_BYTES), only after that the
|
|
# invalidation messages have a chance to trigger further eviction.
|
|
set used [s used_memory]
|
|
set limit [expr {$used - 40000}]
|
|
r config set maxmemory $limit
|
|
|
|
# make sure some eviction happened
|
|
set evicted [s evicted_keys]
|
|
if {$::verbose} { puts "evicted: $evicted" }
|
|
|
|
# make sure we didn't drain the database
|
|
assert_range [r dbsize] 200 300
|
|
|
|
assert_range $evicted 10 50
|
|
foreach rd $clients {
|
|
$rd read ;# make sure we have some invalidation message waiting
|
|
$rd close
|
|
}
|
|
|
|
# eviction continues (known problem described in #8069)
|
|
# for now this test only make sures the eviction loop itself doesn't
|
|
# have feedback loop
|
|
set evicted [s evicted_keys]
|
|
if {$::verbose} { puts "evicted: $evicted" }
|
|
}
|
|
}
|
|
|
|
start_server {tags {"maxmemory" "external:skip"}} {
|
|
test {propagation with eviction} {
|
|
set repl [attach_to_replication_stream]
|
|
|
|
r set asdf1 1
|
|
r set asdf2 2
|
|
r set asdf3 3
|
|
|
|
r config set maxmemory-policy allkeys-lru
|
|
r config set maxmemory 1
|
|
|
|
wait_for_condition 5000 10 {
|
|
[r dbsize] eq 0
|
|
} else {
|
|
fail "Not all keys have been evicted"
|
|
}
|
|
|
|
r config set maxmemory 0
|
|
r config set maxmemory-policy noeviction
|
|
|
|
r set asdf4 4
|
|
|
|
assert_replication_stream $repl {
|
|
{select *}
|
|
{set asdf1 1}
|
|
{set asdf2 2}
|
|
{set asdf3 3}
|
|
{del asdf*}
|
|
{del asdf*}
|
|
{del asdf*}
|
|
{set asdf4 4}
|
|
}
|
|
close_replication_stream $repl
|
|
|
|
r config set maxmemory 0
|
|
r config set maxmemory-policy noeviction
|
|
}
|
|
}
|
|
|
|
start_server {tags {"maxmemory" "external:skip"}} {
|
|
test {propagation with eviction in MULTI} {
|
|
set repl [attach_to_replication_stream]
|
|
|
|
r config set maxmemory-policy allkeys-lru
|
|
|
|
r multi
|
|
r incr x
|
|
r config set maxmemory 1
|
|
r incr x
|
|
assert_equal [r exec] {1 OK 2}
|
|
|
|
wait_for_condition 5000 10 {
|
|
[r dbsize] eq 0
|
|
} else {
|
|
fail "Not all keys have been evicted"
|
|
}
|
|
|
|
assert_replication_stream $repl {
|
|
{multi}
|
|
{select *}
|
|
{incr x}
|
|
{incr x}
|
|
{exec}
|
|
{del x}
|
|
}
|
|
close_replication_stream $repl
|
|
|
|
r config set maxmemory 0
|
|
r config set maxmemory-policy noeviction
|
|
}
|
|
}
|
|
|
|
start_server {tags {"maxmemory" "external:skip"}} {
|
|
test {lru/lfu value of the key just added} {
|
|
r config set maxmemory-policy allkeys-lru
|
|
r set foo a
|
|
assert {[r object idletime foo] <= 2}
|
|
r del foo
|
|
r set foo 1
|
|
r get foo
|
|
assert {[r object idletime foo] <= 2}
|
|
|
|
r config set maxmemory-policy allkeys-lfu
|
|
r del foo
|
|
r set foo a
|
|
assert {[r object freq foo] == 5}
|
|
}
|
|
}
|