This commit adds two new fields in the INFO output, stats section:
expired_stale_perc:0.34
expired_time_cap_reached_count:58
The first field is an estimate of the number of keys that are yet in
memory but are already logically expired. They reason why those keys are
yet not reclaimed is because the active expire cycle can't spend more
time on the process of reclaiming the keys, and at the same time nobody
is accessing such keys. However as the active expire cycle runs, while
it will eventually have to return to the caller, because of time limit
or because there are less than 25% of keys logically expired in each
given database, it collects the stats in order to populate this INFO
field.
Note that expired_stale_perc is a running average, where the current
sample accounts for 5% and the history for 95%, so you'll see it
changing smoothly over time.
The other field, expired_time_cap_reached_count, counts the number
of times the expire cycle had to stop, even if still it was finding a
sizeable number of keys yet to expire, because of the time limit.
This allows people handling operations to understand if the Redis
server, during mass-expiration events, is able to collect keys fast
enough usually. It is normal for this field to increment during mass
expires, but normally it should very rarely increment. When instead it
constantly increments, it means that the current workloads is using
a very important percentage of CPU time to expire keys.
This feature was created thanks to the hints of Rashmi Ramesh and
Bart Robinson from Twitter. In private email exchanges, they noted how
it was important to improve the observability of this parameter in the
Redis server. Actually in big deployments, the amount of keys that are
yet to expire in each server, even if they are logically expired, may
account for a very big amount of wasted memory.
We have this operation in two places: when caching the master and
when linking a new client after the client creation. By having an API
for this we avoid incurring in errors when modifying one of the two
places forgetting the other. The function is also a good place where to
document why we cache the linked list node.
Related to #4497 and #4210.
We have this operation in two places: when caching the master and
when linking a new client after the client creation. By having an API
for this we avoid incurring in errors when modifying one of the two
places forgetting the other. The function is also a good place where to
document why we cache the linked list node.
Related to #4497 and #4210.
The function in its initial form, and after the fixes for the PSYNC2
bugs, required code duplication in multiple spots. This commit modifies
it in order to always compute the script name independently, and to
return the SDS of the SHA of the body: this way it can be used in all
the places, including for SCRIPT LOAD, without duplicating the code to
create the Lua function name. Note that this requires to re-compute the
body SHA1 in the case of EVAL seeing a script for the first time, but
this should not change scripting performance in any way because new
scripts definition is a rare event happening the first time a script is
seen, and the SHA1 computation is anyway not a very slow process against
the typical Redis script and compared to the actua Lua byte compiling of
the body.
Note that the function used to assert() if a duplicated script was
loaded, however actually now two times over three, we want the function
to handle duplicated scripts just fine: this happens in SCRIPT LOAD and
in RDB AUX "lua" loading. Moreover the assert was not defending against
some obvious failure mode, so now the function always tests against
already defined functions at start.
The function in its initial form, and after the fixes for the PSYNC2
bugs, required code duplication in multiple spots. This commit modifies
it in order to always compute the script name independently, and to
return the SDS of the SHA of the body: this way it can be used in all
the places, including for SCRIPT LOAD, without duplicating the code to
create the Lua function name. Note that this requires to re-compute the
body SHA1 in the case of EVAL seeing a script for the first time, but
this should not change scripting performance in any way because new
scripts definition is a rare event happening the first time a script is
seen, and the SHA1 computation is anyway not a very slow process against
the typical Redis script and compared to the actua Lua byte compiling of
the body.
Note that the function used to assert() if a duplicated script was
loaded, however actually now two times over three, we want the function
to handle duplicated scripts just fine: this happens in SCRIPT LOAD and
in RDB AUX "lua" loading. Moreover the assert was not defending against
some obvious failure mode, so now the function always tests against
already defined functions at start.
In the case of slaves loading the RDB from master, or in other similar
cases, the script is already defined, and the function registering the
script should not fail in the assert() call.
In the case of slaves loading the RDB from master, or in other similar
cases, the script is already defined, and the function registering the
script should not fail in the assert() call.
XADD was suboptimal in the first incarnation of the command, not being
able to accept an ID (very useufl for replication), nor options for
having capped streams.
The keyspace notification for streams was not implemented.
XADD was suboptimal in the first incarnation of the command, not being
able to accept an ID (very useufl for replication), nor options for
having capped streams.
The keyspace notification for streams was not implemented.
With lists we need to signal only on key creation, but streams can
provide data to clients listening at every new item added.
To make this slightly more efficient we now track different classes of
blocked clients to avoid signaling keys when there is nobody listening.
A typical case is when the stream is used as a time series DB and
accessed only by range with XRANGE.
With lists we need to signal only on key creation, but streams can
provide data to clients listening at every new item added.
To make this slightly more efficient we now track different classes of
blocked clients to avoid signaling keys when there is nobody listening.
A typical case is when the stream is used as a time series DB and
accessed only by range with XRANGE.
This is currently needed in order to fix#4483, but this can be
useful in other contexts, so maybe later we may want to remove the
conditionals and always save/load scripts.
Note that we are using the "lua" AUX field here, in order to guarantee
backward compatibility of the RDB file. The unknown AUX fields must be
discarded by past versions of Redis.
