Example:
db0:keys=221913,expires=221913,avg_ttl=655
The algorithm uses a running average with only two samples (current and
previous). Keys found to be expired are considered at TTL zero even if
the actual TTL can be negative.
The TTL is reported in milliseconds.
Example:
db0:keys=221913,expires=221913,avg_ttl=655
The algorithm uses a running average with only two samples (current and
previous). Keys found to be expired are considered at TTL zero even if
the actual TTL can be negative.
The TTL is reported in milliseconds.
We don't want to repeat a fast cycle too soon, the previous code was
broken, we need to wait two times the period *since* the start of the
previous cycle in order to avoid there is an even space between cycles:
.-> start .-> second start
| |
+-------------+-------------+--------------+
| first cycle | pause | second cycle |
+-------------+-------------+--------------+
The second and first start must be PERIOD*2 useconds apart hence the *2
in the new code.
We don't want to repeat a fast cycle too soon, the previous code was
broken, we need to wait two times the period *since* the start of the
previous cycle in order to avoid there is an even space between cycles:
.-> start .-> second start
| |
+-------------+-------------+--------------+
| first cycle | pause | second cycle |
+-------------+-------------+--------------+
The second and first start must be PERIOD*2 useconds apart hence the *2
in the new code.
This commit makes the fast collection cycle time configurable, at
the same time it does not allow to run a new fast collection cycle
for the same amount of time as the max duration of the fast
collection cycle.
This commit makes the fast collection cycle time configurable, at
the same time it does not allow to run a new fast collection cycle
for the same amount of time as the max duration of the fast
collection cycle.
The main idea here is that when we are no longer to expire keys at the
rate the are created, we can't block more in the normal expire cycle as
this would result in too big latency spikes.
For this reason the commit introduces a "fast" expire cycle that does
not run for more than 1 millisecond but is called in the beforeSleep()
hook of the event loop, so much more often, and with a frequency bound
to the frequency of executed commnads.
The fast expire cycle is only called when the standard expiration
algorithm runs out of time, that is, consumed more than
REDIS_EXPIRELOOKUPS_TIME_PERC of CPU in a given cycle without being able
to take the number of already expired keys that are yet not collected
to a number smaller than 25% of the number of keys.
You can test this commit with different loads, but a simple way is to
use the following:
Extreme load with pipelining:
redis-benchmark -r 100000000 -n 100000000 \
-P 32 set ele:rand:000000000000 foo ex 2
Remove the -P32 in order to avoid the pipelining for a more real-world
load.
In another terminal tab you can monitor the Redis behavior with:
redis-cli -i 0.1 -r -1 info keyspace
and
redis-cli --latency-history
Note: this commit will make Redis printing a lot of debug messages, it
is not a good idea to use it in production.
The main idea here is that when we are no longer to expire keys at the
rate the are created, we can't block more in the normal expire cycle as
this would result in too big latency spikes.
For this reason the commit introduces a "fast" expire cycle that does
not run for more than 1 millisecond but is called in the beforeSleep()
hook of the event loop, so much more often, and with a frequency bound
to the frequency of executed commnads.
The fast expire cycle is only called when the standard expiration
algorithm runs out of time, that is, consumed more than
REDIS_EXPIRELOOKUPS_TIME_PERC of CPU in a given cycle without being able
to take the number of already expired keys that are yet not collected
to a number smaller than 25% of the number of keys.
You can test this commit with different loads, but a simple way is to
use the following:
Extreme load with pipelining:
redis-benchmark -r 100000000 -n 100000000 \
-P 32 set ele:rand:000000000000 foo ex 2
Remove the -P32 in order to avoid the pipelining for a more real-world
load.
In another terminal tab you can monitor the Redis behavior with:
redis-cli -i 0.1 -r -1 info keyspace
and
redis-cli --latency-history
Note: this commit will make Redis printing a lot of debug messages, it
is not a good idea to use it in production.
Thanks to @run and @badboy for spotting this.
Triva: clang was not able to provide me a warning about that when
compiling.
This closes#1024 and #1207, committing the change myself as the pull
requests no longer apply cleanly after other changes to the same
function.
Thanks to @run and @badboy for spotting this.
Triva: clang was not able to provide me a warning about that when
compiling.
This closes#1024 and #1207, committing the change myself as the pull
requests no longer apply cleanly after other changes to the same
function.
Actaully the string is modified in-place and a reallocation is never
needed, so there is no need to return the new sds string pointer as
return value of the function, that is now just "void".
Actaully the string is modified in-place and a reallocation is never
needed, so there is no need to return the new sds string pointer as
return value of the function, that is now just "void".
Now that EMBSTR encoding exists we calculate the amount of memory used
by the SDS part of a Redis String object in two different ways:
1) For raw string object, the size of the allocation is considered.
2) For embstr objects, the length of the string itself is used.
The new function takes care of this logic.
Now that EMBSTR encoding exists we calculate the amount of memory used
by the SDS part of a Redis String object in two different ways:
1) For raw string object, the size of the allocation is considered.
2) For embstr objects, the length of the string itself is used.
The new function takes care of this logic.
