This should smooth CPU and RAM usage spikes related to these periodic tasks,
by reducing the probability that multiple concurrent periodic tasks are performed at the same time.
This eliminates the need in .(*T) casting for results obtained from Load()
Leave atomic.Value for map, since atomic.Pointer[map[...]...] makes double pointer to map,
because map is already a pointer type.
It has been appeared that some production workloads could suffer for some time
after every reset of the previous cache when it gets less than 5% of requests
after the needed item isn't found in the current cache. This could result
in reduced cache hit rates, which, in turn, could increase CPU, disk IO and RAM
usage needed for reading, unpacking and caching the missed data from disk.
This commit reduces the cache miss threshold for resetting the previous cache from 5% to 1%.
This should reduce the possible negative impact after each cache reset by at least 5x,
while reducing the total memory used by caches.
This is a follow-up for d906d8573e
This increases the maximum time for cache population with new entries from 20 minutes to 40 minutes.
This
This change shouldn't increase memory usage for caches, since the prev cache cleaner
should free up memory by deleting unused prev cache as soon as possible.
See 08ca45d238 for details on prev cache cleaner.
This means that the majority of requests are successfully served from the current cache,
so the previous cache can be reset in order to free up memory.
Previously limits for new caches were taken from cache stats.
These limits could mismatch the original limits. This could result in failed cache load
if the stored cache has been created with the limits obtained from cache stats.
The vm_cache_size_max_bytes metric can be used for determining caches which reach their capacity via the following query:
vm_cache_size_bytes / vm_cache_size_max_bytes > 0.9
Previously the switch occurred when the cache size becomes 100% of its capacity. The cache size could never reach 100% capacity.
This could prevent from switching from the split cache to full cache, thus reducing the cache effectiveness.
Previously the stats for cache misses could be improperly counted, because it had inflated cache misses
if the entry was missing in the curr cache, but was existing in the prev cache.
The same applies to cache requests - they were inflated if the entry was missing in the curr cache.
Previously the switch from `split` to `whole` mode had been performed too early,
e.g. when the current cache size became bigger than 1/4 of the allowed cache size.
Now it is performed when the current cache size becomes bigger than 1/2 of the allowed cache size.
This change can reduce memory usage for data ingestion path when big number of active time series are ingested.
This should prevent from cache stats counters going down after cache rotation,
which may corrupt `cache hit ratio` graph on the official Grafan dasbhoards
when using the following query:
1 - (sum(rate(vm_cache_misses_total[5m])) by (type) / sum(rate(vm_cache_requests_total[5m])) by (type))
This should reduce the amount of RAM required for processing time series
with non-zero churn rate.
The previous cache behavior can be restored with `-cache.oldBehavior` command-line flag.
