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https://issues.apache.org/jira/browse/KAFKA-8027?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Prashant updated KAFKA-8027:
----------------------------
Description:
We observed this during a performance test of our stream application which
tracks user's activity and provides REST interface to query the window state
store. We used default configuration of Materialized i.e. withCachingEnabled
for storing user behaviour stats in a window state store (CompositeWindowStore
with CachingWindowStore as underlyin which internally uses RocksDBStore for
persistent).
While querying window store with store.fetch(key, long, long), it internally
tries to fetch the range from ThreadCache which uses a byte iterator to search
for a key in cache and on a cache miss it goes to RocksDBStore for result. So,
when number of keys in cache becomes large this ThreadCache search starts
taking time (range Iterator on all keys) which impacts WindowStore query
performance.
Workaround: If we disable cache with switch on Materialized instance i.e.
withCachingDisabled, key search is delegated directly to RocksDBStore which is
way faster and completed search in microseconds against millis in case of
CachingWindowStore.
Stats: With Unique users > 0.5M, random search for a key i.e. UserId:
withCachingEnabled : 40 < t < 80ms (upper bound increases as unique users grow)
withCahingDisabled: t < 1ms (Almost constant time)
was:
We observed this during a performance test of our stream application which
tracks user's activity and provides REST interface to query the window state
store. We used default configuration of Materialized i.e. withCachingEnabled
for storing user behaviour stats in a window state store (CompositeWindowStore
with CachingWindowStore as underlyin which internally uses RocksDBStore for
persistent).
While querying window store with store.fetch(key, long, long), it internally
tries to fetch the range from ThreadCache which uses a byte iterator to search
for a key in cache and on a cache miss it goes to RocksDBStore for result. So,
when number of keys in cache becomes large this ThreadCache search starts
taking time (range Iterator on all keys) which impacts WindowStore query
performance.
Workaround: If we disable cache with switch on Materialized instance i.e.
withCachingDisabled, key search is delegated directly to RocksDBStore which is
way faster and completed search in microseconds against millis in case of
CachingWindowStore.
Stats: With Unique users > 0.5M, random search for a key i.e. UserId:
withCachingEnabled : 40 < t < 80ms (upper bound increases as unique users
grow) withCahingDisabled: t < 1ms (Almost constant time)
> Gradual decline in performance of CachingWindowStore provider when number of
> keys grow
> --------------------------------------------------------------------------------------
>
> Key: KAFKA-8027
> URL: https://issues.apache.org/jira/browse/KAFKA-8027
> Project: Kafka
> Issue Type: Bug
> Components: streams
> Affects Versions: 2.1.0
> Reporter: Prashant
> Priority: Major
> Labels: interactivequ, kafka-streams
>
> We observed this during a performance test of our stream application which
> tracks user's activity and provides REST interface to query the window state
> store. We used default configuration of Materialized i.e. withCachingEnabled
> for storing user behaviour stats in a window state store
> (CompositeWindowStore with CachingWindowStore as underlyin which internally
> uses RocksDBStore for persistent).
> While querying window store with store.fetch(key, long, long), it internally
> tries to fetch the range from ThreadCache which uses a byte iterator to
> search for a key in cache and on a cache miss it goes to RocksDBStore for
> result. So, when number of keys in cache becomes large this ThreadCache
> search starts taking time (range Iterator on all keys) which impacts
> WindowStore query performance.
>
> Workaround: If we disable cache with switch on Materialized instance i.e.
> withCachingDisabled, key search is delegated directly to RocksDBStore which
> is way faster and completed search in microseconds against millis in case of
> CachingWindowStore.
>
> Stats: With Unique users > 0.5M, random search for a key i.e. UserId:
>
> withCachingEnabled : 40 < t < 80ms (upper bound increases as unique users
> grow)
> withCahingDisabled: t < 1ms (Almost constant time)
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