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https://issues.apache.org/jira/browse/KAFKA-9148?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sophie Blee-Goldman updated KAFKA-9148:
---------------------------------------
Description:
We recently upgraded our RocksDB dependency to 5.18 for its memory-management
abilities (namely the WriteBufferManager, see KAFKA-8215). Unfortunately,
someone from Flink recently discovered a ~8% performance regression that exists
in all versions 5.18+ (up through the current newest version, 6.2.2). Flink was
able to react to this by downgrading to 5.17 and [picking the
WriteBufferManage|https://github.com/dataArtisans/frocksdb/pull/4]r to their
fork (fRocksDB).
Due to this and other reasons enumerated below, we should consider also forking
our own RocksDB for Streams.
Pros:
* We can avoid passing sudden breaking changes on to our users, such removal
of methods with no deprecation period (see discussion on KAFKA-8897)
* We can pick whichever version has the best performance for our needs, and
pick over any new features, metrics, etc that we need to use rather than being
forced to upgrade (and breaking user code, introducing regression, etc)
* The Java API seems to be a very low priority to the rocksdb folks.
** They leave out critical functionality, features, and configuration options
that have been in the c++ API for a very long time
** Those that do make it over often have random gaps in the API such as
setters but no getters (see [rocksdb PR
#5186|https://github.com/facebook/rocksdb/pull/5186])
** Others are poorly designed and require too many trips across the JNI,
making otherwise incredibly useful features prohibitively expensive.
*** [Custom comparator|#issuecomment-83145980]]: a custom comparator could
significantly improve the performance of session windows. This is trivial to do
but given the high performance cost of crossing the jni, it is currently only
practical to use a c++ comparator
*** [Prefix Seek|https://github.com/facebook/rocksdb/issues/6004]: not
currently used by Streams but a commonly requested feature, and may also allow
improved range queries
** Even when an external contributor develops a solution for poorly performing
Java functionality and helpfully tries to contribute their patch back to
rocksdb, it gets ignored by the rocksdb people ([rocksdb PR
#2283|https://github.com/facebook/rocksdb/pull/2283])
Cons:
* more work
Given that we rarely upgrade the Rocks dependency, use only some fraction of
its features, and would need or want to make only minimal changes ourselves, it
seems like we could actually get away with very little extra work by forking
rocksdb. Note that as of this writing the frocksdb repo has only needed to open
5 PRs on top of the actual rocksdb (two of them trivial).
was:
We recently upgraded our RocksDB dependency to 5.18 for its memory-management
abilities (namely the WriteBufferManager, see KAFKA-8215). Unfortunately,
someone from Flink recently discovered a ~8% performance regression that exists
in all versions 5.18+ (up through the current newest version, 6.2.2). Flink was
able to react to this by downgrading to 5.17 and [picking the
WriteBufferManage|https://github.com/dataArtisans/frocksdb/pull/4]r to their
fork (fRocksDB).
Due to this and other reasons enumerated below, we should consider also forking
our own RocksDB for Streams.
Pros:
* We can avoid passing sudden breaking changes on to our users, such removal
of methods with no deprecation period (see discussion on KAFKA-8897)
* We can pick whichever version has the best performance for our needs, and
pick over any new features, metrics, etc that we need to use rather than being
forced to upgrade (and breaking user code, introducing regression, etc)
* The Java API seems to be a very low priority to the rocksdb folks.
** They leave out critical functionality, features, and configuration options
that have been in the c++ API for a very long time
** Those that do make it over often have random gaps in the API such as
setters but no getters (see [rocksdb PR
#5186|https://github.com/facebook/rocksdb/pull/5186])
** Others are poorly designed and require too many trips across the JNI,
making otherwise incredibly useful features prohibitively expensive.
*** [Custom comparator|#issuecomment-83145980]]: a custom comparator could
significantly improve the performance of session windows. This is trivial to do
but given the high performance cost of crossing the jni, it is currently only
practical to use a c++ comparator
*** [Prefix Seek|https://github.com/facebook/rocksdb/issues/6004]: not
currently used by Streams but a commonly requested feature, and may also allow
improved range queries
** Even when an external contributor develops a solution for poorly performing
Java functionality and helpfully tries to contribute their patch back to
rocksdb, it gets ignored by the rocksdb people ([rocksdb PR
#2283|https://github.com/facebook/rocksdb/pull/2283])
Cons:
* more work
Given that we rarely upgrade the Rocks dependency, use only some fraction of
its features, and would need or want to make only minimal changes ourselves, it
seems like we could actually get away with very little extra work by forking
rocksdb.
> Consider forking RocksDB for Streams
> -------------------------------------
>
> Key: KAFKA-9148
> URL: https://issues.apache.org/jira/browse/KAFKA-9148
> Project: Kafka
> Issue Type: Improvement
> Components: streams
> Reporter: Sophie Blee-Goldman
> Priority: Major
>
> We recently upgraded our RocksDB dependency to 5.18 for its memory-management
> abilities (namely the WriteBufferManager, see KAFKA-8215). Unfortunately,
> someone from Flink recently discovered a ~8% performance regression that
> exists in all versions 5.18+ (up through the current newest version, 6.2.2).
> Flink was able to react to this by downgrading to 5.17 and [picking the
> WriteBufferManage|https://github.com/dataArtisans/frocksdb/pull/4]r to their
> fork (fRocksDB).
> Due to this and other reasons enumerated below, we should consider also
> forking our own RocksDB for Streams.
> Pros:
> * We can avoid passing sudden breaking changes on to our users, such removal
> of methods with no deprecation period (see discussion on KAFKA-8897)
> * We can pick whichever version has the best performance for our needs, and
> pick over any new features, metrics, etc that we need to use rather than
> being forced to upgrade (and breaking user code, introducing regression, etc)
> * The Java API seems to be a very low priority to the rocksdb folks.
> ** They leave out critical functionality, features, and configuration
> options that have been in the c++ API for a very long time
> ** Those that do make it over often have random gaps in the API such as
> setters but no getters (see [rocksdb PR
> #5186|https://github.com/facebook/rocksdb/pull/5186])
> ** Others are poorly designed and require too many trips across the JNI,
> making otherwise incredibly useful features prohibitively expensive.
> *** [Custom comparator|#issuecomment-83145980]]: a custom comparator could
> significantly improve the performance of session windows. This is trivial to
> do but given the high performance cost of crossing the jni, it is currently
> only practical to use a c++ comparator
> *** [Prefix Seek|https://github.com/facebook/rocksdb/issues/6004]: not
> currently used by Streams but a commonly requested feature, and may also
> allow improved range queries
> ** Even when an external contributor develops a solution for poorly
> performing Java functionality and helpfully tries to contribute their patch
> back to rocksdb, it gets ignored by the rocksdb people ([rocksdb PR
> #2283|https://github.com/facebook/rocksdb/pull/2283])
> Cons:
> * more work
> Given that we rarely upgrade the Rocks dependency, use only some fraction of
> its features, and would need or want to make only minimal changes ourselves,
> it seems like we could actually get away with very little extra work by
> forking rocksdb. Note that as of this writing the frocksdb repo has only
> needed to open 5 PRs on top of the actual rocksdb (two of them trivial).
>
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