YufeiLiu created FLINK-20496:
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Summary: RocksDB partitioned index filter option
Key: FLINK-20496
URL: https://issues.apache.org/jira/browse/FLINK-20496
Project: Flink
Issue Type: Improvement
Components: Runtime / State Backends
Reporter: YufeiLiu
When using RocksDBStateBackend and enabling
{{state.backend.rocksdb.memory.managed}} and
{{state.backend.rocksdb.memory.fixed-per-slot}}, flink will strictly limited
rocksdb memory usage which contains "write buffer" and "block cache". With
these options rocksdb stores index and filters in block cache, because in
default options index/filters can grows unlimited.
But it's lead another issue, if high-priority cache(configure by
{{state.backend.rocksdb.memory.high-prio-pool-ratio}}) can't fit all
index/filters blocks, it will load all metadata from disk when cache missed,
and program went extremely slow. According to [Partitioned Index
Filters|https://github.com/facebook/rocksdb/wiki/Partitioned-Index-Filters][1],
we can enable two-level index having acceptable performance when index/filters
cache missed.
Enable these options can get over 10x faster in my case[2], I think we can add
an option {{state.backend.rocksdb.partitioned-index-filters}} and default value
is false, so we can use this feature easily.
[1] Partitioned Index Filters:
https://github.com/facebook/rocksdb/wiki/Partitioned-Index-Filters
[2] Deduplicate scenario, state.backend.rocksdb.memory.fixed-per-slot=256M,
SSD, elapsed time 4.91ms -> 0.33ms.
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