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1 Commits

Author SHA1 Message Date
Peter Dillinger
bae6f58696 Basic MultiGet support for partitioned filters (#6757)
Summary:
In MultiGet, access each applicable filter partition only once
per batch, rather than for each applicable key. Also,

* Fix Bloom stats for MultiGet
* Fix/refactor MultiGetContext::Range::KeysLeft, including
* Add efficient BitsSetToOne implementation
* Assert that MultiGetContext::Range does not go beyond shift range

Performance test: Generate db:

    $ ./db_bench --benchmarks=fillrandom --num=15000000 --cache_index_and_filter_blocks -bloom_bits=10 -partition_index_and_filters=true
    ...

Before (middle performing run of three; note some missing Bloom stats):

    $ ./db_bench --use-existing-db --benchmarks=multireadrandom --num=15000000 --cache_index_and_filter_blocks --bloom_bits=10 --threads=16 --cache_size=20000000 -partition_index_and_filters -batch_size=32 -multiread_batched -statistics --duration=20 2>&1 | egrep 'micros/op|block.cache.filter.hit|bloom.filter.(full|use)|number.multiget'
    multireadrandom :      26.403 micros/op 597517 ops/sec; (548427 of 671968 found)
    rocksdb.block.cache.filter.hit COUNT : 83443275
    rocksdb.bloom.filter.useful COUNT : 0
    rocksdb.bloom.filter.full.positive COUNT : 0
    rocksdb.bloom.filter.full.true.positive COUNT : 7931450
    rocksdb.number.multiget.get COUNT : 385984
    rocksdb.number.multiget.keys.read COUNT : 12351488
    rocksdb.number.multiget.bytes.read COUNT : 793145000
    rocksdb.number.multiget.keys.found COUNT : 7931450

After (middle performing run of three):

    $ ./db_bench_new --use-existing-db --benchmarks=multireadrandom --num=15000000 --cache_index_and_filter_blocks --bloom_bits=10 --threads=16 --cache_size=20000000 -partition_index_and_filters -batch_size=32 -multiread_batched -statistics --duration=20 2>&1 | egrep 'micros/op|block.cache.filter.hit|bloom.filter.(full|use)|number.multiget'
    multireadrandom :      21.024 micros/op 752963 ops/sec; (705188 of 863968 found)
    rocksdb.block.cache.filter.hit COUNT : 49856682
    rocksdb.bloom.filter.useful COUNT : 45684579
    rocksdb.bloom.filter.full.positive COUNT : 10395458
    rocksdb.bloom.filter.full.true.positive COUNT : 9908456
    rocksdb.number.multiget.get COUNT : 481984
    rocksdb.number.multiget.keys.read COUNT : 15423488
    rocksdb.number.multiget.bytes.read COUNT : 990845600
    rocksdb.number.multiget.keys.found COUNT : 9908456

So that's about 25% higher throughput even for random keys
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6757

Test Plan: unit test included

Reviewed By: anand1976

Differential Revision: D21243256

Pulled By: pdillinger

fbshipit-source-id: 5644a1468d9e8c8575be02f4e04bc5d62dbbb57f
2020-04-28 14:49:34 -07:00