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20 Commits (1d2950b8dd38009d0719e4a857f5a42bb1bc9675)
| Author | SHA1 | Message | Date |
|---|---|---|---|
Yanqin Jin
|
3e02c6e05a |
Point-lookup returns timestamps of Delete and SingleDelete (#10056)
Summary: If caller specifies a non-null `timestamp` argument in `DB::Get()` or a non-null `timestamps` in `DB::MultiGet()`, RocksDB will return the timestamps of the point tombstones. Note: DeleteRange is still unsupported. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10056 Test Plan: make check Reviewed By: ltamasi Differential Revision: D36677956 Pulled By: riversand963 fbshipit-source-id: 2d7af02cc7237b1829cd269086ea895a49d501ae |
3 years ago |
|
anand76
|
57997ddaaf |
Multi file concurrency in MultiGet using coroutines and async IO (#9968)
Summary: This PR implements a coroutine version of batched MultiGet in order to concurrently read from multiple SST files in a level using async IO, thus reducing the latency of the MultiGet. The API from the user perspective is still synchronous and single threaded, with the RocksDB part of the processing happening in the context of the caller's thread. In Version::MultiGet, the decision is made whether to call synchronous or coroutine code. A good way to review this PR is to review the first 4 commits in order - de773b3, 70c2f70, 10b50e1, and 377a597 - before reviewing the rest. TODO: 1. Figure out how to build it in CircleCI (requires some dependencies to be installed) 2. Do some stress testing with coroutines enabled No regression in synchronous MultiGet between this branch and main - ``` ./db_bench -use_existing_db=true --db=/data/mysql/rocksdb/prefix_scan -benchmarks="readseq,multireadrandom" -key_size=32 -value_size=512 -num=5000000 -batch_size=64 -multiread_batched=true -use_direct_reads=false -duration=60 -ops_between_duration_checks=1 -readonly=true -adaptive_readahead=true -threads=16 -cache_size=10485760000 -async_io=false -multiread_stride=40000 -statistics ``` Branch - ```multireadrandom : 4.025 micros/op 3975111 ops/sec 60.001 seconds 238509056 operations; 2062.3 MB/s (14767808 of 14767808 found)``` Main - ```multireadrandom : 3.987 micros/op 4013216 ops/sec 60.001 seconds 240795392 operations; 2082.1 MB/s (15231040 of 15231040 found)``` More benchmarks in various scenarios are given below. The measurements were taken with ```async_io=false``` (no coroutines) and ```async_io=true``` (use coroutines). For an IO bound workload (with every key requiring an IO), the coroutines version shows a clear benefit, being ~2.6X faster. For CPU bound workloads, the coroutines version has ~6-15% higher CPU utilization, depending on how many keys overlap an SST file. 1. Single thread IO bound workload on remote storage with sparse MultiGet batch keys (~1 key overlap/file) - No coroutines - ```multireadrandom : 831.774 micros/op 1202 ops/sec 60.001 seconds 72136 operations; 0.6 MB/s (72136 of 72136 found)``` Using coroutines - ```multireadrandom : 318.742 micros/op 3137 ops/sec 60.003 seconds 188248 operations; 1.6 MB/s (188248 of 188248 found)``` 2. Single thread CPU bound workload (all data cached) with ~1 key overlap/file - No coroutines - ```multireadrandom : 4.127 micros/op 242322 ops/sec 60.000 seconds 14539384 operations; 125.7 MB/s (14539384 of 14539384 found)``` Using coroutines - ```multireadrandom : 4.741 micros/op 210935 ops/sec 60.000 seconds 12656176 operations; 109.4 MB/s (12656176 of 12656176 found)``` 3. Single thread CPU bound workload with ~2 key overlap/file - No coroutines - ```multireadrandom : 3.717 micros/op 269000 ops/sec 60.000 seconds 16140024 operations; 139.6 MB/s (16140024 of 16140024 found)``` Using coroutines - ```multireadrandom : 4.146 micros/op 241204 ops/sec 60.000 seconds 14472296 operations; 125.1 MB/s (14472296 of 14472296 found)``` 4. CPU bound multi-threaded (16 threads) with ~4 key overlap/file - No coroutines - ```multireadrandom : 4.534 micros/op 3528792 ops/sec 60.000 seconds 211728728 operations; 1830.7 MB/s (12737024 of 12737024 found) ``` Using coroutines - ```multireadrandom : 4.872 micros/op 3283812 ops/sec 60.000 seconds 197030096 operations; 1703.6 MB/s (12548032 of 12548032 found) ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/9968 Reviewed By: akankshamahajan15 Differential Revision: D36348563 Pulled By: anand1976 fbshipit-source-id: c0ce85a505fd26ebfbb09786cbd7f25202038696 |
3 years ago |
|
Peter Dillinger
|
9d0cae7104 |
Eliminate unnecessary (slow) block cache Ref()ing in MultiGet (#9899)
Summary: When MultiGet() determines that multiple query keys can be served by examining the same data block in block cache (one Lookup()), each PinnableSlice referring to data in that data block needs to hold on to the block in cache so that they can be released at arbitrary times by the API user. Historically this is accomplished with extra calls to Ref() on the Handle from Lookup(), with each PinnableSlice cleanup calling Release() on the Handle, but this creates extra contention on the block cache for the extra Ref()s and Release()es, especially because they hit the same cache shard repeatedly. In the case of merge operands (possibly more cases?), the problem was compounded by doing an extra Ref()+eventual Release() for each merge operand for a key reusing a block (which could be the same key!), rather than one Ref() per key. (Note: the non-shared case with `biter` was already one per key.) This change optimizes MultiGet not to rely on these extra, contentious Ref()+Release() calls by instead, in the shared block case, wrapping the cache Release() cleanup in a refcounted object referenced by the PinnableSlices, such that after the last wrapped reference is released, the cache entry is Release()ed. Relaxed atomic refcounts should be much faster than mutex-guarded Ref() and Release(), and much less prone to a performance cliff when MultiGet() does a lot of block sharing. Note that I did not use std::shared_ptr, because that would require an extra indirection object (shared_ptr itself new/delete) in order to associate a ref increment/decrement with a Cleanable cleanup entry. (If I assumed it was the size of two pointers, I could do some hackery to make it work without the extra indirection, but that's too fragile.) Some details: * Fixed (removed) extra block cache tracing entries in cases of cache entry reuse in MultiGet, but it's likely that in some other cases traces are missing (XXX comment inserted) * Moved existing implementations for cleanable.h from iterator.cc to new cleanable.cc * Improved API comments on Cleanable * Added a public SharedCleanablePtr class to cleanable.h in case others could benefit from the same pattern (potentially many Cleanables and/or smart pointers referencing a shared Cleanable) * Add a typedef for MultiGetContext::Mask * Some variable renaming for clarity Pull Request resolved: https://github.com/facebook/rocksdb/pull/9899 Test Plan: Added unit tests for SharedCleanablePtr. Greatly enhanced ability of existing tests to detect cache use-after-free. * Release PinnableSlices from MultiGet as they are read rather than in bulk (in db_test_util wrapper). * In ASAN build, default to using a trivially small LRUCache for block_cache so that entries are immediately erased when unreferenced. (Updated two tests that depend on caching.) New ASAN testsuite running time seems OK to me. If I introduce a bug into my implementation where we skip the shared cleanups on block reuse, ASAN detects the bug in `db_basic_test *MultiGet*`. If I remove either of the above testing enhancements, the bug is not detected. Consider for follow-up work: manipulate or randomize ordering of PinnableSlice use and release from MultiGet db_test_util wrapper. But in typical cases, natural ordering gives pretty good functional coverage. Performance test: In the extreme (but possible) case of MultiGetting the same or adjacent keys in a batch, throughput can improve by an order of magnitude. `./db_bench -benchmarks=multireadrandom -db=/dev/shm/testdb -readonly -num=5 -duration=10 -threads=20 -multiread_batched -batch_size=200` Before ops/sec, num=5: 1,384,394 Before ops/sec, num=500: 6,423,720 After ops/sec, num=500: 10,658,794 After ops/sec, num=5: 16,027,257 Also note that previously, with high parallelism, having query keys concentrated in a single block was worse than spreading them out a bit. Now concentrated in a single block is faster than spread out, which is hopefully consistent with natural expectation. Random query performance: with num=1000000, over 999 x 10s runs running before & after simultaneously (each -threads=12): Before: multireadrandom [AVG 999 runs] : 1088699 (± 7344) ops/sec; 120.4 (± 0.8 ) MB/sec After: multireadrandom [AVG 999 runs] : 1090402 (± 7230) ops/sec; 120.6 (± 0.8 ) MB/sec Possibly better, possibly in the noise. Reviewed By: anand1976 Differential Revision: D35907003 Pulled By: pdillinger fbshipit-source-id: bbd244d703649a8ca12d476f2d03853ed9d1a17e |
3 years ago |
|
Peter Dillinger
|
ea89c77f27 |
Fix major bug with MultiGet, DeleteRange, and memtable Bloom (#9453)
Summary: MemTable::MultiGet was not considering range tombstones before querying Bloom filter. This means range tombstones would be skipped for keys (or prefixes) with no other entries in the memtable. This could cause old values for a key (in SST files) to still show up until the range tombstone covering it has been flushed. This is fixed by essentially disabling the memtable Bloom filter when there are any range tombstones. (This could be better optimized in the future, but good enough for now.) Did some other cleanup/optimization in the same code to (more than) offset the cost of checking on range tombstones in more cases. There is now notable improvement when memtable_whole_key_filtering and prefix_extractor are used together (unusual), and this makes MultiGet closer to the Get implementation. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9453 Test Plan: new unit test added. Added memtable Bloom to crash test. Performance testing -------------------- Build WAL-only DB (recovers to memtable): ``` TEST_TMPDIR=/dev/shm/rocksdb ./db_bench -benchmarks=fillrandom -num=1000000 -write_buffer_size=250000000 ``` Query test command, to maximize sensitivity to the changed code: ``` TEST_TMPDIR=/dev/shm/rocksdb ./db_bench -use_existing_db -readonly -benchmarks=multireadrandom -num=10000000 -write_buffer_size=250000000 -memtable_bloom_size_ratio=0.015 -multiread_batched -batch_size=24 -threads=8 -memtable_whole_key_filtering=$MWKF -prefix_size=$PXS ``` (Note -num here is 10x larger for mostly memtable misses) Before & after run simultaneously, average over 10 iterations per data point, ops/sec. MWKF=0 PXS=0 (Bloom disabled) Before: 5724844 After: 6722066 MWKF=0 PXS=7 (prefixes hardly unique; Bloom not useful) Before: 9981319 After: 10237990 MWKF=0 PXS=8 (prefixes unique; Bloom useful) Before: 12081715 After: 12117603 MWKF=1 PXS=0 (whole key Bloom useful) Before: 11944354 After: 12096085 MWKF=1 PXS=7 (whole key Bloom useful in new version; prefixes not useful in old version) Before: 9444299 After: 11826029 MWKF=1 PXS=7 (whole key Bloom useful in new version; prefixes useful in old version) Before: 11784465 After: 11778591 Only in this last case is the 'before' *slightly* faster, perhaps because hashing prefixes is slightly faster than hashing whole keys. Otherwise, 'after' is faster. Reviewed By: ajkr Differential Revision: D33805025 Pulled By: pdillinger fbshipit-source-id: 597523cae4f4eafdf6ae6bb2bc6cb46f83b017bf |
3 years ago |
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Yanqin Jin
|
b512f4bc76 |
Batch blob read IO for MultiGet (#8699)
Summary: In batched `MultiGet()`, RocksDB batches blob read IO and uses `RandomAccessFileReader::MultiRead()` to read the blobs instead of issuing multiple `Read()`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8699 Test Plan: ``` make check ``` Reviewed By: ltamasi Differential Revision: D31030861 Pulled By: riversand963 fbshipit-source-id: a0df6060cbfd54cff9515a4eee08807b1dbcb0c8 |
3 years ago |
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Peter Dillinger
|
4750421ece |
Replace most typedef with using= (#8751)
Summary:
Old typedef syntax is confusing
Most but not all changes with
perl -pi -e 's/typedef (.*) ([a-zA-Z0-9_]+);/using $2 = $1;/g' list_of_files
make format
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8751
Test Plan: existing
Reviewed By: zhichao-cao
Differential Revision: D30745277
Pulled By: pdillinger
fbshipit-source-id: 6f65f0631c3563382d43347896020413cc2366d9
|
3 years ago |
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Levi Tamasi
|
1afbd1948c |
Add initial blob support to batched MultiGet (#7766)
Summary: The patch adds initial support for reading blobs to the batched `MultiGet` API. The current implementation simply retrieves the blob values as the blob indexes are encountered; that is, reads from blob files are currently not batched. (This will be optimized in a separate phase.) In addition, the patch removes some dead code related to BlobDB from the batched `MultiGet` implementation, namely the `is_blob` / `is_blob_index` flags that are passed around in `DBImpl` and `MemTable` / `MemTableListVersion`. These were never hooked up to anything and wouldn't work anyways, since a single flag is not sufficient to communicate the "blobness" of multiple key-values. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7766 Test Plan: `make check` Reviewed By: jay-zhuang Differential Revision: D25479290 Pulled By: ltamasi fbshipit-source-id: 7aba2d290e31876ee592bcf1adfd1018713a8000 |
4 years ago |
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Jay Zhuang
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881e0dcc09 |
Fix MultiGet unable to query timestamp data issue (#7589)
Summary: The filter query key should not contain timestamp. The timestamp is stripped for Get(), but not MultiGet(). Pull Request resolved: https://github.com/facebook/rocksdb/pull/7589 Reviewed By: riversand963 Differential Revision: D24494661 Pulled By: jay-zhuang fbshipit-source-id: fc5ff40f9d683a89a760c6ff0ab3aed05a70c317 |
4 years ago |
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Jay Zhuang
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1bdaef7a06 |
Status check enforcement for timestamp_basic_test (#7454)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/7454 Reviewed By: riversand963 Differential Revision: D23981719 Pulled By: jay-zhuang fbshipit-source-id: 01073f73e54c17067b886c4a2f179b2804198399 |
4 years ago |
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Akanksha Mahajan
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bcefc59e9f |
Allow MultiGet users to limit cumulative value size (#6826)
Summary: 1. Add a value_size in read options which limits the cumulative value size of keys read in batches. Once the size exceeds read_options.value_size, all the remaining keys are returned with status Abort without further fetching any key. 2. Add a unit test case MultiGetBatchedValueSizeSimple the reads keys from memory and sst files. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6826 Test Plan: 1. make check -j64 2. Add a new unit test case Reviewed By: anand1976 Differential Revision: D21471483 Pulled By: akankshamahajan15 fbshipit-source-id: dea51b8e76d5d1df38ece8cdb29933b1d798b900 |
5 years ago |
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Peter Dillinger
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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
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5 years ago |
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Yanqin Jin
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d4398e08fc |
Fix timestamp support for MultiGet (#6748)
Summary: 1. Avoid nullptr dereference when passing timestamp to KeyContext creation. 2. Construct LookupKey correctly with timestamp when creating MultiGetContext. 3. Compare without timestamp when sorting KeyContexts. Fixes https://github.com/facebook/rocksdb/issues/6745 Test plan (dev server): make check Pull Request resolved: https://github.com/facebook/rocksdb/pull/6748 Reviewed By: pdillinger Differential Revision: D21258691 Pulled By: riversand963 fbshipit-source-id: 44e65b759c18b9986947783edf03be4f890bb004 |
5 years ago |
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Huisheng Liu
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a6ce5c823b |
multiget support for timestamps (#6483)
Summary:
Add timestamp support for MultiGet().
timestamp from readoptions is honored, and timestamps can be returned along with values.
MultiReadRandom perf test (10 minutes) on the same development machine ram drive with the same DB data shows no regression (within marge of error). The test is adapted from https://github.com/facebook/rocksdb/wiki/RocksDB-In-Memory-Workload-Performance-Benchmarks.
base line (commit
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5 years ago |
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sdong
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fdf882ded2 |
Replace namespace name "rocksdb" with ROCKSDB_NAMESPACE (#6433)
Summary: When dynamically linking two binaries together, different builds of RocksDB from two sources might cause errors. To provide a tool for user to solve the problem, the RocksDB namespace is changed to a flag which can be overridden in build time. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6433 Test Plan: Build release, all and jtest. Try to build with ROCKSDB_NAMESPACE with another flag. Differential Revision: D19977691 fbshipit-source-id: aa7f2d0972e1c31d75339ac48478f34f6cfcfb3e |
5 years ago |
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Cheng Chang
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152f8a8ffe |
Remove unnecessary computation of index (#6406)
Summary: `index` can be replaced by `iter`, saving the computation of `index++`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6406 Test Plan: make check Differential Revision: D19905056 Pulled By: cheng-chang fbshipit-source-id: add4638959c0d2e4e77a11f3fa04ffabaf0de790 |
5 years ago |
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anand76
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6c7b1a0cc7 |
Batched MultiGet API for multiple column families (#5816)
Summary: Add a new API that allows a user to call MultiGet specifying multiple keys belonging to different column families. This is mainly useful for users who want to do a consistent read of keys across column families, with the added performance benefits of batching and returning values using PinnableSlice. As part of this change, the code in the original multi-column family MultiGet for acquiring the super versions has been refactored into a separate function that can be used by both, the batching and the non-batching versions of MultiGet. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5816 Test Plan: make check make asan_check asan_crash_test Differential Revision: D18408676 Pulled By: anand1976 fbshipit-source-id: 933e7bec91dd70e7b633be4ff623a1116cc28c8d |
5 years ago |
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Vijay Nadimpalli
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4c49e38f15 |
MultiGet batching in memtable (#5818)
Summary: RocksDB has a MultiGet() API that implements batched key lookup for higher performance (https://github.com/facebook/rocksdb/blob/master/include/rocksdb/db.h#L468). Currently, batching is implemented in BlockBasedTableReader::MultiGet() for SST file lookups. One of the ways it improves performance is by pipelining bloom filter lookups (by prefetching required cachelines for all the keys in the batch, and then doing the probe) and thus hiding the cache miss latency. The same concept can be extended to the memtable as well. This PR involves implementing a pipelined bloom filter lookup in DynamicBloom, and implementing MemTable::MultiGet() that can leverage it. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5818 Test Plan: Existing tests Performance Test: Ran the below command which fills up the memtable and makes sure there are no flushes and then call multiget. Ran it on master and on the new change and see atleast 1% performance improvement across all the test runs I did. Sometimes the improvement was upto 5%. TEST_TMPDIR=/data/users/$USER/benchmarks/feature/ numactl -C 10 ./db_bench -benchmarks="fillseq,multireadrandom" -num=600000 -compression_type="none" -level_compaction_dynamic_level_bytes -write_buffer_size=200000000 -target_file_size_base=200000000 -max_bytes_for_level_base=16777216 -reads=90000 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 -statistics -memtable_whole_key_filtering=true -memtable_bloom_size_ratio=10 Differential Revision: D17578869 Pulled By: vjnadimpalli fbshipit-source-id: 23dc651d9bf49db11d22375bf435708875a1f192 |
5 years ago |
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anand76
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e10570331d |
Support row cache with batched MultiGet (#5706)
Summary: This PR adds support for row cache in ```rocksdb::TableCache::MultiGet```. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5706 Test Plan: 1. Unit tests in db_basic_test 2. db_bench results with batch size of 2 (```Get``` is faster than ```MultiGet``` for single key) - Get - readrandom : 3.935 micros/op 254116 ops/sec; 28.1 MB/s (22870998 of 22870999 found) MultiGet - multireadrandom : 3.743 micros/op 267190 ops/sec; (24047998 of 24047998 found) Command used - TEST_TMPDIR=/dev/shm/multiget numactl -C 10 ./db_bench -use_existing_db=true -use_existing_keys=false -benchmarks="readtorowcache,[read|multiread]random" -write_buffer_size=16777216 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -row_cache_size=4194304000 -batch_size=2 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=131072 Differential Revision: D17086297 Pulled By: anand1976 fbshipit-source-id: 85784378da913e05f1baf31ec1b4e7c9345e7f57 |
5 years ago |
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Zhongyi Xie
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5d27d65bef |
multiget: fix memory issues due to vector auto resizing (#5279)
Summary: This PR fixes three memory issues found by ASAN * in db_stress, the key vector for MultiGet is created using `emplace_back` which could potentially invalidates references to the underlying storage (vector<string>) due to auto resizing. Fix by calling reserve in advance. * Similar issue in construction of GetContext autovector in version_set.cc * In multiget_context.h use T[] specialization for unique_ptr that holds a char array Pull Request resolved: https://github.com/facebook/rocksdb/pull/5279 Differential Revision: D15202893 Pulled By: miasantreble fbshipit-source-id: 14cc2cda0ed64d29f2a1e264a6bfdaa4294ee75d |
6 years ago |
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anand76
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fefd4b98c5 |
Introduce a new MultiGet batching implementation (#5011)
Summary: This PR introduces a new MultiGet() API, with the underlying implementation grouping keys based on SST file and batching lookups in a file. The reason for the new API is twofold - the definition allows callers to allocate storage for status and values on stack instead of std::vector, as well as return values as PinnableSlices in order to avoid copying, and it keeps the original MultiGet() implementation intact while we experiment with batching. Batching is useful when there is some spatial locality to the keys being queries, as well as larger batch sizes. The main benefits are due to - 1. Fewer function calls, especially to BlockBasedTableReader::MultiGet() and FullFilterBlockReader::KeysMayMatch() 2. Bloom filter cachelines can be prefetched, hiding the cache miss latency The next step is to optimize the binary searches in the level_storage_info, index blocks and data blocks, since we could reduce the number of key comparisons if the keys are relatively close to each other. The batching optimizations also need to be extended to other formats, such as PlainTable and filter formats. This also needs to be added to db_stress. Benchmark results from db_bench for various batch size/locality of reference combinations are given below. Locality was simulated by offsetting the keys in a batch by a stride length. Each SST file is about 8.6MB uncompressed and key/value size is 16/100 uncompressed. To focus on the cpu benefit of batching, the runs were single threaded and bound to the same cpu to eliminate interference from other system events. The results show a 10-25% improvement in micros/op from smaller to larger batch sizes (4 - 32). Batch Sizes 1 | 2 | 4 | 8 | 16 | 32 Random pattern (Stride length 0) 4.158 | 4.109 | 4.026 | 4.05 | 4.1 | 4.074 - Get 4.438 | 4.302 | 4.165 | 4.122 | 4.096 | 4.075 - MultiGet (no batching) 4.461 | 4.256 | 4.277 | 4.11 | 4.182 | 4.14 - MultiGet (w/ batching) Good locality (Stride length 16) 4.048 | 3.659 | 3.248 | 2.99 | 2.84 | 2.753 4.429 | 3.728 | 3.406 | 3.053 | 2.911 | 2.781 4.452 | 3.45 | 2.833 | 2.451 | 2.233 | 2.135 Good locality (Stride length 256) 4.066 | 3.786 | 3.581 | 3.447 | 3.415 | 3.232 4.406 | 4.005 | 3.644 | 3.49 | 3.381 | 3.268 4.393 | 3.649 | 3.186 | 2.882 | 2.676 | 2.62 Medium locality (Stride length 4096) 4.012 | 3.922 | 3.768 | 3.61 | 3.582 | 3.555 4.364 | 4.057 | 3.791 | 3.65 | 3.57 | 3.465 4.479 | 3.758 | 3.316 | 3.077 | 2.959 | 2.891 dbbench command used (on a DB with 4 levels, 12 million keys)- TEST_TMPDIR=/dev/shm numactl -C 10 ./db_bench.tmp -use_existing_db=true -benchmarks="readseq,multireadrandom" -write_buffer_size=4194304 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 Pull Request resolved: https://github.com/facebook/rocksdb/pull/5011 Differential Revision: D14348703 Pulled By: anand1976 fbshipit-source-id: 774406dab3776d979c809522a67bedac6c17f84b |
6 years ago |