Summary:
With Ribbon filter work and possible variance in actual bits
per key (or prefix; general term "entry") to achieve certain FP rates,
I've received a request to be able to track actual bits per key in
generated filters. This change adds a num_filter_entries table
property, which can be combined with filter_size to get bits per key
(entry).
This can vary from num_entries in at least these ways:
* Different versions of same key are only counted once in filters.
* With prefix filters, several user keys map to the same filter entry.
* A single filter can include both prefixes and user keys.
Note that FilterBlockBuilder::NumAdded() didn't do anything useful
except distinguish empty from non-empty.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8323
Test Plan: basic unit test included, others updated
Reviewed By: jay-zhuang
Differential Revision: D28596210
Pulled By: pdillinger
fbshipit-source-id: 529a111f3c84501e5a470bc84705e436ee68c376
Summary:
Deprecate CalculateNumEntry and replace with
ApproximateNumEntries (better name) using size_t instead of int and
uint32_t, to minimize confusing casts and bad overflow behavior
(possible though probably not realistic). Bloom sizes are now explicitly
capped at max size supported by implementations: just under 4GiB for
fv=5 Bloom, and just under 512MiB for fv<5 Legacy Bloom. This
hardening could help to set up for fuzzing.
Also, since RocksDB only uses this information as an approximation
for trying to hit certain sizes for partitioned filters, it's more important
that the function be reasonably fast than for it to be completely
accurate. It's hard enough to be 100% accurate for Ribbon (currently
reversing CalculateSpace) that adding optimize_filters_for_memory
into the mix is just not worth trying to be 100% accurate for num
entries for bytes.
Also:
- Cleaned up filter_policy.h to remove MSVC warning handling and
potentially unsafe use of exception for "not implemented"
- Correct the number of entries limit beyond which current Ribbon
implementation falls back on Bloom instead.
- Consistently use "num_entries" rather than "num_entry"
- Remove LegacyBloomBitsBuilder::CalculateNumEntry as it's essentially
obsolete from general implementation
BuiltinFilterBitsBuilder::CalculateNumEntries.
- Fix filter_bench to skip some tests that don't make sense when only
one or a small number of filters has been generated.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7726
Test Plan:
expanded existing unit tests for CalculateSpace /
ApproximateNumEntries. Also manually used filter_bench to verify Legacy and
fv=5 Bloom size caps work (much too expensive for unit test). Note that
the actual bits per key is below requested due to space cap.
$ ./filter_bench -impl=0 -bits_per_key=20 -average_keys_per_filter=256000000 -vary_key_count_ratio=0 -m_keys_total_max=256 -allow_bad_fp_rate
...
Total size (MB): 511.992
Bits/key stored: 16.777
...
$ ./filter_bench -impl=2 -bits_per_key=20 -average_keys_per_filter=2000000000 -vary_key_count_ratio=0 -m_keys_total_max=2000
...
Total size (MB): 4096
Bits/key stored: 17.1799
...
$
Reviewed By: jay-zhuang
Differential Revision: D25239800
Pulled By: pdillinger
fbshipit-source-id: f94e6d065efd31e05ec630ae1a82e6400d8390c4
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
Summary:
This change enables custom implementations of FilterPolicy to
wrap a variety of NewBloomFilterPolicy and select among them based on
contextual information such as table level and compaction style.
* Moves FilterBuildingContext to public API and elaborates it with more
useful data. (It would be nice to put more general options-like data,
but at the time this object is constructed, we are using internal APIs
ImmutableCFOptions and MutableCFOptions and don't have easy access to
ColumnFamilyOptions that I can tell.)
* Renames BloomFilterPolicy::GetFilterBitsBuilderInternal to
GetBuilderWithContext, because it's now public.
* Plumbs through the table's "level_at_creation" for filter building
context.
* Simplified some tests by adding GetBuilder() to
MockBlockBasedTableTester.
* Adds test as DBBloomFilterTest.ContextCustomFilterPolicy, including
sample wrapper class LevelAndStyleCustomFilterPolicy.
* Fixes a cross-test bug in DBBloomFilterTest.OptimizeFiltersForHits
where it does not reset perf context.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6088
Test Plan: make check, valgrind on db_bloom_filter_test
Differential Revision: D18697817
Pulled By: pdillinger
fbshipit-source-id: 5f987a2d7b07cc7a33670bc08ca6b4ca698c1cf4
Summary:
Adds an improved, replacement Bloom filter implementation (FastLocalBloom) for full and partitioned filters in the block-based table. This replacement is faster and more accurate, especially for high bits per key or millions of keys in a single filter.
Speed
The improved speed, at least on recent x86_64, comes from
* Using fastrange instead of modulo (%)
* Using our new hash function (XXH3 preview, added in a previous commit), which is much faster for large keys and only *slightly* slower on keys around 12 bytes if hashing the same size many thousands of times in a row.
* Optimizing the Bloom filter queries with AVX2 SIMD operations. (Added AVX2 to the USE_SSE=1 build.) Careful design was required to support (a) SIMD-optimized queries, (b) compatible non-SIMD code that's simple and efficient, (c) flexible choice of number of probes, and (d) essentially maximized accuracy for a cache-local Bloom filter. Probes are made eight at a time, so any number of probes up to 8 is the same speed, then up to 16, etc.
* Prefetching cache lines when building the filter. Although this optimization could be applied to the old structure as well, it seems to balance out the small added cost of accumulating 64 bit hashes for adding to the filter rather than 32 bit hashes.
Here's nominal speed data from filter_bench (200MB in filters, about 10k keys each, 10 bits filter data / key, 6 probes, avg key size 24 bytes, includes hashing time) on Skylake DE (relatively low clock speed):
$ ./filter_bench -quick -impl=2 -net_includes_hashing # New Bloom filter
Build avg ns/key: 47.7135
Mixed inside/outside queries...
Single filter net ns/op: 26.2825
Random filter net ns/op: 150.459
Average FP rate %: 0.954651
$ ./filter_bench -quick -impl=0 -net_includes_hashing # Old Bloom filter
Build avg ns/key: 47.2245
Mixed inside/outside queries...
Single filter net ns/op: 63.2978
Random filter net ns/op: 188.038
Average FP rate %: 1.13823
Similar build time but dramatically faster query times on hot data (63 ns to 26 ns), and somewhat faster on stale data (188 ns to 150 ns). Performance differences on batched and skewed query loads are between these extremes as expected.
The only other interesting thing about speed is "inside" (query key was added to filter) vs. "outside" (query key was not added to filter) query times. The non-SIMD implementations are substantially slower when most queries are "outside" vs. "inside". This goes against what one might expect or would have observed years ago, as "outside" queries only need about two probes on average, due to short-circuiting, while "inside" always have num_probes (say 6). The problem is probably the nastily unpredictable branch. The SIMD implementation has few branches (very predictable) and has pretty consistent running time regardless of query outcome.
Accuracy
The generally improved accuracy (re: Issue https://github.com/facebook/rocksdb/issues/5857) comes from a better design for probing indices
within a cache line (re: Issue https://github.com/facebook/rocksdb/issues/4120) and improved accuracy for millions of keys in a single filter from using a 64-bit hash function (XXH3p). Design details in code comments.
Accuracy data (generalizes, except old impl gets worse with millions of keys):
Memory bits per key: FP rate percent old impl -> FP rate percent new impl
6: 5.70953 -> 5.69888
8: 2.45766 -> 2.29709
10: 1.13977 -> 0.959254
12: 0.662498 -> 0.411593
16: 0.353023 -> 0.0873754
24: 0.261552 -> 0.0060971
50: 0.225453 -> ~0.00003 (less than 1 in a million queries are FP)
Fixes https://github.com/facebook/rocksdb/issues/5857
Fixes https://github.com/facebook/rocksdb/issues/4120
Unlike the old implementation, this implementation has a fixed cache line size (64 bytes). At 10 bits per key, the accuracy of this new implementation is very close to the old implementation with 128-byte cache line size. If there's sufficient demand, this implementation could be generalized.
Compatibility
Although old releases would see the new structure as corrupt filter data and read the table as if there's no filter, we've decided only to enable the new Bloom filter with new format_version=5. This provides a smooth path for automatic adoption over time, with an option for early opt-in.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6007
Test Plan: filter_bench has been used thoroughly to validate speed, accuracy, and correctness. Unit tests have been carefully updated to exercise new and old implementations, as well as the logic to select an implementation based on context (format_version).
Differential Revision: D18294749
Pulled By: pdillinger
fbshipit-source-id: d44c9db3696e4d0a17caaec47075b7755c262c5f
Summary:
Some filtering tests were unfriendly to new implementations of
FilterBitsBuilder because of dynamic_cast to FullFilterBitsBuilder. Most
of those have now been cleaned up, worked around, or at least changed
from crash on dynamic_cast failure to individual test failure.
Also put some clarifying comments on filter-related APIs.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5960
Test Plan: make check
Differential Revision: D18121223
Pulled By: pdillinger
fbshipit-source-id: e83827d9d5d96315d96f8e25a99cd70f497d802c
Summary:
The parts that are used to implement FilterPolicy /
NewBloomFilterPolicy and not used other than for the block-based table
should be consolidated under table/block_based/filter_policy*. I don't
foresee sharing these APIs with e.g. the Plain Table because they don't
expose hashes for reuse in indexing.
This change is step 1 of 2:
(a) mv table/full_filter_bits_builder.h to
table/block_based/filter_policy_internal.h which I expect to expand
soon to internally reveal more implementation details for testing.
(b) consolidate eventual contents of table/block_based/filter_policy.cc
in util/bloom.cc, which has the most elaborate revision history
(see step 2 ...)
Step 2 soon to follow:
mv util/bloom.cc table/block_based/filter_policy.cc
This gets its own PR so that git has the best chance of following the
rename for blame purposes. Note that low-level shared implementation
details of Bloom filters are in util/bloom_impl.h.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5963
Test Plan: make check
Differential Revision: D18121199
Pulled By: pdillinger
fbshipit-source-id: 8f21732c3d8909777e3240e4ac3123d73140326a
Summary:
Amongst other things, PR https://github.com/facebook/rocksdb/issues/5504 refactored the filter block readers so that
only the filter block contents are stored in the block cache (as opposed to the
earlier design where the cache stored the filter block reader itself, leading to
potentially dangling pointers and concurrency bugs). However, this change
introduced a performance hit since with the new code, the metadata fields are
re-parsed upon every access. This patch reunites the block contents with the
filter bits reader to eliminate this overhead; since this is still a self-contained
pure data object, it is safe to store it in the cache. (Note: this is similar to how
the zstd digest is handled.)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5936
Test Plan:
make asan_check
filter_bench results for the old code:
```
$ ./filter_bench -quick
WARNING: Assertions are enabled; benchmarks unnecessarily slow
Building...
Build avg ns/key: 26.7153
Number of filters: 16669
Total memory (MB): 200.009
Bits/key actual: 10.0647
----------------------------
Inside queries...
Dry run (46b) ns/op: 33.4258
Single filter ns/op: 42.5974
Random filter ns/op: 217.861
----------------------------
Outside queries...
Dry run (25d) ns/op: 32.4217
Single filter ns/op: 50.9855
Random filter ns/op: 219.167
Average FP rate %: 1.13993
----------------------------
Done. (For more info, run with -legend or -help.)
$ ./filter_bench -quick -use_full_block_reader
WARNING: Assertions are enabled; benchmarks unnecessarily slow
Building...
Build avg ns/key: 26.5172
Number of filters: 16669
Total memory (MB): 200.009
Bits/key actual: 10.0647
----------------------------
Inside queries...
Dry run (46b) ns/op: 32.3556
Single filter ns/op: 83.2239
Random filter ns/op: 370.676
----------------------------
Outside queries...
Dry run (25d) ns/op: 32.2265
Single filter ns/op: 93.5651
Random filter ns/op: 408.393
Average FP rate %: 1.13993
----------------------------
Done. (For more info, run with -legend or -help.)
```
With the new code:
```
$ ./filter_bench -quick
WARNING: Assertions are enabled; benchmarks unnecessarily slow
Building...
Build avg ns/key: 25.4285
Number of filters: 16669
Total memory (MB): 200.009
Bits/key actual: 10.0647
----------------------------
Inside queries...
Dry run (46b) ns/op: 31.0594
Single filter ns/op: 43.8974
Random filter ns/op: 226.075
----------------------------
Outside queries...
Dry run (25d) ns/op: 31.0295
Single filter ns/op: 50.3824
Random filter ns/op: 226.805
Average FP rate %: 1.13993
----------------------------
Done. (For more info, run with -legend or -help.)
$ ./filter_bench -quick -use_full_block_reader
WARNING: Assertions are enabled; benchmarks unnecessarily slow
Building...
Build avg ns/key: 26.5308
Number of filters: 16669
Total memory (MB): 200.009
Bits/key actual: 10.0647
----------------------------
Inside queries...
Dry run (46b) ns/op: 33.2968
Single filter ns/op: 58.6163
Random filter ns/op: 291.434
----------------------------
Outside queries...
Dry run (25d) ns/op: 32.1839
Single filter ns/op: 66.9039
Random filter ns/op: 292.828
Average FP rate %: 1.13993
----------------------------
Done. (For more info, run with -legend or -help.)
```
Differential Revision: D17991712
Pulled By: ltamasi
fbshipit-source-id: 7ea205550217bfaaa1d5158ebd658e5832e60f29
Summary:
Example: using the tool before and after PR https://github.com/facebook/rocksdb/issues/5784 shows that
the refactoring, presumed performance-neutral, actually sped up SST
filters by about 3% to 8% (repeatable result):
Before:
- Dry run ns/op: 22.4725
- Single filter ns/op: 51.1078
- Random filter ns/op: 120.133
After:
+ Dry run ns/op: 22.2301
+ Single filter run ns/op: 47.4313
+ Random filter ns/op: 115.9
Only tests filters for the block-based table (full filters and
partitioned filters - same implementation; not block-based filters),
which seems to be the recommended format/implementation.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5825
Differential Revision: D17804987
Pulled By: pdillinger
fbshipit-source-id: 0f18a9c254c57f7866030d03e7fa4ba503bac3c5
Summary:
RocksDB has historically stored uncompression dictionary objects in the block
cache as opposed to storing just the block contents. This neccesitated
evicting the object upon table close. With the new code, only the raw blocks
are stored in the cache, eliminating the need for eviction.
In addition, the patch makes the following improvements:
1) Compression dictionary blocks are now prefetched/pinned similarly to
index/filter blocks.
2) A copy operation got eliminated when the uncompression dictionary is
retrieved.
3) Errors related to retrieving the uncompression dictionary are propagated as
opposed to silently ignored.
Note: the patch temporarily breaks the compression dictionary evicition stats.
They will be fixed in a separate phase.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5584
Test Plan: make asan_check
Differential Revision: D16344151
Pulled By: ltamasi
fbshipit-source-id: 2962b295f5b19628f9da88a3fcebbce5a5017a7b
Summary:
Currently, when the block cache is used for the filter block, it is not
really the block itself that is stored in the cache but a FilterBlockReader
object. Since this object is not pure data (it has, for instance, pointers that
might dangle, including in one case a back pointer to the TableReader), it's not
really sharable. To avoid the issues around this, the current code erases the
cache entries when the TableReader is closed (which, BTW, is not sufficient
since a concurrent TableReader might have picked up the object in the meantime).
Instead of doing this, the patch moves the FilterBlockReader out of the cache
altogether, and decouples the filter reader object from the filter block.
In particular, instead of the TableReader owning, or caching/pinning the
FilterBlockReader (based on the customer's settings), with the change the
TableReader unconditionally owns the FilterBlockReader, which in turn
owns/caches/pins the filter block. This change also enables us to reuse the code
paths historically used for data blocks for filters as well.
Note:
Eviction statistics for filter blocks are temporarily broken. We plan to fix this in a
separate phase.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5504
Test Plan: make asan_check
Differential Revision: D16036974
Pulled By: ltamasi
fbshipit-source-id: 770f543c5fb4ed126fd1e04bfd3809cf4ff9c091
Summary:
BlockCacheLookupContext only contains the caller for now.
We will trace block accesses at five places:
1. BlockBasedTable::GetFilter.
2. BlockBasedTable::GetUncompressedDict.
3. BlockBasedTable::MaybeReadAndLoadToCache. (To trace access on data, index, and range deletion block.)
4. BlockBasedTable::Get. (To trace the referenced key and whether the referenced key exists in a fetched data block.)
5. BlockBasedTable::MultiGet. (To trace the referenced key and whether the referenced key exists in a fetched data block.)
We create the context at:
1. BlockBasedTable::Get. (kUserGet)
2. BlockBasedTable::MultiGet. (kUserMGet)
3. BlockBasedTable::NewIterator. (either kUserIterator, kCompaction, or external SST ingestion calls this function.)
4. BlockBasedTable::Open. (kPrefetch)
5. Index/Filter::CacheDependencies. (kPrefetch)
6. BlockBasedTable::ApproximateOffsetOf. (kCompaction or kUserApproximateSize).
I loaded 1 million key-value pairs into the database and ran the readrandom benchmark with a single thread. I gave the block cache 10 GB to make sure all reads hit the block cache after warmup. The throughput is comparable.
Throughput of this PR: 231334 ops/s.
Throughput of the master branch: 238428 ops/s.
Experiment setup:
RocksDB: version 6.2
Date: Mon Jun 10 10:42:51 2019
CPU: 24 * Intel Core Processor (Skylake)
CPUCache: 16384 KB
Keys: 20 bytes each
Values: 100 bytes each (100 bytes after compression)
Entries: 1000000
Prefix: 20 bytes
Keys per prefix: 0
RawSize: 114.4 MB (estimated)
FileSize: 114.4 MB (estimated)
Write rate: 0 bytes/second
Read rate: 0 ops/second
Compression: NoCompression
Compression sampling rate: 0
Memtablerep: skip_list
Perf Level: 1
Load command: ./db_bench --benchmarks="fillseq" --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --statistics --cache_index_and_filter_blocks --cache_size=10737418240 --disable_auto_compactions=1 --disable_wal=1 --compression_type=none --min_level_to_compress=-1 --compression_ratio=1 --num=1000000
Run command: ./db_bench --benchmarks="readrandom,stats" --use_existing_db --threads=1 --duration=120 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --statistics --cache_index_and_filter_blocks --cache_size=10737418240 --disable_auto_compactions=1 --disable_wal=1 --compression_type=none --min_level_to_compress=-1 --compression_ratio=1 --num=1000000 --duration=120
TODOs:
1. Create a caller for external SST file ingestion and differentiate the callers for iterator.
2. Integrate tracer to trace block cache accesses.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5421
Differential Revision: D15704258
Pulled By: HaoyuHuang
fbshipit-source-id: 4aa8a55f8cb1576ffb367bfa3186a91d8f06d93a
Summary:
There are too many types of files under util/. Some test related files don't belong to there or just are just loosely related. Mo
ve them to a new directory test_util/, so that util/ is cleaner.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5377
Differential Revision: D15551366
Pulled By: siying
fbshipit-source-id: 0f5c8653832354ef8caa31749c0143815d719e2c
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
Summary:
Currently it is not possible to change bloom filter config without restart the db, which is causing a lot of operational complexity for users.
This PR aims to make it possible to dynamically change bloom filter config.
Closes https://github.com/facebook/rocksdb/pull/3601
Differential Revision: D7253114
Pulled By: miasantreble
fbshipit-source-id: f22595437d3e0b86c95918c484502de2ceca120c
Summary:
bc0da4b512 optimized bloom filters by skipping duplicate entires when the whole key and prefixes are both added to the bloom. It however used empty string as the initial value of the last entry added to the bloom. This is incorrect since empty key/prefix are valid entires by themselves. This patch fixes that.
Closes https://github.com/facebook/rocksdb/pull/3776
Differential Revision: D7778803
Pulled By: maysamyabandeh
fbshipit-source-id: d5a065daebee17f9403cac51e9d5626aac87bfbc
Summary:
Currently we rely on FilterBitsBuilder to skip the duplicate keys. It does that by comparing that hash of the key to the hash of the last added entry. This logic breaks however when we have whole_key_filtering mixed with prefix blooms as their addition to FilterBitsBuilder will be interleaved. The patch fixes that by comparing the last whole key and last prefix with the whole key and prefix of the new key respectively and skip the call to FilterBitsBuilder if it is a duplicate.
Closes https://github.com/facebook/rocksdb/pull/3764
Differential Revision: D7744413
Pulled By: maysamyabandeh
fbshipit-source-id: 15df73bbbafdfd754d4e1f42ea07f47b03bc5eb8
Summary:
This is an effort to club all string related utility functions into one common place, in string_util, so that it is easier for everyone to know what string processing functions are available. Right now they seem to be spread out across multiple modules, like logging and options_helper.
Check the sub-commits for easier reviewing.
Closes https://github.com/facebook/rocksdb/pull/2094
Differential Revision: D4837730
Pulled By: sagar0
fbshipit-source-id: 344278a
Summary: With `table_options.cache_index_and_filter_blocks = true`, index and filter blocks are stored in block cache. Then people are curious how much of the block cache total size is used by indexes and bloom filters. It will be nice we have a way to report that. It can help people tune performance and plan for optimized hardware setting. We add several enum values for db Statistics. BLOCK_CACHE_INDEX/FILTER_BYTES_INSERT - BLOCK_CACHE_INDEX/FILTER_BYTES_ERASE = current INDEX/FILTER total block size in bytes.
Test Plan:
write a test case called `DBBlockCacheTest.IndexAndFilterBlocksStats`. The result is:
```
[gzh@dev9927.prn1 ~/local/rocksdb] make db_block_cache_test -j64 && ./db_block_cache_test --gtest_filter=DBBlockCacheTest.IndexAndFilterBlocksStats
Makefile:101: Warning: Compiling in debug mode. Don't use the resulting binary in production
GEN util/build_version.cc
make: `db_block_cache_test' is up to date.
Note: Google Test filter = DBBlockCacheTest.IndexAndFilterBlocksStats
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from DBBlockCacheTest
[ RUN ] DBBlockCacheTest.IndexAndFilterBlocksStats
[ OK ] DBBlockCacheTest.IndexAndFilterBlocksStats (689 ms)
[----------] 1 test from DBBlockCacheTest (689 ms total)
[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (689 ms total)
[ PASSED ] 1 test.
```
Reviewers: IslamAbdelRahman, andrewkr, sdong
Reviewed By: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D58677
Summary:
Our existing test notation is very similar to what is used in gtest. It makes it easy to adopt what is different.
In this diff I modify existing [[ https://code.google.com/p/googletest/wiki/Primer#Test_Fixtures:_Using_the_Same_Data_Configuration_for_Multiple_Te | test fixture ]] classes to inherit from `testing::Test`. Also for unit tests that use fixture class, `TEST` is replaced with `TEST_F` as required in gtest.
There are several custom `main` functions in our existing tests. To make this transition easier, I modify all `main` functions to fallow gtest notation. But eventually we can remove them and use implementation of `main` that gtest provides.
```lang=bash
% cat ~/transform
#!/bin/sh
files=$(git ls-files '*test\.cc')
for file in $files
do
if grep -q "rocksdb::test::RunAllTests()" $file
then
if grep -Eq '^class \w+Test {' $file
then
perl -pi -e 's/^(class \w+Test) {/${1}: public testing::Test {/g' $file
perl -pi -e 's/^(TEST)/${1}_F/g' $file
fi
perl -pi -e 's/(int main.*\{)/${1}::testing::InitGoogleTest(&argc, argv);/g' $file
perl -pi -e 's/rocksdb::test::RunAllTests/RUN_ALL_TESTS/g' $file
fi
done
% sh ~/transform
% make format
```
Second iteration of this diff contains only scripted changes.
Third iteration contains manual changes to fix last errors and make it compilable.
Test Plan:
Build and notice no errors.
```lang=bash
% USE_CLANG=1 make check -j55
```
Tests are still testing.
Reviewers: meyering, sdong, rven, igor
Reviewed By: igor
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D35157
Summary:
When using latest clang (3.6 or 3.7/trunck) rocksdb is failing with many errors. Almost all of them are missing override errors. This diff adds missing override keyword. No manual changes.
Prerequisites: bear and clang 3.5 build with extra tools
```lang=bash
% USE_CLANG=1 bear make all # generate a compilation database http://clang.llvm.org/docs/JSONCompilationDatabase.html
% clang-modernize -p . -include . -add-override
% make format
```
Test Plan:
Make sure all tests are passing.
```lang=bash
% #Use default fb code clang.
% make check
```
Verify less error and no missing override errors.
```lang=bash
% # Have trunk clang present in path.
% ROCKSDB_NO_FBCODE=1 CC=clang CXX=clang++ make
```
Reviewers: igor, kradhakrishnan, rven, meyering, sdong
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D34077
Summary: Remember whole key or prefix filtering on/off in SST files. If user opens the DB with a different setting that cannot be satisfied while reading the SST file, ignore the bloom filter.
Test Plan: Add a unit test for it
Reviewers: yhchiang, igor, rven
Reviewed By: rven
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D32889
Summary:
We need to turn on -Wshorten-64-to-32 for mobile. See D1671432 (internal phabricator) for details.
This diff turns on the warning flag and fixes all the errors. There were also some interesting errors that I might call bugs, especially in plain table. Going forward, I think it makes sense to have this flag turned on and be very very careful when converting 64-bit to 32-bit variables.
Test Plan: compiles
Reviewers: ljin, rven, yhchiang, sdong
Reviewed By: yhchiang
Subscribers: bobbaldwin, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D28689
Summary:
1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file.
2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter.
3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type.
4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h.
5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc
Benchmark: base commit 1d23b5c470
Command:
db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1
Read QPS increase for about 30% from 2230002 to 2991411.
Test Plan:
make all check
valgrind db_test
db_stress --use_block_based_filter = 0
./auto_sanity_test.sh
Reviewers: igor, yhchiang, ljin, sdong
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D20979