Commit Graph

47 Commits

Author SHA1 Message Date
Peter Dillinger
239d17a19c Support optimize_filters_for_memory for Ribbon filter (#7774)
Summary:
Primarily this change refactors the optimize_filters_for_memory
code for Bloom filters, based on malloc_usable_size, to also work for
Ribbon filters.

This change also replaces the somewhat slow but general
BuiltinFilterBitsBuilder::ApproximateNumEntries with
implementation-specific versions for Ribbon (new) and Legacy Bloom
(based on a recently deleted version). The reason is to emphasize
speed in ApproximateNumEntries rather than 100% accuracy.

Justification: ApproximateNumEntries (formerly CalculateNumEntry) is
only used by RocksDB for range-partitioned filters, called each time we
start to construct one. (In theory, it should be possible to reuse the
estimate, but the abstractions provided by FilterPolicy don't really
make that workable.) But this is only used as a heuristic estimate for
hitting a desired partitioned filter size because of alignment to data
blocks, which have various numbers of unique keys or prefixes. The two
factors lead us to prioritize reasonable speed over 100% accuracy.

optimize_filters_for_memory adds extra complication, because precisely
calculating num_entries for some allowed number of bytes depends on state
with optimize_filters_for_memory enabled. And the allocator-agnostic
implementation of optimize_filters_for_memory, using malloc_usable_size,
means we would have to actually allocate memory, many times, just to
precisely determine how many entries (keys) could be added and stay below
some size budget, for the current state. (In a draft, I got this
working, and then realized the balance of speed vs. accuracy was all
wrong.)

So related to that, I have made CalculateSpace, an internal-only API
only used for testing, non-authoritative also if
optimize_filters_for_memory is enabled. This simplifies some code.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/7774

Test Plan:
unit test updated, and for FilterSize test, range of tested
values is greatly expanded (still super fast)

Also tested `db_bench -benchmarks=fillrandom,stats -bloom_bits=10 -num=1000000 -partition_index_and_filters -format_version=5 [-optimize_filters_for_memory] [-use_ribbon_filter]` with temporary debug output of generated filter sizes.

Bloom+optimize_filters_for_memory:

      1 Filter size: 197 (224 in memory)
    134 Filter size: 3525 (3584 in memory)
    107 Filter size: 4037 (4096 in memory)
    Total on disk: 904,506
    Total in memory: 918,752

Ribbon+optimize_filters_for_memory:

      1 Filter size: 3061 (3072 in memory)
    110 Filter size: 3573 (3584 in memory)
     58 Filter size: 4085 (4096 in memory)
    Total on disk: 633,021 (-30.0%)
    Total in memory: 634,880 (-30.9%)

Bloom (no offm):

      1 Filter size: 261 (320 in memory)
      1 Filter size: 3333 (3584 in memory)
    240 Filter size: 3717 (4096 in memory)
    Total on disk: 895,674 (-1% on disk vs. +offm; known tolerable overhead of offm)
    Total in memory: 986,944 (+7.4% vs. +offm)

Ribbon (no offm):

      1 Filter size: 2949 (3072 in memory)
      1 Filter size: 3381 (3584 in memory)
    167 Filter size: 3701 (4096 in memory)
    Total on disk: 624,397 (-30.3% vs. Bloom)
    Total in memory: 690,688 (-30.0% vs. Bloom)

Note that optimize_filters_for_memory is even more effective for Ribbon filter than for cache-local Bloom, because it can close the unused memory gap even tighter than Bloom filter, because of 16 byte increments for Ribbon vs. 64 byte increments for Bloom.

Reviewed By: jay-zhuang

Differential Revision: D25592970

Pulled By: pdillinger

fbshipit-source-id: 606fdaa025bb790d7e9c21601e8ea86e10541912
2020-12-18 14:31:03 -08:00
Peter Dillinger
003e72b201 Use size_t for filter APIs, protect against overflow (#7726)
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
2020-12-11 22:18:12 -08:00
Peter Dillinger
0baa5055f1 Add Ribbon schema test to bloom_test (#7696)
Summary:
These new unit tests should ensure that we don't accidentally
change the interpretation of bits for what I call Standard128Ribbon
filter internally, available publicly as NewExperimentalRibbonFilterPolicy.
There is very little intuitive reason for the values we check against in
these tests; I just plug in the right expected values upon watching the
test fail initially.

Most (but not all) of the tests are essentially "whitebox" "round-trip." We
create a filter from fixed keys, and first compare the checksum of those
filter bytes against a saved value. We also run queries against other fixed
keys, comparing which return false positives against a saved set.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/7696

Test Plan: test addition and refactoring only

Reviewed By: jay-zhuang

Differential Revision: D25082289

Pulled By: pdillinger

fbshipit-source-id: b5ca646fdcb5a1c2ad2085eda4a1fd44c4287f67
2020-11-22 19:52:04 -08:00
Peter Dillinger
60af964372 Experimental (production candidate) SST schema for Ribbon filter (#7658)
Summary:
Added experimental public API for Ribbon filter:
NewExperimentalRibbonFilterPolicy(). This experimental API will
take a "Bloom equivalent" bits per key, and configure the Ribbon
filter for the same FP rate as Bloom would have but ~30% space
savings. (Note: optimize_filters_for_memory is not yet implemented
for Ribbon filter. That can be added with no effect on schema.)

Internally, the Ribbon filter is configured using a "one_in_fp_rate"
value, which is 1 over desired FP rate. For example, use 100 for 1%
FP rate. I'm expecting this will be used in the future for configuring
Bloom-like filters, as I expect people to more commonly hold constant
the filter accuracy and change the space vs. time trade-off, rather than
hold constant the space (per key) and change the accuracy vs. time
trade-off, though we might make that available.

### Benchmarking

```
$ ./filter_bench -impl=2 -quick -m_keys_total_max=200 -average_keys_per_filter=100000 -net_includes_hashing
Building...
Build avg ns/key: 34.1341
Number of filters: 1993
Total size (MB): 238.488
Reported total allocated memory (MB): 262.875
Reported internal fragmentation: 10.2255%
Bits/key stored: 10.0029
----------------------------
Mixed inside/outside queries...
  Single filter net ns/op: 18.7508
  Random filter net ns/op: 258.246
    Average FP rate %: 0.968672
----------------------------
Done. (For more info, run with -legend or -help.)
$ ./filter_bench -impl=3 -quick -m_keys_total_max=200 -average_keys_per_filter=100000 -net_includes_hashing
Building...
Build avg ns/key: 130.851
Number of filters: 1993
Total size (MB): 168.166
Reported total allocated memory (MB): 183.211
Reported internal fragmentation: 8.94626%
Bits/key stored: 7.05341
----------------------------
Mixed inside/outside queries...
  Single filter net ns/op: 58.4523
  Random filter net ns/op: 363.717
    Average FP rate %: 0.952978
----------------------------
Done. (For more info, run with -legend or -help.)
```

168.166 / 238.488 = 0.705  -> 29.5% space reduction

130.851 / 34.1341 = 3.83x construction time for this Ribbon filter vs. lastest Bloom filter (could make that as little as about 2.5x for less space reduction)

### Working around a hashing "flaw"

bloom_test discovered a flaw in the simple hashing applied in
StandardHasher when num_starts == 1 (num_slots == 128), showing an
excessively high FP rate.  The problem is that when many entries, on the
order of number of hash bits or kCoeffBits, are associated with the same
start location, the correlation between the CoeffRow and ResultRow (for
efficiency) can lead to a solution that is "universal," or nearly so, for
entries mapping to that start location. (Normally, variance in start
location breaks the effective association between CoeffRow and
ResultRow; the same value for CoeffRow is effectively different if start
locations are different.) Without kUseSmash and with num_starts > 1 (thus
num_starts ~= num_slots), this flaw should be completely irrelevant.  Even
with 10M slots, the chances of a single slot having just 16 (or more)
entries map to it--not enough to cause an FP problem, which would be local
to that slot if it happened--is 1 in millions. This spreadsheet formula
shows that: =1/(10000000*(1 - POISSON(15, 1, TRUE)))

As kUseSmash==false (the setting for Standard128RibbonBitsBuilder) is
intended for CPU efficiency of filters with many more entries/slots than
kCoeffBits, a very reasonable work-around is to disallow num_starts==1
when !kUseSmash, by making the minimum non-zero number of slots
2*kCoeffBits. This is the work-around I've applied. This also means that
the new Ribbon filter schema (Standard128RibbonBitsBuilder) is not
space-efficient for less than a few hundred entries. Because of this, I
have made it fall back on constructing a Bloom filter, under existing
schema, when that is more space efficient for small filters. (We can
change this in the future if we want.)

TODO: better unit tests for this case in ribbon_test, and probably
update StandardHasher for kUseSmash case so that it can scale nicely to
small filters.

### Other related changes

* Add Ribbon filter to stress/crash test
* Add Ribbon filter to filter_bench as -impl=3
* Add option string support, as in "filter_policy=experimental_ribbon:5.678;"
where 5.678 is the Bloom equivalent bits per key.
* Rename internal mode BloomFilterPolicy::kAuto to kAutoBloom
* Add a general BuiltinFilterBitsBuilder::CalculateNumEntry based on
binary searching CalculateSpace (inefficient), so that subclasses
(especially experimental ones) don't have to provide an efficient
implementation inverting CalculateSpace.
* Minor refactor FastLocalBloomBitsBuilder for new base class
XXH3pFilterBitsBuilder shared with new Standard128RibbonBitsBuilder,
which allows the latter to fall back on Bloom construction in some
extreme cases.
* Mostly updated bloom_test for Ribbon filter, though a test like
FullBloomTest::Schema is a next TODO to ensure schema stability
(in case this becomes production-ready schema as it is).
* Add some APIs to ribbon_impl.h for configuring Ribbon filters.
Although these are reasonably covered by bloom_test, TODO more unit
tests in ribbon_test
* Added a "tool" FindOccupancyForSuccessRate to ribbon_test to get data
for constructing the linear approximations in GetNumSlotsFor95PctSuccess.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/7658

Test Plan:
Some unit tests updated but other testing is left TODO. This
is considered experimental but laying down schema compatibility as early
as possible in case it proves production-quality. Also tested in
stress/crash test.

Reviewed By: jay-zhuang

Differential Revision: D24899349

Pulled By: pdillinger

fbshipit-source-id: 9715f3e6371c959d923aea8077c9423c7a9f82b8
2020-11-12 20:46:14 -08:00
Yanqin Jin
394210f280 Remove unused includes (#7604)
Summary:
This is a PR generated **semi-automatically** by an internal tool to remove unused includes and `using` statements.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/7604

Test Plan: make check

Reviewed By: ajkr

Differential Revision: D24579392

Pulled By: riversand963

fbshipit-source-id: c4bfa6c6b08da1de186690d37eb73d8fff45aecd
2020-10-28 23:22:27 -07:00
Peter Dillinger
5b2bbacb6f Minimize memory internal fragmentation for Bloom filters (#6427)
Summary:
New experimental option BBTO::optimize_filters_for_memory builds
filters that maximize their use of "usable size" from malloc_usable_size,
which is also used to compute block cache charges.

Rather than always "rounding up," we track state in the
BloomFilterPolicy object to mix essentially "rounding down" and
"rounding up" so that the average FP rate of all generated filters is
the same as without the option. (YMMV as heavily accessed filters might
be unluckily lower accuracy.)

Thus, the option near-minimizes what the block cache considers as
"memory used" for a given target Bloom filter false positive rate and
Bloom filter implementation. There are no forward or backward
compatibility issues with this change, though it only works on the
format_version=5 Bloom filter.

With Jemalloc, we see about 10% reduction in memory footprint (and block
cache charge) for Bloom filters, but 1-2% increase in storage footprint,
due to encoding efficiency losses (FP rate is non-linear with bits/key).

Why not weighted random round up/down rather than state tracking? By
only requiring malloc_usable_size, we don't actually know what the next
larger and next smaller usable sizes for the allocator are. We pick a
requested size, accept and use whatever usable size it has, and use the
difference to inform our next choice. This allows us to narrow in on the
right balance without tracking/predicting usable sizes.

Why not weight history of generated filter false positive rates by
number of keys? This could lead to excess skew in small filters after
generating a large filter.

Results from filter_bench with jemalloc (irrelevant details omitted):

    (normal keys/filter, but high variance)
    $ ./filter_bench -quick -impl=2 -average_keys_per_filter=30000 -vary_key_count_ratio=0.9
    Build avg ns/key: 29.6278
    Number of filters: 5516
    Total size (MB): 200.046
    Reported total allocated memory (MB): 220.597
    Reported internal fragmentation: 10.2732%
    Bits/key stored: 10.0097
    Average FP rate %: 0.965228
    $ ./filter_bench -quick -impl=2 -average_keys_per_filter=30000 -vary_key_count_ratio=0.9 -optimize_filters_for_memory
    Build avg ns/key: 30.5104
    Number of filters: 5464
    Total size (MB): 200.015
    Reported total allocated memory (MB): 200.322
    Reported internal fragmentation: 0.153709%
    Bits/key stored: 10.1011
    Average FP rate %: 0.966313

    (very few keys / filter, optimization not as effective due to ~59 byte
     internal fragmentation in blocked Bloom filter representation)
    $ ./filter_bench -quick -impl=2 -average_keys_per_filter=1000 -vary_key_count_ratio=0.9
    Build avg ns/key: 29.5649
    Number of filters: 162950
    Total size (MB): 200.001
    Reported total allocated memory (MB): 224.624
    Reported internal fragmentation: 12.3117%
    Bits/key stored: 10.2951
    Average FP rate %: 0.821534
    $ ./filter_bench -quick -impl=2 -average_keys_per_filter=1000 -vary_key_count_ratio=0.9 -optimize_filters_for_memory
    Build avg ns/key: 31.8057
    Number of filters: 159849
    Total size (MB): 200
    Reported total allocated memory (MB): 208.846
    Reported internal fragmentation: 4.42297%
    Bits/key stored: 10.4948
    Average FP rate %: 0.811006

    (high keys/filter)
    $ ./filter_bench -quick -impl=2 -average_keys_per_filter=1000000 -vary_key_count_ratio=0.9
    Build avg ns/key: 29.7017
    Number of filters: 164
    Total size (MB): 200.352
    Reported total allocated memory (MB): 221.5
    Reported internal fragmentation: 10.5552%
    Bits/key stored: 10.0003
    Average FP rate %: 0.969358
    $ ./filter_bench -quick -impl=2 -average_keys_per_filter=1000000 -vary_key_count_ratio=0.9 -optimize_filters_for_memory
    Build avg ns/key: 30.7131
    Number of filters: 160
    Total size (MB): 200.928
    Reported total allocated memory (MB): 200.938
    Reported internal fragmentation: 0.00448054%
    Bits/key stored: 10.1852
    Average FP rate %: 0.963387

And from db_bench (block cache) with jemalloc:

    $ ./db_bench -db=/dev/shm/dbbench.no_optimize -benchmarks=fillrandom -format_version=5 -value_size=90 -bloom_bits=10 -num=2000000 -threads=8 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=false
    $ ./db_bench -db=/dev/shm/dbbench -benchmarks=fillrandom -format_version=5 -value_size=90 -bloom_bits=10 -num=2000000 -threads=8 -optimize_filters_for_memory -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=false
    $ (for FILE in /dev/shm/dbbench.no_optimize/*.sst; do ./sst_dump --file=$FILE --show_properties | grep 'filter block' ; done) | awk '{ t += $4; } END { print t; }'
    17063835
    $ (for FILE in /dev/shm/dbbench/*.sst; do ./sst_dump --file=$FILE --show_properties | grep 'filter block' ; done) | awk '{ t += $4; } END { print t; }'
    17430747
    $ #^ 2.1% additional filter storage
    $ ./db_bench -db=/dev/shm/dbbench.no_optimize -use_existing_db -benchmarks=readrandom,stats -statistics -bloom_bits=10 -num=2000000 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=false -duration=10 -cache_index_and_filter_blocks -cache_size=1000000000
    rocksdb.block.cache.index.add COUNT : 33
    rocksdb.block.cache.index.bytes.insert COUNT : 8440400
    rocksdb.block.cache.filter.add COUNT : 33
    rocksdb.block.cache.filter.bytes.insert COUNT : 21087528
    rocksdb.bloom.filter.useful COUNT : 4963889
    rocksdb.bloom.filter.full.positive COUNT : 1214081
    rocksdb.bloom.filter.full.true.positive COUNT : 1161999
    $ #^ 1.04 % observed FP rate
    $ ./db_bench -db=/dev/shm/dbbench -use_existing_db -benchmarks=readrandom,stats -statistics -bloom_bits=10 -num=2000000 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=false -optimize_filters_for_memory -duration=10 -cache_index_and_filter_blocks -cache_size=1000000000
    rocksdb.block.cache.index.add COUNT : 33
    rocksdb.block.cache.index.bytes.insert COUNT : 8448592
    rocksdb.block.cache.filter.add COUNT : 33
    rocksdb.block.cache.filter.bytes.insert COUNT : 18220328
    rocksdb.bloom.filter.useful COUNT : 5360933
    rocksdb.bloom.filter.full.positive COUNT : 1321315
    rocksdb.bloom.filter.full.true.positive COUNT : 1262999
    $ #^ 1.08 % observed FP rate, 13.6% less memory usage for filters

(Due to specific key density, this example tends to generate filters that are "worse than average" for internal fragmentation. "Better than average" cases can show little or no improvement.)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6427

Test Plan: unit test added, 'make check' with gcc, clang and valgrind

Reviewed By: siying

Differential Revision: D22124374

Pulled By: pdillinger

fbshipit-source-id: f3e3aa152f9043ddf4fae25799e76341d0d8714e
2020-06-22 13:32:07 -07:00
sdong
afa3518839 Revert "Update googletest from 1.8.1 to 1.10.0 (#6808)" (#6923)
Summary:
This reverts commit 8d87e9cea1.

Based on offline discussions, it's too early to upgrade to gtest 1.10, as it prevents some developers from using an older version of gtest to integrate to some other systems. Revert it for now.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6923

Reviewed By: pdillinger

Differential Revision: D21864799

fbshipit-source-id: d0726b1ff649fc911b9378f1763316200bd363fc
2020-06-03 15:55:03 -07:00
Adam Retter
8d87e9cea1 Update googletest from 1.8.1 to 1.10.0 (#6808)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/6808

Reviewed By: anand1976

Differential Revision: D21483984

Pulled By: pdillinger

fbshipit-source-id: 70c5eff2bd54ddba469761d95e4cd4611fb8e598
2020-06-01 20:33:42 -07:00
Huisheng Liu
07a3f7f008 fix MSVC build failures (#6517)
Summary:
fix a few build warnings that are treated as failures with more strict MSVC warning settings
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6517

Differential Revision: D20401325

Pulled By: pdillinger

fbshipit-source-id: b44979dfaafdc7b3b8cb44a565400a99b331dd30
2020-03-12 08:42:39 -07:00
sdong
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
2020-02-20 12:09:57 -08:00
Peter Dillinger
ca3b6c28c9 Expose and elaborate FilterBuildingContext (#6088)
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
2019-11-26 18:24:10 -08:00
Peter Dillinger
57f3032285 Allow fractional bits/key in BloomFilterPolicy (#6092)
Summary:
There's no technological impediment to allowing the Bloom
filter bits/key to be non-integer (fractional/decimal) values, and it
provides finer control over the memory vs. accuracy trade-off. This is
especially handy in using the format_version=5 Bloom filter in place
of the old one, because bits_per_key=9.55 provides the same accuracy as
the old bits_per_key=10.

This change not only requires refining the logic for choosing the best
num_probes for a given bits/key setting, it revealed a flaw in that logic.
As bits/key gets higher, the best num_probes for a cache-local Bloom
filter is closer to bpk / 2 than to bpk * 0.69, the best choice for a
standard Bloom filter. For example, at 16 bits per key, the best
num_probes is 9 (FP rate = 0.0843%) not 11 (FP rate = 0.0884%).
This change fixes and refines that logic (for the format_version=5
Bloom filter only, just in case) based on empirical tests to find
accuracy inflection points between each num_probes.

Although bits_per_key is now specified as a double, the new Bloom
filter converts/rounds this to "millibits / key" for predictable/precise
internal computations. Just in case of unforeseen compatibility
issues, we round to the nearest whole number bits / key for the
legacy Bloom filter, so as not to unlock new behaviors for it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6092

Test Plan: unit tests included

Differential Revision: D18711313

Pulled By: pdillinger

fbshipit-source-id: 1aa73295f152a995328cb846ef9157ae8a05522a
2019-11-26 15:59:34 -08:00
Peter Dillinger
f059c7d9b9 New Bloom filter implementation for full and partitioned filters (#6007)
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
2019-11-13 16:44:01 -08:00
Peter Dillinger
685e895652 Prepare filter tests for more implementations (#5967)
Summary:
This change sets up for alternate implementations underlying
BloomFilterPolicy:

* Refactor BloomFilterPolicy and expose in internal .h file so that it's easy to iterate over / select implementations for testing, regardless of what the best public interface will look like. Most notably updated db_bloom_filter_test to use this.
* Hide FullFilterBitsBuilder from unit tests (alternate derived classes planned); expose the part important for testing (CalculateSpace), as abstract class BuiltinFilterBitsBuilder. (Also cleaned up internally exposed interface to CalculateSpace.)
* Rename BloomTest -> BlockBasedBloomTest for clarity (despite ongoing confusion between block-based table and block-based filter)
* Assert that block-based filter construction interface is only used on BloomFilterPolicy appropriately constructed. (A couple of tests updated to add ", true".)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5967

Test Plan: make check

Differential Revision: D18138704

Pulled By: pdillinger

fbshipit-source-id: 55ef9273423b0696309e251f50b8c1b5e9ec7597
2019-10-31 14:12:33 -07:00
Peter Dillinger
013babc685 Clean up some filter tests and comments (#5960)
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
2019-10-24 18:48:16 -07:00
Peter Dillinger
dd19014a7a FilterPolicy consolidation, part 1/2 (#5963)
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
2019-10-24 13:20:35 -07:00
Peter Dillinger
5f8f2fda0e Refactor / clean up / optimize FullFilterBitsReader (#5941)
Summary:
FullFilterBitsReader, after creating in BloomFilterPolicy, was
responsible for decoding metadata bits. This meant that
FullFilterBitsReader::MayMatch had some metadata checks in order to
implement "always true" or "always false" functionality in the case
of inconsistent or trivial metadata. This made for ugly
mixing-of-concerns code and probably had some runtime cost. It also
didn't really support plugging in alternative filter implementations
with extensions to the existing metadata schema.

BloomFilterPolicy::GetFilterBitsReader is now (exclusively) responsible
for decoding filter metadata bits and constructing appropriate instances
deriving from FilterBitsReader. "Always false" and "always true" derived
classes allow FullFilterBitsReader not to be concerned with handling of
trivial or inconsistent metadata. This also makes for easy expansion
to alternative filter implementations in new, alternative derived
classes. This change makes calls to FilterBitsReader::MayMatch
*necessarily* virtual because there's now more than one built-in
implementation. Compared with the previous implementation's extra
'if' checks in MayMatch, there's no consistent performance difference,
measured by (an older revision of) filter_bench (differences here seem
to be within noise):

    Inside queries...
    -  Dry run (407) ns/op: 35.9996
    +  Dry run (407) ns/op: 35.2034
    -  Single filter ns/op: 47.5483
    +  Single filter ns/op: 47.4034
    -  Batched, prepared ns/op: 43.1559
    +  Batched, prepared ns/op: 42.2923
    ...
    -  Random filter ns/op: 150.697
    +  Random filter ns/op: 149.403
    ----------------------------
    Outside queries...
    -  Dry run (980) ns/op: 34.6114
    +  Dry run (980) ns/op: 34.0405
    -  Single filter ns/op: 56.8326
    +  Single filter ns/op: 55.8414
    -  Batched, prepared ns/op: 48.2346
    +  Batched, prepared ns/op: 47.5667
    -  Random filter ns/op: 155.377
    +  Random filter ns/op: 153.942
         Average FP rate %: 1.1386

Also, the FullFilterBitsReader ctor was responsible for a surprising
amount of CPU in production, due in part to inefficient determination of
the CACHE_LINE_SIZE used to construct the filter being read. The
overwhelming common case (same as my CACHE_LINE_SIZE) is now
substantially optimized, as shown with filter_bench with
-new_reader_every=1 (old option - see below) (repeatable result):

    Inside queries...
    -  Dry run (453) ns/op: 118.799
    +  Dry run (453) ns/op: 105.869
    -  Single filter ns/op: 82.5831
    +  Single filter ns/op: 74.2509
    ...
    -  Random filter ns/op: 224.936
    +  Random filter ns/op: 194.833
    ----------------------------
    Outside queries...
    -  Dry run (aa1) ns/op: 118.503
    +  Dry run (aa1) ns/op: 104.925
    -  Single filter ns/op: 90.3023
    +  Single filter ns/op: 83.425
    ...
    -  Random filter ns/op: 220.455
    +  Random filter ns/op: 175.7
         Average FP rate %: 1.13886

However PR#5936 has/will reclaim most of this cost. After that PR, the optimization of this code path is likely negligible, but nonetheless it's clear we aren't making performance any worse.

Also fixed inadequate check of consistency between filter data size and
num_lines. (Unit test updated.)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5941

Test Plan:
previously added unit tests FullBloomTest.CorruptFilters and
FullBloomTest.RawSchema

Differential Revision: D18018353

Pulled By: pdillinger

fbshipit-source-id: 8e04c2b4a7d93223f49a237fd52ef2483929ed9c
2019-10-18 14:50:52 -07:00
Peter Dillinger
93edd51c4a bloom_test.cc: include <array> (#5920)
Summary:
Fix build failure on some platforms, reported in issue https://github.com/facebook/rocksdb/issues/5914
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5920

Test Plan: make bloom_test && ./bloom_test

Differential Revision: D17918328

Pulled By: pdillinger

fbshipit-source-id: b822004d4442de0171db2aeff433677783f7b94e
2019-10-14 15:38:31 -07:00
Peter Dillinger
9f54446525 Fix type in shift operation in bloom_test (#5882)
Summary:
Broken type for shift in PR#5834. Fixing code means fixing
expected values in test.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5882

Test Plan: thisisthetest

Differential Revision: D17746136

Pulled By: pdillinger

fbshipit-source-id: d3c456ed30b433d55fcab6fc7d836940fe3b46b8
2019-10-03 13:19:20 -07:00
Peter Dillinger
9e4913ce9d Add FullBloomTest.CorruptFilters,RawSchema (#5834)
Summary:
There was significant untested logic in FullFilterBitsReader in
the handling of serialized Bloom filter bits that cannot be generated by
FullFilterBitsBuilder in the current compilation. These now test many of
those corner-case behaviors, including bad metadata or filters created
with different cache line size than the current compiled-in value.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5834

Test Plan: thisisthetest

Differential Revision: D17726372

Pulled By: pdillinger

fbshipit-source-id: fb7b8003b5a8e6fb4666fe95206128f3d5835fc7
2019-10-02 15:33:48 -07:00
sdong
e8263dbdaa Apply formatter to recent 200+ commits. (#5830)
Summary:
Further apply formatter to more recent commits.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5830

Test Plan: Run all existing tests.

Differential Revision: D17488031

fbshipit-source-id: 137458fd94d56dd271b8b40c522b03036943a2ab
2019-09-20 12:04:26 -07:00
Peter Dillinger
68626249c3 Refactor/consolidate legacy Bloom implementation details (#5784)
Summary:
Refactoring to consolidate implementation details of legacy
Bloom filters. This helps to organize and document some related,
obscure code.

Also added make/cpp var TEST_CACHE_LINE_SIZE so that it's easy to
compile and run unit tests for non-native cache line size. (Fixed a
related test failure in db_properties_test.)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5784

Test Plan:
make check, including Recently added Bloom schema unit tests
(in ./plain_table_db_test && ./bloom_test), and including with
TEST_CACHE_LINE_SIZE=128U and TEST_CACHE_LINE_SIZE=256U. Tested the
schema tests with temporary fault injection into new implementations.

Some performance testing with modified unit tests suggest a small to moderate
improvement in speed.

Differential Revision: D17381384

Pulled By: pdillinger

fbshipit-source-id: ee42586da996798910fc45ac0b6289147f16d8df
2019-09-16 16:17:09 -07:00
Peter Dillinger
d3a6726f02 Revert changes from PR#5784 accidentally in PR#5780 (#5810)
Summary:
This will allow us to fix history by having the code changes for PR#5784 properly attributed to it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5810

Differential Revision: D17400231

Pulled By: pdillinger

fbshipit-source-id: 2da8b1cdf2533cfedb35b5526eadefb38c291f09
2019-09-16 11:38:53 -07:00
Peter Dillinger
aa2486b23c Refactor some confusing logic in PlainTableReader
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/5780

Test Plan: existing plain table unit test

Differential Revision: D17368629

Pulled By: pdillinger

fbshipit-source-id: f25409cdc2f39ebe8d5cbb599cf820270e6b5d26
2019-09-13 10:26:36 -07:00
Peter Dillinger
108c619acb Add regression test for serialized Bloom filters (#5778)
Summary:
Check that we don't accidentally change the on-disk format of
existing Bloom filter implementations, including for various
CACHE_LINE_SIZE (by changing temporarily).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5778

Test Plan: thisisthetest

Differential Revision: D17269630

Pulled By: pdillinger

fbshipit-source-id: c77017662f010a77603b7d475892b1f0d5563d8b
2019-09-09 14:51:30 -07:00
HouBingjian
ac97e6930f bloom test check fail on arm (#5745)
Summary:
FullFilterBitsBuilder::CalculateSpace use CACHE_LINE_SIZE which is 64@X86 but 128@ARM64
when it run bloom_test.FullVaryingLengths it failed on ARM64 server,
the assert can be fixed by change  128->CACHE_LINE_SIZE*2 as merged
ASSERT_LE(FilterSize(), (size_t)((length * 10 / 8) + CACHE_LINE_SIZE * 2 + 5)) << length;

run  bloom_test
before fix:
/root/rocksdb-master/util/bloom_test.cc:281: Failure
Expected: (FilterSize()) <= ((size_t)((length * 10 / 8) + 128 + 5)), actual: 389 vs 383
200
[  FAILED  ] FullBloomTest.FullVaryingLengths (32 ms)
[----------] 4 tests from FullBloomTest (32 ms total)

[----------] Global test environment tear-down
[==========] 7 tests from 2 test cases ran. (116 ms total)
[  PASSED  ] 6 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] FullBloomTest.FullVaryingLengths

after fix:
Filters: 37 good, 0 mediocre
[       OK ] FullBloomTest.FullVaryingLengths (90 ms)
[----------] 4 tests from FullBloomTest (90 ms total)

[----------] Global test environment tear-down
[==========] 7 tests from 2 test cases ran. (174 ms total)
[  PASSED  ] 7 tests.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5745

Differential Revision: D17076047

fbshipit-source-id: e7beb5d55d4855fceb2b84bc8119a6b0759de635
2019-09-05 17:03:24 -07:00
Siying Dong
000b9ec217 Move some logging related files to logging/ (#5387)
Summary:
Many logging related source files are under util/. It will be more structured if they are together.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5387

Differential Revision: D15579036

Pulled By: siying

fbshipit-source-id: 3850134ed50b8c0bb40a0c8ae1f184fa4081303f
2019-05-31 17:23:59 -07:00
Siying Dong
8843129ece Move some memory related files from util/ to memory/ (#5382)
Summary:
Move arena, allocator, and memory tools under util to a separate memory/ directory.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5382

Differential Revision: D15564655

Pulled By: siying

fbshipit-source-id: 9cd6b5d0d3d52b39606e19221fa154596e5852a5
2019-05-30 17:44:09 -07:00
Siying Dong
e9e0101ca4 Move test related files under util/ to test_util/ (#5377)
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
2019-05-30 11:25:51 -07:00
Michael Liu
ca89ac2ba9 Apply modernize-use-override (2nd iteration)
Summary:
Use C++11’s override and remove virtual where applicable.
Change are automatically generated.

Reviewed By: Orvid

Differential Revision: D14090024

fbshipit-source-id: 1e9432e87d2657e1ff0028e15370a85d1739ba2a
2019-02-14 14:41:36 -08:00
Andrew Kryczka
63f1c0a57d fix gflags namespace
Summary:
I started adding gflags support for cmake on linux and got frustrated that I'd need to duplicate the build_detect_platform logic, which determines namespace based on attempting compilation. We can do it differently -- use the GFLAGS_NAMESPACE macro if available, and if not, that indicates it's an old gflags version without configurable namespace so we can simply hardcode "google".
Closes https://github.com/facebook/rocksdb/pull/3212

Differential Revision: D6456973

Pulled By: ajkr

fbshipit-source-id: 3e6d5bde3ca00d4496a120a7caf4687399f5d656
2017-12-01 10:42:05 -08:00
Siying Dong
3c327ac2d0 Change RocksDB License
Summary: Closes https://github.com/facebook/rocksdb/pull/2589

Differential Revision: D5431502

Pulled By: siying

fbshipit-source-id: 8ebf8c87883daa9daa54b2303d11ce01ab1f6f75
2017-07-15 16:11:23 -07:00
Maysam Yabandeh
45b9bb0331 Cut filter partition based on metadata_block_size
Summary:
Currently metadata_block_size controls only index partition size. With this patch a partition is cut after any of index or filter partitions reaches metadata_block_size.
Closes https://github.com/facebook/rocksdb/pull/2452

Differential Revision: D5275651

Pulled By: maysamyabandeh

fbshipit-source-id: 5057e4424b4c8902043782e6bf8c38f0c4f25160
2017-07-02 10:42:12 -07:00
Siying Dong
d616ebea23 Add GPLv2 as an alternative license.
Summary: Closes https://github.com/facebook/rocksdb/pull/2226

Differential Revision: D4967547

Pulled By: siying

fbshipit-source-id: dd3b58ae1e7a106ab6bb6f37ab5c88575b125ab4
2017-04-27 18:06:12 -07:00
Tomas Kolda
04d58970cb AIX and Solaris Sparc Support
Summary:
Replacement of #2147

The change was squashed due to a lot of conflicts.
Closes https://github.com/facebook/rocksdb/pull/2194

Differential Revision: D4929799

Pulled By: siying

fbshipit-source-id: 5cd49c254737a1d5ac13f3c035f128e86524c581
2017-04-21 20:48:04 -07:00
Baraa Hamodi
21e95811d1 Updated all copyright headers to the new format. 2016-02-09 15:12:00 -08:00
Igor Canadi
1b7ea8ce81 Skipped tests shouldn't be failures
Summary: If we skip a test, we shouldn't mark `make check` as failure. This fixes travis CI test.

Test Plan: Travis CI

Reviewers: noetzli, sdong

Reviewed By: sdong

Subscribers: dhruba, leveldb

Differential Revision: https://reviews.facebook.net/D47031
2015-09-15 18:10:36 -07:00
Igor Sugak
b4b69e4f77 rocksdb: switch to gtest
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
2015-03-17 14:08:00 -07:00
Igor Canadi
767777c2bd Turn on -Wshorten-64-to-32 and fix all the errors
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
2014-11-11 16:47:22 -05:00
Feng Zhu
0af157f9bf Implement full filter for block based table.
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
2014-09-08 10:37:05 -07:00
Igor Canadi
fec4269966 Fix more gflag namespace issues 2014-05-09 08:41:02 -07:00
Haobo Xu
3c02c363b3 [RocksDB] [Performance Branch] Added dynamic bloom, to be used for memable non-existing key filtering
Summary: as title

Test Plan: dynamic_bloom_test

Reviewers: dhruba, sdong, kailiu

CC: leveldb

Differential Revision: https://reviews.facebook.net/D14385
2013-12-11 00:15:14 -08:00
Dhruba Borthakur
9cd221094c Add appropriate LICENSE and Copyright message.
Summary:
Add appropriate LICENSE and Copyright message.

Test Plan:
make check

Reviewers:

CC:

Task ID: #

Blame Rev:
2013-10-16 17:48:41 -07:00
Dhruba Borthakur
a143ef9b38 Change namespace from leveldb to rocksdb
Summary:
Change namespace from leveldb to rocksdb. This allows a single
application to link in open-source leveldb code as well as
rocksdb code into the same process.

Test Plan: compile rocksdb

Reviewers: emayanke

Reviewed By: emayanke

CC: leveldb

Differential Revision: https://reviews.facebook.net/D13287
2013-10-04 11:59:26 -07:00
Dhruba Borthakur
1186192ed1 Replace include/leveldb with include/rocksdb.
Summary: Replace include/leveldb with include/rocksdb.

Test Plan:
make clean; make check
make clean; make release

Differential Revision: https://reviews.facebook.net/D12489
2013-08-23 10:51:00 -07:00
Dhruba Borthakur
aa42c66814 Fix all warnings generated by -Wall option to the compiler.
Summary:
The default compilation process now uses "-Wall" to compile.
Fix all compilation error generated by gcc.

Test Plan: make all check

Reviewers: heyongqiang, emayanke, sheki

Reviewed By: heyongqiang

CC: MarkCallaghan

Differential Revision: https://reviews.facebook.net/D6525
2012-11-06 14:07:31 -08:00
Sanjay Ghemawat
85584d497e Added bloom filter support.
In particular, we add a new FilterPolicy class.  An instance
of this class can be supplied in Options when opening a
database.  If supplied, the instance is used to generate
summaries of keys (e.g., a bloom filter) which are placed in
sstables.  These summaries are consulted by DB::Get() so we
can avoid reading sstable blocks that are guaranteed to not
contain the key we are looking for.

This change provides one implementation of FilterPolicy
based on bloom filters.

Other changes:
- Updated version number to 1.4.
- Some build tweaks.
- C binding for CompactRange.
- A few more benchmarks: deleteseq, deleterandom, readmissing, seekrandom.
- Minor .gitignore update.
2012-04-17 08:36:46 -07:00