Summary: removed reference to options in WriteBatch and DBImpl::Get()
Test Plan: make all check
Reviewers: yhchiang, igor, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23049
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
Summary: Fix compaction bug in Cuckoo Table Builder. Use kvs_.size() instead of num_entries in FileSize() method. Also added tests.
Test Plan:
make check all
Also ran db_bench to generate multiple files.
Reviewers: sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22743
Summary:
Simply code by removing code path which does not use Arena
from NewInternalIterator
Test Plan:
make all check
make valgrind_check
Reviewers: sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22395
Summary:
As a preparation to support updating some options dynamically, I'd like
to first introduce ImmutableOptions, which is a subset of Options that
cannot be changed during the course of a DB lifetime without restart.
ColumnFamily will keep both Options and ImmutableOptions. Any component
below ColumnFamily should only take ImmutableOptions in their
constructor. Other options should be taken from APIs, which will be
allowed to adjust dynamically.
I am yet to make changes to memtable and other related classes to take
ImmutableOptions in their ctor. That can be done in a seprate diff as
this one is already pretty big.
Test Plan: make all check
Reviewers: yhchiang, igor, sdong
Reviewed By: sdong
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D22545
1, const qualifiers on return types make no sense and will trigger a compile warning: warning: type qualifiers ignored on function return type [-Wignored-qualifiers]
2, class HistogramImpl has virtual functions and thus should have a virtual destructor
3, with some toolchain, the macro __STDC_FORMAT_MACROS is predefined and thus should be checked before define
Change-Id: I69747a03bfae88671bfbb2637c80d17600159c99
Signed-off-by: liuhuahang <liuhuahang@zerus.co>
Summary: It only covers Open() with default column family right now
Test Plan: make release
Reviewers: igor, yhchiang, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22467
This eliminates the need to remember to call PERF_TIMER_STOP when a section has
been timed. This allows more useful design with the perf timers and enables
possible return value optimizations. Simplistic example:
class Foo {
public:
Foo(int v) : m_v(v);
private:
int m_v;
}
Foo makeFrobbedFoo(int *errno)
{
*errno = 0;
return Foo();
}
Foo bar(int *errno)
{
PERF_TIMER_GUARD(some_timer);
return makeFrobbedFoo(errno);
}
int main(int argc, char[] argv)
{
Foo f;
int errno;
f = bar(&errno);
if (errno)
return -1;
return 0;
}
After bar() is called, perf_context.some_timer would be incremented as if
Stop(&perf_context.some_timer) was called at the end, and the compiler is still
able to produce optimizations on the return value from makeFrobbedFoo() through
to main().
Summary: gcc on our dev boxes is not happy about __attribute__((unused))
Test Plan: compiles now
Reviewers: sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22707
Summary: We need to set contbuild for this :)
Test Plan: compiles
Reviewers: sdong, yhchiang, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22701
Summary:
Use inlined hash functions instead of function pointer. Make number of buckets a power of two and use bitwise and instead of mod.
After these changes, we get almost 50% improvement in performance.
Results:
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.231us (4.3 Mqps) with batch size of 0
Time taken per op is 0.229us (4.4 Mqps) with batch size of 0
Time taken per op is 0.185us (5.4 Mqps) with batch size of 0
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.108us (9.3 Mqps) with batch size of 10
Time taken per op is 0.100us (10.0 Mqps) with batch size of 10
Time taken per op is 0.103us (9.7 Mqps) with batch size of 10
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.101us (9.9 Mqps) with batch size of 25
Time taken per op is 0.098us (10.2 Mqps) with batch size of 25
Time taken per op is 0.097us (10.3 Mqps) with batch size of 25
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.100us (10.0 Mqps) with batch size of 50
Time taken per op is 0.097us (10.3 Mqps) with batch size of 50
Time taken per op is 0.097us (10.3 Mqps) with batch size of 50
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.102us (9.8 Mqps) with batch size of 100
Time taken per op is 0.098us (10.2 Mqps) with batch size of 100
Time taken per op is 0.115us (8.7 Mqps) with batch size of 100
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.201us (5.0 Mqps) with batch size of 0
Time taken per op is 0.155us (6.5 Mqps) with batch size of 0
Time taken per op is 0.152us (6.6 Mqps) with batch size of 0
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.089us (11.3 Mqps) with batch size of 10
Time taken per op is 0.084us (11.9 Mqps) with batch size of 10
Time taken per op is 0.086us (11.6 Mqps) with batch size of 10
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.087us (11.5 Mqps) with batch size of 25
Time taken per op is 0.085us (11.7 Mqps) with batch size of 25
Time taken per op is 0.093us (10.8 Mqps) with batch size of 25
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.094us (10.6 Mqps) with batch size of 50
Time taken per op is 0.094us (10.7 Mqps) with batch size of 50
Time taken per op is 0.093us (10.8 Mqps) with batch size of 50
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.092us (10.9 Mqps) with batch size of 100
Time taken per op is 0.089us (11.2 Mqps) with batch size of 100
Time taken per op is 0.088us (11.3 Mqps) with batch size of 100
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.154us (6.5 Mqps) with batch size of 0
Time taken per op is 0.168us (6.0 Mqps) with batch size of 0
Time taken per op is 0.190us (5.3 Mqps) with batch size of 0
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.081us (12.4 Mqps) with batch size of 10
Time taken per op is 0.077us (13.0 Mqps) with batch size of 10
Time taken per op is 0.083us (12.1 Mqps) with batch size of 10
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 25
Time taken per op is 0.073us (13.7 Mqps) with batch size of 25
Time taken per op is 0.073us (13.7 Mqps) with batch size of 25
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.076us (13.1 Mqps) with batch size of 50
Time taken per op is 0.072us (13.8 Mqps) with batch size of 50
Time taken per op is 0.072us (13.8 Mqps) with batch size of 50
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 100
Time taken per op is 0.074us (13.6 Mqps) with batch size of 100
Time taken per op is 0.073us (13.6 Mqps) with batch size of 100
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.190us (5.3 Mqps) with batch size of 0
Time taken per op is 0.186us (5.4 Mqps) with batch size of 0
Time taken per op is 0.184us (5.4 Mqps) with batch size of 0
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.079us (12.7 Mqps) with batch size of 10
Time taken per op is 0.070us (14.2 Mqps) with batch size of 10
Time taken per op is 0.072us (14.0 Mqps) with batch size of 10
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 25
Time taken per op is 0.072us (14.0 Mqps) with batch size of 25
Time taken per op is 0.071us (14.1 Mqps) with batch size of 25
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.082us (12.1 Mqps) with batch size of 50
Time taken per op is 0.071us (14.1 Mqps) with batch size of 50
Time taken per op is 0.073us (13.6 Mqps) with batch size of 50
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 100
Time taken per op is 0.077us (13.0 Mqps) with batch size of 100
Time taken per op is 0.078us (12.8 Mqps) with batch size of 100
Test Plan:
make check all
make valgrind_check
make asan_check
Reviewers: sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22539
Summary:
When reading from kBlockCacheTier, ForwardIterator's internal child iterators
may end up in the incomplete state (read was unable to complete without doing
disk I/O). `ForwardIterator::status()` will correctly report that; however, the
iterator may be stuck in that state until all sub-iterators are rebuilt:
* `NeedToSeekImmutable()` may return false even if some sub-iterators are
incomplete
* one of the child iterators may be an empty iterator without any state other
that the kIncomplete status (created using `NewErrorIterator()`); seeking on
any such iterator has no effect -- we need to construct it again
Akin to rebuilding iterators after a superversion bump, this diff makes forward
iterator reset all incomplete child iterators when `Seek()` or `Next()` are
called.
Test Plan: TEST_TMPDIR=/dev/shm/rocksdbtest ROCKSDB_TESTS=TailingIterator ./db_test
Reviewers: igor, sdong, ljin
Reviewed By: ljin
Subscribers: lovro, march, leveldb
Differential Revision: https://reviews.facebook.net/D22575
Summary:
1. remove class InternalFilterPolicy in db/dbformat.h
2. Transformation from internal key to user key is done in filter_block.cc
3. This is a preparation for patch D20979
Test Plan:
make all check
valgrind ./db_test
Reviewers: igor, yhchiang, ljin, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22509
Summary: This implements a cache friendly version of Cuckoo Hash in which, in case of collission, we try to insert in next few locations. The size of the neighborhood to check is taken as an input parameter in builder and stored in the table.
Test Plan:
make check all
cuckoo_table_{db,reader,builder}_test
Reviewers: sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22455
Summary:
- New Uint64 comparator
- Modify Reader and Builder to take custom user comparators instead of bytewise comparator
- Modify logic for choosing unused user key in builder
- Modify iterator logic in reader
- test changes
Test Plan:
cuckoo_table_{builder,reader,db}_test
make check all
Reviewers: ljin, sdong
Reviewed By: ljin
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D22377
Summary: Add a virtual function in table factory that will print table options
Test Plan: make release
Reviewers: igor, yhchiang, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22149
Summary:
I will move compression related options in a separate diff since this
diff is already pretty lengthy.
I guess I will also need to change JNI accordingly :(
Test Plan: make all check
Reviewers: yhchiang, igor, sdong
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21915
Summary:
- Implement Prepare method
- Rewrite performance tests in cuckoo_table_reader_test to write new file only if one doesn't already exist.
- Add performance tests for batch lookup along with prefetching.
Test Plan:
./cuckoo_table_reader_test --enable_perf
Results (We get better results if we used int64 comparator instead of string comparator (TBD in future diffs)):
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.208us (4.8 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.182us (5.5 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.161us (6.2 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.161us (6.2 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.163us (6.1 Mqps) with batch size of 100
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.252us (4.0 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.192us (5.2 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.195us (5.1 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.191us (5.2 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.194us (5.1 Mqps) with batch size of 100
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.228us (4.4 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.185us (5.4 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.186us (5.4 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.188us (5.3 Mqps) with batch size of 100
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.325us (3.1 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.196us (5.1 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.199us (5.0 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.196us (5.1 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.209us (4.8 Mqps) with batch size of 100
Reviewers: sdong, yhchiang, igor, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22167
Summary:
Currently, PlainTable must use mmap_reads. When PlainTable is used but
allow_mmap_reads is not set, rocksdb will fail in flush.
This diff improve Options sanitization and add MmapReadRequired() to
TableFactory.
Test Plan:
export ROCKSDB_TESTS=PlainTableOptionsSanitizeTest
make db_test -j32
./db_test
Reviewers: sdong, ljin
Reviewed By: ljin
Subscribers: you, leveldb
Differential Revision: https://reviews.facebook.net/D21939
Summary: Make table_reader_bench cover all the three table formats.
Test Plan: Run it using three options
Reviewers: radheshyamb, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22137
Summary:
Avoid retrying to read property block from a table when it does not exist
in updating stats for compensating deletion entries.
In addition, ReadTableProperties() now returns Status::NotFound instead
of Status::Corruption when table properties does not exist in the file.
Test Plan:
make db_test -j32
export ROCKSDB_TESTS=CompactionDeleteionTrigger
./db_test
Reviewers: ljin, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21867
Summary:
Contains the following changes:
- Implementation of cuckoo_table_factory
- Adding cuckoo table into AdaptiveTableFactory
- Adding cuckoo_table_db_test, similar to lines of plain_table_db_test
- Minor fixes to Reader: When a key is found in the table, return the key found instead of the search key.
- Minor fixes to Builder: Add table properties that are required by Version::UpdateTemporaryStats() during Get operation. Don't define curr_node as a reference variable as the memory locations may get reassigned during tree.push_back operation, leading to invalid memory access.
Test Plan:
cuckoo_table_reader_test --enable_perf
cuckoo_table_builder_test
cuckoo_table_db_test
make check all
make valgrind_check
make asan_check
Reviewers: sdong, igor, yhchiang, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21219
* Script for building the unity.cc file via Makefile
* Unity executable Makefile target for testing builds
* Source code changes to fix compilation of unity build
Summary:
Add a DB Property "rocksdb.estimate-table-readers-mem" to return estimated memory usage by all loaded table readers, other than allocated from block cache.
Refactor the property codes to allow getting property from a version, with DB mutex not acquired.
Test Plan: Add several checks of this new property in existing codes for various cases.
Reviewers: yhchiang, ljin
Reviewed By: ljin
Subscribers: xjin, igor, leveldb
Differential Revision: https://reviews.facebook.net/D20733
Summary:
- Maintain a list of key-value pairs as vectors during Add operation.
- Start building hash table only when Finish() is called.
- This approach takes more time and space but avoids taking file_size, key and value lengths.
- Rewrote cuckoo_table_builder_test
I did not know about IterKey while writing this diff. I shall change places where IterKey could be used instead of std::string tomorrow. Please review rest of the logic.
Test Plan:
cuckoo_table_reader_test --enable_perf
cuckoo_table_builder_test
valgrind_check
asan_check
Reviewers: sdong, igor, yhchiang, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20907
Summary:
- Reads key-value pairs from file and builds an in-memory index of key-to-bucket id map in sorted order of key.
- Assumes bytewise comparator for sorting keys.
- Test changes
Test Plan:
cuckoo_table_reader_test --enable_perf
valgrind_check
asan_check
Reviewers: yhchiang, sdong, ljin
Reviewed By: ljin
Subscribers: leveldb, igor
Differential Revision: https://reviews.facebook.net/D20721
Summary: port::MemoryBarrier() is not recommended to use outside of port. Remove it.
Test Plan: run table_reader_bench
Reviewers: ljin, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21075
Summary:
1. logging when create and delete manifest file
2. fix formating in table/format.cc
Test Plan:
make all check
run db_bench, track the LOG file.
Reviewers: ljin, yhchiang, igor, yufei.zhu, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21009
Summary: Made some small changes to fix the broken mac build
Test Plan: make check all in both linux and mac. All tests pass.
Reviewers: sdong, igor, ljin, yhchiang
Reviewed By: ljin, yhchiang
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20895
Summary:
When compression is enabled, and blocksize is not too big, use the
space in stack to hold bytes read from block.
Bencmark:
base version: commit 8f09d53fd1
malloc: 1.30% -> 0.98%
free: 1.49% -> 1.07%
Test Plan:
make all check
Reviewers: ljin, yhchiang, dhruba, igor, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20679
Summary:
Define Block::Iter to be an independent class to be used by block_based_table_reader
When creating data and index iterator, update an existing iterator rather than new one
Thus malloc and free could be reduced
Benchmark,
Base:
commit 76286ee67e
commands:
--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=2621440 --use_hash_search=1 --block_size=1024 --block_restart_interval=1 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1
malloc: 3.30% -> 1.42%
free: 3.59%->1.61%
Test Plan:
make all check
run db_stress
valgrind ./db_test ./table_test
Reviewers: ljin, yhchiang, dhruba, igor, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20655
Summary:
- Copy the key and value to in-memory hash table during Add operation. Also modified cuckoo_table_reader_test to use this.
- Store only the user_key in in-memory hash table if it is last level file.
- Handle Carryover while chosing unused key in Finish() method in case unused key was never found before Finish() call.
Test Plan:
cuckoo_table_reader_test --enable_perf
cuckoo_table_builder_test
valgrind_check
asan_check
Reviewers: sdong, yhchiang, igor, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20715
Summary:
Make StatisticsImpl being able to forward stats to provided statistics
implementation. The main purpose is to allow us to collect internal
stats in the future even when user supplies custom statistics
implementation. It avoids intrumenting 2 sets of stats collection code.
One immediate use case is tuning advisor, which needs to collect some
internal stats, users may not be interested.
Test Plan:
ran db_bench and see stats show up at the end of run
Will run make all check since some tests rely on statistics
Reviewers: yhchiang, sdong, igor
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D20145
Summary:
In block based table's hash index checking, when looking for a key that doesn't exist, there is a high chance that a false block is returned because of hash bucket conflicts. In this revision, another check is done to filter out some of those cases: comparing previous key of the block boundary to see whether the target block is what we are looking for.
In a favored test setting (bloom filter disabled, 8 L0 files), I saw about 80% improvements. In a non-favored test setting (bloom filter enabled, files are all in L1, files are all cached), I see the performance penalty is less than 3%.
Test Plan: make all check
Reviewers: haobo, ljin
Reviewed By: ljin
Subscribers: wuj, leveldb, zagfox, yhchiang
Differential Revision: https://reviews.facebook.net/D20595
Summary:
Contains:
- Implementation of TableReader based on Cuckoo Hashing
- Unittests for CuckooTableReader
- Performance test for TableReader
Test Plan:
make cuckoo_table_reader_test
./cuckoo_table_reader_test
make valgrind_check
make asan_check
Reviewers: yhchiang, sdong, igor, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20511
Summary:
Contains the following changes in CuckooTableBuilder:
- Take an extra parameter in constructor to identify last level file.
- Implement a better way to identify if a bucket has been inserted into the tree already during BFS search.
- Minor typos
Test Plan:
make cuckoo_table_builder
./cuckoo_table_builder
make valgrind_check
Reviewers: sdong, igor, yhchiang, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20445
Summary:
Modify a functioin TrimAppend in dbformat.h: IterKey. Write a test for it in dbformat_test
Use IterKey in block::Iter to replace std::string to reduce malloc.
Evaluate it using perf record.
malloc: 4.26% -> 2.91%
free: 3.61% -> 3.08%
Test Plan:
make all check
./valgrind db_test dbformat_test
Reviewers: ljin, haobo, yhchiang, dhruba, igor, sdong
Reviewed By: sdong
Differential Revision: https://reviews.facebook.net/D20433
Igor Canadi