Summary:
NextAndGetResult() is not implemented in memtable and is very simply implemented in level iterator. The result is that for a normal leveled iterator, performance regression will be observed for calling PrepareValue() for most iterator Next(). Mitigate the problem by implementing the function for both iterators. In level iterator, the implementation cannot be perfect as when calling file iterator's SeekToFirst() we don't have information about whether the value is prepared. Fortunately, the first key should not cause a big portion of the CPu.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7179
Test Plan: Run normal crash test for a while.
Reviewed By: anand1976
Differential Revision: D22783840
fbshipit-source-id: c19f45cdf21b756190adef97a3b66ccde3936e05
Summary:
During memtable lookup, an unrecognized value type should be reported as
Status::Corruption.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7121
Test Plan: make check
Reviewed By: cheng-chang
Differential Revision: D22512124
Pulled By: riversand963
fbshipit-source-id: 9b97be7d9b230c5aae9205f96054420e5ea09066
Summary:
We are still keeping unity build working. So it's a good idea to add to a pre-commit CI.
A latest GCC docker image just to get a little bit more coverage. Fix three small issues to make it pass.
Also make unity_test to run db_basic_test rather than db_test to cut the test time. There is no point to run expensive tests here. It was set to run db_test before db_basic_test was separated out.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7026
Test Plan: watch tests to pass.
Reviewed By: zhichao-cao
Differential Revision: D22223197
fbshipit-source-id: baa3b6cbb623bf359829b63ce35715c75bcb0ed4
Summary:
Preliminary user-timestamp support for delete.
If ["a", ts=100] exists, you can delete it by calling `DB::Delete(write_options, key)` in which `write_options.timestamp` points to a `ts` higher than 100.
Implementation
A new ValueType, i.e. `kTypeDeletionWithTimestamp` is added for deletion marker with timestamp.
The reason for a separate `kTypeDeletionWithTimestamp`: RocksDB may drop tombstones (keys with kTypeDeletion) when compacting them to the bottom level. This is OK and useful if timestamp is disabled. When timestamp is enabled, should we still reuse `kTypeDeletion`, we may drop the tombstone with a more recent timestamp, causing deleted keys to re-appear.
Test plan (dev server)
```
make check
```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6253
Reviewed By: ltamasi
Differential Revision: D20995328
Pulled By: riversand963
fbshipit-source-id: a9e5c22968ad76f98e3dc6ee0151265a3f0df619
Summary:
1. Add a value_size in read options which limits the cumulative value size of keys read in batches. Once the size exceeds read_options.value_size, all the remaining keys are returned with status Abort without further fetching any key.
2. Add a unit test case MultiGetBatchedValueSizeSimple the reads keys from memory and sst files.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6826
Test Plan:
1. make check -j64
2. Add a new unit test case
Reviewed By: anand1976
Differential Revision: D21471483
Pulled By: akankshamahajan15
fbshipit-source-id: dea51b8e76d5d1df38ece8cdb29933b1d798b900
Summary:
Based on https://github.com/facebook/rocksdb/issues/6648 (CLA Signed), but heavily modified / extended:
* Implicit capture of this via [=] deprecated in C++20, and [=,this] not standard before C++20 -> now using explicit capture lists
* Implicit copy operator deprecated in gcc 9 -> add explicit '= default' definition
* std::random_shuffle deprecated in C++17 and removed in C++20 -> migrated to a replacement in RocksDB random.h API
* Add the ability to build with different std version though -DCMAKE_CXX_STANDARD=11/14/17/20 on the cmake command line
* Minimal rebuild flag of MSVC is deprecated and is forbidden with /std:c++latest (C++20)
* Added MSVC 2019 C++11 & MSVC 2019 C++20 in AppVeyor
* Added GCC 9 C++11 & GCC9 C++20 in Travis
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6697
Test Plan: make check and CI
Reviewed By: cheng-chang
Differential Revision: D21020318
Pulled By: pdillinger
fbshipit-source-id: 12311be5dbd8675a0e2c817f7ec50fa11c18ab91
Summary:
Add timestamp support for MultiGet().
timestamp from readoptions is honored, and timestamps can be returned along with values.
MultiReadRandom perf test (10 minutes) on the same development machine ram drive with the same DB data shows no regression (within marge of error). The test is adapted from https://github.com/facebook/rocksdb/wiki/RocksDB-In-Memory-Workload-Performance-Benchmarks.
base line (commit 17bef7d3a):
multireadrandom : 104.173 micros/op 307167 ops/sec; (5462999 of 5462999 found)
This PR:
multireadrandom : 104.199 micros/op 307095 ops/sec; (5307999 of 5307999 found)
.\db_bench --db=r:\rocksdb.github --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --cache_size=2147483648 --cache_numshardbits=6 --compression_type=none --compression_ratio=1 --min_level_to_compress=-1 --disable_seek_compaction=1 --hard_rate_limit=2 --write_buffer_size=134217728 --max_write_buffer_number=2 --level0_file_num_compaction_trigger=8 --target_file_size_base=134217728 --max_bytes_for_level_base=1073741824 --disable_wal=0 --wal_dir=r:\rocksdb.github\WAL_LOG --sync=0 --verify_checksum=1 --statistics=0 --stats_per_interval=0 --stats_interval=1048576 --histogram=0 --use_plain_table=1 --open_files=-1 --memtablerep=prefix_hash --bloom_bits=10 --bloom_locality=1 --duration=600 --benchmarks=multireadrandom --use_existing_db=1 --num=25000000 --threads=32 --allow_concurrent_memtable_write=0
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6483
Reviewed By: anand1976
Differential Revision: D20498373
Pulled By: riversand963
fbshipit-source-id: 8505f22bc40fd791bc7dd05e48d7e67c91edb627
Summary:
Added new Get() methods that return timestamp. Dummy implementation is given so that classes derived from DB don't need to be touched to provide their implementation. MultiGet is not included.
ReadRandom perf test (10 minutes) on the same development machine ram drive with the same DB data shows no regression (within marge of error). The test is adapted from https://github.com/facebook/rocksdb/wiki/RocksDB-In-Memory-Workload-Performance-Benchmarks.
base line (commit 72ee067b9):
101.712 micros/op 314602 ops/sec; 36.0 MB/s (5658999 of 5658999 found)
This PR:
100.288 micros/op 319071 ops/sec; 36.5 MB/s (5674999 of 5674999 found)
./db_bench --db=r:\rocksdb.github --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --cache_size=2147483648 --cache_numshardbits=6 --compression_type=none --compression_ratio=1 --min_level_to_compress=-1 --disable_seek_compaction=1 --hard_rate_limit=2 --write_buffer_size=134217728 --max_write_buffer_number=2 --level0_file_num_compaction_trigger=8 --target_file_size_base=134217728 --max_bytes_for_level_base=1073741824 --disable_wal=0 --wal_dir=r:\rocksdb.github\WAL_LOG --sync=0 --verify_checksum=1 --delete_obsolete_files_period_micros=314572800 --max_background_compactions=4 --max_background_flushes=0 --level0_slowdown_writes_trigger=16 --level0_stop_writes_trigger=24 --statistics=0 --stats_per_interval=0 --stats_interval=1048576 --histogram=0 --use_plain_table=1 --open_files=-1 --mmap_read=1 --mmap_write=0 --memtablerep=prefix_hash --bloom_bits=10 --bloom_locality=1 --duration=600 --benchmarks=readrandom --use_existing_db=1 --num=25000000 --threads=32
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6409
Differential Revision: D20200086
Pulled By: riversand963
fbshipit-source-id: 490edd74d924f62bd8ae9c29c2a6bbbb8410ca50
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:
Add a new option ReadOptions.auto_prefix_mode. When set to true, iterator should return the same result as total order seek, but may choose to do prefix seek internally, based on iterator upper bounds. Also fix two previous bugs when handling prefix extrator changes: (1) reverse iterator should not rely on upper bound to determine prefix. Fix it with skipping prefix check. (2) block-based filter is not handled properly.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6314
Test Plan: (1) add a unit test; (2) add the check to stress test and run see whether it can pass at least one run.
Differential Revision: D19458717
fbshipit-source-id: 51c1bcc5cdd826c2469af201979a39600e779bce
Summary:
- Updated our included xxhash implementation to version 0.7.2 (== the latest dev version as of 2019-10-09).
- Using XXH_NAMESPACE (like other fb projects) to avoid potential name collisions.
- Added fastrange64, and unit tests for it and fastrange32. These are faster alternatives to hash % range.
- Use preview version of XXH3 instead of MurmurHash64A for NPHash64
-- Had to update cache_test to increase probability of passing for any given hash function.
- Use fastrange64 instead of % with uses of NPHash64
-- Had to fix WritePreparedTransactionTest.CommitOfDelayedPrepared to avoid deadlock apparently caused by new hash collision.
- Set default seed for NPHash64 because specifying a seed rarely makes sense for it.
- Removed unnecessary include xxhash.h in a popular .h file
- Rename preview version of XXH3 to XXH3p for clarity and to ease backward compatibility in case final version of XXH3 is integrated.
Relying on existing unit tests for NPHash64-related changes. Each new implementation of fastrange64 passed unit tests when manipulating my local build to select it. I haven't done any integration performance tests, but I consider the improved performance of the pieces being swapped in to be well established.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5909
Differential Revision: D18125196
Pulled By: pdillinger
fbshipit-source-id: f6bf83d49d20cbb2549926adf454fd035f0ecc0d
Summary:
RocksDB has a MultiGet() API that implements batched key lookup for higher performance (https://github.com/facebook/rocksdb/blob/master/include/rocksdb/db.h#L468). Currently, batching is implemented in BlockBasedTableReader::MultiGet() for SST file lookups. One of the ways it improves performance is by pipelining bloom filter lookups (by prefetching required cachelines for all the keys in the batch, and then doing the probe) and thus hiding the cache miss latency. The same concept can be extended to the memtable as well. This PR involves implementing a pipelined bloom filter lookup in DynamicBloom, and implementing MemTable::MultiGet() that can leverage it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5818
Test Plan:
Existing tests
Performance Test:
Ran the below command which fills up the memtable and makes sure there are no flushes and then call multiget. Ran it on master and on the new change and see atleast 1% performance improvement across all the test runs I did. Sometimes the improvement was upto 5%.
TEST_TMPDIR=/data/users/$USER/benchmarks/feature/ numactl -C 10 ./db_bench -benchmarks="fillseq,multireadrandom" -num=600000 -compression_type="none" -level_compaction_dynamic_level_bytes -write_buffer_size=200000000 -target_file_size_base=200000000 -max_bytes_for_level_base=16777216 -reads=90000 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4 -statistics -memtable_whole_key_filtering=true -memtable_bloom_size_ratio=10
Differential Revision: D17578869
Pulled By: vjnadimpalli
fbshipit-source-id: 23dc651d9bf49db11d22375bf435708875a1f192
Summary:
Use delete to disable automatic generated methods instead of private, and put the constructor together for more clear.This modification cause the unused field warning, so add unused attribute to disable this warning.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5009
Differential Revision: D17288733
fbshipit-source-id: 8a767ce096f185f1db01bd28fc88fef1cdd921f3
Summary:
Since DynamicBloom is now only used in-memory, we're free to
change it without schema compatibility issues. The new implementation
is drawn from (with manifest permission)
303542a767/bloom_simulation_tests/foo.cc (L613)
This has several speed advantages over the prior implementation:
* Uses fastrange instead of %
* Minimum logic to determine first (and all) probed memory addresses
* (Major) Two probes per 64-bit memory fetch/write.
* Very fast and effective (murmur-like) hash expansion/re-mixing. (At
least on recent CPUs, integer multiplication is very cheap.)
While a Bloom filter with 512-bit cache locality has about a 1.15x FP
rate penalty (e.g. 0.84% to 0.97%), further restricting to two probes
per 64 bits incurs an additional 1.12x FP rate penalty (e.g. 0.97% to
1.09%). Nevertheless, the unit tests show no "mediocre" FP rate samples,
unlike the old implementation with more erratic FP rates.
Especially for the memtable, we expect speed to outweigh somewhat higher
FP rates. For example, a negative table query would have to be 1000x
slower than a BF query to justify doubling BF query time to shave 10% off
FP rate (working assumption around 1% FP rate). While that seems likely
for SSTs, my data suggests a speed factor of roughly 50x for the memtable
(vs. BF; ~1.5% lower write throughput when enabling memtable Bloom
filter, after this change). Thus, it's probably not worth even 5% more
time in the Bloom filter to shave off 1/10th of the Bloom FP rate, or 0.1%
in absolute terms, and it's probably at least 20% slower to recoup that
much FP rate from this new implementation. Because of this, we do not see
a need for a 'locality' option that affects the MemTable Bloom filter
and have decoupled the MemTable Bloom filter from Options::bloom_locality.
Note that just 3% more memory to the Bloom filter (10.3 bits per key vs.
just 10) is able to make up for the ~12% FP rate drop in the new
implementation:
[] # Nearly "ideal" FP-wise but reasonably fast cache-local implementation
[~/wormhashing/bloom_simulation_tests] ./foo_gcc_IMPL_CACHE_WORM64_FROM32_any.out 10000000 6 10 $RANDOM 100000000
./foo_gcc_IMPL_CACHE_WORM64_FROM32_any.out time: 3.29372 sampled_fp_rate: 0.00985956 ...
[] # Close match to this new implementation
[~/wormhashing/bloom_simulation_tests] ./foo_gcc_IMPL_CACHE_MUL64_BLOCK_FROM32_any.out 10000000 6 10.3 $RANDOM 100000000
./foo_gcc_IMPL_CACHE_MUL64_BLOCK_FROM32_any.out time: 2.10072 sampled_fp_rate: 0.00985655 ...
[] # Old locality=1 implementation
[~/wormhashing/bloom_simulation_tests] ./foo_gcc_IMPL_CACHE_ROCKSDB_DYNAMIC_any.out 10000000 6 10 $RANDOM 100000000
./foo_gcc_IMPL_CACHE_ROCKSDB_DYNAMIC_any.out time: 3.95472 sampled_fp_rate: 0.00988943 ...
Also note the dramatic speed improvement vs. alternatives.
--
Performance unit test: DynamicBloomTest.concurrent_with_perf is updated
to report more precise timing data. (Measure running time of each
thread, not just longest running thread, etc.) Results averaged over
various sizes enabled with --enable_perf and 20 runs each; old dynamic
bloom refers to locality=1, the faster of the old:
old dynamic bloom, avg add latency = 65.6468
new dynamic bloom, avg add latency = 44.3809
old dynamic bloom, avg query latency = 50.6485
new dynamic bloom, avg query latency = 43.2186
old avg parallel add latency = 41.678
new avg parallel add latency = 24.5238
old avg parallel hit latency = 14.6322
new avg parallel hit latency = 12.3939
old avg parallel miss latency = 16.7289
new avg parallel miss latency = 12.2134
Tested on a dedicated 64-bit production machine at Facebook. Significant
improvement all around.
Despite now using std::atomic<uint64_t>, quick before-and-after test on
a 32-bit machine (Intel Atom N270, released 2008) shows no regression in
performance, in some cases modest improvement.
--
Performance integration test (synthetic): with DEBUG_LEVEL=0, used
TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=fillrandom,readmissing,readrandom,stats --num=2000000
and optionally with -memtable_whole_key_filtering -memtable_bloom_size_ratio=0.01
300 runs each configuration.
Write throughput change by enabling memtable bloom:
Old locality=0: -3.06%
Old locality=1: -2.37%
New: -1.50%
conclusion -> seems to substantially close the gap
Readmissing throughput change by enabling memtable bloom:
Old locality=0: +34.47%
Old locality=1: +34.80%
New: +33.25%
conclusion -> maybe a small new penalty from FP rate
Readrandom throughput change by enabling memtable bloom:
Old locality=0: +31.54%
Old locality=1: +31.13%
New: +30.60%
conclusion -> maybe also from FP rate (after memtable flush)
--
Another conclusion we can draw from this new implementation is that the
existing 32-bit hash function is not inherently crippling the Bloom
filter speed or accuracy, below about 5 million keys. For speed, the
implementation is essentially the same whether starting with 32-bits or
64-bits of hash; it just determines whether the first multiplication
after fastrange is a pseudorandom expansion or needed re-mix. Note that
this multiplication can occur while memory is fetching.
For accuracy, in a standard configuration, you need about 5 million
keys before you have about a 1.1x FP penalty due to using a
32-bit hash vs. 64-bit:
[~/wormhashing/bloom_simulation_tests] ./foo_gcc_IMPL_CACHE_MUL64_BLOCK_FROM32_any.out $((5 * 1000 * 1000 * 10)) 6 10 $RANDOM 100000000
./foo_gcc_IMPL_CACHE_MUL64_BLOCK_FROM32_any.out time: 2.52069 sampled_fp_rate: 0.0118267 ...
[~/wormhashing/bloom_simulation_tests] ./foo_gcc_IMPL_CACHE_MUL64_BLOCK_any.out $((5 * 1000 * 1000 * 10)) 6 10 $RANDOM 100000000
./foo_gcc_IMPL_CACHE_MUL64_BLOCK_any.out time: 2.43871 sampled_fp_rate: 0.0109059
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5762
Differential Revision: D17214194
Pulled By: pdillinger
fbshipit-source-id: ad9da031772e985fd6b62a0e1db8e81892520595
Summary:
MyRocks currently sets `max_write_buffer_number_to_maintain` in order to maintain enough history for transaction conflict checking. The effectiveness of this approach depends on the size of memtables. When memtables are small, it may not keep enough history; when memtables are large, this may consume too much memory.
We are proposing a new way to configure memtable list history: by limiting the memory usage of immutable memtables. The new option is `max_write_buffer_size_to_maintain` and it will take precedence over the old `max_write_buffer_number_to_maintain` if they are both set to non-zero values. The new option accounts for the total memory usage of flushed immutable memtables and mutable memtable. When the total usage exceeds the limit, RocksDB may start dropping immutable memtables (which is also called trimming history), starting from the oldest one.
The semantics of the old option actually works both as an upper bound and lower bound. History trimming will start if number of immutable memtables exceeds the limit, but it will never go below (limit-1) due to history trimming.
In order the mimic the behavior with the new option, history trimming will stop if dropping the next immutable memtable causes the total memory usage go below the size limit. For example, assuming the size limit is set to 64MB, and there are 3 immutable memtables with sizes of 20, 30, 30. Although the total memory usage is 80MB > 64MB, dropping the oldest memtable will reduce the memory usage to 60MB < 64MB, so in this case no memtable will be dropped.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5022
Differential Revision: D14394062
Pulled By: miasantreble
fbshipit-source-id: 60457a509c6af89d0993f988c9b5c2aa9e45f5c5
Summary:
This is a new API added to db.h to allow for fetching all merge operands associated with a Key. The main motivation for this API is to support use cases where doing a full online merge is not necessary as it is performance sensitive. Example use-cases:
1. Update subset of columns and read subset of columns -
Imagine a SQL Table, a row is encoded as a K/V pair (as it is done in MyRocks). If there are many columns and users only updated one of them, we can use merge operator to reduce write amplification. While users only read one or two columns in the read query, this feature can avoid a full merging of the whole row, and save some CPU.
2. Updating very few attributes in a value which is a JSON-like document -
Updating one attribute can be done efficiently using merge operator, while reading back one attribute can be done more efficiently if we don't need to do a full merge.
----------------------------------------------------------------------------------------------------
API :
Status GetMergeOperands(
const ReadOptions& options, ColumnFamilyHandle* column_family,
const Slice& key, PinnableSlice* merge_operands,
GetMergeOperandsOptions* get_merge_operands_options,
int* number_of_operands)
Example usage :
int size = 100;
int number_of_operands = 0;
std::vector<PinnableSlice> values(size);
GetMergeOperandsOptions merge_operands_info;
db_->GetMergeOperands(ReadOptions(), db_->DefaultColumnFamily(), "k1", values.data(), merge_operands_info, &number_of_operands);
Description :
Returns all the merge operands corresponding to the key. If the number of merge operands in DB is greater than merge_operands_options.expected_max_number_of_operands no merge operands are returned and status is Incomplete. Merge operands returned are in the order of insertion.
merge_operands-> Points to an array of at-least merge_operands_options.expected_max_number_of_operands and the caller is responsible for allocating it. If the status returned is Incomplete then number_of_operands will contain the total number of merge operands found in DB for key.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5604
Test Plan:
Added unit test and perf test in db_bench that can be run using the command:
./db_bench -benchmarks=getmergeoperands --merge_operator=sortlist
Differential Revision: D16657366
Pulled By: vjnadimpalli
fbshipit-source-id: 0faadd752351745224ee12d4ae9ef3cb529951bf
Summary:
It's useful to be able to (optionally) associate key-value pairs with user-provided timestamps. This PR is an early effort towards this goal and continues the work of facebook#4942. A suite of new unit tests exist in DBBasicTestWithTimestampWithParam. Support for timestamp requires the user to provide timestamp as a slice in `ReadOptions` and `WriteOptions`. All timestamps of the same database must share the same length, format, etc. The format of the timestamp is the same throughout the same database, and the user is responsible for providing a comparator function (Comparator) to order the <key, timestamp> tuples. Once created, the format and length of the timestamp cannot change (at least for now).
Test plan (on devserver):
```
$COMPILE_WITH_ASAN=1 make -j32 all
$./db_basic_test --gtest_filter=Timestamp/DBBasicTestWithTimestampWithParam.PutAndGet/*
$make check
```
All tests must pass.
We also run the following db_bench tests to verify whether there is regression on Get/Put while timestamp is not enabled.
```
$TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillseq,readrandom -num=1000000
$TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=1000000
```
Repeat for 6 times for both versions.
Results are as follows:
```
| | readrandom | fillrandom |
| master | 16.77 MB/s | 47.05 MB/s |
| PR5079 | 16.44 MB/s | 47.03 MB/s |
```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5079
Differential Revision: D15132946
Pulled By: riversand963
fbshipit-source-id: 833a0d657eac21182f0f206c910a6438154c742c
Summary:
this PR fixes the following compile warning:
```
db/memtable.cc: In member function ‘virtual void rocksdb::MemTableIterator::Seek(const rocksdb::Slice&)’:
db/memtable.cc:321:22: error: declaration of ‘user_key’ shadows a member of 'this' [-Werror=shadow]
Slice user_key(ExtractUserKey(k));
^
db/memtable.cc: In member function ‘virtual void rocksdb::MemTableIterator::SeekForPrev(const rocksdb::Slice&)’:
db/memtable.cc:338:22: error: declaration of ‘user_key’ shadows a member of 'this' [-Werror=shadow]
Slice user_key(ExtractUserKey(k));
^
```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5204
Differential Revision: D14970160
Pulled By: miasantreble
fbshipit-source-id: 388eb089f90c4528cc6d615dd4607fb53ceac705
Summary:
Before using prefix extractor `InDomain()` should be check. All uses in memtable.cc didn't check `InDomain()`.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5190
Differential Revision: D14923773
Pulled By: miasantreble
fbshipit-source-id: b3ad60bcca5f3a1a2b929a6eb34b0b7ba6326f04
Summary:
Create new function NPHash64() and GetSliceNPHash64(), which are currently
implemented using murmurhash.
Replace the current direct call of murmurhash() to use the new functions
if the hash results are not used in on-disk format.
This will make it easier to try out or switch to alternative functions
in the uses where data format compatibility doesn't need to be considered.
This part shouldn't have any performance impact.
Also, the sharded cache hash function is changed to the new format, because
it falls into this categoery. It doesn't show visible performance impact
in db_bench results. CPU showed by perf is increased from about 0.2% to 0.4%
in an extreme benchmark setting (4KB blocks, no-compression, everything
cached in block cache). We've known that the current hash function used,
our own Hash() has serious hash quality problem. It can generate a lots of
conflicts with similar input. In this use case, it means extra lock contention
for reads from the same file. This slight CPU regression is worthy to me
to counter the potential bad performance with hot keys. And hopefully this
will get further improved in the future with a better hash function.
cache_test's condition is relaxed a little bit to. The new hash is slightly
more skewed in this use case, but I manually checked the data and see
the hash results are still in a reasonable range.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5155
Differential Revision: D14834821
Pulled By: siying
fbshipit-source-id: ec9a2c0a2f8ae4b54d08b13a5c2e9cc97aa80cb5
Summary:
MyRocks calls `GetForUpdate` on `INSERT`, for unique key check, and in almost all cases GetForUpdate returns empty result. For such cases, whole key bloom filter is helpful.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4985
Differential Revision: D14118257
Pulled By: miasantreble
fbshipit-source-id: d35cb7109c62fd5ad541a26968e3a3e16d3e85ea
Summary:
I didn't find where customized hash function is used in DynamicBloom. This can only reduce performance. Remove it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4915
Differential Revision: D13794452
Pulled By: siying
fbshipit-source-id: e38669b11e01444d2d782da11c7decabbd851819
Summary:
To avoid a race on the flag, make it an atomic_bool. This
doesn't seem to significantly affect benchmarks.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4801
Differential Revision: D13523845
Pulled By: abhimadan
fbshipit-source-id: 3bc29f53c50a4e06cd9f8c6232a4bb221868e055
Summary:
To support the flush/compaction use cases of RangeDelAggregator
in v2, FragmentedRangeTombstoneIterator now supports dropping tombstones
that cannot be read in the compaction output file. Furthermore,
FragmentedRangeTombstoneIterator supports the "snapshot striping" use
case by allowing an iterator to be split by a list of snapshots.
RangeDelAggregatorV2 will use these changes in a follow-up change.
In the process of making these changes, other miscellaneous cleanups
were also done in these files.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4740
Differential Revision: D13287382
Pulled By: abhimadan
fbshipit-source-id: f5aeb03e1b3058049b80c02a558ee48f723fa48c
Summary:
Removed `one_time_use` flag, which removed the need for some
tests, and changed all `NewRangeTombstoneIterator` methods to return
`FragmentedRangeTombstoneIterators`.
These changes also led to removing `RangeDelAggregatorV2::AddUnfragmentedTombstones`
and one of the `MemTableListVersion::AddRangeTombstoneIterators` methods.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4692
Differential Revision: D13106570
Pulled By: abhimadan
fbshipit-source-id: cbab5432d7fc2d9cdfd8d9d40361a1bffaa8f845
Summary:
Since a range tombstone seen at one level will cover all keys
in the range at lower levels, there was a short-circuiting check in Get
that reported a key was not found at most one file after the range
tombstone was discovered. However, this was incorrect for merge
operands, since a deletion might only cover some merge operands,
which implies that the key should be found. This PR fixes this logic in
the Version portion of Get, and removes the logic from the MemTable
portion of Get, since the perforamnce benefit provided there is minimal.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4698
Differential Revision: D13142484
Pulled By: abhimadan
fbshipit-source-id: cbd74537c806032f2bfa564724d01a80df7c8f10
Summary:
WriteBufferManger is not invoked when allocating memory for memtable if the limit is not set even if a cache is passed. It is inconsistent from the comment syas. Fix it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4695
Differential Revision: D13112722
Pulled By: siying
fbshipit-source-id: 0b27eef63867f679cd06033ea56907c0569597f4
Summary:
Rather than storing a `vector<RangeTombstone>`, we now store a
`vector<RangeTombstoneStack>` and a `vector<SequenceNumber>`. A
`RangeTombstoneStack` contains the start and end keys of a range tombstone
fragment, and indices into the seqnum vector to indicate which sequence
numbers the fragment is located at. The diagram below illustrates an
example:
```
tombstones_: [a, b) [c, e) [h, k)
| \ / \ / |
| \ / \ / |
v v v v
tombstone_seqs_: [ 5 3 10 7 2 8 6 ]
```
This format allows binary searching the tombstone list to use less key
comparisons, which helps in cases where there are many overlapping
tombstones. Also, this format makes it easier to add DBIter-like
semantics to `FragmentedRangeTombstoneIterator` in the future.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4632
Differential Revision: D13053103
Pulled By: abhimadan
fbshipit-source-id: e8220cc712fcf5be4d602913bb23ace8ea5f8ef0
Summary:
This allows tombstone fragmenting to only be performed when the table is opened, and cached for subsequent accesses.
On the same DB used in #4449, running `readrandom` results in the following:
```
readrandom : 0.983 micros/op 1017076 ops/sec; 78.3 MB/s (63103 of 100000 found)
```
Now that Get performance in the presence of range tombstones is reasonable, I also compared the performance between a DB with range tombstones, "expanded" range tombstones (several point tombstones that cover the same keys the equivalent range tombstone would cover, a common workaround for DeleteRange), and no range tombstones. The created DBs had 5 million keys each, and DeleteRange was called at regular intervals (depending on the total number of range tombstones being written) after 4.5 million Puts. The table below summarizes the results of a `readwhilewriting` benchmark (in order to provide somewhat more realistic results):
```
Tombstones? | avg micros/op | stddev micros/op | avg ops/s | stddev ops/s
----------------- | ------------- | ---------------- | ------------ | ------------
None | 0.6186 | 0.04637 | 1,625,252.90 | 124,679.41
500 Expanded | 0.6019 | 0.03628 | 1,666,670.40 | 101,142.65
500 Unexpanded | 0.6435 | 0.03994 | 1,559,979.40 | 104,090.52
1k Expanded | 0.6034 | 0.04349 | 1,665,128.10 | 125,144.57
1k Unexpanded | 0.6261 | 0.03093 | 1,600,457.50 | 79,024.94
5k Expanded | 0.6163 | 0.05926 | 1,636,668.80 | 154,888.85
5k Unexpanded | 0.6402 | 0.04002 | 1,567,804.70 | 100,965.55
10k Expanded | 0.6036 | 0.05105 | 1,667,237.70 | 142,830.36
10k Unexpanded | 0.6128 | 0.02598 | 1,634,633.40 | 72,161.82
25k Expanded | 0.6198 | 0.04542 | 1,620,980.50 | 116,662.93
25k Unexpanded | 0.5478 | 0.0362 | 1,833,059.10 | 121,233.81
50k Expanded | 0.5104 | 0.04347 | 1,973,107.90 | 184,073.49
50k Unexpanded | 0.4528 | 0.03387 | 2,219,034.50 | 170,984.32
```
After a large enough quantity of range tombstones are written, range tombstone Gets can become faster than reading from an equivalent DB with several point tombstones.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4493
Differential Revision: D10842844
Pulled By: abhimadan
fbshipit-source-id: a7d44534f8120e6aabb65779d26c6b9df954c509
Summary:
Previously, range tombstones were accumulated from every level, which
was necessary if a range tombstone in a higher level covered a key in a lower
level. However, RangeDelAggregator::AddTombstones's complexity is based on
the number of tombstones that are currently stored in it, which is wasteful in
the Get case, where we only need to know the highest sequence number of range
tombstones that cover the key from higher levels, and compute the highest covering
sequence number at the current level. This change introduces this optimization, and
removes the use of RangeDelAggregator from the Get path.
In the benchmark results, the following command was used to initialize the database:
```
./db_bench -db=/dev/shm/5k-rts -use_existing_db=false -benchmarks=filluniquerandom -write_buffer_size=1048576 -compression_type=lz4 -target_file_size_base=1048576 -max_bytes_for_level_base=4194304 -value_size=112 -key_size=16 -block_size=4096 -level_compaction_dynamic_level_bytes=true -num=5000000 -max_background_jobs=12 -benchmark_write_rate_limit=20971520 -range_tombstone_width=100 -writes_per_range_tombstone=100 -max_num_range_tombstones=50000 -bloom_bits=8
```
...and the following command was used to measure read throughput:
```
./db_bench -db=/dev/shm/5k-rts/ -use_existing_db=true -benchmarks=readrandom -disable_auto_compactions=true -num=5000000 -reads=100000 -threads=32
```
The filluniquerandom command was only run once, and the resulting database was used
to measure read performance before and after the PR. Both binaries were compiled with
`DEBUG_LEVEL=0`.
Readrandom results before PR:
```
readrandom : 4.544 micros/op 220090 ops/sec; 16.9 MB/s (63103 of 100000 found)
```
Readrandom results after PR:
```
readrandom : 11.147 micros/op 89707 ops/sec; 6.9 MB/s (63103 of 100000 found)
```
So it's actually slower right now, but this PR paves the way for future optimizations (see #4493).
----
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4449
Differential Revision: D10370575
Pulled By: abhimadan
fbshipit-source-id: 9a2e152be1ef36969055c0e9eb4beb0d96c11f4d
Summary:
Leverage existing `FlushJob` to implement atomic flush of multiple column families.
This PR depends on other PRs and is a subset of #3752 . This PR itself is not sufficient in fulfilling atomic flush.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4262
Differential Revision: D9283109
Pulled By: riversand963
fbshipit-source-id: 65401f913e4160b0a61c0be6cd02adc15dad28ed
Summary:
This PR addresses issue #3865 and implements the following approach to fix it:
- adds `MergeContext::GetOperandsDirectionForward` and `MergeContext::GetOperandsDirectionBackward` to query merge operands in a specific order
- `MergeContext::GetOperands` becomes a shortcut for `MergeContext::GetOperandsDirectionForward`
- pass `MergeContext::GetOperandsDirectionBackward` to `MergeOperator::ShouldMerge` and document the order
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4266
Differential Revision: D9360750
Pulled By: sagar0
fbshipit-source-id: 20cb73ff017760b062ecdcf4382560767086e092
Summary:
- Avoid `strdup` to use jemalloc on Windows
- Use `size_t` for consistency
- Add GCC 8 to Travis
- Add CMAKE_BUILD_TYPE=Release to Travis
Pull Request resolved: https://github.com/facebook/rocksdb/pull/3433
Differential Revision: D6837948
Pulled By: sagar0
fbshipit-source-id: b8543c3a4da9cd07ee9a33f9f4623188e233261f
Summary:
This is implemented by extending ReadCallback with another function `MaxUnpreparedSequenceNumber` which returns the largest visible sequence number for the current transaction, if there is uncommitted data written to DB. Otherwise, it returns zero, indicating no uncommitted data.
There are the places where reads had to be modified.
- Get and Seek/Next was just updated to seek to max(snapshot_seq, MaxUnpreparedSequenceNumber()) instead, and iterate until a key was visible.
- Prev did not need need updates since it did not use the Seek to sequence number optimization. Assuming that locks were held when writing unprepared keys, and ValidateSnapshot runs, there should only be committed keys and unprepared keys of the current transaction, all of which are visible. Prev will simply iterate to get the last visible key.
- Reseeking to skip keys optimization was also disabled for write unprepared, since it's possible to hit the max_skip condition even while reseeking. There needs to be some way to resolve infinite looping in this case.
Closes https://github.com/facebook/rocksdb/pull/3955
Differential Revision: D8286688
Pulled By: lth
fbshipit-source-id: 25e42f47fdeb5f7accea0f4fd350ef35198caafe
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:
Adding some stats that would be helpful to monitor if the DB has gone to unlikely stats that would hurt the performance. These are mostly when we end up needing to acquire a mutex.
Closes https://github.com/facebook/rocksdb/pull/3683
Differential Revision: D7529393
Pulled By: maysamyabandeh
fbshipit-source-id: f7d36279a8f39bd84d8ddbf64b5c97f670c5d6d9
Summary:
Summary
========
`InlineSkipList<>::Insert` takes the `key` parameter as a C-string. Then, it performs multiple comparisons with it requiring the `GetLengthPrefixedSlice()` to be spawn in `MemTable::KeyComparator::operator()(const char* prefix_len_key1, const char* prefix_len_key2)` on the same data over and over. The patch tries to optimize that.
Rough performance comparison
=====
Big keys, no compression.
```
$ ./db_bench --writes 20000000 --benchmarks="fillrandom" --compression_type none -key_size 256
(...)
fillrandom : 4.222 micros/op 236836 ops/sec; 80.4 MB/s
```
```
$ ./db_bench --writes 20000000 --benchmarks="fillrandom" --compression_type none -key_size 256
(...)
fillrandom : 4.064 micros/op 246059 ops/sec; 83.5 MB/s
```
TODO
======
In ~~a separated~~ this PR:
- [x] Go outside the write path. Maybe even eradicate the C-string-taking variant of `KeyIsAfterNode` entirely.
- [x] Try to cache the transformations applied by `KeyComparator` & friends in situations where we havy many comparisons with the same key.
Closes https://github.com/facebook/rocksdb/pull/3516
Differential Revision: D7059300
Pulled By: ajkr
fbshipit-source-id: 6f027dbb619a488129f79f79b5f7dbe566fb2dbb
Summary:
The MemTableRep API was broken by this commit: 813719e952
This patch reverts the changes and instead adds InsertKey (and etc.) overloads to extend the MemTableRep API without breaking the existing classes that inherit from it.
Closes https://github.com/facebook/rocksdb/pull/3513
Differential Revision: D7004134
Pulled By: maysamyabandeh
fbshipit-source-id: e568d91fe1e17dd76c0c1f6c7dd51a18633b1c4f
Summary:
- removed a few unneeded variables
- fused some variable declarations and their assignments
- fixed right-trimming code in string_util.cc to not underflow
- simplifed an assertion
- move non-nullptr check assertion before dereferencing of that pointer
- pass an std::string function parameter by const reference instead of by value (avoiding potential copy)
Closes https://github.com/facebook/rocksdb/pull/3507
Differential Revision: D7004679
Pulled By: sagar0
fbshipit-source-id: 52944952d9b56dfcac3bea3cd7878e315bb563c4
Summary:
Currently DB does not accept duplicate keys (keys with the same user key and the same sequence number). If Memtable returns false when receiving such keys, we can benefit from this signal to properly increase the sequence number in the rare cases when we have a duplicate key in the write batch written to DB under WritePrepared transactions.
Closes https://github.com/facebook/rocksdb/pull/3418
Differential Revision: D6822412
Pulled By: maysamyabandeh
fbshipit-source-id: adea3ce5073131cd38ed52b16bea0673b1a19e77
Summary:
Previously setting `write_buffer_size` with `SetOptions` would only apply to new memtables. An internal user wanted it to take effect immediately, instead of at an arbitrary future point, to prevent OOM.
This PR makes the memtable's size mutable, and makes `SetOptions()` mutate it. There is one case when we preserve the old behavior, which is when memtable prefix bloom filter is enabled and the user is increasing the memtable's capacity. That's because the prefix bloom filter's size is fixed and wouldn't work as well on a larger memtable.
Closes https://github.com/facebook/rocksdb/pull/3119
Differential Revision: D6228304
Pulled By: ajkr
fbshipit-source-id: e44bd9d10a5f8c9d8c464bf7436070bb3eafdfc9
Summary:
With FIFO compaction we would like to get the oldest data time for monitoring. The problem is we don't have timestamp for each key in the DB. As an approximation, we expose the earliest of sst file "creation_time" property.
My plan is to override the property with a more accurate value with blob db, where we actually have timestamp.
Closes https://github.com/facebook/rocksdb/pull/2842
Differential Revision: D5770600
Pulled By: yiwu-arbug
fbshipit-source-id: 03833c8f10bbfbee62f8ea5c0d03c0cafb5d853a
sdong