Summary:
New memory technologies are being developed by various hardware vendors (Intel DCPMM is one such technology currently available). These new memory types require different libraries for allocation and management (such as PMDK and memkind). The high capacities available make it possible to provision large caches (up to several TBs in size), beyond what is achievable with DRAM.
The new allocator provided in this PR uses the memkind library to allocate memory on different media.
**Performance**
We tested the new allocator using db_bench.
- For each test, we vary the size of the block cache (relative to the size of the uncompressed data in the database).
- The database is filled sequentially. Throughput is then measured with a readrandom benchmark.
- We use a uniform distribution as a worst-case scenario.
The plot shows throughput (ops/s) relative to a configuration with no block cache and default allocator.
For all tests, p99 latency is below 500 us.
**Changes**
- Add MemkindKmemAllocator
- Add --use_cache_memkind_kmem_allocator db_bench option (to create an LRU block cache with the new allocator)
- Add detection of memkind library with KMEM DAX support
- Add test for MemkindKmemAllocator
**Minimum Requirements**
- kernel 5.3.12
- ndctl v67 - https://github.com/pmem/ndctl
- memkind v1.10.0 - https://github.com/memkind/memkind
**Memory Configuration**
The allocator uses the MEMKIND_DAX_KMEM memory kind. Follow the instructions on[ memkind’s GitHub page](https://github.com/memkind/memkind) to set up NVDIMM memory accordingly.
Note on memory allocation with NVDIMM memory exposed as system memory.
- The MemkindKmemAllocator will only allocate from NVDIMM memory (using memkind_malloc with MEMKIND_DAX_KMEM kind).
- The default allocator is not restricted to RAM by default. Based on NUMA node latency, the kernel should allocate from local RAM preferentially, but it’s a kernel decision. numactl --preferred/--membind can be used to allocate preferentially/exclusively from the local RAM node.
**Usage**
When creating an LRU cache, pass a MemkindKmemAllocator object as argument.
For example (replace capacity with the desired value in bytes):
```
#include "rocksdb/cache.h"
#include "memory/memkind_kmem_allocator.h"
NewLRUCache(
capacity /*size_t*/,
6 /*cache_numshardbits*/,
false /*strict_capacity_limit*/,
false /*cache_high_pri_pool_ratio*/,
std::make_shared<MemkindKmemAllocator>());
```
Refer to [RocksDB’s block cache documentation](https://github.com/facebook/rocksdb/wiki/Block-Cache) to assign the LRU cache as block cache for a database.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6214
Reviewed By: cheng-chang
Differential Revision: D19292435
fbshipit-source-id: 7202f47b769e7722b539c86c2ffd669f64d7b4e1
Summary:
This commit is fixing a bug that readrandom test returns many NotFound in db_bench from Version 6.2.
Pull Request resolved: https://github.com/facebook/rocksdb/issues/6664
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6665
Reviewed By: cheng-chang
Differential Revision: D20911298
Pulled By: ajkr
fbshipit-source-id: c2658d4dbb35798ccbf67dff6e64923fb731ef81
Summary:
This PR adds support for pipelined & parallel compression optimization for `BlockBasedTableBuilder`. This optimization makes block building, block compression and block appending a pipeline, and uses multiple threads to accelerate block compression. Users can set `CompressionOptions::parallel_threads` greater than 1 to enable compression parallelism.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6262
Reviewed By: ajkr
Differential Revision: D20651306
fbshipit-source-id: 62125590a9c15b6d9071def9dc72589c1696a4cb
Summary:
I start to see following failures:
tools/db_bench_tool.cc: In constructor ‘rocksdb::NormalDistribution::NormalDistribution(unsigned int, unsigned int)’:
tools/db_bench_tool.cc:1528:58: error: declaration of ‘max’ shadows a member of 'this' [-Werror=shadow]
NormalDistribution(unsigned int min, unsigned int max) :
^
tools/db_bench_tool.cc:1528:58: error: declaration of ‘min’ shadows a member of 'this' [-Werror=shadow]
tools/db_bench_tool.cc: In constructor ‘rocksdb::UniformDistribution::UniformDistribution(unsigned int, unsigned int)’:
tools/db_bench_tool.cc:1546:59: error: declaration of ‘max’ shadows a member of 'this' [-Werror=shadow]
UniformDistribution(unsigned int min, unsigned int max) :
^
tools/db_bench_tool.cc:1546:59: error: declaration of ‘min’ shadows a member of 'this' [-Werror=shadow]
when I build from GCC 4.8. Rename those variables to fix the problem.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6537
Test Plan: make all with the compiler that used to show the failure.
Differential Revision: D20448741
fbshipit-source-id: 18bcf012dbe020f22f79038a9b08f447befa2574
Summary:
Some combinatino of --index_with_first_key and --index_shortening_mode can signifcantly improve performance for large values. Expose them in db_bench.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5859
Test Plan: Run them with the new options and observe the behavior.
Differential Revision: D20104434
fbshipit-source-id: 21d48a732a9caf20b82312c7d7557d747ea3c304
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:
Right, when reading from option files, no readahead is used and 8KB buffer is used. It might introduce high latency if the file system provide high latency and doesn't do readahead. Instead, introduce a readahead to the file. When calling inside DB, infer the value from options.log_readahead. Otherwise, a default 512KB readahead size is used.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6372
Test Plan: Add --log_readahead_size in db_bench. Run it with several options and observe read size from option files using strace.
Differential Revision: D19727739
fbshipit-source-id: e6d8053b0a64259abc087f1f388b9cd66fa8a583
Summary:
We see some odd errors complaining math. However, it doesn't seem that it is needed to be included. Remove the include of math.h. Just removing it from db_bench doesn't seem to break anything. Replacing sqrt from std::sqrt seems to work for histogram.cc
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6373
Test Plan: Watch Travis and appveyor to run.
Differential Revision: D19730068
fbshipit-source-id: d3ad41defcdd9f51c2da1a3673fb258f5dfacf47
Summary:
The patch makes it possible to set the BlobDB configuration option
`garbage_collection_cutoff` on the command line. In addition, it changes
the `db_bench` code so that the default values of BlobDB related
parameters are taken from the defaults of the actual BlobDB
configuration options (note: this changes the the default of
`blob_db_bytes_per_sync`).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6211
Test Plan: Ran `db_bench` with various values of the new parameter.
Differential Revision: D19166895
Pulled By: ltamasi
fbshipit-source-id: 305ccdf0123b9db032b744715810babdc3e3b7d5
Summary:
In the previous PR https://github.com/facebook/rocksdb/issues/4788, user can use db_bench mix_graph option to generate the workload that is from the social graph. The key is generated based on the key access hotness. In this PR, user can further model the key-range hotness and fit those to two-term-exponential distribution. First, user cuts the whole key space into small key ranges (e.g., key-ranges are the same size and the key-range number is the number of SST files). Then, user calculates the average access count per key of each key-range as the key-range hotness. Next, user fits the key-range hotness to two-term-exponential distribution (f(x) = f(x) = a*exp(b*x) + c*exp(d*x)) and generate the value of a, b, c, and d. They are the parameters in db_bench: prefix_dist_a, prefix_dist_b, prefix_dist_c, and prefix_dist_d. Finally, user can run db_bench by specify the parameters.
For example:
`./db_bench --benchmarks="mixgraph" -use_direct_io_for_flush_and_compaction=true -use_direct_reads=true -cache_size=268435456 -key_dist_a=0.002312 -key_dist_b=0.3467 -keyrange_dist_a=14.18 -keyrange_dist_b=-2.917 -keyrange_dist_c=0.0164 -keyrange_dist_d=-0.08082 -keyrange_num=30 -value_k=0.2615 -value_sigma=25.45 -iter_k=2.517 -iter_sigma=14.236 -mix_get_ratio=0.85 -mix_put_ratio=0.14 -mix_seek_ratio=0.01 -sine_mix_rate_interval_milliseconds=5000 -sine_a=350 -sine_b=0.0105 -sine_d=50000 --perf_level=2 -reads=1000000 -num=5000000 -key_size=48`
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5953
Test Plan: run db_bench with different parameters and checked the results.
Differential Revision: D18053527
Pulled By: zhichao-cao
fbshipit-source-id: 171f8b3142bd76462f1967c58345ad7e4f84bab7
Summary:
Since we already parse env_uri from command line and creates custom Env
accordingly, we should invoke the methods of such Envs instead of using
Env::Default().
Test Plan (on devserver):
```
$make db_bench db_stress
$./db_bench -benchmarks=fillseq
./db_stress
```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5943
Differential Revision: D18018550
Pulled By: riversand963
fbshipit-source-id: 03b61329aaae0dfd914a0b902cc677f570f102e3
Summary:
In the current trace replay, all the queries are serialized and called by single threads. It may not simulate the original application query situations closely. The multi-threads replay is implemented in this PR. Users can set the number of threads to replay the trace. The queries generated according to the trace records are scheduled in the thread pool job queue.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5934
Test Plan: test with make check and real trace replay.
Differential Revision: D17998098
Pulled By: zhichao-cao
fbshipit-source-id: 87eecf6f7c17a9dc9d7ab29dd2af74f6f60212c8
Summary:
Currently, db_bench only supports PutWithTTL operations for BlobDB but
not regular Puts. The patch adds support for regular (non-TTL) Puts and also
changes the default for blob_db_max_ttl_range to zero, which corresponds
to no TTL.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5921
Test Plan:
make check
./db_bench -benchmarks=fillrandom -statistics -stats_interval_seconds=1
-duration=90 -num=500000 -use_blob_db=1 -blob_db_file_size=1000000
-target_file_size_base=1000000 (issues Put operations with no TTL)
./db_bench -benchmarks=fillrandom -statistics -stats_interval_seconds=1
-duration=90 -num=500000 -use_blob_db=1 -blob_db_file_size=1000000
-target_file_size_base=1000000 -blob_db_max_ttl_range=86400 (issues
PutWithTTL operations with random TTLs in the [0, blob_db_max_ttl_range)
interval, as before)
Differential Revision: D17919798
Pulled By: ltamasi
fbshipit-source-id: b946c3522b836b92b4c157ffbad24f92ba2b0a16
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
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:
The ObjectRegistry class replaces the Registrar and NewCustomObjects. Objects are registered with the registry by Type (the class must implement the static const char *Type() method).
This change is necessary for a few reasons:
- By having a class (rather than static template instances), the class can be passed between compilation units, meaning that objects could be registered and shared from a dynamic library with an executable.
- By having a class with instances, different units could have different objects registered. This could be useful if, for example, one Option allowed for a dynamic library and one did not.
When combined with some other PRs (being able to load shared libraries, a Configurable interface to configure objects to/from string), this code will allow objects in external shared libraries to be added to a RocksDB image at run-time, rather than requiring every new extension to be built into the main library and called explicitly by every program.
Test plan (on riversand963's devserver)
```
$COMPILE_WITH_ASAN=1 make -j32 all && sleep 1 && make check
```
All tests pass.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5293
Differential Revision: D16363396
Pulled By: riversand963
fbshipit-source-id: fbe4acb615bfc11103eef40a0b288845791c0180
Summary:
Sometimes it is helpful to fetch the whole history of stats after benchmark runs. Add such an option
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5532
Test Plan: Run the benchmark manually and observe the output is as expected.
Differential Revision: D16097764
fbshipit-source-id: 10b5b735a22a18be198b8f348be11f11f8806904
Summary:
Formatting fixes in db_bench_tool that were accidentally omitted
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5525
Test Plan: Unit tests
Differential Revision: D16078516
Pulled By: elipoz
fbshipit-source-id: bf8df0e3f08092a91794ebf285396d9b8a335bb9
Summary:
This PR continues the work in https://github.com/facebook/rocksdb/pull/4748 and https://github.com/facebook/rocksdb/pull/4535 by adding a new DBOption `persist_stats_to_disk` which instructs RocksDB to persist stats history to RocksDB itself. When statistics is enabled, and both options `stats_persist_period_sec` and `persist_stats_to_disk` are set, RocksDB will periodically write stats to a built-in column family in the following form: key -> (timestamp in microseconds)#(stats name), value -> stats value. The existing API `GetStatsHistory` will detect the current value of `persist_stats_to_disk` and either read from in-memory data structure or from the hidden column family on disk.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5046
Differential Revision: D15863138
Pulled By: miasantreble
fbshipit-source-id: bb82abdb3f2ca581aa42531734ac799f113e931b
Summary:
This PR integrates the block cache tracing into db_bench. It adds three command line arguments.
-block_cache_trace_file (Block cache trace file path.) type: string default: ""
-block_cache_trace_max_trace_file_size_in_bytes (The maximum block cache
trace file size in bytes. Block cache accesses will not be logged if the
trace file size exceeds this threshold. Default is 64 GB.) type: int64
default: 68719476736
-block_cache_trace_sampling_frequency (Block cache trace sampling
frequency, termed s. It uses spatial downsampling and samples accesses to
one out of s blocks.) type: int32 default: 1
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5459
Differential Revision: D15832031
Pulled By: HaoyuHuang
fbshipit-source-id: 0ecf2f2686557251fe741a2769b21170777efa3d
Summary:
When using `PRIu64` type of printf specifier, current code base does the following:
```
#ifndef __STDC_FORMAT_MACROS
#define __STDC_FORMAT_MACROS
#endif
#include <inttypes.h>
```
However, this can be simplified to
```
#include <cinttypes>
```
as long as flag `-std=c++11` is used.
This should solve issues like https://github.com/facebook/rocksdb/issues/5159
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5402
Differential Revision: D15701195
Pulled By: miasantreble
fbshipit-source-id: 6dac0a05f52aadb55e9728038599d3d2e4b59d03
Summary:
1. Fix a bug in WAL replay in which write batches with old sequence numbers are mistakenly inserted into memtables.
2. Add support for benchmarking secondary instance to db_bench_tool.
With changes made in this PR, we can start benchmarking secondary instance
using two processes. It is also possible to vary the frequency at which the
secondary instance tries to catch up with the primary. The info log of the
secondary can be found in a directory whose path can be specified with
'-secondary_path'.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5170
Differential Revision: D15564608
Pulled By: riversand963
fbshipit-source-id: ce97688ed3d33f69d3a0b9266ebbbbf887aa0ec8
Summary:
There are too many types of files under util/. Some test related files don't belong to there or just are just loosely related. Mo
ve them to a new directory test_util/, so that util/ is cleaner.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5377
Differential Revision: D15551366
Pulled By: siying
fbshipit-source-id: 0f5c8653832354ef8caa31749c0143815d719e2c
Summary:
This enables the user to set TransactionDBOptions::skip_concurrency_control so the standard `DB::Write(const WriteOptions& opts, WriteBatch* updates)` would skip the concurrency control. This would give higher throughput to the users who know their use case doesn't need concurrency control.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5330
Differential Revision: D15525932
Pulled By: maysamyabandeh
fbshipit-source-id: 68421ac1ba34f549a4a8de9ce4c2dccf6fb4b06b
Summary:
In the current db_bench trace replay, the replay process strictly follows the timestamp to issue the queries. In some cases, user does not care about the time. Therefore, fast forward is needed for users to speed up the replay process.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5273
Differential Revision: D15389232
Pulled By: zhichao-cao
fbshipit-source-id: 735d629b9d2a167b05af3e4fa0ddf9d5d0be1806
Summary:
Performing unordered writes in rocksdb when unordered_write option is set to true. When enabled the writes to memtable are done without joining any write thread. This offers much higher write throughput since the upcoming writes would not have to wait for the slowest memtable write to finish. The tradeoff is that the writes visible to a snapshot might change over time. If the application cannot tolerate that, it should implement its own mechanisms to work around that. Using TransactionDB with WRITE_PREPARED write policy is one way to achieve that. Doing so increases the max throughput by 2.2x without however compromising the snapshot guarantees.
The patch is prepared based on an original by siying
Existing unit tests are extended to include unordered_write option.
Benchmark Results:
```
TEST_TMPDIR=/dev/shm/ ./db_bench_unordered --benchmarks=fillrandom --threads=32 --num=10000000 -max_write_buffer_number=16 --max_background_jobs=64 --batch_size=8 --writes=3000000 -level0_file_num_compaction_trigger=99999 --level0_slowdown_writes_trigger=99999 --level0_stop_writes_trigger=99999 -enable_pipelined_write=false -disable_auto_compactions --unordered_write=1
```
With WAL
- Vanilla RocksDB: 78.6 MB/s
- WRITER_PREPARED with unordered_write: 177.8 MB/s (2.2x)
- unordered_write: 368.9 MB/s (4.7x with relaxed snapshot guarantees)
Without WAL
- Vanilla RocksDB: 111.3 MB/s
- WRITER_PREPARED with unordered_write: 259.3 MB/s MB/s (2.3x)
- unordered_write: 645.6 MB/s (5.8x with relaxed snapshot guarantees)
- WRITER_PREPARED with unordered_write disable concurrency control: 185.3 MB/s MB/s (2.35x)
Limitations:
- The feature is not yet extended to `max_successive_merges` > 0. The feature is also incompatible with `enable_pipelined_write` = true as well as with `allow_concurrent_memtable_write` = false.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5218
Differential Revision: D15219029
Pulled By: maysamyabandeh
fbshipit-source-id: 38f2abc4af8780148c6128acdba2b3227bc81759
Summary:
Improve the iterators performance when the user explicitly sets the readahead size via `ReadOptions.readahead_size`.
1. Stop creating new table readers when the user explicitly sets readahead size.
2. Make use of an internal buffer based on `FilePrefetchBuffer` instead of using `ReadaheadRandomAccessFileReader`, to handle the user readahead requests (for both buffered and direct io cases).
3. Add `readahead_size` to db_bench.
**Benchmarks:**
https://gist.github.com/sagar0/53693edc320a18abeaeca94ca32f5737
For 1 MB readahead, Buffered IO performance improves by 28% and Direct IO performance improves by 50%.
For 512KB readahead, Buffered IO performance improves by 30% and Direct IO performance improves by 67%.
**Test Plan:**
Updated `DBIteratorTest.ReadAhead` test to make sure that:
- no new table readers are created for iterators on setting ReadOptions.readahead_size
- At least "readahead" number of bytes are actually getting read on each iterator read.
TODO later:
- Use similar logic for compactions as well.
- This ties in nicely with #4052 and paves the way for removing ReadaheadRandomAcessFile later.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5246
Differential Revision: D15107946
Pulled By: sagar0
fbshipit-source-id: 2c1149729ca7d779e4e8b7710ba6f4e8cbfd3bea
Summary:
I needed this change to be able to build the v6.0.1 release on Windows.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5227
Differential Revision: D15033815
Pulled By: sagar0
fbshipit-source-id: 579f3b8e694c34c0d43527eb2fa37175e37f5911
Summary:
Depending on the config, manual compaction (leveled compaction style) does following compactions:
L0->L1
L1->L2
...
Ln-1 -> Ln
Ln -> Ln
The final Ln -> Ln compaction is partly unnecessary as it recompacts all the files that were just generated by the Ln-1 -> Ln. We should avoid recompacting such files. This rule should be applied to Lmax only.
Resolves issue https://github.com/facebook/rocksdb/issues/4995
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5138
Differential Revision: D14940106
Pulled By: miasantreble
fbshipit-source-id: 8d3cf5507a17e76f3333cfd4bac5256d005636e5
Summary:
This PR introduces a new MultiGet() API, with the underlying implementation grouping keys based on SST file and batching lookups in a file. The reason for the new API is twofold - the definition allows callers to allocate storage for status and values on stack instead of std::vector, as well as return values as PinnableSlices in order to avoid copying, and it keeps the original MultiGet() implementation intact while we experiment with batching.
Batching is useful when there is some spatial locality to the keys being queries, as well as larger batch sizes. The main benefits are due to -
1. Fewer function calls, especially to BlockBasedTableReader::MultiGet() and FullFilterBlockReader::KeysMayMatch()
2. Bloom filter cachelines can be prefetched, hiding the cache miss latency
The next step is to optimize the binary searches in the level_storage_info, index blocks and data blocks, since we could reduce the number of key comparisons if the keys are relatively close to each other. The batching optimizations also need to be extended to other formats, such as PlainTable and filter formats. This also needs to be added to db_stress.
Benchmark results from db_bench for various batch size/locality of reference combinations are given below. Locality was simulated by offsetting the keys in a batch by a stride length. Each SST file is about 8.6MB uncompressed and key/value size is 16/100 uncompressed. To focus on the cpu benefit of batching, the runs were single threaded and bound to the same cpu to eliminate interference from other system events. The results show a 10-25% improvement in micros/op from smaller to larger batch sizes (4 - 32).
Batch Sizes
1 | 2 | 4 | 8 | 16 | 32
Random pattern (Stride length 0)
4.158 | 4.109 | 4.026 | 4.05 | 4.1 | 4.074 - Get
4.438 | 4.302 | 4.165 | 4.122 | 4.096 | 4.075 - MultiGet (no batching)
4.461 | 4.256 | 4.277 | 4.11 | 4.182 | 4.14 - MultiGet (w/ batching)
Good locality (Stride length 16)
4.048 | 3.659 | 3.248 | 2.99 | 2.84 | 2.753
4.429 | 3.728 | 3.406 | 3.053 | 2.911 | 2.781
4.452 | 3.45 | 2.833 | 2.451 | 2.233 | 2.135
Good locality (Stride length 256)
4.066 | 3.786 | 3.581 | 3.447 | 3.415 | 3.232
4.406 | 4.005 | 3.644 | 3.49 | 3.381 | 3.268
4.393 | 3.649 | 3.186 | 2.882 | 2.676 | 2.62
Medium locality (Stride length 4096)
4.012 | 3.922 | 3.768 | 3.61 | 3.582 | 3.555
4.364 | 4.057 | 3.791 | 3.65 | 3.57 | 3.465
4.479 | 3.758 | 3.316 | 3.077 | 2.959 | 2.891
dbbench command used (on a DB with 4 levels, 12 million keys)-
TEST_TMPDIR=/dev/shm numactl -C 10 ./db_bench.tmp -use_existing_db=true -benchmarks="readseq,multireadrandom" -write_buffer_size=4194304 -target_file_size_base=4194304 -max_bytes_for_level_base=16777216 -num=12000000 -reads=12000000 -duration=90 -threads=1 -compression_type=none -cache_size=4194304000 -batch_size=32 -disable_auto_compactions=true -bloom_bits=10 -cache_index_and_filter_blocks=true -pin_l0_filter_and_index_blocks_in_cache=true -multiread_batched=true -multiread_stride=4
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5011
Differential Revision: D14348703
Pulled By: anand1976
fbshipit-source-id: 774406dab3776d979c809522a67bedac6c17f84b
Summary:
The code convention we are following, Google C++ Style, discourage
alias in header files, especially public headers:
https://google.github.io/styleguide/cppguide.html#Aliases
Remove some of them. Might removed some from .cc files as well to be consistent.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5113
Differential Revision: D14633030
Pulled By: siying
fbshipit-source-id: b990edc919d5de60295992284f980195e501d424
Summary:
This is a feature to sample data-block compressibility and and report them as stats. 1 in N (tunable) blocks is sampled for compressibility using two algorithms:
1. lz4 or snappy for fast compression
2. zstd or zlib for slow but higher compression.
The stats are reported to the caller as raw-bytes and compressed-bytes. The block continues to be compressed for storage using the specified CompressionType.
The db_bench_tool how has a command line option for specifying the sampling rate. It's default value is 0 (no sampling). To test the overhead for a certain value, users can compare the performance of db_bench_tool, varying the sampling rate. It is unlikely to have a noticeable impact for high values like 20.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4842
Differential Revision: D13629011
Pulled By: shobhitdayal
fbshipit-source-id: 14ca668bcab6499b2a1734edf848eb62a4f4fafa
Summary:
In the MixGraph benchmark of db_bench, The max buffer size used for value of KV-pair might be extremely large (64MB), which might cause function stack overflow in some platforms, reduced to 1MB.
Added the finished ops printing in MixGraph benchmark.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5051
Differential Revision: D14379571
Pulled By: zhichao-cao
fbshipit-source-id: 24084fbe38f60f2902d9a40f6bc9a25e4e2c9bb9
Summary:
Added an option, `-use_existing_keys`, which can be set to run
benchmarks against an arbitrary existing database. Now users can
benchmark against their actual database rather than synthetic data.
Before the run begins, it loads all the keys into memory, then uses that
set of keys rather than synthesizing new ones in `GenerateKeyFromInt`.
This is mainly intended for small-scale DBs where the memory consumption
is not a concern.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5017
Differential Revision: D14270303
Pulled By: riversand963
fbshipit-source-id: 6328df9dffb5e19170270dd00a69f4bbe424e5ed
