Summary:
fix a data race introduced in https://github.com/facebook/rocksdb/issues/10547 (P5295241720), first reported by pdillinger. The race is between the `std::atomic_load_explicit` in NewRangeTombstoneIteratorInternal and the `std::atomic_store_explicit` in MemTable::Add() that operate on `cached_range_tombstone_`. P5295241720 shows that `atomic_store_explicit` initializes some mutex which `atomic_load_explicit` could be trying to call `lock()` on at the same time. This fix moves the initialization to memtable constructor.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10680
Test Plan: `USE_CLANG=1 COMPILE_WITH_TSAN=1 make -j24 whitebox_crash_test`
Reviewed By: ajkr
Differential Revision: D39528696
Pulled By: cbi42
fbshipit-source-id: ee740841044438e18ad2b8ea567444dd542dd8e2
Summary:
Each read from memtable used to read and fragment all the range tombstones into a `FragmentedRangeTombstoneList`. https://github.com/facebook/rocksdb/issues/10380 improved the inefficient here by caching a `FragmentedRangeTombstoneList` with each immutable memtable. This PR extends the caching to mutable memtables. The fragmented range tombstone can be constructed in either read (This PR) or write path (https://github.com/facebook/rocksdb/issues/10584). With both implementation, each `DeleteRange()` will invalidate the cache, and the difference is where the cache is re-constructed.`CoreLocalArray` is used to store the cache with each memtable so that multi-threaded reads can be efficient. More specifically, each core will have a shared_ptr to a shared_ptr pointing to the current cache. Each read thread will only update the reference count in its core-local shared_ptr, and this is only needed when reading from mutable memtables.
The choice between write path and read path is not an easy one: they are both improvement compared to no caching in the current implementation, but they favor different operations and could cause regression in the other operation (read vs write). The write path caching in (https://github.com/facebook/rocksdb/issues/10584) leads to a cleaner implementation, but I chose the read path caching here to avoid significant regression in write performance when there is a considerable amount of range tombstones in a single memtable (the number from the benchmark below suggests >1000 with concurrent writers). Note that even though the fragmented range tombstone list is only constructed in `DeleteRange()` operations, it could block other writes from proceeding, and hence affects overall write performance.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10547
Test Plan:
- TestGet() in stress test is updated in https://github.com/facebook/rocksdb/issues/10553 to compare Get() result against expected state: `./db_stress_branch --readpercent=57 --prefixpercent=4 --writepercent=25 -delpercent=5 --iterpercent=5 --delrangepercent=4`
- Perf benchmark: tested read and write performance where a memtable has 0, 1, 10, 100 and 1000 range tombstones.
```
./db_bench --benchmarks=fillrandom,readrandom --writes_per_range_tombstone=200 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=200000 --reads=100000 --disable_auto_compactions --max_num_range_tombstones=1000
```
Write perf regressed since the cost of constructing fragmented range tombstone list is shifted from every read to a single write. 6cbe5d8e172dc5f1ef65c9d0a6eedbd9987b2c72 is included in the last column as a reference to see performance impact on multi-thread reads if `CoreLocalArray` is not used.
micros/op averaged over 5 runs: first 4 columns are for fillrandom, last 4 columns are for readrandom.
| |fillrandom main | write path caching | read path caching |memtable V3 (https://github.com/facebook/rocksdb/issues/10308) | readrandom main | write path caching | read path caching |memtable V3 |
|--- |--- |--- |--- |--- | --- | --- | --- | --- |
| 0 |6.35 |6.15 |5.82 |6.12 |2.24 |2.26 |2.03 |2.07 |
| 1 |5.99 |5.88 |5.77 |6.28 |2.65 |2.27 |2.24 |2.5 |
| 10 |6.15 |6.02 |5.92 |5.95 |5.15 |2.61 |2.31 |2.53 |
| 100 |5.95 |5.78 |5.88 |6.23 |28.31 |2.34 |2.45 |2.94 |
| 100 25 threads |52.01 |45.85 |46.18 |47.52 |35.97 |3.34 |3.34 |3.56 |
| 1000 |6.0 |7.07 |5.98 |6.08 |333.18 |2.86 |2.7 |3.6 |
| 1000 25 threads |52.6 |148.86 |79.06 |45.52 |473.49 |3.66 |3.48 |4.38 |
- Benchmark performance of`readwhilewriting` from https://github.com/facebook/rocksdb/issues/10552, 100 range tombstones are written: `./db_bench --benchmarks=readwhilewriting --writes_per_range_tombstone=500 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=100000 --reads=500000 --disable_auto_compactions --max_num_range_tombstones=10000 --finish_after_writes`
readrandom micros/op:
| |main |write path caching |read path caching |memtable V3 |
|---|---|---|---|---|
| single thread |48.28 |1.55 |1.52 |1.96 |
| 25 threads |64.3 |2.55 |2.67 |2.64 |
Reviewed By: ajkr
Differential Revision: D38895410
Pulled By: cbi42
fbshipit-source-id: 930bfc309dd1b2f4e8e9042f5126785bba577559
Summary:
The patch adds a new API `GetEntity` that can be used to perform
wide-column point lookups. It also extends the `Get` code path and
the `MemTable` / `MemTableList` and `Version` / `GetContext` logic
accordingly so that wide-column entities can be served from both
memtables and SSTs. If the result of a lookup is a wide-column entity
(`kTypeWideColumnEntity`), it is passed to the application in deserialized
form; if it is a plain old key-value (`kTypeValue`), it is presented as a
wide-column entity with a single default (anonymous) column.
(In contrast, regular `Get` returns plain old key-values as-is, and
returns the value of the default column for wide-column entities, see
https://github.com/facebook/rocksdb/issues/10483 .)
The result of `GetEntity` is a self-contained `PinnableWideColumns` object.
`PinnableWideColumns` contains a `PinnableSlice`, which either stores the
underlying data in its own buffer or holds on to a cache handle. It also contains
a `WideColumns` instance, which indexes the contents of the `PinnableSlice`,
so applications can access the values of columns efficiently.
There are several pieces of functionality which are currently not supported
for wide-column entities: there is currently no `MultiGetEntity` or wide-column
iterator; also, `Merge` and `GetMergeOperands` are not supported, and there
is no `GetEntity` implementation for read-only and secondary instances.
We plan to implement these in future PRs.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10540
Test Plan: `make check`
Reviewed By: akankshamahajan15
Differential Revision: D38847474
Pulled By: ltamasi
fbshipit-source-id: 42311a34ccdfe88b3775e847a5e2a5296e002b5b
Summary:
- Right now each read fragments the memtable range tombstones https://github.com/facebook/rocksdb/issues/4808. This PR explores the idea of fragmenting memtable range tombstones in the write path and reads can just read this cached fragmented tombstone without any fragmenting cost. This PR only does the caching for immutable memtable, and does so right before a memtable is added to an immutable memtable list. The fragmentation is done without holding mutex to minimize its performance impact.
- db_bench is updated to print out the number of range deletions executed if there is any.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10380
Test Plan:
- CI, added asserts in various places to check whether a fragmented range tombstone list should have been constructed.
- Benchmark: as this PR only optimizes immutable memtable path, the number of writes in the benchmark is chosen such an immutable memtable is created and range tombstones are in that memtable.
```
single thread:
./db_bench --benchmarks=fillrandom,readrandom --writes_per_range_tombstone=1 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=500000 --reads=100000 --max_num_range_tombstones=100
multi_thread
./db_bench --benchmarks=fillrandom,readrandom --writes_per_range_tombstone=1 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=15000 --reads=20000 --threads=32 --max_num_range_tombstones=100
```
Commit 99cdf16464a057ca44de2f747541dedf651bae9e is included in benchmark result. It was an earlier attempt where tombstones are fragmented for each write operation. Reader threads share it using a shared_ptr which would slow down multi-thread read performance as seen in benchmark results.
Results are averaged over 5 runs.
Single thread result:
| Max # tombstones | main fillrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR | main readrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR |
| ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| 0 |6.68 |6.57 |6.72 |4.72 |4.79 |4.54 |
| 1 |6.67 |6.58 |6.62 |5.41 |4.74 |4.72 |
| 10 |6.59 |6.5 |6.56 |7.83 |4.69 |4.59 |
| 100 |6.62 |6.75 |6.58 |29.57 |5.04 |5.09 |
| 1000 |6.54 |6.82 |6.61 |320.33 |5.22 |5.21 |
32-thread result: note that "Max # tombstones" is per thread.
| Max # tombstones | main fillrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR | main readrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR |
| ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| 0 |234.52 |260.25 |239.42 |5.06 |5.38 |5.09 |
| 1 |236.46 |262.0 |231.1 |19.57 |22.14 |5.45 |
| 10 |236.95 |263.84 |251.49 |151.73 |21.61 |5.73 |
| 100 |268.16 |296.8 |280.13 |2308.52 |22.27 |6.57 |
Reviewed By: ajkr
Differential Revision: D37916564
Pulled By: cbi42
fbshipit-source-id: 05d6d2e16df26c374c57ddcca13a5bfe9d5b731e
Summary:
The patch fixes a couple of issues related to in-place updates: 1) the value type was not passed from
`MemTableInserter::PutCFImpl` to `MemTable::Update` and 2) `MemTable::UpdateCallback` was called
for any value type (with the callee's logic assuming `kTypeValue`) even though the callback mechanism
is only safe for plain values.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10254
Test Plan: `make check`
Reviewed By: riversand963
Differential Revision: D37463644
Pulled By: ltamasi
fbshipit-source-id: 33802477dac0691681f416ae84c4d9742c6fe41a
Summary:
Especially after updating to C++17, I don't see a compelling case for
*requiring* any folly components in RocksDB. I was able to purge the existing
hard dependencies, and it can be quite difficult to strip out non-trivial components
from folly for use in RocksDB. (The prospect of doing that on F14 has changed
my mind on the best approach here.)
But this change creates an optional integration where we can plug in
components from folly at compile time, starting here with F14FastMap to replace
std::unordered_map when possible (probably no public APIs for example). I have
replaced the biggest CPU users of std::unordered_map with compile-time
pluggable UnorderedMap which will use F14FastMap when USE_FOLLY is set.
USE_FOLLY is always set in the Meta-internal buck build, and a simulation of
that is in the Makefile for public CI testing. A full folly build is not needed, but
checking out the full folly repo is much simpler for getting the dependency,
and anything else we might want to optionally integrate in the future.
Some picky details:
* I don't think the distributed mutex stuff is actually used, so it was easy to remove.
* I implemented an alternative to `folly::constexpr_log2` (which is much easier
in C++17 than C++11) so that I could pull out the hard dependencies on
`ConstexprMath.h`
* I had to add noexcept move constructors/operators to some types to make
F14's complainUnlessNothrowMoveAndDestroy check happy, and I added a
macro to make that easier in some common cases.
* Updated Meta-internal buck build to use folly F14Map (always)
No updates to HISTORY.md nor INSTALL.md as this is not (yet?) considered a
production integration for open source users.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9546
Test Plan:
CircleCI tests updated so that a couple of them use folly.
Most internal unit & stress/crash tests updated to use Meta-internal latest folly.
(Note: they should probably use buck but they currently use Makefile.)
Example performance improvement: when filter partitions are pinned in cache,
they are tracked by PartitionedFilterBlockReader::filter_map_ and we can build
a test that exercises that heavily. Build DB with
```
TEST_TMPDIR=/dev/shm/rocksdb ./db_bench -benchmarks=fillrandom -num=10000000 -disable_wal=1 -write_buffer_size=30000000 -bloom_bits=16 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -partition_index_and_filters
```
and test with (simultaneous runs with & without folly, ~20 times each to see
convergence)
```
TEST_TMPDIR=/dev/shm/rocksdb ./db_bench_folly -readonly -use_existing_db -benchmarks=readrandom -num=10000000 -bloom_bits=16 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -partition_index_and_filters -duration=40 -pin_l0_filter_and_index_blocks_in_cache
```
Average ops/s no folly: 26229.2
Average ops/s with folly: 26853.3 (+2.4%)
Reviewed By: ajkr
Differential Revision: D34181736
Pulled By: pdillinger
fbshipit-source-id: ffa6ad5104c2880321d8a1aa7187e00ab0d02e94
Summary:
MemTable::MultiGet was not considering range tombstones before
querying Bloom filter. This means range tombstones would be skipped for
keys (or prefixes) with no other entries in the memtable. This could cause
old values for a key (in SST files) to still show up until the range tombstone
covering it has been flushed.
This is fixed by essentially disabling the memtable Bloom filter when there
are any range tombstones. (This could be better optimized in the future, but
good enough for now.)
Did some other cleanup/optimization in the same code to (more than) offset
the cost of checking on range tombstones in more cases. There is now
notable improvement when memtable_whole_key_filtering and prefix_extractor
are used together (unusual), and this makes MultiGet closer to the Get
implementation.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9453
Test Plan:
new unit test added. Added memtable Bloom to crash test.
Performance testing
--------------------
Build WAL-only DB (recovers to memtable):
```
TEST_TMPDIR=/dev/shm/rocksdb ./db_bench -benchmarks=fillrandom -num=1000000 -write_buffer_size=250000000
```
Query test command, to maximize sensitivity to the changed code:
```
TEST_TMPDIR=/dev/shm/rocksdb ./db_bench -use_existing_db -readonly -benchmarks=multireadrandom -num=10000000 -write_buffer_size=250000000 -memtable_bloom_size_ratio=0.015 -multiread_batched -batch_size=24 -threads=8 -memtable_whole_key_filtering=$MWKF -prefix_size=$PXS
```
(Note -num here is 10x larger for mostly memtable misses)
Before & after run simultaneously, average over 10 iterations per data point, ops/sec.
MWKF=0 PXS=0 (Bloom disabled)
Before: 5724844
After: 6722066
MWKF=0 PXS=7 (prefixes hardly unique; Bloom not useful)
Before: 9981319
After: 10237990
MWKF=0 PXS=8 (prefixes unique; Bloom useful)
Before: 12081715
After: 12117603
MWKF=1 PXS=0 (whole key Bloom useful)
Before: 11944354
After: 12096085
MWKF=1 PXS=7 (whole key Bloom useful in new version; prefixes not useful in old version)
Before: 9444299
After: 11826029
MWKF=1 PXS=7 (whole key Bloom useful in new version; prefixes useful in old version)
Before: 11784465
After: 11778591
Only in this last case is the 'before' *slightly* faster, perhaps because hashing prefixes is slightly faster than hashing whole keys. Otherwise, 'after' is faster.
Reviewed By: ajkr
Differential Revision: D33805025
Pulled By: pdillinger
fbshipit-source-id: 597523cae4f4eafdf6ae6bb2bc6cb46f83b017bf
Summary:
- Make MemoryAllocator and its implementations into a Customizable class.
- Added a "DefaultMemoryAllocator" which uses new and delete
- Added a "CountedMemoryAllocator" that counts the number of allocs and free
- Updated the existing tests to use these new allocators
- Changed the memkind allocator test into a generic test that can test the various allocators.
- Added tests for creating all of the allocators
- Added tests to verify/create the JemallocNodumpAllocator using its options.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8980
Reviewed By: zhichao-cao
Differential Revision: D32990403
Pulled By: mrambacher
fbshipit-source-id: 6fdfe8218c10dd8dfef34344a08201be1fa95c76
Summary:
After https://github.com/facebook/rocksdb/issues/8725, keys added to `WriteBatch` may be timestamp-suffixed, while `WriteBatch` has no awareness of the timestamp size. Therefore, `WriteBatch` can no longer calculate timestamp checksum separately from the rest of the key's checksum in all cases.
This PR changes the definition of key in KV checksum to include the timestamp suffix. That way we do not need to worry about where the timestamp begins within the key. I believe the only practical effect of this change is now `AssignTimestamp()` requires recomputing the whole key checksum (`UpdateK()`) rather than just the timestamp portion (`UpdateT()`).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8914
Test Plan:
run stress command that used to fail
```
$ ./db_stress --batch_protection_bytes_per_key=8 -clear_column_family_one_in=0 -test_batches_snapshots=1
```
Reviewed By: riversand963
Differential Revision: D30925715
Pulled By: ajkr
fbshipit-source-id: c143f7ccb46c0efb390ad57ef415c250d754deff
Summary:
Changes the API of the MemPurge process: the `bool experimental_allow_mempurge` and `experimental_mempurge_policy` flags have been replaced by a `double experimental_mempurge_threshold` option.
This change of API reflects another major change introduced in this PR: the MemPurgeDecider() function now works by sampling the memtables being flushed to estimate the overall amount of useful payload (payload minus the garbage), and then compare this useful payload estimate with the `double experimental_mempurge_threshold` value.
Therefore, when the value of this flag is `0.0` (default value), mempurge is simply deactivated. On the other hand, a value of `DBL_MAX` would be equivalent to always going through a mempurge regardless of the garbage ratio estimate.
At the moment, a `double experimental_mempurge_threshold` value else than 0.0 or `DBL_MAX` is opnly supported`with the `SkipList` memtable representation.
Regarding the sampling, this PR includes the introduction of a `MemTable::UniqueRandomSample` function that collects (approximately) random entries from the memtable by using the new `SkipList::Iterator::RandomSeek()` under the hood, or by iterating through each memtable entry, depending on the target sample size and the total number of entries.
The unit tests have been readapted to support this new API.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8628
Reviewed By: pdillinger
Differential Revision: D30149315
Pulled By: bjlemaire
fbshipit-source-id: 1feef5390c95db6f4480ab4434716533d3947f27
Summary:
Add `experimental_mempurge_policy` option flag and introduce two new `MemPurge` (Memtable Garbage Collection) policies: 'ALWAYS' and 'ALTERNATE'. Default value: ALTERNATE.
`ALWAYS`: every flush will first go through a `MemPurge` process. If the output is too big to fit into a single memtable, then the mempurge is aborted and a regular flush process carries on. `ALWAYS` is designed for user that need to reduce the number of L0 SST file created to a strict minimum, and can afford a small dent in performance (possibly hits to CPU usage, read efficiency, and maximum burst write throughput).
`ALTERNATE`: a flush is transformed into a `MemPurge` except if one of the memtables being flushed is the product of a previous `MemPurge`. `ALTERNATE` is a good tradeoff between reduction in number of L0 SST files created and performance. `ALTERNATE` perform particularly well for completely random garbage ratios, or garbage ratios anywhere in (0%,50%], and even higher when there is a wild variability in garbage ratios.
This PR also includes support for `experimental_mempurge_policy` in `db_bench`.
Testing was done locally by replacing all the `MemPurge` policies of the unit tests with `ALTERNATE`, as well as local testing with `db_crashtest.py` `whitebox` and `blackbox`. Overall, if an `ALWAYS` mempurge policy passes the tests, there is no reasons why an `ALTERNATE` policy would fail, and therefore the mempurge policy was set to `ALWAYS` for all mempurge unit tests.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8583
Reviewed By: pdillinger
Differential Revision: D29888050
Pulled By: bjlemaire
fbshipit-source-id: e2cf26646d66679f6f5fb29842624615610759c1
Summary:
The main challenge to make the memtable garbage collection prototype (nicknamed `mempurge`) was to not get rid of WAL files that contain unflushed (but mempurged) data. That was successfully guaranteed by not writing the VersionEdit to the MANIFEST file after a successful mempurge.
By not writing VersionEdits to the `MANIFEST` file after a succesful mempurge operation, we do not change the earliest log file number that contains unflushed data: `cfd->GetLogNumber()` (`cfd->SetLogNumber()` is only called in `VersionSet::ProcessManifestWrites`). As a result, a number of functions introduced earlier just for the mempurge operation are not obscolete/redundant. (e.g.: `FlushJob::ExtractEarliestLogFileNumber`), and this PR aims at cleaning up all these now-unnecessary functions. In particular, we no longer need to store the earliest log file number in the `MemTable` struct itself. This PR therefore also reverts the `MemTable` struct to its original form.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8558
Test Plan: Already included in `db_flush_test.cc`.
Reviewed By: anand1976
Differential Revision: D29764351
Pulled By: bjlemaire
fbshipit-source-id: 0f43b260fa270251862512f397d3f24ee62e8437
Summary:
In this PR, `mempurge` is made compatible with the Write Ahead Log: in case of recovery, the DB is now capable of recovering the data that was "mempurged" and kept in the `imm()` list of immutable memtables.
The twist was to add a uint64_t to the `memtable` struct to store the number of the earliest log file containing entries from the `memtable`. When a `Flush` operation is replaced with a `MemPurge`, the `VersionEdit` (which usually contains the new min log file number to pick up for recovery and the level 0 file path of the newly created SST file) is no longer appended to the manifest log, and every time the `deleteWal` method is called, a check is made on the list of immutable memtables.
This PR also includes a unit test that verifies that no data is lost upon Reopening of the database when the mempurge feature is activated. This extensive unit test includes two column families, with valid data contained in the imm() at time of "crash"/reopening (recovery).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8528
Reviewed By: pdillinger
Differential Revision: D29701097
Pulled By: bjlemaire
fbshipit-source-id: 072a900fb6ccc1edcf5eef6caf88f3060238edf9
Summary:
Implement an experimental feature called "MemPurge", which consists in purging "garbage" bytes out of a memtable and reuse the memtable struct instead of making it immutable and eventually flushing its content to storage.
The prototype is by default deactivated and is not intended for use. It is intended for correctness and validation testing. At the moment, the "MemPurge" feature can be switched on by using the `options.experimental_allow_mempurge` flag. For this early stage, when the allow_mempurge flag is set to `true`, all the flush operations will be rerouted to perform a MemPurge. This is a temporary design decision that will give us the time to explore meaningful heuristics to use MemPurge at the right time for relevant workloads . Moreover, the current MemPurge operation only supports `Puts`, `Deletes`, `DeleteRange` operations, and handles `Iterators` as well as `CompactionFilter`s that are invoked at flush time .
Three unit tests are added to `db_flush_test.cc` to test if MemPurge works correctly (and checks that the previously mentioned operations are fully supported thoroughly tested).
One noticeable design decision is the timing of the MemPurge operation in the memtable workflow: for this prototype, the mempurge happens when the memtable is switched (and usually made immutable). This is an inefficient process because it implies that the entirety of the MemPurge operation happens while holding the db_mutex. Future commits will make the MemPurge operation a background task (akin to the regular flush operation) and aim at drastically enhancing the performance of this operation. The MemPurge is also not fully "WAL-compatible" yet, but when the WAL is full, or when the regular MemPurge operation fails (or when the purged memtable still needs to be flushed), a regular flush operation takes place. Later commits will also correct these behaviors.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8454
Reviewed By: anand1976
Differential Revision: D29433971
Pulled By: bjlemaire
fbshipit-source-id: 6af48213554e35048a7e03816955100a80a26dc5
Summary:
The ImmutableCFOptions contained a bunch of fields that belonged to the ImmutableDBOptions. This change cleans that up by introducing an ImmutableOptions struct. Following the pattern of Options struct, this class inherits from the DB and CFOption structs (of the Immutable form).
Only one structural change (the ImmutableCFOptions::fs was changed to a shared_ptr from a raw one) is in this PR. All of the other changes involve moving the member variables from the ImmutableCFOptions into the ImmutableOptions and changing member variables or function parameters as required for compilation purposes.
Follow-on PRs may do a further clean-up of the code, such as renaming variables (such as "ImmutableOptions cf_options") and potentially eliminating un-needed function parameters (there is no longer a need to pass both an ImmutableDBOptions and an ImmutableOptions to a function).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8262
Reviewed By: pdillinger
Differential Revision: D28226540
Pulled By: mrambacher
fbshipit-source-id: 18ae71eadc879dedbe38b1eb8e6f9ff5c7147dbf
Summary:
For performance purposes, the lower level routines were changed to use a SystemClock* instead of a std::shared_ptr<SystemClock>. The shared ptr has some performance degradation on certain hardware classes.
For most of the system, there is no risk of the pointer being deleted/invalid because the shared_ptr will be stored elsewhere. For example, the ImmutableDBOptions stores the Env which has a std::shared_ptr<SystemClock> in it. The SystemClock* within the ImmutableDBOptions is essentially a "short cut" to gain access to this constant resource.
There were a few classes (PeriodicWorkScheduler?) where the "short cut" property did not hold. In those cases, the shared pointer was preserved.
Using db_bench readrandom perf_level=3 on my EC2 box, this change performed as well or better than 6.17:
6.17: readrandom : 28.046 micros/op 854902 ops/sec; 61.3 MB/s (355999 of 355999 found)
6.18: readrandom : 32.615 micros/op 735306 ops/sec; 52.7 MB/s (290999 of 290999 found)
PR: readrandom : 27.500 micros/op 871909 ops/sec; 62.5 MB/s (367999 of 367999 found)
(Note that the times for 6.18 are prior to revert of the SystemClock).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8033
Reviewed By: pdillinger
Differential Revision: D27014563
Pulled By: mrambacher
fbshipit-source-id: ad0459eba03182e454391b5926bf5cdd45657b67
Summary:
This PR adds the foundation classes for key-value integrity protection and the first use case: protecting live updates from the source buffers added to `WriteBatch` through the destination buffer in `MemTable`. The width of the protection info is not yet configurable -- only eight bytes per key is supported. This PR allows users to enable protection by constructing `WriteBatch` with `protection_bytes_per_key == 8`. It does not yet expose a way for users to get integrity protection via other write APIs (e.g., `Put()`, `Merge()`, `Delete()`, etc.).
The foundation classes (`ProtectionInfo.*`) embed the coverage info in their type, and provide `Protect.*()` and `Strip.*()` functions to navigate between types with different coverage. For making bytes per key configurable (for powers of two up to eight) in the future, these classes are templated on the unsigned integer type used to store the protection info. That integer contains the XOR'd result of hashes with independent seeds for all covered fields. For integer fields, the hash is computed on the raw unadjusted bytes, so the result is endian-dependent. The most significant bytes are truncated when the hash value (8 bytes) is wider than the protection integer.
When `WriteBatch` is constructed with `protection_bytes_per_key == 8`, we hold a `ProtectionInfoKVOTC` (i.e., one that covers key, value, optype aka `ValueType`, timestamp, and CF ID) for each entry added to the batch. The protection info is generated from the original buffers passed by the user, as well as the original metadata generated internally. When writing to memtable, each entry is transformed to a `ProtectionInfoKVOTS` (i.e., dropping coverage of CF ID and adding coverage of sequence number), since at that point we know the sequence number, and have already selected a memtable corresponding to a particular CF. This protection info is verified once the entry is encoded in the `MemTable` buffer.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7748
Test Plan:
- an integration test to verify a wide variety of single-byte changes to the encoded `MemTable` buffer are caught
- add to stress/crash test to verify it works in variety of configs/operations without intentional corruption
- [deferred] unit tests for `ProtectionInfo.*` classes for edge cases like KV swap, `SliceParts` and `Slice` APIs are interchangeable, etc.
Reviewed By: pdillinger
Differential Revision: D25754492
Pulled By: ajkr
fbshipit-source-id: e481bac6c03c2ab268be41359730f1ceb9964866
Summary:
Introduces and uses a SystemClock class to RocksDB. This class contains the time-related functions of an Env and these functions can be redirected from the Env to the SystemClock.
Many of the places that used an Env (Timer, PerfStepTimer, RepeatableThread, RateLimiter, WriteController) for time-related functions have been changed to use SystemClock instead. There are likely more places that can be changed, but this is a start to show what can/should be done. Over time it would be nice to migrate most (if not all) of the uses of the time functions from the Env to the SystemClock.
There are several Env classes that implement these functions. Most of these have not been converted yet to SystemClock implementations; that will come in a subsequent PR. It would be good to unify many of the Mock Timer implementations, so that they behave similarly and be tested similarly (some override Sleep, some use a MockSleep, etc).
Additionally, this change will allow new methods to be introduced to the SystemClock (like https://github.com/facebook/rocksdb/issues/7101 WaitFor) in a consistent manner across a smaller number of classes.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7858
Reviewed By: pdillinger
Differential Revision: D26006406
Pulled By: mrambacher
fbshipit-source-id: ed10a8abbdab7ff2e23d69d85bd25b3e7e899e90
Summary:
The patch adds initial support for reading blobs to the batched `MultiGet` API.
The current implementation simply retrieves the blob values as the blob indexes
are encountered; that is, reads from blob files are currently not batched. (This
will be optimized in a separate phase.) In addition, the patch removes some dead
code related to BlobDB from the batched `MultiGet` implementation, namely the
`is_blob` / `is_blob_index` flags that are passed around in `DBImpl` and `MemTable` /
`MemTableListVersion`. These were never hooked up to anything and wouldn't
work anyways, since a single flag is not sufficient to communicate the "blobness"
of multiple key-values.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7766
Test Plan: `make check`
Reviewed By: jay-zhuang
Differential Revision: D25479290
Pulled By: ltamasi
fbshipit-source-id: 7aba2d290e31876ee592bcf1adfd1018713a8000
Summary:
This PR updates `MemTable::Add()`, `MemTable::Update()`, and
`MemTable::UpdateCallback()` to return `Status` objects, and adapts the
client code in `MemTableInserter`. The goal is to prepare these
functions for key-value checksum, where we want to verify key-value
integrity while adding to memtable. After this PR, the memtable mutation
functions can report a failed integrity check by returning `Status::Corruption`.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7656
Reviewed By: riversand963
Differential Revision: D24900497
Pulled By: ajkr
fbshipit-source-id: 1a7e80581e3774676f2bbba2f0a0b04890f40009
Summary:
Add a new Option "allow_data_in_errors". When it's set by users, it allows them to opt-in to get error messages containing corrupted keys/values. Corrupt keys, values will be logged in the messages, logs, status etc. that will help users with the useful information regarding affected data.
By default value is set false to prevent users data to be exposed in the messages.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7420
Test Plan:
1. make check -j64
2. Add a new test case
Reviewed By: ajkr
Differential Revision: D23835028
Pulled By: akankshamahajan15
fbshipit-source-id: 8d2eba8fb898e79fcf1fccc07295065a75eb59b1
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:
We have observed an increase in CPU load caused by frequent calls to
`ColumnFamilyData::InstallSuperVersion` from `DBImpl::TrimMemtableHistory`
when using `max_write_buffer_size_to_maintain` to limit the amount of
memtable history maintained for transaction conflict checking. Part of the issue
is that trimming can potentially be scheduled even if there is no memtable
history. The patch adds a check that fixes this.
See also https://github.com/facebook/rocksdb/pull/6169.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6177
Test Plan:
Compared `perf` output for
```
./db_bench -benchmarks=randomtransaction -optimistic_transaction_db=1 -statistics -stats_interval_seconds=1 -duration=90 -num=500000 --max_write_buffer_size_to_maintain=16000000 --transaction_set_snapshot=1 --threads=32
```
before and after the change. There is a significant reduction for the call chain
`rocksdb::DBImpl::TrimMemtableHistory` -> `rocksdb::ColumnFamilyData::InstallSuperVersion` ->
`rocksdb::ThreadLocalPtr::StaticMeta::Scrape` even without https://github.com/facebook/rocksdb/pull/6169.
Differential Revision: D19057445
Pulled By: ltamasi
fbshipit-source-id: dff81882d7b280e17eda7d9b072a2d4882c50f79
Summary:
When there are concurrent flush job on the same CF, `OnFlushCompleted` can be called before the flush result being install to LSM. Fixing the issue by passing `FlushJobInfo` through `MemTable`, and the thread who commit the flush result can fetch the `FlushJobInfo` and fire `OnFlushCompleted` on behave of the thread actually writing the SST.
Fix https://github.com/facebook/rocksdb/issues/5892
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5908
Test Plan: Add new test. The test will fail without the fix.
Differential Revision: D17916144
Pulled By: riversand963
fbshipit-source-id: e18df67d9533b5baee52ae3605026cdeb05cbe10
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:
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:
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:
Right now when a flush is triggered, the memory consumption is logged but data size is not.
It's useful to log both when we debug unexpected small flushed file size.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4979
Differential Revision: D14071979
Pulled By: siying
fbshipit-source-id: 0cd60449c5205eb00e0fbc299084418f609904ed
Summary:
as titled.
Since different bg flush threads can flush different sets of column families
(due to column family creation and drop), we decide not to let one thread
perform atomic flush result installation for other threads. Bg flush threads
will install their atomic flush results sequentially to MANIFEST, using
a conditional variable, i.e. atomic_flush_install_cv_ to coordinate.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4791
Differential Revision: D13498930
Pulled By: riversand963
fbshipit-source-id: dd7482fc41f4bd22dad1e1ef7d4764ef424688d7
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:
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:
Ran the following commands to recursively change all the files under RocksDB:
```
find . -type f -name "*.cc" -exec sed -i 's/ unique_ptr/ std::unique_ptr/g' {} +
find . -type f -name "*.cc" -exec sed -i 's/<unique_ptr/<std::unique_ptr/g' {} +
find . -type f -name "*.cc" -exec sed -i 's/ shared_ptr/ std::shared_ptr/g' {} +
find . -type f -name "*.cc" -exec sed -i 's/<shared_ptr/<std::shared_ptr/g' {} +
```
Running `make format` updated some formatting on the files touched.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4638
Differential Revision: D12934992
Pulled By: sagar0
fbshipit-source-id: 45a15d23c230cdd64c08f9c0243e5183934338a8
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:
Memtables are selected for flushing by the flush job. Currently we
have listener which is invoked when memtables for a column family are
flushed. That listener does not indicate which memtable was flushed in
the notification. If clients want to know if particular data in the
memtable was retired, there is no straight forward way to know this.
This method will help users who implement memtablerep factory and extend
interface for memtablerep, to know if the data in the memtable was
retired.
Another option that was tried, was to depend on memtable destructor to
be called after flush to mark that data was persisted. This works all
the time but sometimes there can huge delays between actual flush
happening and memtable getting destroyed. Hence, if anyone who is
waiting for data to persist will have to wait that longer.
It is expected that anyone who is implementing this method to have
return quickly as it blocks RocksDB.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4304
Reviewed By: riversand963
Differential Revision: D9472312
Pulled By: gdrane
fbshipit-source-id: 8e693308dee749586af3a4c5d4fcf1fa5276ea4d
Summary:
Given that index value is a BlockHandle, which is basically an <offset, size> pair we can apply delta encoding on the values. The first value at each index restart interval encoded the full BlockHandle but the rest encode only the size. Refer to IndexBlockIter::DecodeCurrentValue for the detail of the encoding. This reduces the index size which helps using the block cache more efficiently. The feature is enabled with using format_version 4.
The feature comes with a bit of cpu overhead which should be paid back by the higher cache hits due to smaller index block size.
Results with sysbench read-only using 4k blocks and using 16 index restart interval:
Format 2:
19585 rocksdb read-only range=100
Format 3:
19569 rocksdb read-only range=100
Format 4:
19352 rocksdb read-only range=100
Pull Request resolved: https://github.com/facebook/rocksdb/pull/3983
Differential Revision: D8361343
Pulled By: maysamyabandeh
fbshipit-source-id: f882ee082322acac32b0072e2bdbb0b5f854e651
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:
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:
Flush() call could be waiting indefinitely if min_write_buffer_number_to_merge is used. Consider the sequence:
1. User call Flush() with flush_options.wait = true
2. The manual flush started in the background
3. New memtable become immutable because of writes. The new memtable will not trigger flush if min_write_buffer_number_to_merge is not reached.
4. The manual flush finish.
Because of the new memtable created at step 3 not being flush, previous logic of WaitForFlushMemTable() keep waiting, despite the memtables it intent to flush has been flushed.
Here instead of checking if there are any more memtables to flush, WaitForFlushMemTable() also check the id of the earliest memtable. If the id is larger than that of latest memtable at the time flush was initiated, it means all the memtable at the time of flush start has all been flush.
Closes https://github.com/facebook/rocksdb/pull/3378
Differential Revision: D6746789
Pulled By: yiwu-arbug
fbshipit-source-id: 35e698f71c7f90b06337a93e6825f4ea3b619bfa
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
Changyu Bi