Summary:
The motivation for this change is a planned feature (related to HyperClockCache) that will depend on a large array that can essentially grow automatically, up to some bound, without the pointer address changing and with guaranteed zero-initialization of the data. Anonymous mmaps provide such functionality, and this change provides an internal API for that.
The other existing use of anonymous mmap in RocksDB is for allocating in huge pages. That code and other related Arena code used some awkward non-RAII and pre-C++11 idioms, so I cleaned up much of that as well, with RAII, move semantics, constexpr, etc.
More specifcs:
* Minimize conditional compilation
* Add Windows support for anonymous mmaps
* Use std::deque instead of std::vector for more efficient bag
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10810
Test Plan: unit test added for new functionality
Reviewed By: riversand963
Differential Revision: D40347204
Pulled By: pdillinger
fbshipit-source-id: ca83fcc47e50fabf7595069380edd2954f4f879c
Summary:
This should fix an import issue detected in meta internal tests.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10604
Test Plan: Unit Tests.
Reviewed By: hx235
Differential Revision: D39120414
Pulled By: gitbw95
fbshipit-source-id: dbd016d7f47b9f54aab5ea61e8d3cd79734f46af
Summary:
Timer has a limitation that it cannot re-register a task with the same name,
because the cancel only mark the task as invalid and wait for the Timer thread
to clean it up later, before the task is cleaned up, the same task name cannot
be added. Which makes the task option update likely to fail, which basically
cancel and re-register the same task name. Change the periodic task name to a
random unique id and store it in periodic_task_scheduler.
Also refactor the `periodic_work` to `periodic_task` to make each job function
as a `task`.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10379
Test Plan: unittests
Reviewed By: ajkr
Differential Revision: D38000615
Pulled By: jay-zhuang
fbshipit-source-id: e4135f9422e3b53aaec8eda54f4e18ce633a279e
Summary:
The patch introduces a new class called `BlobContents`, which represents
a single uncompressed blob value. We currently use `std::string` for this
purpose; `BlobContents` is somewhat smaller but the primary reason for a
dedicated class is that it enables certain improvements and optimizations
like eliding a copy when inserting a blob into the cache, using custom
allocators, or more control over and better accounting of the memory usage
of cached blobs (see https://github.com/facebook/rocksdb/issues/10484).
(We plan to implement these in subsequent PRs.)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10571
Test Plan: `make check`
Reviewed By: riversand963
Differential Revision: D39000965
Pulled By: ltamasi
fbshipit-source-id: f296eddf9dec4fc3e11cad525b462bdf63c78f96
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:
To help service owners to manage their memory budget effectively, we have been working towards counting all major memory users inside RocksDB towards a single global memory limit (see e.g. https://github.com/facebook/rocksdb/wiki/Write-Buffer-Manager#cost-memory-used-in-memtable-to-block-cache). The global limit is specified by the capacity of the block-based table's block cache, and is technically implemented by inserting dummy entries ("reservations") into the block cache. The goal of this task is to support charging the memory usage of the new blob cache against this global memory limit when the backing cache of the blob cache and the block cache are different.
This PR is a part of https://github.com/facebook/rocksdb/issues/10156
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10321
Reviewed By: ltamasi
Differential Revision: D37913590
Pulled By: gangliao
fbshipit-source-id: eaacf23907f82dc7d18964a3f24d7039a2937a72
Summary:
Which will be used for tiered storage to preclude hot data from
compacting to the cold tier (the last level).
Internally, adding seqno to time mapping. A periodic_task is scheduled
to record the current_seqno -> current_time in certain cadence. When
memtable flush, the mapping informaiton is stored in sstable property.
During compaction, the mapping information are merged and get the
approximate time of sequence number, which is used to determine if a key
is recently inserted or not and preclude it from the last level if it's
recently inserted (within the `preclude_last_level_data_seconds`).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10338
Test Plan: CI
Reviewed By: siying
Differential Revision: D37810187
Pulled By: jay-zhuang
fbshipit-source-id: 6953be7a18a99de8b1cb3b162d712f79c2b4899f
Summary:
Support per_key_placement for last level compaction, which will
be used for tiered compaction.
* compaction iterator reports which level a key should output to;
* compaction get the output level information and check if it's safe to
output the data to penultimate level;
* all compaction output files will be installed.
* extra internal compaction stats added for penultimate level.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9964
Test Plan:
* Unittest
* db_bench, no significate difference: https://gist.github.com/jay-zhuang/3645f8fb97ec0ab47c10704bb39fd6e4
* microbench manual compaction no significate difference: https://gist.github.com/jay-zhuang/ba679b3e89e24992615ee9eef310e6dd
* run the db_stress multiple times (not covering the new feature) looks good (internal: https://fburl.com/sandcastle/9w84pp2m)
Reviewed By: ajkr
Differential Revision: D36249494
Pulled By: jay-zhuang
fbshipit-source-id: a96da57c8031c1df83e4a7a8567b657a112b80a3
Summary:
The patch builds on https://github.com/facebook/rocksdb/pull/9915 and adds
a new API called `PutEntity` that can be used to write a wide-column entity
to the database. The new API is added to both `DB` and `WriteBatch`. Note
that currently there is no way to retrieve these entities; more precisely, all
read APIs (`Get`, `MultiGet`, and iterator) return `NotSupported` when they
encounter a wide-column entity that is required to answer a query. Read-side
support (as well as other missing functionality like `Merge`, compaction filter,
and timestamp support) will be added in later PRs.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10242
Test Plan: `make check`
Reviewed By: riversand963
Differential Revision: D37369748
Pulled By: ltamasi
fbshipit-source-id: 7f5e412359ed7a400fd80b897dae5599dbcd685d
Summary:
There is currently no caching mechanism for blobs, which is not ideal especially when the database resides on remote storage (where we cannot rely on the OS page cache). As part of this task, we would like to make it possible for the application to configure a blob cache.
In this task, we added a new abstraction layer `BlobSource` to retrieve blobs from either blob cache or raw blob file. Note: For simplicity, the current PR only includes `GetBlob()`. `MultiGetBlob()` will be included in the next PR.
This PR is a part of https://github.com/facebook/rocksdb/issues/10156
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10178
Reviewed By: ltamasi
Differential Revision: D37250507
Pulled By: gangliao
fbshipit-source-id: 3fc4a55a0cea955a3147bdc7dba06430e377259b
Summary:
folly DistributedMutex is faster than standard mutexes though
imposes some static obligations on usage. See
https://github.com/facebook/folly/blob/main/folly/synchronization/DistributedMutex.h
for details. Here we use this alternative for our Cache implementations
(especially LRUCache) for better locking performance, when RocksDB is
compiled with folly.
Also added information about which distributed mutex implementation is
being used to cache_bench output and to DB LOG.
Intended follow-up:
* Use DMutex in more places, perhaps improving API to support non-scoped
locking
* Fix linking with fbcode compiler (needs ROCKSDB_NO_FBCODE=1 currently)
Credit: Thanks Siying for reminding me about this line of work that was previously
left unfinished.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10179
Test Plan:
for correctness, existing tests. CircleCI config updated.
Also Meta-internal buck build updated.
For performance, ran simultaneous before & after cache_bench. Out of three
comparison runs, the middle improvement to ops/sec was +21%:
Baseline: USE_CLANG=1 DEBUG_LEVEL=0 make -j24 cache_bench (fbcode
compiler)
```
Complete in 20.201 s; Rough parallel ops/sec = 1584062
Thread ops/sec = 107176
Operation latency (ns):
Count: 32000000 Average: 9257.9421 StdDev: 122412.04
Min: 134 Median: 3623.0493 Max: 56918500
Percentiles: P50: 3623.05 P75: 10288.02 P99: 30219.35 P99.9: 683522.04 P99.99: 7302791.63
```
New: (add USE_FOLLY=1)
```
Complete in 16.674 s; Rough parallel ops/sec = 1919135 (+21%)
Thread ops/sec = 135487
Operation latency (ns):
Count: 32000000 Average: 7304.9294 StdDev: 108530.28
Min: 132 Median: 3777.6012 Max: 91030902
Percentiles: P50: 3777.60 P75: 10169.89 P99: 24504.51 P99.9: 59721.59 P99.99: 1861151.83
```
Reviewed By: anand1976
Differential Revision: D37182983
Pulled By: pdillinger
fbshipit-source-id: a17eb05f25b832b6a2c1356f5c657e831a5af8d1
Summary:
In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using
the public API, because of its inefficiency. Although we normally maintain read compatibility
on old DBs forever, filters are not required for reading a DB, only for optimizing read
performance. Thus, it should be acceptable to remove this code and the substantial
maintenance burden it carries as useful features are developed and validated (such
as user timestamp).
This change completely removes the code for reading and writing the old block-based
filters, net removing about 1370 lines of code no longer needed. Options removed from
testing / benchmarking tools. The prior existence is only evident in a couple of places:
* `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in
a major release to minimize source code incompatibilities.
* A warning is logged when an old table file is opened that used the old block-based
filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing
should suffice. Unfortunately, sst_dump does not tell you whether a file uses
block-based filter, and the structure of the code makes it very difficult to fix.
* To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`)
for metaindex is maintained (for now).
Other notes:
* In some cases where numbers are associated with filter configurations, we have had to
update the assigned numbers so that they all correspond to something that exists.
* Fixed potential stat counting bug by assuming `filter_checked = false` for cases
like `filter == nullptr` rather than assuming `filter_checked = true`
* Removed obsolete `block_offset` and `prefix_extractor` parameters from several
functions.
* Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)`
because the caller guarantees the prefix extractor exists and is compatible
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184
Test Plan:
tests updated, manually test new warning in LOG using base version to
generate a DB
Reviewed By: riversand963
Differential Revision: D37212647
Pulled By: pdillinger
fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80
Summary:
In RocksDB, keys are associated with (internal) sequence numbers which denote when the keys are written
to the database. Sequence numbers in different RocksDB instances are unrelated, thus not comparable.
It is nice if we can associate sequence numbers with their corresponding actual timestamps. One thing we can
do is to support user-defined timestamp, which allows the applications to specify the format of custom timestamps
and encode a timestamp with each key. More details can be found at https://github.com/facebook/rocksdb/wiki/User-defined-Timestamp-%28Experimental%29.
This PR provides a different but complementary approach. We can associate rocksdb snapshots (defined in
https://github.com/facebook/rocksdb/blob/7.2.fb/include/rocksdb/snapshot.h#L20) with **user-specified** timestamps.
Since a snapshot is essentially an object representing a sequence number, this PR establishes a bi-directional mapping between sequence numbers and timestamps.
In the past, snapshots are usually taken by readers. The current super-version is grabbed, and a `rocksdb::Snapshot`
object is created with the last published sequence number of the super-version. You can see that the reader actually
has no good idea of what timestamp to assign to this snapshot, because by the time the `GetSnapshot()` is called,
an arbitrarily long period of time may have already elapsed since the last write, which is when the last published
sequence number is written.
This observation motivates the creation of "timestamped" snapshots on the write path. Currently, this functionality is
exposed only to the layer of `TransactionDB`. Application can tell RocksDB to create a snapshot when a transaction
commits, effectively associating the last sequence number with a timestamp. It is also assumed that application will
ensure any two snapshots with timestamps should satisfy the following:
```
snapshot1.seq < snapshot2.seq iff. snapshot1.ts < snapshot2.ts
```
If the application can guarantee that when a reader takes a timestamped snapshot, there is no active writes going on
in the database, then we also allow the user to use a new API `TransactionDB::CreateTimestampedSnapshot()` to create
a snapshot with associated timestamp.
Code example
```cpp
// Create a timestamped snapshot when committing transaction.
txn->SetCommitTimestamp(100);
txn->SetSnapshotOnNextOperation();
txn->Commit();
// A wrapper API for convenience
Status Transaction::CommitAndTryCreateSnapshot(
std::shared_ptr<TransactionNotifier> notifier,
TxnTimestamp ts,
std::shared_ptr<const Snapshot>* ret);
// Create a timestamped snapshot if caller guarantees no concurrent writes
std::pair<Status, std::shared_ptr<const Snapshot>> snapshot = txn_db->CreateTimestampedSnapshot(100);
```
The snapshots created in this way will be managed by RocksDB with ref-counting and potentially shared with
other readers. We provide the following APIs for readers to retrieve a snapshot given a timestamp.
```cpp
// Return the timestamped snapshot correponding to given timestamp. If ts is
// kMaxTxnTimestamp, then we return the latest timestamped snapshot if present.
// Othersise, we return the snapshot whose timestamp is equal to `ts`. If no
// such snapshot exists, then we return null.
std::shared_ptr<const Snapshot> TransactionDB::GetTimestampedSnapshot(TxnTimestamp ts) const;
// Return the latest timestamped snapshot if present.
std::shared_ptr<const Snapshot> TransactionDB::GetLatestTimestampedSnapshot() const;
```
We also provide two additional APIs for stats collection and reporting purposes.
```cpp
Status TransactionDB::GetAllTimestampedSnapshots(
std::vector<std::shared_ptr<const Snapshot>>& snapshots) const;
// Return timestamped snapshots whose timestamps fall in [ts_lb, ts_ub) and store them in `snapshots`.
Status TransactionDB::GetTimestampedSnapshots(
TxnTimestamp ts_lb,
TxnTimestamp ts_ub,
std::vector<std::shared_ptr<const Snapshot>>& snapshots) const;
```
To prevent the number of timestamped snapshots from growing infinitely, we provide the following API to release
timestamped snapshots whose timestamps are older than or equal to a given threshold.
```cpp
void TransactionDB::ReleaseTimestampedSnapshotsOlderThan(TxnTimestamp ts);
```
Before shutdown, RocksDB will release all timestamped snapshots.
Comparison with user-defined timestamp and how they can be combined:
User-defined timestamp persists every key with a timestamp, while timestamped snapshots maintain a volatile
mapping between snapshots (sequence numbers) and timestamps.
Different internal keys with the same user key but different timestamps will be treated as different by compaction,
thus a newer version will not hide older versions (with smaller timestamps) unless they are eligible for garbage collection.
In contrast, taking a timestamped snapshot at a certain sequence number and timestamp prevents all the keys visible in
this snapshot from been dropped by compaction. Here, visible means (seq < snapshot and most recent).
The timestamped snapshot supports the semantics of reading at an exact point in time.
Timestamped snapshots can also be used with user-defined timestamp.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9879
Test Plan:
```
make check
TEST_TMPDIR=/dev/shm make crash_test_with_txn
```
Reviewed By: siying
Differential Revision: D35783919
Pulled By: riversand963
fbshipit-source-id: 586ad905e169189e19d3bfc0cb0177a7239d1bd4
Summary:
The patch adds some low-level logic that can be used to serialize/deserialize
a sorted vector of wide columns to/from a simple binary searchable string
representation. Currently, there is no user-facing API; this will be implemented in
subsequent stages.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9915
Test Plan: `make check`
Reviewed By: siying
Differential Revision: D35978076
Pulled By: ltamasi
fbshipit-source-id: 33f5f6628ec3bcd8c8beab363b1978ac047a8788
Summary:
This PR adds timestamp support to a read only DB instance opened as `DBImplReadOnly`. A follow up PR will add the same support to `CompactedDBImpl`.
With this, read only database has these timestamp related APIs:
`ReadOptions.timestamp` : read should return the latest data visible to this specified timestamp
`Iterator::timestamp()` : returns the timestamp associated with the key, value
`DB:Get(..., std::string* timestamp)` : returns the timestamp associated with the key, value in `timestamp`
Test plan (on devserver):
```
$COMPILE_WITH_ASAN=1 make -j24 all
$./db_with_timestamp_basic_test --gtest_filter=DBBasicTestWithTimestamp.ReadOnlyDB*
```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10004
Reviewed By: riversand963
Differential Revision: D36434422
Pulled By: jowlyzhang
fbshipit-source-id: 5d949e65b1ffb845758000e2b310fdd4aae71cfb
Summary:
This PR implements a coroutine version of batched MultiGet in order to concurrently read from multiple SST files in a level using async IO, thus reducing the latency of the MultiGet. The API from the user perspective is still synchronous and single threaded, with the RocksDB part of the processing happening in the context of the caller's thread. In Version::MultiGet, the decision is made whether to call synchronous or coroutine code.
A good way to review this PR is to review the first 4 commits in order - de773b3, 70c2f70, 10b50e1, and 377a597 - before reviewing the rest.
TODO:
1. Figure out how to build it in CircleCI (requires some dependencies to be installed)
2. Do some stress testing with coroutines enabled
No regression in synchronous MultiGet between this branch and main -
```
./db_bench -use_existing_db=true --db=/data/mysql/rocksdb/prefix_scan -benchmarks="readseq,multireadrandom" -key_size=32 -value_size=512 -num=5000000 -batch_size=64 -multiread_batched=true -use_direct_reads=false -duration=60 -ops_between_duration_checks=1 -readonly=true -adaptive_readahead=true -threads=16 -cache_size=10485760000 -async_io=false -multiread_stride=40000 -statistics
```
Branch - ```multireadrandom : 4.025 micros/op 3975111 ops/sec 60.001 seconds 238509056 operations; 2062.3 MB/s (14767808 of 14767808 found)```
Main - ```multireadrandom : 3.987 micros/op 4013216 ops/sec 60.001 seconds 240795392 operations; 2082.1 MB/s (15231040 of 15231040 found)```
More benchmarks in various scenarios are given below. The measurements were taken with ```async_io=false``` (no coroutines) and ```async_io=true``` (use coroutines). For an IO bound workload (with every key requiring an IO), the coroutines version shows a clear benefit, being ~2.6X faster. For CPU bound workloads, the coroutines version has ~6-15% higher CPU utilization, depending on how many keys overlap an SST file.
1. Single thread IO bound workload on remote storage with sparse MultiGet batch keys (~1 key overlap/file) -
No coroutines - ```multireadrandom : 831.774 micros/op 1202 ops/sec 60.001 seconds 72136 operations; 0.6 MB/s (72136 of 72136 found)```
Using coroutines - ```multireadrandom : 318.742 micros/op 3137 ops/sec 60.003 seconds 188248 operations; 1.6 MB/s (188248 of 188248 found)```
2. Single thread CPU bound workload (all data cached) with ~1 key overlap/file -
No coroutines - ```multireadrandom : 4.127 micros/op 242322 ops/sec 60.000 seconds 14539384 operations; 125.7 MB/s (14539384 of 14539384 found)```
Using coroutines - ```multireadrandom : 4.741 micros/op 210935 ops/sec 60.000 seconds 12656176 operations; 109.4 MB/s (12656176 of 12656176 found)```
3. Single thread CPU bound workload with ~2 key overlap/file -
No coroutines - ```multireadrandom : 3.717 micros/op 269000 ops/sec 60.000 seconds 16140024 operations; 139.6 MB/s (16140024 of 16140024 found)```
Using coroutines - ```multireadrandom : 4.146 micros/op 241204 ops/sec 60.000 seconds 14472296 operations; 125.1 MB/s (14472296 of 14472296 found)```
4. CPU bound multi-threaded (16 threads) with ~4 key overlap/file -
No coroutines - ```multireadrandom : 4.534 micros/op 3528792 ops/sec 60.000 seconds 211728728 operations; 1830.7 MB/s (12737024 of 12737024 found) ```
Using coroutines - ```multireadrandom : 4.872 micros/op 3283812 ops/sec 60.000 seconds 197030096 operations; 1703.6 MB/s (12548032 of 12548032 found) ```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9968
Reviewed By: akankshamahajan15
Differential Revision: D36348563
Pulled By: anand1976
fbshipit-source-id: c0ce85a505fd26ebfbb09786cbd7f25202038696
Summary:
To support a project to prototype and evaluate algorithmic
enhancments and alternatives to LRUCache, here I have separated out
LRUCache into internal-only "FastLRUCache" and cut it down to
essentials, so that details like secondary cache handling and
priorities do not interfere with prototyping. These can be
re-integrated later as needed, along with refactoring to minimize code
duplication (which would slow down prototyping for now).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9917
Test Plan:
unit tests updated to ensure basic functionality has (likely)
been preserved
Reviewed By: anand1976
Differential Revision: D35995554
Pulled By: pdillinger
fbshipit-source-id: d67b20b7ada3b5d3bfe56d897a73885894a1d9db
Summary:
When MultiGet() determines that multiple query keys can be
served by examining the same data block in block cache (one Lookup()),
each PinnableSlice referring to data in that data block needs to hold
on to the block in cache so that they can be released at arbitrary
times by the API user. Historically this is accomplished with extra
calls to Ref() on the Handle from Lookup(), with each PinnableSlice
cleanup calling Release() on the Handle, but this creates extra
contention on the block cache for the extra Ref()s and Release()es,
especially because they hit the same cache shard repeatedly.
In the case of merge operands (possibly more cases?), the problem was
compounded by doing an extra Ref()+eventual Release() for each merge
operand for a key reusing a block (which could be the same key!), rather
than one Ref() per key. (Note: the non-shared case with `biter` was
already one per key.)
This change optimizes MultiGet not to rely on these extra, contentious
Ref()+Release() calls by instead, in the shared block case, wrapping
the cache Release() cleanup in a refcounted object referenced by the
PinnableSlices, such that after the last wrapped reference is released,
the cache entry is Release()ed. Relaxed atomic refcounts should be
much faster than mutex-guarded Ref() and Release(), and much less prone
to a performance cliff when MultiGet() does a lot of block sharing.
Note that I did not use std::shared_ptr, because that would require an
extra indirection object (shared_ptr itself new/delete) in order to
associate a ref increment/decrement with a Cleanable cleanup entry. (If
I assumed it was the size of two pointers, I could do some hackery to
make it work without the extra indirection, but that's too fragile.)
Some details:
* Fixed (removed) extra block cache tracing entries in cases of cache
entry reuse in MultiGet, but it's likely that in some other cases traces
are missing (XXX comment inserted)
* Moved existing implementations for cleanable.h from iterator.cc to
new cleanable.cc
* Improved API comments on Cleanable
* Added a public SharedCleanablePtr class to cleanable.h in case others
could benefit from the same pattern (potentially many Cleanables and/or
smart pointers referencing a shared Cleanable)
* Add a typedef for MultiGetContext::Mask
* Some variable renaming for clarity
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9899
Test Plan:
Added unit tests for SharedCleanablePtr.
Greatly enhanced ability of existing tests to detect cache use-after-free.
* Release PinnableSlices from MultiGet as they are read rather than in
bulk (in db_test_util wrapper).
* In ASAN build, default to using a trivially small LRUCache for block_cache
so that entries are immediately erased when unreferenced. (Updated two
tests that depend on caching.) New ASAN testsuite running time seems
OK to me.
If I introduce a bug into my implementation where we skip the shared
cleanups on block reuse, ASAN detects the bug in
`db_basic_test *MultiGet*`. If I remove either of the above testing
enhancements, the bug is not detected.
Consider for follow-up work: manipulate or randomize ordering of
PinnableSlice use and release from MultiGet db_test_util wrapper. But in
typical cases, natural ordering gives pretty good functional coverage.
Performance test:
In the extreme (but possible) case of MultiGetting the same or adjacent keys
in a batch, throughput can improve by an order of magnitude.
`./db_bench -benchmarks=multireadrandom -db=/dev/shm/testdb -readonly -num=5 -duration=10 -threads=20 -multiread_batched -batch_size=200`
Before ops/sec, num=5: 1,384,394
Before ops/sec, num=500: 6,423,720
After ops/sec, num=500: 10,658,794
After ops/sec, num=5: 16,027,257
Also note that previously, with high parallelism, having query keys
concentrated in a single block was worse than spreading them out a bit. Now
concentrated in a single block is faster than spread out, which is hopefully
consistent with natural expectation.
Random query performance: with num=1000000, over 999 x 10s runs running before & after simultaneously (each -threads=12):
Before: multireadrandom [AVG 999 runs] : 1088699 (± 7344) ops/sec; 120.4 (± 0.8 ) MB/sec
After: multireadrandom [AVG 999 runs] : 1090402 (± 7230) ops/sec; 120.6 (± 0.8 ) MB/sec
Possibly better, possibly in the noise.
Reviewed By: anand1976
Differential Revision: D35907003
Pulled By: pdillinger
fbshipit-source-id: bbd244d703649a8ca12d476f2d03853ed9d1a17e
Summary:
Add a merge operator that allows users to register specific aggregation function so that they can does aggregation based per key using different aggregation types.
See comments of function CreateAggMergeOperator() for actual usage.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9780
Test Plan: Add a unit test to coverage various cases.
Reviewed By: ltamasi
Differential Revision: D35267444
fbshipit-source-id: 5b02f31c4f3e17e96dd4025cdc49fca8c2868628
Summary:
The P95 and P99 metrics are flaky, similar to DBGet ones which removed
in https://github.com/facebook/rocksdb/issues/9742 .
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9844
Test Plan: `$ ./buckifier/buckify_rocksdb.py`
Reviewed By: ajkr
Differential Revision: D35655531
Pulled By: jay-zhuang
fbshipit-source-id: c1409f0fba4e23d461a65f988c27ac5e2ae85d13
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:
Various renaming and fixes to get rid of remaining uses of
"backupable" which is terminology leftover from the original, flawed
design of BackupableDB. Now any DB can be backed up, using BackupEngine.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9792
Test Plan: CI
Reviewed By: ajkr
Differential Revision: D35334386
Pulled By: pdillinger
fbshipit-source-id: 2108a42b4575c8cccdfd791c549aae93ec2f3329
Summary:
DBGet p95 and p99 have high variation, remove them for now.
Also increase the iteration to 3 to avoid false positive.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9742
Test Plan: Internal CI
Reviewed By: ajkr
Differential Revision: D35082820
Pulled By: jay-zhuang
fbshipit-source-id: facc1d56b94e54aa8c8852c207aae2ae4e4924b0
Summary:
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9629
Pessimistic transactions use pessimistic concurrency control, i.e. locking. Keys are
locked upon first operation that writes the key or has the intention of writing. For example,
`PessimisticTransaction::Put()`, `PessimisticTransaction::Delete()`,
`PessimisticTransaction::SingleDelete()` will write to or delete a key, while
`PessimisticTransaction::GetForUpdate()` is used by application to indicate
to RocksDB that the transaction has the intention of performing write operation later
in the same transaction.
Pessimistic transactions support two-phase commit (2PC). A transaction can be
`Prepared()`'ed and then `Commit()`. The prepare phase is similar to a promise: once
`Prepare()` succeeds, the transaction has acquired the necessary resources to commit.
The resources include locks, persistence of WAL, etc.
Write-committed transaction is the default pessimistic transaction implementation. In
RocksDB write-committed transaction, `Prepare()` will write data to the WAL as a prepare
section. `Commit()` will write a commit marker to the WAL and then write data to the
memtables. While writing to the memtables, different keys in the transaction's write batch
will be assigned different sequence numbers in ascending order.
Until commit/rollback, the transaction holds locks on the keys so that no other transaction
can write to the same keys. Furthermore, the keys' sequence numbers represent the order
in which they are committed and should be made visible. This is convenient for us to
implement support for user-defined timestamps.
Since column families with and without timestamps can co-exist in the same database,
a transaction may or may not involve timestamps. Based on this observation, we add two
optional members to each `PessimisticTransaction`, `read_timestamp_` and
`commit_timestamp_`. If no key in the transaction's write batch has timestamp, then
setting these two variables do not have any effect. For the rest of this commit, we discuss
only the cases when these two variables are meaningful.
read_timestamp_ is used mainly for validation, and should be set before first call to
`GetForUpdate()`. Otherwise, the latter will return non-ok status. `GetForUpdate()` calls
`TryLock()` that can verify if another transaction has written the same key since
`read_timestamp_` till this call to `GetForUpdate()`. If another transaction has indeed
written the same key, then validation fails, and RocksDB allows this transaction to
refine `read_timestamp_` by increasing it. Note that a transaction can still use `Get()`
with a different timestamp to read, but the result of the read should not be used to
determine data that will be written later.
commit_timestamp_ must be set after finishing writing and before transaction commit.
This applies to both 2PC and non-2PC cases. In the case of 2PC, it's usually set after
prepare phase succeeds.
We currently require that the commit timestamp be chosen after all keys are locked. This
means we disallow the `TransactionDB`-level APIs if user-defined timestamp is used
by the transaction. Specifically, calling `PessimisticTransactionDB::Put()`,
`PessimisticTransactionDB::Delete()`, `PessimisticTransactionDB::SingleDelete()`,
etc. will return non-ok status because they specify timestamps before locking the keys.
Users are also prompted to use the `Transaction` APIs when they receive the non-ok status.
Reviewed By: ltamasi
Differential Revision: D31822445
fbshipit-source-id: b82abf8e230216dc89cc519564a588224a88fd43
Summary:
Implement a streaming compression API (compress/uncompress) to use for WAL compression. The log_writer would use the compress class/API to compress a record before writing it out in chunks. The log_reader would use the uncompress class/API to uncompress the chunks and combine into a single record.
Added unit test to verify the API for different sizes/compression types.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9619
Test Plan: make -j24 check
Reviewed By: anand1976
Differential Revision: D34437346
Pulled By: sidroyc
fbshipit-source-id: b180569ad2ddcf3106380f8758b556cc0ad18382
Summary:
**Summary:**
RocksDB uses a block cache to reduce IO and make queries more efficient. The block cache is based on the LRU algorithm (LRUCache) and keeps objects containing uncompressed data, such as Block, ParsedFullFilterBlock etc. It allows the user to configure a second level cache (rocksdb::SecondaryCache) to extend the primary block cache by holding items evicted from it. Some of the major RocksDB users, like MyRocks, use direct IO and would like to use a primary block cache for uncompressed data and a secondary cache for compressed data. The latter allows us to mitigate the loss of the Linux page cache due to direct IO.
This PR includes a concrete implementation of rocksdb::SecondaryCache that integrates with compression libraries such as LZ4 and implements an LRU cache to hold compressed blocks.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9518
Test Plan:
In this PR, the lru_secondary_cache_test.cc includes the following tests:
1. The unit tests for the secondary cache with either compression or no compression, such as basic tests, fails tests.
2. The integration tests with both primary cache and this secondary cache .
**Follow Up:**
1. Statistics (e.g. compression ratio) will be added in another PR.
2. Once this implementation is ready, I will do some shadow testing and benchmarking with UDB to measure the impact.
Reviewed By: anand1976
Differential Revision: D34430930
Pulled By: gitbw95
fbshipit-source-id: 218d78b672a2f914856d8a90ff32f2f5b5043ded
Summary:
Users can set the priority for file reads associated with their operation by setting `ReadOptions::rate_limiter_priority` to something other than `Env::IO_TOTAL`. Rate limiting `VerifyChecksum()` and `VerifyFileChecksums()` is the motivation for this PR, so it also includes benchmarks and minor bug fixes to get that working.
`RandomAccessFileReader::Read()` already had support for rate limiting compaction reads. I changed that rate limiting to be non-specific to compaction, but rather performed according to the passed in `Env::IOPriority`. Now the compaction read rate limiting is supported by setting `rate_limiter_priority = Env::IO_LOW` on its `ReadOptions`.
There is no default value for the new `Env::IOPriority` parameter to `RandomAccessFileReader::Read()`. That means this PR goes through all callers (in some cases multiple layers up the call stack) to find a `ReadOptions` to provide the priority. There are TODOs for cases I believe it would be good to let user control the priority some day (e.g., file footer reads), and no TODO in cases I believe it doesn't matter (e.g., trace file reads).
The API doc only lists the missing cases where a file read associated with a provided `ReadOptions` cannot be rate limited. For cases like file ingestion checksum calculation, there is no API to provide `ReadOptions` or `Env::IOPriority`, so I didn't count that as missing.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9424
Test Plan:
- new unit tests
- new benchmarks on ~50MB database with 1MB/s read rate limit and 100ms refill interval; verified with strace reads are chunked (at 0.1MB per chunk) and spaced roughly 100ms apart.
- setup command: `./db_bench -benchmarks=fillrandom,compact -db=/tmp/testdb -target_file_size_base=1048576 -disable_auto_compactions=true -file_checksum=true`
- benchmarks command: `strace -ttfe pread64 ./db_bench -benchmarks=verifychecksum,verifyfilechecksums -use_existing_db=true -db=/tmp/testdb -rate_limiter_bytes_per_sec=1048576 -rate_limit_bg_reads=1 -rate_limit_user_ops=true -file_checksum=true`
- crash test using IO_USER priority on non-validation reads with https://github.com/facebook/rocksdb/issues/9567 reverted: `python3 tools/db_crashtest.py blackbox --max_key=1000000 --write_buffer_size=524288 --target_file_size_base=524288 --level_compaction_dynamic_level_bytes=true --duration=3600 --rate_limit_bg_reads=true --rate_limit_user_ops=true --rate_limiter_bytes_per_sec=10485760 --interval=10`
Reviewed By: hx235
Differential Revision: D33747386
Pulled By: ajkr
fbshipit-source-id: a2d985e97912fba8c54763798e04f006ccc56e0c
Summary:
After https://github.com/facebook/rocksdb/issues/9515 added a unique_ptr to Status, we see some
warnings-as-error in some internal builds like this:
```
stderr: rocksdb/src/db/compaction/compaction_job.cc:2839:7: error:
offset of on non-standard-layout type 'struct CompactionServiceResult'
[-Werror,-Winvalid-offsetof]
{offsetof(struct CompactionServiceResult, status),
^ ~~~~~~
```
I see three potential solutions to resolving this:
* Expand our use of an idiom that works around the warning (see offset_of
functions removed in this change, inspired by
https://gist.github.com/graphitemaster/494f21190bb2c63c5516) However,
this construction is invoking undefined behavior that assumes consistent
layout with no compiler-introduced indirection. A compiler incompatible
with our assumptions will likely compile the code and exhibit undefined
behavior.
* Migrate to something in place of offset, like a function mapping
CompactionServiceResult* to Status* (for the `status` field). This might
be required in the long term.
* **Selected:** Use our new C++17 dependency to use offsetof in a well-defined way
when the compiler allows it. From a comment on
https://gist.github.com/graphitemaster/494f21190bb2c63c5516:
> A final note: in C++17, offsetof is conditionally supported, which
> means that you can use it on any type (not just standard layout
> types) and the compiler will error if it can't compile it correctly.
> That appears to be the best option if you can live with C++17 and
> don't need constexpr support.
The C++17 semantics are confirmed on
https://en.cppreference.com/w/cpp/types/offsetof, so we can suppress the
warning as long as we accept that we might run into a compiler that
rejects the code, and at that point we will find a solution, such as
the more intrusive "migrate" solution above.
Although this is currently only showing in our buck build, it will
surely show up also with make and cmake, so I have updated those
configurations as well.
Also in the buck build, -Wno-expansion-to-defined does not appear to be
needed anymore (both current compiler configurations) so I
removed it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9563
Test Plan: Tried out buck builds with both current compiler configurations
Reviewed By: riversand963
Differential Revision: D34220931
Pulled By: pdillinger
fbshipit-source-id: d39436008259bd1eaaa87c77be69fb2a5b559e1f
Summary:
Added a CountedFileSystem that tracks a number of file operations (opens, closes, deletes, renames, flushes, syncs, fsyncs, reads, writes). This class was based on the ReportFileOpEnv from db_bench.
This is a stepping stone PR to be able to change the SpecialEnv into a SpecialFileSystem, where several of the file varieties wish to do operation counting.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9283
Reviewed By: pdillinger
Differential Revision: D33062004
Pulled By: mrambacher
fbshipit-source-id: d0d297a7fb9c48c06cbf685e5fa755c27193b6f5
Summary:
Regexes are considered potentially problematic for use in
registering RocksDB extensions, so we are removing
ObjectLibrary::Register() and the Regex public API it depended on (now
unused).
In reference to https://github.com/facebook/rocksdb/issues/9389
Why?
* The power of Regexes can make it hard to reason about which extension
will match what. (The replacement API isn't perfect, but we are at least
"holding the line" on patterns we have seen in practice.)
* It is easy to make regexes that don't quite mean what you think they
mean, such as forgetting that the `.` in `foo.bar` can match any character
or that matching is nondeterministic, as in `a🅱️42` matching `.*:[0-9]+`.
* Some regexes and implementations can have disastrously bad
performance. This might not be much practical concern for ObjectLibray
here, but we don't want to encourage potentially dangerous further use
in production code. (Testing code is fine. See TestRegex.)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9439
Test Plan: CI
Reviewed By: mrambacher
Differential Revision: D33792342
Pulled By: pdillinger
fbshipit-source-id: 4f64dcb04764e639162c8977a5fa196f67754cec
Summary:
This PR moves HDFS support from RocksDB repo to a separate repo. The new (temporary?) repo
in this PR serves as an example before we finalize the decision on where and who to host hdfs support. At this point,
people can start from the example repo and fork.
Java/JNI is not included yet, and needs to be done later if necessary.
The goal is to include this commit in RocksDB 7.0 release.
Reference:
https://github.com/ajkr/dedupfs by ajkr
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9170
Test Plan:
Follow the instructions in https://github.com/riversand963/rocksdb-hdfs-env/blob/master/README.md. Build and run db_bench and db_stress.
make check
Reviewed By: ajkr
Differential Revision: D33751662
Pulled By: riversand963
fbshipit-source-id: 22b4db7f31762ed417a20239f5a08dcd1696244f
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:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).
The goal is a really fast cache key with practically ideal stability and
uniqueness properties without external dependencies (e.g. from FileSystem).
A fixed key size of 16 bytes should enable future optimizations to the
concurrent hash table for block cache, which is a heavy CPU user /
bottleneck, but there appears to be measurable performance improvement
even with no changes to LRUCache.
This change replaces a lot of disjointed and ugly code handling cache
keys with calls to a simple, clean new internal API (cache_key.h).
(Preserving the old cache key logic under an option would be very ugly
and likely negate the performance gain of the new approach. Complete
replacement carries some inherent risk, but I think that's acceptable
with sufficient analysis and testing.)
The scheme for encoding new cache keys is complicated but explained
in cache_key.cc.
Also: EndianSwapValue is moved to math.h to be next to other bit
operations. (Explains some new include "math.h".) ReverseBits operation
added and unit tests added to hash_test for both.
Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126
Test Plan:
### Basic correctness
Several tests needed updates to work with the new functionality, mostly
because we are no longer relying on filesystem for stable cache keys
so table builders & readers need more context info to agree on cache
keys. This functionality is so core, a huge number of existing tests
exercise the cache key functionality.
### Performance
Create db with
`TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters`
And test performance with
`TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4`
using DEBUG_LEVEL=0 and simultaneous before & after runs.
Before ops/sec, avg over 100 runs: 121924
After ops/sec, avg over 100 runs: 125385 (+2.8%)
### Collision probability
I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity
over many months, by making some pessimistic simplifying assumptions:
* Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys)
* All of every file is cached for its entire lifetime
We use a simple table with skewed address assignment and replacement on address collision
to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output
with `./cache_bench -stress_cache_key -sck_keep_bits=40`:
```
Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day
Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached)
```
These come from default settings of 2.5M files per day of 32 MB each, and
`-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of
the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation
is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality.
More default assumptions, relatively pessimistic:
* 100 DBs in same process (doesn't matter much)
* Re-open DB in same process (new session ID related to old session ID) on average
every 100 files generated
* Restart process (all new session IDs unrelated to old) 24 times per day
After enough data, we get a result at the end:
```
(keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected)
```
If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data:
```
(keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected)
(keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected)
```
The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases:
```
197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected)
```
I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data.
Reviewed By: zhichao-cao
Differential Revision: D33171746
Pulled By: pdillinger
fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
Summary:
Current db_stress does not cover complex read-write transactions. Therefore, this PR adds
coverage for emulated MyRocks-style transactions in `MultiOpsTxnsStressTest`. To achieve this, we need:
- Add a new operation type 'customops' so that we can add new complex groups of operations, e.g. transactions involving multiple read-write operations.
- Implement three read-write transactions and two read-only ones to emulate MyRocks-style transactions.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8936
Test Plan:
```
make check
./db_stress -test_multi_ops_txns -use_txn -clear_column_family_one_in=0 -column_families=1 -writepercent=0 -delpercent=0 -delrangepercent=0 -customopspercent=60 -readpercent=20 -prefixpercent=0 -iterpercent=20 -reopen=0 -ops_per_thread=100000
```
Next step is to add more configurability and refine input generation and result reporting, which will done in separate follow-up PRs.
Reviewed By: zhichao-cao
Differential Revision: D31071795
Pulled By: riversand963
fbshipit-source-id: 50d7c828346ec643311336b904848a1588a37006
Summary:
The `Statistics` objects are meant to be shared across translation
units, but this was prevented by declaring them static. We need to
ensure they are defined once in the program. The effect is now
`StressTest::PrintStatistics()` can actually print statistics since it
now sees non-null values when `--statistics=1`.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9260
Reviewed By: zhichao-cao
Differential Revision: D32910162
Pulled By: ajkr
fbshipit-source-id: c926d6f556177987bee5fa3cbc87597803b230ee
Summary:
The patch adds a new BlobDB configuration option `blob_compaction_readahead_size`
that can be used to enable prefetching data from blob files during compaction.
This is important when using storage with higher latencies like HDDs or remote filesystems.
If enabled, prefetching is used for all cases when blobs are read during compaction,
namely garbage collection, compaction filters (when the existing value has to be read from
a blob file), and `Merge` (when the value of the base `Put` is stored in a blob file).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9187
Test Plan: Ran `make check` and the stress/crash test.
Reviewed By: riversand963
Differential Revision: D32565512
Pulled By: ltamasi
fbshipit-source-id: 87be9cebc3aa01cc227bec6b5f64d827b8164f5d
Summary:
* New public header unique_id.h and function GetUniqueIdFromTableProperties
which computes a universally unique identifier based on table properties
of table files from recent RocksDB versions.
* Generation of DB session IDs is refactored so that they are
guaranteed unique in the lifetime of a process running RocksDB.
(SemiStructuredUniqueIdGen, new test included.) Along with file numbers,
this enables SST unique IDs to be guaranteed unique among SSTs generated
in a single process, and "better than random" between processes.
See https://github.com/pdillinger/unique_id
* In addition to public API producing 'external' unique IDs, there is a function
for producing 'internal' unique IDs, with functions for converting between the
two. In short, the external ID is "safe" for things people might do with it, and
the internal ID enables more "power user" features for the future. Specifically,
the external ID goes through a hashing layer so that any subset of bits in the
external ID can be used as a hash of the full ID, while also preserving
uniqueness guarantees in the first 128 bits (bijective both on first 128 bits
and on full 192 bits).
Intended follow-up:
* Use the internal unique IDs in cache keys. (Avoid conflicts with https://github.com/facebook/rocksdb/issues/8912) (The file offset can be XORed into
the third 64-bit value of the unique ID.)
* Publish the external unique IDs in FileStorageInfo (https://github.com/facebook/rocksdb/issues/8968)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8990
Test Plan:
Unit tests added, and checking of unique ids in stress test.
NOTE in stress test we do not generate nearly enough files to thoroughly
stress uniqueness, but the test trims off pieces of the ID to check for
uniqueness so that we can infer (with some assumptions) stronger
properties in the aggregate.
Reviewed By: zhichao-cao, mrambacher
Differential Revision: D31582865
Pulled By: pdillinger
fbshipit-source-id: 1f620c4c86af9abe2a8d177b9ccf2ad2b9f48243
Summary:
Background: Cache warming up will cause potential read performance degradation due to reading blocks from storage to the block cache. Since in production, the workload and access pattern to a certain DB is stable, it is a potential solution to dump out the blocks belonging to a certain DB to persist storage (e.g., to a file) and bulk-load the blocks to Secondary cache before the DB is relaunched. For example, when migrating a DB form host A to host B, it will take a short period of time, the access pattern to blocks in the block cache will not change much. It is efficient to dump out the blocks of certain DB, migrate to the destination host and insert them to the Secondary cache before we relaunch the DB.
Design: we introduce the interface of CacheDumpWriter and CacheDumpRead for user to store the blocks dumped out from block cache. RocksDB will encode all the information and send the string to the writer. User can implement their own writer it they want. CacheDumper and CacheLoad are introduced to save the blocks and load the blocks respectively.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8912
Test Plan: add new tests to lru_cache_test and pass make check.
Reviewed By: pdillinger
Differential Revision: D31452871
Pulled By: zhichao-cao
fbshipit-source-id: 11ab4f5d03e383f476947116361d54188d36ec48
Summary:
This is a precursor refactoring to enable an upcoming feature: persistence failure correctness testing.
- Changed `--expected_values_path` to `--expected_values_dir` and migrated "db_crashtest.py" to use the new flag. For persistence failure correctness testing there are multiple possible correct states since unsynced data is allowed to be dropped. Making it possible to restore all these possible correct states will eventually involve files containing snapshots of expected values and DB trace files.
- The expected values directory is managed by an `ExpectedStateManager` instance. Managing expected state files is separated out of `SharedState` to prevent `SharedState` from becoming too complex when the new files and features (snapshotting, tracing, and restoring) are introduced.
- Migrated expected values file access/management out of `SharedState` into a separate class called `ExpectedState`. This is not exposed directly to the test but rather the `ExpectedState` for the latest values file is accessed via a pass-through API on `ExpectedStateManager`. This forces the test to always access the single latest `ExpectedState`.
- Changed the initialization of the latest expected values file to use a tempfile followed by rename, and also add cleanup logic for possible stranded tempfiles.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8913
Test Plan:
run in several ways; try to make sure it's not obviously broken.
- crashtest blackbox without TEST_TMPDIR
```
$ python3 tools/db_crashtest.py blackbox --simple --write_buffer_size=1048576 --target_file_size_base=1048576 --max_bytes_for_level_base=4194304 --max_key=100000 --value_size_mult=33 --compression_type=none --duration=120 --interval=10 --compression_type=none --blob_compression_type=none
```
- crashtest blackbox with TEST_TMPDIR
```
$ TEST_TMPDIR=/dev/shm python3 tools/db_crashtest.py blackbox --simple --write_buffer_size=1048576 --target_file_size_base=1048576 --max_bytes_for_level_base=4194304 --max_key=100000 --value_size_mult=33 --compression_type=none --duration=120 --interval=10 --compression_type=none --blob_compression_type=none
```
- crashtest whitebox with TEST_TMPDIR
```
$ TEST_TMPDIR=/dev/shm python3 tools/db_crashtest.py whitebox --simple --write_buffer_size=1048576 --target_file_size_base=1048576 --max_bytes_for_level_base=4194304 --max_key=100000 --value_size_mult=33 --compression_type=none --duration=120 --interval=10 --compression_type=none --blob_compression_type=none --random_kill_odd=88887
```
- db_stress without expected_values_dir
```
$ ./db_stress --write_buffer_size=1048576 --target_file_size_base=1048576 --max_bytes_for_level_base=4194304 --max_key=100000 --value_size_mult=33 --compression_type=none --ops_per_thread=10000 --clear_column_family_one_in=0 --destroy_db_initially=true
```
- db_stress with expected_values_dir and manual corruption
```
$ ./db_stress --write_buffer_size=1048576 --target_file_size_base=1048576 --max_bytes_for_level_base=4194304 --max_key=100000 --value_size_mult=33 --compression_type=none --ops_per_thread=10000 --clear_column_family_one_in=0 --destroy_db_initially=true --expected_values_dir=./
// modify one byte in "./LATEST.state"
$ ./db_stress --write_buffer_size=1048576 --target_file_size_base=1048576 --max_bytes_for_level_base=4194304 --max_key=100000 --value_size_mult=33 --compression_type=none --ops_per_thread=10000 --clear_column_family_one_in=0 --destroy_db_initially=false --expected_values_dir=./
...
Verification failed for column family 0 key 0000000000000000 (0): Value not found: NotFound:
...
```
Reviewed By: riversand963
Differential Revision: D30921951
Pulled By: ajkr
fbshipit-source-id: babfe218062e55d018c9b046536c0289fb78f41c
Peter Dillinger