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:
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:
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:
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
Summary:
* Consolidate use of std::regex for testing to testharness.cc, to
minimize Facebook linters constantly flagging uses in non-production
code.
* Improve syntax and error messages for asserting some string matches a
regex in tests.
* Add a public Regex wrapper class to encapsulate existing usage in
ObjectRegistry.
* Remove unnecessary include <regex>
* Put warnings that use of Regex in production code could cause bad
performance or stack overflow.
Intended follow-up work:
* Replace std::regex with another underlying implementation like RE2
* Improve ObjectRegistry interface in terms of possibly confusing literal
string matching vs. regex and in terms of reporting invalid regex.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8740
Test Plan:
tests updated, basic unit test for public Regex, and some manual
testing of temporary changes to see example error messages:
utilities/backupable/backupable_db_test.cc:917: Failure
000010_1162373755_138626.blob (child.name)
does not match regex
[0-9]+_[0-9]+_[0-9]+[.]blobHAHAHA (pattern)
db/db_basic_test.cc:74: Failure
R3SHSBA8C4U0CIMV2ZB0 (sid3)
does not match regex [0-9A-Z]{20}HAHAHA
Reviewed By: mrambacher
Differential Revision: D30706246
Pulled By: pdillinger
fbshipit-source-id: ba845e8f563ccad39bdb58f44f04e9da8f78c3fd
Summary:
Env::GenerateUniqueId() works fine on Windows and on POSIX
where /proc/sys/kernel/random/uuid exists. Our other implementation is
flawed and easily produces collision in a new multi-threaded test.
As we rely more heavily on DB session ID uniqueness, this becomes a
serious issue.
This change combines several individually suitable entropy sources
for reliable generation of random unique IDs, with goal of uniqueness
and portability, not cryptographic strength nor maximum speed.
Specifically:
* Moves code for getting UUIDs from the OS to port::GenerateRfcUuid
rather than in Env implementation details. Callers are now told whether
the operation fails or succeeds.
* Adds an internal API GenerateRawUniqueId for generating high-quality
128-bit unique identifiers, by combining entropy from three "tracks":
* Lots of info from default Env like time, process id, and hostname.
* std::random_device
* port::GenerateRfcUuid (when working)
* Built-in implementations of Env::GenerateUniqueId() will now always
produce an RFC 4122 UUID string, either from platform-specific API or
by converting the output of GenerateRawUniqueId.
DB session IDs now use GenerateRawUniqueId while DB IDs (not as
critical) try to use port::GenerateRfcUuid but fall back on
GenerateRawUniqueId with conversion to an RFC 4122 UUID.
GenerateRawUniqueId is declared and defined under env/ rather than util/
or even port/ because of the Env dependency.
Likely follow-up: enhance GenerateRawUniqueId to be faster after the
first call and to guarantee uniqueness within the lifetime of a single
process (imparting the same property onto DB session IDs).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8708
Test Plan:
A new mini-stress test in env_test checks the various public
and internal APIs for uniqueness, including each track of
GenerateRawUniqueId individually. We can't hope to verify anywhere close
to 128 bits of entropy, but it can at least detect flaws as bad as the
old code. Serial execution of the new tests takes about 350 ms on
my machine.
Reviewed By: zhichao-cao, mrambacher
Differential Revision: D30563780
Pulled By: pdillinger
fbshipit-source-id: de4c9ff4b2f581cf784fcedb5f39f16e5185c364
Summary:
Context:
To help cap various memory usage by a single limit of the block cache capacity, we charge the memory usage through inserting/releasing dummy entries in the block cache. CacheReservationManager is such a class (non thread-safe) responsible for inserting/removing dummy entries to reserve cache space for memory used by the class user.
- Refactored the inner private class CacheRep of WriteBufferManager into public CacheReservationManager class for reusability such as for https://github.com/facebook/rocksdb/pull/8428
- Encapsulated implementation details of cache key generation and dummy entries insertion/release in cache reservation as discussed in https://github.com/facebook/rocksdb/pull/8506#discussion_r666550838
- Consolidated increase/decrease cache reservation into one API - UpdateCacheReservation.
- Adjusted the previous dummy entry release algorithm in decreasing cache reservation to be loop-releasing dummy entries to stay symmetric to dummy entry insertion algorithm
- Made the previous dummy entry release algorithm in delayed decrease mode more aggressive for better decreasing cache reservation when memory used is less likely to increase back.
Previously, the algorithms only release 1 dummy entries when new_mem_used < 3/4 * cache_allocated_size_ and cache_allocated_size_ - kSizeDummyEntry > new_mem_used.
Now, the algorithms loop-releases as many dummy entries as possible when new_mem_used < 3/4 * cache_allocated_size_.
- Updated WriteBufferManager's test cases to adapt to changes on the release algorithm mentioned above and left comment for some test cases for clarity
- Replaced the previous cache key prefix generation (utilizing object address related to the cache client) with one that utilizes Cache->NewID() to prevent cache-key collision among dummy entry clients sharing the same cache.
The specific collision we are preventing happens when the object address is reused for a new cache-key prefix while the old cache-key using that same object address in its prefix still exists in the cache. This could happen due to that, under LRU cache policy, there is a possible delay in releasing a cache entry after the cache client object owning that cache entry get deallocated. In this case, the object address related to the cache client object can get reused for other client object to generate a new cache-key prefix.
This prefix generation can be made obsolete after Peter's unification of all the code generating cache key, mentioned in https://github.com/facebook/rocksdb/pull/8506#discussion_r667265255
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8506
Test Plan:
- Passing the added unit tests cache_reservation_manager_test.cc
- Passing existing and adjusted write_buffer_manager_test.cc
Reviewed By: ajkr
Differential Revision: D29644135
Pulled By: hx235
fbshipit-source-id: 0fc93fbfe4a40bb41be85c314f8f2bafa8b741f7
Summary:
`Replayer::Execute()` can directly returns the result (e.g, request latency, DB::Get() return code, returned value, etc.)
`Replayer::Replay()` reports the results via a callback function.
New interface:
`TraceRecordResult` in "rocksdb/trace_record_result.h".
`DBTest2.TraceAndReplay` and `DBTest2.TraceAndManualReplay` are updated accordingly.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8657
Reviewed By: ajkr
Differential Revision: D30290216
Pulled By: autopear
fbshipit-source-id: 3c8d4e6b180ec743de1a9d9dcaee86064c74f0d6
Summary:
New public interfaces:
`TraceRecord` and `TraceRecord::Handler`, available in "rocksdb/trace_record.h".
`Replayer`, available in `rocksdb/utilities/replayer.h`.
User can use `DB::NewDefaultReplayer()` to create a Replayer to auto/manual replay a trace file.
Unit tests:
- `./db_test2 --gtest_filter="DBTest2.TraceAndReplay"`: Updated with the internal API changes.
- `./db_test2 --gtest_filter="DBTest2.TraceAndManualReplay"`: New for manual replay.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8611
Reviewed By: ajkr
Differential Revision: D30266329
Pulled By: autopear
fbshipit-source-id: 1ecb3cbbedae0f6a67c18f0cc82e002b4d81b6f8
Summary:
- Changed MergeOperator, CompactionFilter, and CompactionFilterFactory into Customizable classes.
- Added Options/Configurable/Object Registration for TTL and Cassandra variants
- Changed the StringAppend MergeOperators to accept a string delimiter rather than a simple char. Made the delimiter into a configurable option
- Added tests for new functionality
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8481
Reviewed By: zhichao-cao
Differential Revision: D30136050
Pulled By: mrambacher
fbshipit-source-id: 271d1772835935b6773abaf018ee71e42f9491af
Summary:
Add google benchmark for microbench.
Add ribbon_bench for benchmark ribbon filter vs. other filters.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8493
Test Plan:
added test to CI
To run the benchmark on devhost:
Install benchmark: `$ sudo dnf install google-benchmark-devel`
Build and run:
`$ ROCKSDB_NO_FBCODE=1 DEBUG_LEVEL=0 make microbench`
or with cmake:
`$ mkdir build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release -DWITH_BENCHMARK=1 && make microbench`
Reviewed By: pdillinger
Differential Revision: D29589649
Pulled By: jay-zhuang
fbshipit-source-id: 8fed13b562bef4472f161ecacec1ab6b18911dff
Summary:
Follow-up to https://github.com/facebook/rocksdb/issues/8426 .
The patch adds a new kind of `InternalIterator` that wraps another one and
passes each key-value encountered to `BlobGarbageMeter` as inflow.
This iterator will be used as an input iterator for compactions when the input
SSTs reference blob files.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8443
Test Plan: `make check`
Reviewed By: jay-zhuang
Differential Revision: D29311987
Pulled By: ltamasi
fbshipit-source-id: b4493b4c0c0c2e3c2ecc33c8969a5ef02de5d9d8
Summary:
This is part of an alternative approach to https://github.com/facebook/rocksdb/issues/8316.
Unlike that approach, this one relies on key-values getting processed one by one
during compaction, and does not involve persistence.
Specifically, the patch adds a class `BlobGarbageMeter` that can track the number
and total size of blobs in a (sub)compaction's input and output on a per-blob file
basis. This information can then be used to compute the amount of additional
garbage generated by the compaction for any given blob file by subtracting the
"outflow" from the "inflow."
Note: this patch only adds `BlobGarbageMeter` and associated unit tests. I plan to
hook up this class to the input and output of `CompactionIterator` in a subsequent PR.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8426
Test Plan: `make check`
Reviewed By: jay-zhuang
Differential Revision: D29242250
Pulled By: ltamasi
fbshipit-source-id: 597e50ad556540e413a50e804ba15bc044d809bb
Summary:
This PR add support for Merge operation in Integrated BlobDB with base values(i.e DB::Put). Merged values can be retrieved through DB::Get, DB::MultiGet, DB::GetMergeOperands and Iterator operation.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8292
Test Plan: Add new unit tests
Reviewed By: ltamasi
Differential Revision: D28415896
Pulled By: akankshamahajan15
fbshipit-source-id: e9b3478bef51d2f214fb88c31ed3c8d2f4a531ff
Summary:
Logically, subcompactions process a key range [start, end); however, the way
this is currently implemented is that the `CompactionIterator` for any given
subcompaction keeps processing key-values until it actually outputs a key that
is out of range, which is then discarded. Instead of doing this, the patch
introduces a new type of internal iterator called `ClippingIterator` which wraps
another internal iterator and "clips" its range of key-values so that any KVs
returned are strictly in the [start, end) interval. This does eliminate a (minor)
inefficiency by stopping processing in subcompactions exactly at the limit;
however, the main motivation is related to BlobDB: namely, we need this to be
able to measure the amount of garbage generated by a subcompaction
precisely and prevent off-by-one errors.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8327
Test Plan: `make check`
Reviewed By: siying
Differential Revision: D28761541
Pulled By: ltamasi
fbshipit-source-id: ee0e7229f04edabbc7bed5adb51771fbdc287f69
Summary:
This change gathers and publishes statistics about the
kinds of items in block cache. This is especially important for
profiling relative usage of cache by index vs. filter vs. data blocks.
It works by iterating over the cache during periodic stats dump
(InternalStats, stats_dump_period_sec) or on demand when
DB::Get(Map)Property(kBlockCacheEntryStats), except that for
efficiency and sharing among column families, saved data from
the last scan is used when the data is not considered too old.
The new information can be seen in info LOG, for example:
Block cache LRUCache@0x7fca62229330 capacity: 95.37 MB collections: 8 last_copies: 0 last_secs: 0.00178 secs_since: 0
Block cache entry stats(count,size,portion): DataBlock(7092,28.24 MB,29.6136%) FilterBlock(215,867.90 KB,0.888728%) FilterMetaBlock(2,5.31 KB,0.00544%) IndexBlock(217,180.11 KB,0.184432%) WriteBuffer(1,256.00 KB,0.262144%) Misc(1,0.00 KB,0%)
And also through DB::GetProperty and GetMapProperty (here using
ldb just for demonstration):
$ ./ldb --db=/dev/shm/dbbench/ get_property rocksdb.block-cache-entry-stats
rocksdb.block-cache-entry-stats.bytes.data-block: 0
rocksdb.block-cache-entry-stats.bytes.deprecated-filter-block: 0
rocksdb.block-cache-entry-stats.bytes.filter-block: 0
rocksdb.block-cache-entry-stats.bytes.filter-meta-block: 0
rocksdb.block-cache-entry-stats.bytes.index-block: 178992
rocksdb.block-cache-entry-stats.bytes.misc: 0
rocksdb.block-cache-entry-stats.bytes.other-block: 0
rocksdb.block-cache-entry-stats.bytes.write-buffer: 0
rocksdb.block-cache-entry-stats.capacity: 8388608
rocksdb.block-cache-entry-stats.count.data-block: 0
rocksdb.block-cache-entry-stats.count.deprecated-filter-block: 0
rocksdb.block-cache-entry-stats.count.filter-block: 0
rocksdb.block-cache-entry-stats.count.filter-meta-block: 0
rocksdb.block-cache-entry-stats.count.index-block: 215
rocksdb.block-cache-entry-stats.count.misc: 1
rocksdb.block-cache-entry-stats.count.other-block: 0
rocksdb.block-cache-entry-stats.count.write-buffer: 0
rocksdb.block-cache-entry-stats.id: LRUCache@0x7f3636661290
rocksdb.block-cache-entry-stats.percent.data-block: 0.000000
rocksdb.block-cache-entry-stats.percent.deprecated-filter-block: 0.000000
rocksdb.block-cache-entry-stats.percent.filter-block: 0.000000
rocksdb.block-cache-entry-stats.percent.filter-meta-block: 0.000000
rocksdb.block-cache-entry-stats.percent.index-block: 2.133751
rocksdb.block-cache-entry-stats.percent.misc: 0.000000
rocksdb.block-cache-entry-stats.percent.other-block: 0.000000
rocksdb.block-cache-entry-stats.percent.write-buffer: 0.000000
rocksdb.block-cache-entry-stats.secs_for_last_collection: 0.000052
rocksdb.block-cache-entry-stats.secs_since_last_collection: 0
Solution detail - We need some way to flag what kind of blocks each
entry belongs to, preferably without changing the Cache API.
One of the complications is that Cache is a general interface that could
have other users that don't adhere to whichever convention we decide
on for keys and values. Or we would pay for an extra field in the Handle
that would only be used for this purpose.
This change uses a back-door approach, the deleter, to indicate the
"role" of a Cache entry (in addition to the value type, implicitly).
This has the added benefit of ensuring proper code origin whenever we
recognize a particular role for a cache entry; if the entry came from
some other part of the code, it will use an unrecognized deleter, which
we simply attribute to the "Misc" role.
An internal API makes for simple instantiation and automatic
registration of Cache deleters for a given value type and "role".
Another internal API, CacheEntryStatsCollector, solves the problem of
caching the results of a scan and sharing them, to ensure scans are
neither excessive nor redundant so as not to harm Cache performance.
Because code is added to BlocklikeTraits, it is pulled out of
block_based_table_reader.cc into its own file.
This is a reformulation of https://github.com/facebook/rocksdb/issues/8276, without the type checking option
(could still be added), and with actual stat gathering.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8297
Test Plan: manual testing with db_bench, and a couple of basic unit tests
Reviewed By: ltamasi
Differential Revision: D28488721
Pulled By: pdillinger
fbshipit-source-id: 472f524a9691b5afb107934be2d41d84f2b129fb
Summary:
This PR adds a ```-secondary_cache_uri``` option to the cache_bench and db_bench tools to allow the user to specify a custom secondary cache URI. The object registry is used to create an instance of the ```SecondaryCache``` object of the type specified in the URI.
The main cache_bench code is packaged into a separate library, similar to db_bench.
An example invocation of db_bench with a secondary cache URI -
```db_bench --env_uri=ws://ws.flash_sandbox.vll1_2/ -db=anand/nvm_cache_2 -use_existing_db=true -benchmarks=readrandom -num=30000000 -key_size=32 -value_size=256 -use_direct_reads=true -cache_size=67108864 -cache_index_and_filter_blocks=true -secondary_cache_uri='cachelibwrapper://filename=/home/anand76/nvm_cache/cache_file;size=2147483648;regionSize=16777216;admPolicy=random;admProbability=1.0;volatileSize=8388608;bktPower=20;lockPower=12' -partition_index_and_filters=true -duration=1800```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8312
Reviewed By: zhichao-cao
Differential Revision: D28544325
Pulled By: anand1976
fbshipit-source-id: 8f209b9af900c459dc42daa7a610d5f00176eeed
Summary:
As the first part of the effort of having placing different files on different storage types, this change introduces several things:
(1) An experimental interface in FileSystem that specify temperature to a new file created.
(2) A test FileSystemWrapper, SimulatedHybridFileSystem, that simulates HDD for a file of "warm" temperature.
(3) A simple experimental feature ColumnFamilyOptions.bottommost_temperature. RocksDB would pass this value to FileSystem when creating any bottommost file.
(4) A db_bench parameter that applies the (2) and (3) to db_bench.
The motivation of the change is to introduce minimal changes that allow us to evolve tiered storage development.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8222
Test Plan:
./db_bench --benchmarks=fillrandom --write_buffer_size=2000000 -max_bytes_for_level_base=20000000 -level_compaction_dynamic_level_bytes --reads=100 -compaction_readahead_size=20000000 --reads=100000 -num=10000000
followed by
./db_bench --benchmarks=readrandom,stats --write_buffer_size=2000000 -max_bytes_for_level_base=20000000 -simulate_hybrid_fs_file=/tmp/warm_file_list -level_compaction_dynamic_level_bytes -compaction_readahead_size=20000000 --reads=500 --threads=16 -use_existing_db --num=10000000
and see results as expected.
Reviewed By: ajkr
Differential Revision: D28003028
fbshipit-source-id: 4724896d5205730227ba2f17c3fecb11261744ce
Summary:
When WriteBufferManager is shared across DBs and column families
to maintain memory usage under a limit, OOMs have been observed when flush cannot
finish but writes continuously insert to memtables.
In order to avoid OOMs, when memory usage goes beyond buffer_limit_ and DBs tries to write,
this change will stall incoming writers until flush is completed and memory_usage
drops.
Design: Stall condition: When total memory usage exceeds WriteBufferManager::buffer_size_
(memory_usage() >= buffer_size_) WriterBufferManager::ShouldStall() returns true.
DBImpl first block incoming/future writers by calling write_thread_.BeginWriteStall()
(which adds dummy stall object to the writer's queue).
Then DB is blocked on a state State::Blocked (current write doesn't go
through). WBStallInterface object maintained by every DB instance is added to the queue of
WriteBufferManager.
If multiple DBs tries to write during this stall, they will also be
blocked when check WriteBufferManager::ShouldStall() returns true.
End Stall condition: When flush is finished and memory usage goes down, stall will end only if memory
waiting to be flushed is less than buffer_size/2. This lower limit will give time for flush
to complete and avoid continous stalling if memory usage remains close to buffer_size.
WriterBufferManager::EndWriteStall() is called,
which removes all instances from its queue and signal them to continue.
Their state is changed to State::Running and they are unblocked. DBImpl
then signal all incoming writers of that DB to continue by calling
write_thread_.EndWriteStall() (which removes dummy stall object from the
queue).
DB instance creates WBMStallInterface which is an interface to block and
signal DBs during stall.
When DB needs to be blocked or signalled by WriteBufferManager,
state_for_wbm_ state is changed accordingly (RUNNING or BLOCKED).
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7898
Test Plan: Added a new test db/db_write_buffer_manager_test.cc
Reviewed By: anand1976
Differential Revision: D26093227
Pulled By: akankshamahajan15
fbshipit-source-id: 2bbd982a3fb7033f6de6153aa92a221249861aae
Summary:
When compiling RocksDB with Buck for ARM64, the linker complains about missing crc32 symbols that are defined in the crc32c_arm64.cc file. Since this file wasn't included in the build this is totally expected
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8168
Test Plan:
The following no longer fails to link rocksdb:
buck build mode/mac-xcode //eden/fs/service:edenfs#macosx-arm64
Reviewed By: zhichao-cao
Differential Revision: D27664627
Pulled By: xavierd
fbshipit-source-id: fb9d7a538599ee7a08882f87628731de6e641f8d
Summary:
A current limitation of backups is that you don't know the
exact database state of when the backup was taken. With this new
feature, you can at least inspect the backup's DB state without
restoring it by opening it as a read-only DB.
Rather than add something like OpenAsReadOnlyDB to the BackupEngine API,
which would inhibit opening stackable DB implementations read-only
(if/when their APIs support it), we instead provide a DB name and Env
that can be used to open as a read-only DB.
Possible follow-up work:
* Add a version of GetBackupInfo for a single backup.
* Let CreateNewBackup return the BackupID of the newly-created backup.
Implementation details:
Refactored ChrootFileSystem to split off new base class RemapFileSystem,
which allows more general remapping of files. We use this base class to
implement BackupEngineImpl::RemapSharedFileSystem.
To minimize API impact, I decided to just add these fields `name_for_open`
and `env_for_open` to those set by GetBackupInfo when
include_file_details=true. Creating the RemapSharedFileSystem adds a bit
to the memory consumption, perhaps unnecessarily in some cases, but this
has been mitigated by (a) only initialize the RemapSharedFileSystem
lazily when GetBackupInfo with include_file_details=true is called, and
(b) using the existing `shared_ptr<FileInfo>` objects to hold most of the
mapping data.
To enhance API safety, RemapSharedFileSystem is wrapped by new
ReadOnlyFileSystem which rejects any attempts to write. This uncovered a
couple of places in which DB::OpenForReadOnly would write to the
filesystem, so I fixed these. Added a release note because this affects
logging.
Additional minor refactoring in backupable_db.cc to support the new
functionality.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8142
Test Plan:
new test (run with ASAN and UBSAN), added to stress test and
ran it for a while with amplified backup_one_in
Reviewed By: ajkr
Differential Revision: D27535408
Pulled By: pdillinger
fbshipit-source-id: 04666d310aa0261ef6b2385c43ca793ce1dfd148
Summary:
New tests should by default be expected to be parallelizeable
and passing with ASSERT_STATUS_CHECKED. Thus, I'm changing those two
lists to exclusions rather than inclusions.
For the set of exclusions, I only listed things that currently failed
for me when attempting not to exclude, or had some other documented
reason. This marks many more tests as "parallel," which will potentially
cause some failures from self-interference, but we can address those as
they are discovered.
Also changed CircleCI ASC test to be parallelized; the easy way to do
that is to exclude building tests that don't pass ASC, which is now a
small set.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8146
Test Plan: Watch CI, etc.
Reviewed By: riversand963
Differential Revision: D27542782
Pulled By: pdillinger
fbshipit-source-id: bdd74bcd912a963ee33f3fc0d2cad2567dc7740f
Summary:
If the platform is ppc64 and the libc is not GNU libc, then we exclude the range_tree from compilation.
See https://jira.percona.com/browse/PS-7559
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8070
Reviewed By: jay-zhuang
Differential Revision: D27246004
Pulled By: mrambacher
fbshipit-source-id: 59d8433242ce7ce608988341becb4f83312445f5
Summary:
As title. All core db implementations should stay in db_impl.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8082
Test Plan: make check
Reviewed By: ajkr
Differential Revision: D27211442
Pulled By: riversand963
fbshipit-source-id: e0953fde75064740e899aaff7989ff033b7f5232
Summary:
support getUsage and getPinnedUsage in JavaAPI for Cache
also fix a typo in LRUCacheTest.java that the highPriPoolRatio is not valid(set 5, I guess it means 0.05)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7925
Reviewed By: mrambacher
Differential Revision: D26900241
Pulled By: ajkr
fbshipit-source-id: 735d1e40a16fa8919c89c7c7154ba7f81208ec33
Summary:
Removed confusing, awkward, and undocumented internal API
ReadOneLine and replaced with very simple LineFileReader.
In refactoring backupable_db.cc, this has the side benefit of
removing the arbitrary cap on the size of backup metadata files.
Also added Status::MustCheck to make it easy to mark a Status as
"must check." Using this, I can ensure that after
LineFileReader::ReadLine returns false the caller checks GetStatus().
Also removed some excessive conditional compilation in status.h
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8026
Test Plan: added unit test, and running tests with ASSERT_STATUS_CHECKED
Reviewed By: mrambacher
Differential Revision: D26831687
Pulled By: pdillinger
fbshipit-source-id: ef749c265a7a26bb13cd44f6f0f97db2955f6f0f
Summary:
This change only affects non-schema-critical aspects of the production candidate Ribbon filter. Specifically, it refines choice of internal configuration parameters based on inputs. The changes are minor enough that the schema tests in bloom_test, some of which depend on this, are unaffected. There are also some minor optimizations and refactorings.
This would be a schema change for "smash" Ribbon, to fix some known issues with small filters, but "smash" Ribbon is not accessible in public APIs. Unit test CompactnessAndBacktrackAndFpRate updated to test small and medium-large filters. Run with --thoroughness=100 or so for much better detection power (not appropriate for continuous regression testing).
Homogenous Ribbon:
This change adds internally a Ribbon filter variant we call Homogeneous Ribbon, in collaboration with Stefan Walzer. The expected "result" value for every key is zero, instead of computed from a hash. Entropy for queries not to be false positives comes from free variables ("overhead") in the solution structure, which are populated pseudorandomly. Construction is slightly faster for not tracking result values, and never fails. Instead, FP rate can jump up whenever and whereever entries are packed too tightly. For small structures, we can choose overhead to make this FP rate jump unlikely, as seen in updated unit test CompactnessAndBacktrackAndFpRate.
Unlike standard Ribbon, Homogeneous Ribbon seems to scale to arbitrary number of keys when accepting an FP rate penalty for small pockets of high FP rate in the structure. For example, 64-bit ribbon with 8 solution columns and 10% allocated space overhead for slots seems to achieve about 10.5% space overhead vs. information-theoretic minimum based on its observed FP rate with expected pockets of degradation. (FP rate is close to 1/256.) If targeting a higher FP rate with fewer solution columns, Homogeneous Ribbon can be even more space efficient, because the penalty from degradation is relatively smaller. If targeting a lower FP rate, Homogeneous Ribbon is less space efficient, as more allocated overhead is needed to keep the FP rate impact of degradation relatively under control. The new OptimizeHomogAtScale tool in ribbon_test helps to find these optimal allocation overheads for different numbers of solution columns. And Ribbon widths, with 128-bit Ribbon apparently cutting space overheads in half vs. 64-bit.
Other misc item specifics:
* Ribbon APIs in util/ribbon_config.h now provide configuration data for not just 5% construction failure rate (95% success), but also 50% and 0.1%.
* Note that the Ribbon structure does not exhibit "threshold" behavior as standard Xor filter does, so there is a roughly fixed space penalty to cut construction failure rate in half. Thus, there isn't really an "almost sure" setting.
* Although we can extrapolate settings for large filters, we don't have a good formula for configuring smaller filters (< 2^17 slots or so), and efforts to summarize with a formula have failed. Thus, small data is hard-coded from updated FindOccupancy tool.
* Enhances ApproximateNumEntries for public API Ribbon using more precise data (new API GetNumToAdd), thus a more accurate but not perfect reversal of CalculateSpace. (bloom_test updated to expect the greater precision)
* Move EndianSwapValue from coding.h to coding_lean.h to keep Ribbon code easily transferable from RocksDB
* Add some missing 'const' to member functions
* Small optimization to 128-bit BitParity
* Small refactoring of BandingStorage in ribbon_alg.h to support Homogeneous Ribbon
* CompactnessAndBacktrackAndFpRate now has an "expand" test: on construction failure, a possible alternative to re-seeding hash functions is simply to increase the number of slots (allocated space overhead) and try again with essentially the same hash values. (Start locations will be different roundings of the same scaled hash values--because fastrange not mod.) This seems to be as effective or more effective than re-seeding, as long as we increase the number of slots (m) by roughly m += m/w where w is the Ribbon width. This way, there is effectively an expansion by one slot for each ribbon-width window in the banding. (This approach assumes that getting "bad data" from your hash function is as unlikely as it naturally should be, e.g. no adversary.)
* 32-bit and 16-bit Ribbon configurations are added to ribbon_test for understanding their behavior, e.g. with FindOccupancy. They are not considered useful at this time and not tested with CompactnessAndBacktrackAndFpRate.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7879
Test Plan: unit test updates included
Reviewed By: jay-zhuang
Differential Revision: D26371245
Pulled By: pdillinger
fbshipit-source-id: da6600d90a3785b99ad17a88b2a3027710b4ea3a
