Summary:
Blob db rely on base db returning sequence number through write batch after DB::Write(). However after recent changes to the write path, DB::Writ()e no longer return sequence number in some cases. Fixing it by have WriteBatchInternal::InsertInto() always encode sequence number into write batch.
Stacking on #2375.
Closes https://github.com/facebook/rocksdb/pull/2385
Differential Revision: D5148358
Pulled By: yiwu-arbug
fbshipit-source-id: 8bda0aa07b9334ed03ed381548b39d167dc20c33
Summary:
PipelineWriteImpl is an alternative approach to WriteImpl. In WriteImpl, only one thread is allow to write at the same time. This thread will do both WAL and memtable writes for all write threads in the write group. Pending writers wait in queue until the current writer finishes. In the pipeline write approach, two queue is maintained: one WAL writer queue and one memtable writer queue. All writers (regardless of whether they need to write WAL) will still need to first join the WAL writer queue, and after the house keeping work and WAL writing, they will need to join memtable writer queue if needed. The benefit of this approach is that
1. Writers without memtable writes (e.g. the prepare phase of two phase commit) can exit write thread once WAL write is finish. They don't need to wait for memtable writes in case of group commit.
2. Pending writers only need to wait for previous WAL writer finish to be able to join the write thread, instead of wait also for previous memtable writes.
Merging #2056 and #2058 into this PR.
Closes https://github.com/facebook/rocksdb/pull/2286
Differential Revision: D5054606
Pulled By: yiwu-arbug
fbshipit-source-id: ee5b11efd19d3e39d6b7210937b11cefdd4d1c8d
Summary:
Extend TransactionOptions to include max_write_batch_size which determines the maximum size of the writebatch representation. If memory limit is exceeded, the operation will abort with subcode kMemoryLimit.
Closes https://github.com/facebook/rocksdb/pull/2124
Differential Revision: D4861842
Pulled By: lth
fbshipit-source-id: 46fd172ea67cc90bbba829bf0d70cfab2261c161
Summary:
also did minor refactoring
Closes https://github.com/facebook/rocksdb/pull/2115
Differential Revision: D4855818
Pulled By: maysamyabandeh
fbshipit-source-id: fbca6ac57e5c6677fffe8354f7291e596a50cb77
Summary:
Move some files under util/ to new directories env/, monitoring/ options/ and cache/
Closes https://github.com/facebook/rocksdb/pull/2090
Differential Revision: D4833681
Pulled By: siying
fbshipit-source-id: 2fd8bef
Summary:
MemTableInserter default constructs Post processing info
std::map. However, on Windows with 2015 STL the default
constructed map still dynamically allocates one node
which shows up on a profiler and we loose ~40% throughput
on fillrandom benchmark.
Solution: declare a map as std::aligned storage and optionally
construct.
This addresses https://github.com/facebook/rocksdb/issues/1976
Before:
-------------------------------------------------------------------
Initializing RocksDB Options from command-line flags
DB path: [k:\data\BulkLoadRandom_10M_fillonly]
fillrandom : 2.775 micros/op 360334 ops/sec; 280.4 MB/s
Microseconds per write:
Count: 10000000 Average: 2.7749 StdDev: 39.92
Min: 1 Median: 2.0826 Max: 26051
Percentiles: P50: 2.08 P75: 2.55 P99: 3.55 P99.9: 9.58 P99.99: 51.5**6
------------------------------------------------------
After:
Initializing RocksDB Options from command-line flags
DB path: [k:\data\BulkLoadRandom_10M_fillon
Closes https://github.com/facebook/rocksdb/pull/2011
Differential Revision: D4740823
Pulled By: siying
fbshipit-source-id: 1daaa2c
Summary:
Return an error from DeleteRange() (or Write() if the user is using the
low-level WriteBatch API) if an unsupported table type is configured.
Closes https://github.com/facebook/rocksdb/pull/1519
Differential Revision: D4185933
Pulled By: ajkr
fbshipit-source-id: abcdf84
Summary:
This is a previous fix that has a typo
Closes https://github.com/facebook/rocksdb/pull/1487
Differential Revision: D4157381
Pulled By: lightmark
fbshipit-source-id: f079be8
Summary:
When constructing a write batch a client may now call MarkWalTerminationPoint() on that batch. No batch operations after this call will be added written to the WAL but will still be inserted into the Memtable. This facility is used to remove one of the three WriteImpl calls in 2PC transactions. This produces a ~1% perf improvement.
```
RocksDB - unoptimized 2pc, sync_binlog=1, disable_2pc=off
INFO 2016-08-31 14:30:38,814 [main]: REQUEST PHASE COMPLETED. 75000000 requests done in 2619 seconds. Requests/second = 28628
RocksDB - optimized 2pc , sync_binlog=1, disable_2pc=off
INFO 2016-08-31 16:26:59,442 [main]: REQUEST PHASE COMPLETED. 75000000 requests done in 2581 seconds. Requests/second = 29054
```
Test Plan: Two unit tests added.
Reviewers: sdong, yiwu, IslamAbdelRahman
Reviewed By: yiwu
Subscribers: hermanlee4, dhruba, andrewkr
Differential Revision: https://reviews.facebook.net/D64599
Summary:
Mitigate regression bug of options.max_successive_merges hit during DB Recovery
For https://reviews.facebook.net/D62625
Test Plan: make all check
Reviewers: horuff, sdong
Reviewed By: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D62655
Summary:
Add API to WriteBatch to store range deletions in its buffer
which are later added to memtable. In the WriteBatch buffer, a range
deletion is encoded as "<optype><CF ID (optional)><begin key><end key>".
With this diff, the range tombstones are stored inline with the data in
the memtable. It's useful for now because the test cases rely on the
data being accessible via memtable. My next step is to store range
tombstones in a separate area in the memtable.
Test Plan: unit tests
Reviewers: IslamAbdelRahman, sdong, wanning
Reviewed By: wanning
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D61401
Summary:
Stale log files can be deleted out of order. This can happen for various reasons. One of the reason is that no data is ever inserted to a column family and we have an optimization to update its log number, but not all the old log files are cleaned up (the case shown in the unit tests added). It can also happen when we simply delete multiple log files out of order.
This causes data corruption because we simply increase seqID after processing the next row and we may end up with writing data with smaller seqID than what is already flushed to memtables.
In DB recovery, for the oldest files we are replaying, if there it contains no data for any column family, we ignore the sequence IDs in the file.
Test Plan: Add two unit tests that fail without the fix.
Reviewers: IslamAbdelRahman, igor, yiwu
Reviewed By: yiwu
Subscribers: hermanlee4, yoshinorim, leveldb, andrewkr, dhruba
Differential Revision: https://reviews.facebook.net/D60891
Summary: In concurrent memtable insert case, updating counters in MemTable::Add() can count for 5% CPU usage. By batch all the counters and update in the end of the write batch, the CPU overheads are overhead in the use cases where more than one key is updated in one write batch.
Test Plan:
Write throughput increases 12% with this benchmark setting:
TEST_TMPDIR=/dev/shm/ ./db_bench --benchmarks=fillrandom -disable_auto_compactions -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -num=10000000 --writes=1000000 -max_background_flushes=16 -max_write_buffer_number=16 --threads=64 --batch_size=128 -allow_concurrent_memtable_write -enable_write_thread_adaptive_yield
Reviewers: andrewkr, IslamAbdelRahman, ngbronson, igor
Reviewed By: ngbronson
Subscribers: ngbronson, leveldb, andrewkr, dhruba
Differential Revision: https://reviews.facebook.net/D60495
Summary: filter_deltes is not a frequently used feature. Remove it.
Test Plan: Run all test suites.
Reviewers: igor, yhchiang, IslamAbdelRahman
Reviewed By: IslamAbdelRahman
Subscribers: leveldb, andrewkr, dhruba
Differential Revision: https://reviews.facebook.net/D59427
Summary:
We have alot of code duplication whenever we call FullMerge we keep duplicating the instrumentation and statistics code
This is a simple diff to refactor the code to use TimedFullMerge instead of FullMerge
Test Plan: COMPILE_WITH_ASAN=1 make check -j64
Reviewers: andrewkr, yhchiang, sdong
Reviewed By: sdong
Subscribers: andrewkr, dhruba
Differential Revision: https://reviews.facebook.net/D59577
Summary:
1. prepare()
2. crash
3. recover
4. commit()
5. crash
6. data is lost
This is due to the transaction data still only residing in the WAL but because the logs were flushed on the first recovery the data is ignored on the second recovery. We must scan all logs found on recovery and only ignore redundant data at the time of replay. It is not possible to know which logs still contain relevant data at time of recovery. We cannot simply ignore a log because all of the non-2pc data it contains has already been written to L0.
The changes made to MemTableInserter are to ensure that prepared sections are still recovered even if all of the non-2pc data in that log has already been flushed to L0.
Test Plan: Provided test.
Reviewers: sdong
Subscribers: andrewkr, hermanlee4, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D57729
Summary:
Consider the following WAL with 4 batch entries prefixed with their sequence at time of memtable insert.
[1: BEGIN_PREPARE, PUT, PUT, PUT, PUT, END_PREPARE(a)]
[1: BEGIN_PREPARE, PUT, PUT, PUT, PUT, END_PREPARE(b)]
[4: COMMIT(a)]
[7: COMMIT(b)]
The first two batches do not consume any sequence numbers so are both prefixed with seq=1.
For 2pc commit, memtable insertion takes place before COMMIT batch is written to WAL.
We can see that sequence number consumption takes place between WAL entries giving us the seemingly sparse sequence prefix for WAL entries.
This is a valid WAL.
Because with 2PC markers one WriteBatch points to another batch containing its inserts a writebatch can consume more or less sequence numbers than the number of sequence consuming entries that it contains.
We can see that, given the entries in the WAL, 6 sequence ids were consumed. Yet on recovery the maximum sequence consumed would be 7 + 3 (the number of sequence numbers consumed by COMMIT(b))
So, now upon recovery we must track the actual consumption of sequence numbers.
In the provided scenario there will be no sequence gaps, but it is possible to produce a sequence gap. This should not be a problem though. correct?
Test Plan: provided test.
Reviewers: sdong
Subscribers: andrewkr, leveldb, dhruba, hermanlee4
Differential Revision: https://reviews.facebook.net/D57645
Summary:
This diff is built on top of WriteBatch modification: https://reviews.facebook.net/D54093 and adds the required functionality to rocksdb core necessary for rocksdb to support 2PC.
modfication of DBImpl::WriteImpl()
- added two arguments *uint64_t log_used = nullptr, uint64_t log_ref = 0;
- *log_used is an output argument which will return the log number which the incoming batch was inserted into, 0 if no WAL insert took place.
- log_ref is a supplied log_number which all memtables inserted into will reference after the batch insert takes place. This number will reside in 'FindMinPrepLogReferencedByMemTable()' until all Memtables insertinto have flushed.
- Recovery/writepath is now aware of prepared batches and commit and rollback markers.
Test Plan: There is currently no test on this diff. All testing of this functionality takes place in the Transaction layer/diff but I will add some testing.
Reviewers: IslamAbdelRahman, sdong
Subscribers: leveldb, santoshb, andrewkr, vasilep, dhruba, hermanlee4
Differential Revision: https://reviews.facebook.net/D56919
Summary: Adds three new WriteBatch data types: Prepare(xid), Commit(xid), Rollback(xid). Prepare(xid) should precede the (single) operation to which is applies. There can obviously be multiple Prepare(xid) markers. There should only be one Rollback(xid) or Commit(xid) marker yet not both. None of this logic is currently enforced and will most likely be implemented further up such as in the memtableinserter. All three markers are similar to PutLogData in that they are writebatch meta-data, ie stored but not counted. All three markers differ from PutLogData in that they will actually be written to disk. As for WriteBatchWithIndex, Prepare, Commit, Rollback are all implemented just as PutLogData and none are tested just as PutLogData.
Test Plan: single unit test in write_batch_test.
Reviewers: hermanlee4, sdong, anthony
Subscribers: leveldb, dhruba, vasilep, andrewkr
Differential Revision: https://reviews.facebook.net/D57867
Summary: Adds three new WriteBatch data types: Prepare(xid), Commit(xid), Rollback(xid). Prepare(xid) should precede the (single) operation to which is applies. There can obviously be multiple Prepare(xid) markers. There should only be one Rollback(xid) or Commit(xid) marker yet not both. None of this logic is currently enforced and will most likely be implemented further up such as in the memtableinserter. All three markers are similar to PutLogData in that they are writebatch meta-data, ie stored but not counted. All three markers differ from PutLogData in that they will actually be written to disk. As for WriteBatchWithIndex, Prepare, Commit, Rollback are all implemented just as PutLogData and none are tested just as PutLogData.
Test Plan: single unit test in write_batch_test.
Reviewers: hermanlee4, sdong, anthony
Subscribers: andrewkr, vasilep, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D54093
Summary:
- Put key offset and key size in WriteBatchIndexEntry
- Use vector for comparators in WriteBatchEntryComparator
I use a slightly modified version of @yoshinorim code to benchmark
https://gist.github.com/IslamAbdelRahman/b120f4fba8d6ff7d58d2
For Put I create a transaction that put a 1000000 keys and measure the time spent without commit.
For GetForUpdate I read the keys that I added in the Put transaction.
Original time:
```
rm -rf /dev/shm/rocksdb-example/
./txn_bench put 1000000
1000000 OK Ops | took 3.679 seconds
./txn_bench get_for_update 1000000
1000000 OK Ops | took 3.940 seconds
```
New Time
```
rm -rf /dev/shm/rocksdb-example/
./txn_bench put 1000000
1000000 OK Ops | took 2.727 seconds
./txn_bench get_for_update 1000000
1000000 OK Ops | took 3.880 seconds
```
It looks like there is no significant improvement in GetForUpdate() but we can see ~30% improvement in Put()
Test Plan: unittests
Reviewers: yhchiang, anthony, sdong
Reviewed By: sdong
Subscribers: andrewkr, dhruba, yoshinorim
Differential Revision: https://reviews.facebook.net/D55539
record.size() should not be less than 12.
This "magic number" seems to be the WriteBatch header (8 byte sequence
and 4 byte count). Replaced all the places where "12" was used
by WriteBatchInternal::kHeader.
Summary:
copy from task 8196669:
1) Optimistic transactions do not support batching writes from different threads.
2) Pessimistic transactions do not support batching writes if an expiration time is set.
In these 2 cases, we currently do not do any write batching in DBImpl::WriteImpl() because there is a WriteCallback that could decide at the last minute to abort the write. But we could support batching write operations with callbacks if we make sure to process the callbacks correctly.
To do this, we would first need to modify write_thread.cc to stop preventing writes with callbacks from being batched together. Then we would need to change DBImpl::WriteImpl() to call all WriteCallback's in a batch, only write the batches that succeed, and correctly set the state of each batch's WriteThread::Writer.
Test Plan: Added test WriteWithCallbackTest to write_callback_test.cc which creates multiple client threads and verifies that writes are batched and executed properly.
Reviewers: hermanlee4, anthony, ngbronson
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D52863
Summary:
This diff adds support for concurrent adds to the skiplist memtable
implementations. Memory allocation is made thread-safe by the addition of
a spinlock, with small per-core buffers to avoid contention. Concurrent
memtable writes are made via an additional method and don't impose a
performance overhead on the non-concurrent case, so parallelism can be
selected on a per-batch basis.
Write thread synchronization is an increasing bottleneck for higher levels
of concurrency, so this diff adds --enable_write_thread_adaptive_yield
(default off). This feature causes threads joining a write batch
group to spin for a short time (default 100 usec) using sched_yield,
rather than going to sleep on a mutex. If the timing of the yield calls
indicates that another thread has actually run during the yield then
spinning is avoided. This option improves performance for concurrent
situations even without parallel adds, although it has the potential to
increase CPU usage (and the heuristic adaptation is not yet mature).
Parallel writes are not currently compatible with
inplace updates, update callbacks, or delete filtering.
Enable it with --allow_concurrent_memtable_write (and
--enable_write_thread_adaptive_yield). Parallel memtable writes
are performance neutral when there is no actual parallelism, and in
my experiments (SSD server-class Linux and varying contention and key
sizes for fillrandom) they are always a performance win when there is
more than one thread.
Statistics are updated earlier in the write path, dropping the number
of DB mutex acquisitions from 2 to 1 for almost all cases.
This diff was motivated and inspired by Yahoo's cLSM work. It is more
conservative than cLSM: RocksDB's write batch group leader role is
preserved (along with all of the existing flush and write throttling
logic) and concurrent writers are blocked until all memtable insertions
have completed and the sequence number has been advanced, to preserve
linearizability.
My test config is "db_bench -benchmarks=fillrandom -threads=$T
-batch_size=1 -memtablerep=skip_list -value_size=100 --num=1000000/$T
-level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999
-disable_auto_compactions --max_write_buffer_number=8
-max_background_flushes=8 --disable_wal --write_buffer_size=160000000
--block_size=16384 --allow_concurrent_memtable_write" on a two-socket
Xeon E5-2660 @ 2.2Ghz with lots of memory and an SSD hard drive. With 1
thread I get ~440Kops/sec. Peak performance for 1 socket (numactl
-N1) is slightly more than 1Mops/sec, at 16 threads. Peak performance
across both sockets happens at 30 threads, and is ~900Kops/sec, although
with fewer threads there is less performance loss when the system has
background work.
Test Plan:
1. concurrent stress tests for InlineSkipList and DynamicBloom
2. make clean; make check
3. make clean; DISABLE_JEMALLOC=1 make valgrind_check; valgrind db_bench
4. make clean; COMPILE_WITH_TSAN=1 make all check; db_bench
5. make clean; COMPILE_WITH_ASAN=1 make all check; db_bench
6. make clean; OPT=-DROCKSDB_LITE make check
7. verify no perf regressions when disabled
Reviewers: igor, sdong
Reviewed By: sdong
Subscribers: MarkCallaghan, IslamAbdelRahman, anthony, yhchiang, rven, sdong, guyg8, kradhakrishnan, dhruba
Differential Revision: https://reviews.facebook.net/D50589
Summary:
List of changes:
1) Fix the snprintf() usage in cases where wrong variable was used to determine the output buffer size.
2) Remove unnecessary checks before calling delete operator.
3) Increase code correctness by using size_t type when getting vector's size.
4) Unify the coding style by removing namespace::std usage at the top of the file to confirm to the majority usage.
5) Fix various lint errors pointed out by 'arc lint'.
Test Plan:
Code review and build:
git diff
make clean
make -j 32 commit-prereq
arc lint
Reviewers: kradhakrishnan, sdong, rven, anthony, yhchiang, igor
Reviewed By: igor
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D51849
Summary:
There's no need for WriteImpl to flatten the write batch group
into a single WriteBatch if the WAL is disabled. This diff moves the
flattening into the WAL step, and skips flattening entirely if it isn't
needed. It's good for about 5% speedup on a multi-threaded workload
with no WAL.
This diff also adds clarifying comments about the chance for partial
failure of WriteBatchInternal::InsertInto, and always sets bg_error_ if
the memtable state diverges from the logged state or if a WriteBatch
succeeds only partially.
Benchmark for speedup:
db_bench -benchmarks=fillrandom -threads=16 -batch_size=1 -memtablerep=skip_list -value_size=0 --num=200000 -level0_slowdown_writes_trigger=9999 -level0_stop_writes_trigger=9999 -disable_auto_compactions --max_write_buffer_number=8 -max_background_flushes=8 --disable_wal --write_buffer_size=160000000
Test Plan: asserts + make check
Reviewers: sdong, igor
Reviewed By: igor
Subscribers: dhruba
Differential Revision: https://reviews.facebook.net/D50583
Summary:
Parallel writes will only be possible for certain combinations of
flags and WriteBatch contents. Traversing the WriteBatch at write time
to check these conditions would be expensive, but it is very cheap to
keep track of when building WriteBatch-es. When loading WriteBatch-es
during recovery, a deferred computation state is used so that the flags
never need to be computed.
Test Plan:
1. add asserts and EXPECT_EQ-s
2. make check
Reviewers: sdong, igor
Reviewed By: igor
Subscribers: dhruba
Differential Revision: https://reviews.facebook.net/D50337
Summary:
This patch fixes#7460559. It introduces SingleDelete as a new database
operation. This operation can be used to delete keys that were never
overwritten (no put following another put of the same key). If an overwritten
key is single deleted the behavior is undefined. Single deletion of a
non-existent key has no effect but multiple consecutive single deletions are
not allowed (see limitations).
In contrast to the conventional Delete() operation, the deletion entry is
removed along with the value when the two are lined up in a compaction. Note:
The semantics are similar to @igor's prototype that allowed to have this
behavior on the granularity of a column family (
https://reviews.facebook.net/D42093 ). This new patch, however, is more
aggressive when it comes to removing tombstones: It removes the SingleDelete
together with the value whenever there is no snapshot between them while the
older patch only did this when the sequence number of the deletion was older
than the earliest snapshot.
Most of the complex additions are in the Compaction Iterator, all other changes
should be relatively straightforward. The patch also includes basic support for
single deletions in db_stress and db_bench.
Limitations:
- Not compatible with cuckoo hash tables
- Single deletions cannot be used in combination with merges and normal
deletions on the same key (other keys are not affected by this)
- Consecutive single deletions are currently not allowed (and older version of
this patch supported this so it could be resurrected if needed)
Test Plan: make all check
Reviewers: yhchiang, sdong, rven, anthony, yoshinorim, igor
Reviewed By: igor
Subscribers: maykov, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D43179
Summary:
This diff is a collection of cleanups that were initially part of D43179.
Additionally it adds a unified way of defining key-value maps that use a
Comparator for sorting (this was previously implemented in four different
places).
Test Plan: make clean check all
Reviewers: rven, anthony, yhchiang, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D45993
Summary: Implemented this simple wrapper for something else I was working on. Seemed like it makes sense to expose it instead of burying it in some random code.
Test Plan: added test
Reviewers: rven, kradhakrishnan, sdong, yhchiang
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D43293
Summary:
Support RollbackToSavePoint() in WriteBatch and WriteBatchWithIndex. Support for partial transaction rollback is needed for MyRocks.
An alternate implementation of Transaction::RollbackToSavePoint() exists in D40869. However, the other implementation is messier because it is implemented outside of WriteBatch. This implementation is much cleaner and also exposes a potentially useful feature to WriteBatch.
Test Plan: Added unit tests
Reviewers: IslamAbdelRahman, kradhakrishnan, maykov, yoshinorim, hermanlee4, spetrunia, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42723
Summary:
We have addded new stats and perf_context for measuring the merge and filter operation time consumption.
We have bounded all the merge operations within the GUARD statment and collected the total time for these operations in the DB.
Test Plan: WIP
Reviewers: rven, yhchiang, kradhakrishnan, igor, sdong
Reviewed By: sdong
Subscribers: dhruba
Differential Revision: https://reviews.facebook.net/D34377
Summary:
When using latest clang (3.6 or 3.7/trunck) rocksdb is failing with many errors. Almost all of them are missing override errors. This diff adds missing override keyword. No manual changes.
Prerequisites: bear and clang 3.5 build with extra tools
```lang=bash
% USE_CLANG=1 bear make all # generate a compilation database http://clang.llvm.org/docs/JSONCompilationDatabase.html
% clang-modernize -p . -include . -add-override
% make format
```
Test Plan:
Make sure all tests are passing.
```lang=bash
% #Use default fb code clang.
% make check
```
Verify less error and no missing override errors.
```lang=bash
% # Have trunk clang present in path.
% ROCKSDB_NO_FBCODE=1 CC=clang CXX=clang++ make
```
Reviewers: igor, kradhakrishnan, rven, meyering, sdong
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D34077
Summary:
This patch changes concurrency guarantees around ColumnFamilySet::column_families_ and ColumnFamilySet::column_families_data_.
Before:
* When mutating: lock DB mutex and spin lock
* When reading: lock DB mutex OR spin lock
After:
* When mutating: lock DB mutex and be in write thread
* When reading: lock DB mutex or be in write thread
That way, we eliminate the spin lock that protects these hash maps and simplify concurrency. That means we don't need to lock the spin lock during writing, since writing is mutually exclusive with column family create/drop (the only operations that mutate those hash maps).
With these new restrictions, I also needed to move column family create to the write thread (column family drop was already in the write thread).
Even though we don't need to lock the spin lock during write, impact on performance should be minimal -- the spin lock is almost never busy, so locking it is almost free.
This addresses task t5116919.
Test Plan:
make check
Stress test with lots and lots of column family drop and create:
time ./db_stress --threads=30 --ops_per_thread=5000000 --max_key=5000 --column_families=200 --clear_column_family_one_in=100000 --verify_before_write=0 --reopen=15 --max_background_compactions=10 --max_background_flushes=10 --db=/fast-rocksdb-tmp/db_stress/
Reviewers: yhchiang, rven, sdong
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D30651
Summary:
Remove the use of exception in WriteBatch::Handler. Now the default
implementations of Put, Merge, and Delete in WriteBatch::Handler are no-op.
Test Plan:
Add three test cases in write_batch_test
./write_batch_test
Reviewers: sdong, igor
Reviewed By: sdong, igor
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D29835
Summary:
We need to turn on -Wshorten-64-to-32 for mobile. See D1671432 (internal phabricator) for details.
This diff turns on the warning flag and fixes all the errors. There were also some interesting errors that I might call bugs, especially in plain table. Going forward, I think it makes sense to have this flag turned on and be very very careful when converting 64-bit to 32-bit variables.
Test Plan: compiles
Reviewers: ljin, rven, yhchiang, sdong
Reviewed By: yhchiang
Subscribers: bobbaldwin, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D28689
Summary:
Make inplace_update_support and inplace_update_num_locks dynamic.
inplace_callback becomes immutable
We are almost free of references to cfd->options() in db_impl
Test Plan: unit test
Reviewers: igor, yhchiang, rven, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D25293
Summary:
When memtable is full it calls the registered callback. That callback then registers column family as needing the flush. Every write checks if there are some column families that need to be flushed. This completely eliminates the need for MakeRoomForWrite() function and simplifies our Write code-path.
There is some complexity with the concurrency when the column family is dropped. I made it a bit less complex by dropping the column family from the write thread in https://reviews.facebook.net/D22965. Let me know if you want to discuss this.
Test Plan: make check works. I'll also run db_stress with creating and dropping column families for a while.
Reviewers: yhchiang, sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23067
Summary: removed reference to options in WriteBatch and DBImpl::Get()
Test Plan: make all check
Reviewers: yhchiang, igor, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23049
Summary:
Before this diff, whenever we Write to non-existing column family, Write() would fail.
This diff adds an option to not fail a Write() when WriteBatch points to non-existing column family. MongoDB said this would be useful for them, since they might have a transaction updating an index that was dropped by another thread. This way, they don't have to worry about checking if all indexes are alive on every write. They don't care if they lose writes to dropped index.
Test Plan: added a small unit test
Reviewers: sdong, yhchiang, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22143
Summary:
Add WriteBatchWithIndex so that a user can query data out of a WriteBatch, to support MongoDB's read-its-own-write.
WriteBatchWithIndex uses a skiplist to store the binary index. The index stores the offset of the entry in the write batch. When searching for a key, the key for the entry is read by read the entry from the write batch from the offset.
Define a new iterator class for querying data out of WriteBatchWithIndex. A user can create an iterator of the write batch for one column family, seek to a key and keep calling Next() to see next entries.
I will add more unit tests if people are OK about this API.
Test Plan:
make all check
Add unit tests.
Reviewers: yhchiang, igor, MarkCallaghan, ljin
Reviewed By: ljin
Subscribers: dhruba, leveldb, xjin
Differential Revision: https://reviews.facebook.net/D21381
