Summary: RocksDB already depends on C++11, so we might as well all the goodness that C++11 provides. This means that we don't need AtomicPointer anymore. The less things in port/, the easier it will be to port to other platforms.
Test Plan: make check + careful visual review verifying that NoBarried got memory_order_relaxed, while Acquire/Release methods got memory_order_acquire and memory_order_release
Reviewers: rven, yhchiang, ljin, sdong
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D27543
Summary: Now --bench_size is only used in multireadrandom tests, although the codes allow it to run in all write tests. I don't see a reason why we can't enable it.
Test Plan:
Run
./db_bench -benchmarks multirandomwrite --threads=5 -batch_size=16
and see the stats printed out in LOG to make sure batching really happened.
Reviewers: ljin, yhchiang, rven, igor
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D25509
Summary:
Add a function as tittle.
Also use the same parameter to fillseekseq too.
Test Plan: Run seekrandom using the new parameter
Reviewers: ljin, MarkCallaghan
Reviewed By: MarkCallaghan
Subscribers: rven, igor, yhchiang, leveldb
Differential Revision: https://reviews.facebook.net/D25035
Summary: option max_background_flushes doesn't make sense if thread pool size is not set accordingly. Set the thread pool size as what we do for max_background_compactions.
Test Plan: Run db_bench with max_background_flushes > 1
Reviewers: yhchiang, igor, rven, ljin
Reviewed By: ljin
Subscribers: MarkCallaghan, leveldb
Differential Revision: https://reviews.facebook.net/D24717
Summary:
This diff introduces the `lookahead` argument to `SkipListFactory()`. This is an
optimization for the tailing use case which includes many seeks. E.g. consider
the following operations on a skip list iterator:
Seek(x), Next(), Next(), Seek(x+2), Next(), Seek(x+3), Next(), Next(), ...
If `lookahead` is positive, `SkipListRep` will return an iterator which also
keeps track of the previously visited node. Seek() then first does a linear
search starting from that node (up to `lookahead` steps). As in the tailing
example above, this may require fewer than ~log(n) comparisons as with regular
skip list search.
Test Plan:
Added a new benchmark (`fillseekseq`) which simulates the usage pattern. It
first writes N records (with consecutive keys), then measures how much time it
takes to read them by calling `Seek()` and `Next()`.
$ time ./db_bench -num 10000000 -benchmarks fillseekseq -prefix_size 1 \
-key_size 8 -write_buffer_size $[1024*1024*1024] -value_size 50 \
-seekseq_next 2 -skip_list_lookahead=0
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.389 micros/op 2569047 ops/sec;
real 0m21.806s
user 0m12.106s
sys 0m9.672s
$ time ./db_bench [...] -skip_list_lookahead=2
[...]
DB path: [/dev/shm/rocksdbtest/dbbench]
fillseekseq : 0.153 micros/op 6540684 ops/sec;
real 0m19.469s
user 0m10.192s
sys 0m9.252s
Reviewers: ljin, sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb, march, lovro
Differential Revision: https://reviews.facebook.net/D23997
Summary: Building master on OS X has some compile errors due to implicit type conversions which generate warnings which RocksDB's build settings raise as errors.
Test Plan: It compiles!
Reviewers: ljin, igor
Reviewed By: ljin
Differential Revision: https://reviews.facebook.net/D24135
Summary: see above
Test Plan:
make check, ran db_bench and looked at output
- begin *PUBLIC* platform impact section -
Bugzilla: #
- end platform impact -
Reviewers: igor
Differential Revision: https://reviews.facebook.net/D24189
Summary:
Add the MultiGet API to allow prefetching.
With file size of 1.5G, I configured it to have 0.9 hash ratio that can
fill With 115M keys and result in 2 hash functions, the lookup QPS is
~4.9M/s vs. 3M/s for Get().
It is tricky to set the parameters right. Since files size is determined
by power-of-two factor, that means # of keys is fixed in each file. With
big file size (thus smaller # of files), we will have more chance to
waste lot of space in the last file - lower space utilization as a
result. Using smaller file size can improve the situation, but that
harms lookup speed.
Test Plan: db_bench
Reviewers: yhchiang, sdong, igor
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23673
Summary:
Add a CompactedDBImpl that will enabled when calling OpenForReadOnly()
and the DB only has one level (>0) of files. As a performan comparison,
CuckooTable performs 2.1M/s with CompactedDBImpl vs. 1.78M/s with
ReadOnlyDBImpl.
Test Plan: db_bench
Reviewers: yhchiang, igor, sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23553
Summary: It contrains the file size to be 4G max with int
Test Plan:
tried to grep instance and made sure other related variables are also
uint64
Reviewers: sdong, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23697
Summary:
MurmurHash becomes expensive when we do millions Get() a second in one
thread. Add this option to allow the first hash function to use identity
function as hash function. It results in QPS increase from 3.7M/s to
~4.3M/s. I did not observe improvement for end to end RocksDB
performance. This may be caused by other bottlenecks that I will address
in a separate diff.
Test Plan:
```
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=0
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.272us (3.7 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.138us (7.2 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.1 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.142us (7.0 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.144us (6.9 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.201us (5.0 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.123us (8.1 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.121us (8.3 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.112us (8.9 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.251us (4.0 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.107us (9.4 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.099us (10.1 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.100us (10.0 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.116us (8.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.095us (10.5 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.096us (10.4 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.098us (10.2 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.105us (9.5 Mqps) with batch size of 100, # of found keys 73400320
[ljin@dev1964 rocksdb] ./cuckoo_table_reader_test --enable_perf --file_dir=/dev/shm --write --identity_as_first_hash=1
==== Test CuckooReaderTest.WhenKeyExists
==== Test CuckooReaderTest.WhenKeyExistsWithUint64Comparator
==== Test CuckooReaderTest.CheckIterator
==== Test CuckooReaderTest.CheckIteratorUint64
==== Test CuckooReaderTest.WhenKeyNotFound
==== Test CuckooReaderTest.TestReadPerformance
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.230us (4.3 Mqps) with batch size of 0, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.086us (11.7 Mqps) with batch size of 10, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.088us (11.3 Mqps) with batch size of 25, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 50, # of found keys 125829120
With 125829120 items, utilization is 93.75%, number of hash functions: 2.
Time taken per op is 0.083us (12.1 Mqps) with batch size of 100, # of found keys 125829120
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.159us (6.3 Mqps) with batch size of 0, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 10, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.6 Mqps) with batch size of 25, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 50, # of found keys 104857600
With 104857600 items, utilization is 78.12%, number of hash functions: 2.
Time taken per op is 0.082us (12.2 Mqps) with batch size of 100, # of found keys 104857600
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.154us (6.5 Mqps) with batch size of 0, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 10, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.077us (12.9 Mqps) with batch size of 25, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 50, # of found keys 83886080
With 83886080 items, utilization is 62.50%, number of hash functions: 2.
Time taken per op is 0.079us (12.6 Mqps) with batch size of 100, # of found keys 83886080
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.218us (4.6 Mqps) with batch size of 0, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.083us (12.0 Mqps) with batch size of 10, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.085us (11.7 Mqps) with batch size of 25, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.086us (11.6 Mqps) with batch size of 50, # of found keys 73400320
With 73400320 items, utilization is 54.69%, number of hash functions: 2.
Time taken per op is 0.078us (12.8 Mqps) with batch size of 100, # of found keys 73400320
```
Reviewers: sdong, igor, yhchiang
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D23451
Summary:
1. Make filter_block.h a base class. Derive block_based_filter_block and full_filter_block. The previous one is the traditional filter block. The full_filter_block is newly added. It would generate a filter block that contain all the keys in SST file.
2. When querying a key, table would first check if full_filter is available. If not, it would go to the exact data block and check using block_based filter.
3. User could choose to use full_filter or tradional(block_based_filter). They would be stored in SST file with different meta index name. "filter.filter_policy" or "full_filter.filter_policy". Then, Table reader is able to know the fllter block type.
4. Some optimizations have been done for full_filter_block, thus it requires a different interface compared to the original one in filter_policy.h.
5. Actual implementation of filter bits coding/decoding is placed in util/bloom_impl.cc
Benchmark: base commit 1d23b5c470
Command:
db_bench --db=/dev/shm/rocksdb --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --write_buffer_size=134217728 --max_write_buffer_number=2 --target_file_size_base=33554432 --max_bytes_for_level_base=1073741824 --verify_checksum=false --max_background_compactions=4 --use_plain_table=0 --memtablerep=prefix_hash --open_files=-1 --mmap_read=1 --mmap_write=0 --bloom_bits=10 --bloom_locality=1 --memtable_bloom_bits=500000 --compression_type=lz4 --num=393216000 --use_hash_search=1 --block_size=1024 --block_restart_interval=16 --use_existing_db=1 --threads=1 --benchmarks=readrandom —disable_auto_compactions=1
Read QPS increase for about 30% from 2230002 to 2991411.
Test Plan:
make all check
valgrind db_test
db_stress --use_block_based_filter = 0
./auto_sanity_test.sh
Reviewers: igor, yhchiang, ljin, sdong
Reviewed By: sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D20979
Summary:
That way we can see when this graph goes up and be happy.
Couple of changes:
1. title
2. fix db_bench to delete column families before deleting the DB. this was asserting when compiled in debug mode
3. don't sync manifest when disableDataSync. We discussed this offline. I can move it to separate diff if you'd like
Test Plan: ran it
Reviewers: sdong, yhchiang, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D22815
Summary:
- New Uint64 comparator
- Modify Reader and Builder to take custom user comparators instead of bytewise comparator
- Modify logic for choosing unused user key in builder
- Modify iterator logic in reader
- test changes
Test Plan:
cuckoo_table_{builder,reader,db}_test
make check all
Reviewers: ljin, sdong
Reviewed By: ljin
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D22377
Summary:
I will move compression related options in a separate diff since this
diff is already pretty lengthy.
I guess I will also need to change JNI accordingly :(
Test Plan: make all check
Reviewers: yhchiang, igor, sdong
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21915
Summary:
Adding num_column_families flag. Adding support for column families in DoWrite and ReadRandom methods.
[Igor, please let me know if this approach sounds good. I shall add it to other methods too.]
Test Plan: Ran fillseq on 1M keys and 10 Column families and ran readrandom.
Reviewers: sdong, yhchiang, igor, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21387
Summary: Adding flags to use cuckoo table SST in db_bench.cc
Test Plan: Ran benchmark with fillseq and readrandom
Reviewers: sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D21729
Summary: This is a linux-specific system call.
Test Plan: ran db_bench
Reviewers: igor, yhchiang, sdong
Reviewed By: sdong
Subscribers: haobo, leveldb
Differential Revision: https://reviews.facebook.net/D21183
Summary:
Add block_restart_interval in db_bench, default value 16
Test Plan:
make
Reviewers: sdong
Reviewed By: sdong
Differential Revision: https://reviews.facebook.net/D20331
Summary:
Since we have a lot of options for PlainTable, add a struct PlainTableOptions
to manage them
Test Plan: make all check
Reviewers: sdong
Reviewed By: sdong
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D20175
Summary:
add a flag called use_hash_search in db_bench
Test Plan:
make all check
./db_bench --use_hash_search=1
Reviewers: ljin, haobo, yhchiang, sdong
Reviewed By: sdong
Subscribers: igor, dhruba
Differential Revision: https://reviews.facebook.net/D20067
Summary:
Changes:
- Adding numa_aware flag to db_bench.cc
- Using numa.h library to bind memory and cpu of threads to a fixed NUMA node
Result: There seems to be no significant change in the micros/op time with numa_aware enabled. I also tried this with other implementations, including a combination of pthread_setaffinity_np, sched_setaffinity and set_mempolicy methods. It'd be great if someone could point out where I'm going wrong and if we can achieve a better micors/op.
Test Plan:
Ran db_bench tests using following command:
./db_bench --db=/mnt/tmp --num_levels=6 --key_size=20 --prefix_size=20 --keys_per_prefix=0 --value_size=100 --block_size=4096 --cache_size=17179869184 --cache_numshardbits=6 --compression_type=none --compression_ratio=1 --min_level_to_compress=-1 --disable_seek_compaction=1 --hard_rate_limit=2 --write_buffer_size=134217728 --max_write_buffer_number=2 --level0_file_num_compaction_trigger=8 --target_file_size_base=134217728 --max_bytes_for_level_base=1073741824 --disable_wal=0 --wal_dir=/mnt/tmp --sync=0 --disable_data_sync=1 --verify_checksum=1 --delete_obsolete_files_period_micros=314572800 --max_grandparent_overlap_factor=10 --max_background_compactions=4 --max_background_flushes=0 --level0_slowdown_writes_trigger=16 --level0_stop_writes_trigger=24 --statistics=0 --stats_per_interval=0 --stats_interval=1048576 --histogram=0 --use_plain_table=1 --open_files=-1 --mmap_read=1 --mmap_write=0 --memtablerep=prefix_hash --bloom_bits=10 --bloom_locality=1 --perf_level=0 --duration=300 --benchmarks=readwhilewriting --use_existing_db=1 --num=157286400 --threads=24 --writes_per_second=10240 --numa_aware=[False/True]
The tests were run in private devserver with 24 cores and the db was prepopulated using filluniquerandom test. The tests resulted in 0.145 us/op with numa_aware=False and 0.161 us/op with numa_aware=True.
Reviewers: sdong, yhchiang, ljin, igor
Reviewed By: ljin, igor
Subscribers: igor, leveldb
Differential Revision: https://reviews.facebook.net/D19353
Summary:
RandomGenerator::Generate() currently has an assertion len < data_.size().
However, it is actually fine to have len == data_.size().
This diff change the assertion to len <= data_.size().
Test Plan:
make db_bench
./db_bench
Reviewers: haobo, sdong, ljin
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D19269
Summary: as title
Test Plan: make release
Reviewers: haobo, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D19227
Summary: as requested by mark
Test Plan: make release
Reviewers: sdong, haobo
Reviewed By: haobo
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D19221
Summary:
As discussed in our internal group, we don't get much use of seek compaction at the moment, while it's making code more complicated and slower in some cases.
This diff removes seek compaction and (hopefully) all code that was introduced to support seek compaction.
There is one test case that relied on didIO information. I'll try to find another way to implement it.
Test Plan: make check
Reviewers: sdong, haobo, yhchiang, ljin, dhruba
Reviewed By: ljin
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D19161
Summary:
Forward iterator puts everything together in a flat structure instead of
a hierarchy of nested iterators. this should simplify the code and
provide better performance. It also enables more optimization since all
information are accessiable in one place.
Init evaluation shows about 6% improvement
Test Plan: db_test and db_bench
Reviewers: dhruba, igor, tnovak, sdong, haobo
Reviewed By: haobo
Subscribers: sdong, leveldb
Differential Revision: https://reviews.facebook.net/D18795
Summary: One more option to allow iterator refreshing when using normal iterator
Test Plan: ran db_bench
Reviewers: haobo, sdong, igor
Reviewed By: igor
Subscribers: leveldb
Differential Revision: https://reviews.facebook.net/D18849
Summary: Key size limit doesn't seem to be applicable anymore. Remove it.
Test Plan: run a couple of tests in db_bench
Reviewers: haobo, igor, yhchiang, dhruba
Reviewed By: igor
CC: leveldb
Differential Revision: https://reviews.facebook.net/D18723
Summary:
Newer gflags switched from `google` namespace to `gflags` namespace. See: https://github.com/facebook/rocksdb/issues/139 and https://github.com/facebook/rocksdb/issues/102
Unfortunately, they don't define any macro with their namespace, so we need to actually try to compile gflags with two different namespace to figure out which one is the correct one.
Test Plan: works in fbcode environemnt. I'll also try in ubutnu with newer gflags
Reviewers: dhruba
Reviewed By: dhruba
CC: leveldb
Differential Revision: https://reviews.facebook.net/D18537
Summary:
= Major Changes =
* Add a new mem-table representation, HashCuckooRep, which is based cuckoo hash.
Cuckoo hash uses multiple hash functions. This allows each key to have multiple
possible locations in the mem-table.
- Put: When insert a key, it will try to find whether one of its possible
locations is vacant and store the key. If none of its possible
locations are available, then it will kick out a victim key and
store at that location. The kicked-out victim key will then be
stored at a vacant space of its possible locations or kick-out
another victim. In this diff, the kick-out path (known as
cuckoo-path) is found using BFS, which guarantees to be the shortest.
- Get: Simply tries all possible locations of a key --- this guarantees
worst-case constant time complexity.
- Time complexity: O(1) for Get, and average O(1) for Put if the
fullness of the mem-table is below 80%.
- Default using two hash functions, the number of hash functions used
by the cuckoo-hash may dynamically increase if it fails to find a
short-enough kick-out path.
- Currently, HashCuckooRep does not support iteration and snapshots,
as our current main purpose of this is to optimize point access.
= Minor Changes =
* Add IsSnapshotSupported() to DB to indicate whether the current DB
supports snapshots. If it returns false, then DB::GetSnapshot() will
always return nullptr.
Test Plan:
Run existing tests. Will develop a test specifically for cuckoo hash in
the next diff.
Reviewers: sdong, haobo
Reviewed By: sdong
CC: leveldb, dhruba, igor
Differential Revision: https://reviews.facebook.net/D16155
Summary:
also add an override option total_order_iteration if you want to use full
iterator with prefix_extractor
Test Plan: make all check
Reviewers: igor, haobo, sdong, yhchiang
Reviewed By: haobo
CC: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D17805
Summary: While debugging Mac-only issue with ThreadLocalPtr, this was very useful. Let's print out stack trace in MAC OS, too.
Test Plan: Verified that somewhat useful stack trace was generated on mac. Will run PrintStack() on linux, too.
Reviewers: ljin, haobo
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D18189
Summary: Added benchmark functionality on the lines of folly/Benchmark.h
Test Plan: Added unit tests
Reviewers: igor, haobo, sdong, ljin, yhchiang, dhruba
Reviewed By: igor
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17973
Summary: multireadrandom is broken. Fix it
Test Plan: run it and see segfault has gone.
Reviewers: ljin
Reviewed By: ljin
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17781
Summary: This patch introduces a new parameter num_multi_db in db_bench. When this parameter is larger than 1, multiple DBs will be created. In all benchmarks, any operation applies to a random DB among them. This is to benchmark the performance of similar applications.
Test Plan: run db_bench on both of num_multi_db=0 and more.
Reviewers: haobo, ljin, igor
Reviewed By: igor
CC: igor, yhchiang, dhruba, nkg-, leveldb
Differential Revision: https://reviews.facebook.net/D17769
Summary: as title
Test Plan: ran it
Reviewers: igor, haobo, yhchiang
Reviewed By: yhchiang
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17751
Summary: as title
Test Plan: ran it
Reviewers: igor, haobo, yhchiang
Reviewed By: igor
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17655
Summary: Compiling for iOS has by default turned on -Wmissing-prototypes, which causes rocksdb to fail compiling. This diff turns on -Wmissing-prototypes in our compile options and cleans up all functions with missing prototypes.
Test Plan: compiles
Reviewers: dhruba, haobo, ljin, sdong
Reviewed By: ljin
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17649
Summary:
filluniquerandom is painfully slow due to the naive bitmap check to find
out if a key has been seen before. Majority of time is spent on searching
the last few keys. Split a giant BitSet to smaller ones so that we can
quickly check if a BitSet is full and thus can skip quickly.
It used to take over one hour to filluniquerandom for 100M keys, now it
takes about 10 mins.
Test Plan:
unit test
also verified correctness in db_bench and make sure all keys are
generated
Reviewers: igor, haobo, yhchiang
Reviewed By: igor
CC: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D17607
Summary:
clean up the db_bench a little bit. also avoid allocating memory for key
in the loop
Test Plan:
I verified a run with filluniquerandom & readrandom. Iterator seek will be used lot
to measure performance. Will fix whatever comes up
Reviewers: haobo, igor, yhchiang
Reviewed By: igor
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17559
Summary: per sdong's request, this will help processor prefetch on n->key case.
Test Plan: make all check
Reviewers: sdong, haobo, igor
Reviewed By: sdong
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17415
Summary:
By constraining the probes within cache line(s), we can improve the
cache miss rate thus performance. This probably only makes sense for
in-memory workload so defaults the option to off.
Numbers and comparision can be found in wiki:
https://our.intern.facebook.com/intern/wiki/index.php/Ljin/rocksdb_perf/2014_03_17#Bloom_Filter_Study
Test Plan: benchmarked this change substantially. Will run make all check as well
Reviewers: haobo, igor, dhruba, sdong, yhchiang
Reviewed By: haobo
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17133
