Commit Graph

2156 Commits

Author SHA1 Message Date
Igor Canadi
7f19bb93c6 Merge pull request #242 from tdfischer/perf-timer-destructors
Refactor PerfStepTimer to automatically stop on destruct
2014-09-02 13:06:40 -07:00
Feng Zhu
8438a19360 fix dropping column family bug
Summary: 1. db/db_impl.cc:2324 (DBImpl::BackgroundCompaction) should not raise bg_error_ when column family is dropped during compaction.

Test Plan: 1. db_stress

Reviewers: ljin, yhchiang, dhruba, igor, sdong

Reviewed By: igor

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22653
2014-09-02 12:25:58 -07:00
Torrie Fischer
6614a48418 Refactor PerfStepTimer to stop on destruct
This eliminates the need to remember to call PERF_TIMER_STOP when a section has
been timed. This allows more useful design with the perf timers and enables
possible return value optimizations. Simplistic example:

class Foo {
  public:
    Foo(int v) : m_v(v);
  private:
    int m_v;
}

Foo makeFrobbedFoo(int *errno)
{
  *errno = 0;
  return Foo();
}

Foo bar(int *errno)
{
  PERF_TIMER_GUARD(some_timer);

  return makeFrobbedFoo(errno);
}

int main(int argc, char[] argv)
{
  Foo f;
  int errno;

  f = bar(&errno);

  if (errno)
    return -1;
  return 0;
}

After bar() is called, perf_context.some_timer would be incremented as if
Stop(&perf_context.some_timer) was called at the end, and the compiler is still
able to produce optimizations on the return value from makeFrobbedFoo() through
to main().
2014-09-02 12:04:22 -07:00
Igor Canadi
076bd01a29 Fix compile
Summary: gcc on our dev boxes is not happy about __attribute__((unused))

Test Plan: compiles now

Reviewers: sdong, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22707
2014-09-02 11:49:38 -07:00
Igor Canadi
990df99a61 Fix ios compile
Summary: We need to set contbuild for this :)

Test Plan: compiles

Reviewers: sdong, yhchiang, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22701
2014-09-02 10:50:15 -07:00
Igor Canadi
7dcadb1d37 Don't let flush preempt compaction in certain cases
Summary:
I have an application configured with 16 background threads. Write rates are high. L0->L1 compactions is very slow and it limits the concurrency of the system. While it's happening, other 15 threads are idle. However, when there is a need of a flush, that one thread busy with L0->L1 is doing flush, instead of any other 15 threads that are just sitting there.

This diff prevents that. If there are threads that are idle, we don't let flush preempt compaction.

Test Plan: Will run stress test

Reviewers: ljin, sdong, yhchiang

Reviewed By: sdong, yhchiang

Subscribers: dhruba, leveldb

Differential Revision: https://reviews.facebook.net/D22299
2014-09-02 08:34:54 -07:00
Igor Canadi
985a31cf0e Merge pull request #251 from nbougalis/master
Fix candidate file comparison when using path ids
2014-08-31 16:05:06 -04:00
Nik Bougalis
f09329cb01 Fix candidate file comparison when using path ids 2014-08-31 00:54:15 -07:00
Lei Jin
7e9f28cb23 limit max bytes that can be read/written per pread/write syscall
Summary:
BlockBasedTable sst file size can grow to a large size when universal
compaction is used. When index block exceeds 2G, pread seems to fail and
return truncated data and causes "trucated block" error. I tried to use
```
  #define _FILE_OFFSET_BITS 64
```
But the problem still persists. Splitting a big write/read into smaller
batches seems to solve the problem.

Test Plan:
successfully compacted a case with resulting sst file at ~90G (2.1G
index block size)

Reviewers: yhchiang, igor, sdong

Reviewed By: sdong

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22569
2014-08-29 21:21:49 -07:00
Radheshyam Balasundaram
d20b8cfaa1 Improve Cuckoo Table Reader performance. Inlined hash function and number of buckets a power of two.
Summary:
Use inlined hash functions instead of function pointer. Make number of buckets a power of two and use bitwise and instead of mod.
After these changes, we get almost 50% improvement in performance.

Results:
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.231us (4.3 Mqps) with batch size of 0
Time taken per op is 0.229us (4.4 Mqps) with batch size of 0
Time taken per op is 0.185us (5.4 Mqps) with batch size of 0
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.108us (9.3 Mqps) with batch size of 10
Time taken per op is 0.100us (10.0 Mqps) with batch size of 10
Time taken per op is 0.103us (9.7 Mqps) with batch size of 10
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.101us (9.9 Mqps) with batch size of 25
Time taken per op is 0.098us (10.2 Mqps) with batch size of 25
Time taken per op is 0.097us (10.3 Mqps) with batch size of 25
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.100us (10.0 Mqps) with batch size of 50
Time taken per op is 0.097us (10.3 Mqps) with batch size of 50
Time taken per op is 0.097us (10.3 Mqps) with batch size of 50
With 120000000 items, utilization is 89.41%, number of hash functions: 2.
Time taken per op is 0.102us (9.8 Mqps) with batch size of 100
Time taken per op is 0.098us (10.2 Mqps) with batch size of 100
Time taken per op is 0.115us (8.7 Mqps) with batch size of 100

With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.201us (5.0 Mqps) with batch size of 0
Time taken per op is 0.155us (6.5 Mqps) with batch size of 0
Time taken per op is 0.152us (6.6 Mqps) with batch size of 0
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.089us (11.3 Mqps) with batch size of 10
Time taken per op is 0.084us (11.9 Mqps) with batch size of 10
Time taken per op is 0.086us (11.6 Mqps) with batch size of 10
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.087us (11.5 Mqps) with batch size of 25
Time taken per op is 0.085us (11.7 Mqps) with batch size of 25
Time taken per op is 0.093us (10.8 Mqps) with batch size of 25
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.094us (10.6 Mqps) with batch size of 50
Time taken per op is 0.094us (10.7 Mqps) with batch size of 50
Time taken per op is 0.093us (10.8 Mqps) with batch size of 50
With 100000000 items, utilization is 74.51%, number of hash functions: 2.
Time taken per op is 0.092us (10.9 Mqps) with batch size of 100
Time taken per op is 0.089us (11.2 Mqps) with batch size of 100
Time taken per op is 0.088us (11.3 Mqps) with batch size of 100

With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.154us (6.5 Mqps) with batch size of 0
Time taken per op is 0.168us (6.0 Mqps) with batch size of 0
Time taken per op is 0.190us (5.3 Mqps) with batch size of 0
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.081us (12.4 Mqps) with batch size of 10
Time taken per op is 0.077us (13.0 Mqps) with batch size of 10
Time taken per op is 0.083us (12.1 Mqps) with batch size of 10
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 25
Time taken per op is 0.073us (13.7 Mqps) with batch size of 25
Time taken per op is 0.073us (13.7 Mqps) with batch size of 25
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.076us (13.1 Mqps) with batch size of 50
Time taken per op is 0.072us (13.8 Mqps) with batch size of 50
Time taken per op is 0.072us (13.8 Mqps) with batch size of 50
With 80000000 items, utilization is 59.60%, number of hash functions: 2.
Time taken per op is 0.077us (13.0 Mqps) with batch size of 100
Time taken per op is 0.074us (13.6 Mqps) with batch size of 100
Time taken per op is 0.073us (13.6 Mqps) with batch size of 100

With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.190us (5.3 Mqps) with batch size of 0
Time taken per op is 0.186us (5.4 Mqps) with batch size of 0
Time taken per op is 0.184us (5.4 Mqps) with batch size of 0
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.079us (12.7 Mqps) with batch size of 10
Time taken per op is 0.070us (14.2 Mqps) with batch size of 10
Time taken per op is 0.072us (14.0 Mqps) with batch size of 10
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 25
Time taken per op is 0.072us (14.0 Mqps) with batch size of 25
Time taken per op is 0.071us (14.1 Mqps) with batch size of 25
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.082us (12.1 Mqps) with batch size of 50
Time taken per op is 0.071us (14.1 Mqps) with batch size of 50
Time taken per op is 0.073us (13.6 Mqps) with batch size of 50
With 70000000 items, utilization is 52.15%, number of hash functions: 2.
Time taken per op is 0.080us (12.5 Mqps) with batch size of 100
Time taken per op is 0.077us (13.0 Mqps) with batch size of 100
Time taken per op is 0.078us (12.8 Mqps) with batch size of 100

Test Plan:
make check all
make valgrind_check
make asan_check

Reviewers: sdong, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22539
2014-08-29 19:06:15 -07:00
Tomislav Novak
0f9c43ea36 ForwardIterator: reset incomplete iterators on Seek()
Summary:
When reading from kBlockCacheTier, ForwardIterator's internal child iterators
may end up in the incomplete state (read was unable to complete without doing
disk I/O). `ForwardIterator::status()` will correctly report that; however, the
iterator may be stuck in that state until all sub-iterators are rebuilt:

  * `NeedToSeekImmutable()` may return false even if some sub-iterators are
    incomplete
  * one of the child iterators may be an empty iterator without any state other
    that the kIncomplete status (created using `NewErrorIterator()`); seeking on
    any such iterator has no effect -- we need to construct it again

Akin to rebuilding iterators after a superversion bump, this diff makes forward
iterator reset all incomplete child iterators when `Seek()` or `Next()` are
called.

Test Plan: TEST_TMPDIR=/dev/shm/rocksdbtest ROCKSDB_TESTS=TailingIterator ./db_test

Reviewers: igor, sdong, ljin

Reviewed By: ljin

Subscribers: lovro, march, leveldb

Differential Revision: https://reviews.facebook.net/D22575
2014-08-29 16:21:29 -07:00
Lei Jin
722d80c374 reduce recordTick overhead in compaction loop
Summary: It is too expensive to bump ticker to every key/vaue pair

Test Plan: make release

Reviewers: sdong, yhchiang, igor

Reviewed By: igor

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22527
2014-08-29 09:51:09 -07:00
Igor Canadi
22a0a60dc4 Merge pull request #250 from wankai/master
delete unused struct Options
2014-08-29 09:53:18 -04:00
Wankai Zhang
be25ee44fe delete unused struct Options 2014-08-29 17:31:04 +08:00
Igor Canadi
0c26e76b28 Merge pull request #237 from tdfischer/tdfischer/faster-timeout-test
test: db: fix test to have a smaller timeout for when it runs on faster ...
2014-08-28 20:40:10 -04:00
Feng Zhu
1d23b5c470 remove_internal_filter_policy
Summary:
1. remove class InternalFilterPolicy in db/dbformat.h
2. Transformation from internal key to user key is done in filter_block.cc
3. This is a preparation for patch D20979

Test Plan:
make all check
valgrind ./db_test

Reviewers: igor, yhchiang, ljin, sdong

Reviewed By: sdong

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22509
2014-08-28 17:06:29 -07:00
Igor Canadi
2a8faf797c Compact SpatialDB as we go, not at the end 2014-08-28 11:32:49 -07:00
Radheshyam Balasundaram
7f71448388 Implementing a cache friendly version of Cuckoo Hash
Summary: This implements a cache friendly version of Cuckoo Hash in which, in case of collission, we try to insert in next few locations. The size of the neighborhood to check is taken as an input parameter in builder and stored in the table.

Test Plan:
make check all
cuckoo_table_{db,reader,builder}_test

Reviewers: sdong, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22455
2014-08-28 10:42:23 -07:00
Igor Canadi
d977e55596 Don't let other compactions run when manual compaction runs
Summary:
Based on discussions from t4982833. This is just a short-term fix, I plan to revamp manual compaction process as part of t4982812.

Also, I think we should schedule automatic compactions at the very end of manual compactions, not when we're done with one level. I made that change as part of this diff. Let me know if you disagree.

Test Plan: make check for now

Reviewers: sdong, tnovak, yhchiang, ljin

Reviewed By: yhchiang

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22401
2014-08-28 13:06:28 -04:00
Igor Canadi
d5bd6c772b Fix ios compile
Summary: No __thread for ios.

Test Plan: compile works for ios now

Reviewers: ljin, dhruba

Reviewed By: dhruba

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22491
2014-08-28 12:46:05 -04:00
Igor Canadi
6b46f78434 Merge pull request #248 from wankai/master
BlockBuilder typo improvement
2014-08-28 09:42:31 -04:00
Wankai Zhang
528a11c635 Update block_builder.h
more c++11 way noncopyable and keep parameter's name of constructor consistent
2014-08-28 13:37:10 +08:00
Igor Canadi
536e9973e3 Remove assert in vector rep
Summary: This assert makes Insert O(n^2) instead of O(n) in debug mode. Memtable insert is in the critical path. No need to assert uniqunnes of the key here, since we're adding a sequence number to it anyway.

Test Plan: none

Reviewers: sdong, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22443
2014-08-27 11:05:41 -07:00
Radheshyam Balasundaram
4142a3e783 Adding a user comparator for comparing Uint64 slices.
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
2014-08-27 10:39:31 -07:00
Igor Canadi
1913ce27b9 more concurrent flushes in SpatialDB 2014-08-27 08:48:31 -07:00
Igor Canadi
808e809366 Adjust SpatialDB column family options 2014-08-27 07:56:10 -07:00
Igor Canadi
0c39f54dfb Use Vector memtable when bulk loading SpatialDB 2014-08-26 19:23:09 -07:00
Radheshyam Balasundaram
b6fd7811eb Don't do memtable lookup in db_impl_readonly if memtables are empty while opening db.
Summary: In DBImpl::Recover method, while loading memtables, also check if memtables are empty. Use this in DBImplReadonly to determine whether to lookup memtable or not.

Test Plan:
db_test
make check all

Reviewers: sdong, yhchiang, ljin, igor

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22281
2014-08-26 17:19:03 -07:00
Stanislau Hlebik
9dcb75b6d9 Add is-file-deletions-enabled property
Summary:
Add property 'rocksdb.is-file-deletions-enable'
	 which equals disable_delete_obsole_file_

Test Plan: make all check

Reviewers: sdong

Reviewed By: sdong

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22119
2014-08-26 16:26:29 -07:00
Lei Jin
1755581f19 improve OptimizeForPointLookup()
Summary: also fix HISTORY.md

Test Plan: make all check

Reviewers: sdong, yhchiang, igor

Reviewed By: igor

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22437
2014-08-26 14:15:00 -07:00
Igor Canadi
d9c0785812 Fix assertion in PosixRandomAccessFile
Summary:
See https://github.com/facebook/rocksdb/issues/244#issuecomment-53372297
Also see this: https://github.com/facebook/rocksdb/blob/master/util/env_posix.cc#L1075

Test Plan: compiles

Reviewers: yhchiang, ljin, sdong

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22419
2014-08-26 15:28:36 -04:00
Lei Jin
bda6f3363d fix valgrind error in c_test caused by BlockBasedTableOptions
Summary:
It was creating BlockBasedTableOptions object in a loop without calling
destroy()

Test Plan: valgrind ./c_test --leak-check=full --show-reachable=yes

Reviewers: sdong, igor

Reviewed By: igor

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22431
2014-08-26 09:57:25 -07:00
Torrie Fischer
0db6b028e7 Update timeout to 50ms instead of 3. 2014-08-26 09:38:45 -07:00
Igor Canadi
ff6ec0eb17 Optimize SpatialDB
Summary:
Two things:
1. Use hash-based index for data column family
2. Use Get() instead of Iterator Seek() when DB is opened read-only

Test Plan: added read-only test in unit test

Reviewers: yinwang

Reviewed By: yinwang

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22323
2014-08-25 17:50:18 -07:00
Lei Jin
23861857c4 ReadOptions.total_order_seek to allow total order seek for block-based table when hash index is enabled
Summary: as title

Test Plan: table_test

Reviewers: igor, yhchiang, sdong

Reviewed By: sdong

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22239
2014-08-25 16:14:30 -07:00
Lei Jin
a98badff16 print table options
Summary: Add a virtual function in table factory that will print table options

Test Plan: make release

Reviewers: igor, yhchiang, sdong

Reviewed By: sdong

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22149
2014-08-25 14:24:09 -07:00
Lei Jin
66f62e5c78 JNI changes corresponding to BlockBasedTableOptions migration
Summary: as title

Test Plan:
tested on my mac
make rocksdbjava
make jtest

Reviewers: sdong, igor, yhchiang

Reviewed By: yhchiang

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D21963
2014-08-25 14:22:55 -07:00
Lei Jin
384400128f move block based table related options BlockBasedTableOptions
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
2014-08-25 14:22:05 -07:00
Igor Canadi
17b54aea53 Merge pull request #243 from andybons/patch-1
Add missing include to use std::unique_ptr
2014-08-24 10:54:04 -04:00
Andrew Bonventre
050869177e Add missing include to use std::unique_ptr
This was causing issues when including this header from another file.
2014-08-23 13:02:21 -04:00
Igor Canadi
42ea795209 Fix concurrency issue in CompactionPicker
Summary:
I am currently working on a project that uses RocksDB. While debugging some perf issues, I came up across interesting compaction concurrency issue. Namely, I had 15 idle threads and a good comapction to do, but CompactionPicker returned "Compaction nothing to do". Here's how Internal stats looked:

    2014/08/22-08:08:04.551982 7fc7fc3f5700 ------- DUMPING STATS -------
    2014/08/22-08:08:04.552000 7fc7fc3f5700
    ** Compaction Stats [default] **
    Level   Files   Size(MB) Score Read(GB)  Rn(GB) Rnp1(GB) Write(GB) Wnew(GB) RW-Amp W-Amp Rd(MB/s) Wr(MB/s)  Rn(cnt) Rnp1(cnt) Wnp1(cnt) Wnew(cnt)  Comp(sec) Comp(cnt) Avg(sec) Stall(sec) Stall(cnt) Avg(ms)
    ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      L0     7/5        353   1.0      0.0     0.0      0.0       2.3      2.3    0.0   0.0      0.0      9.4        0         0         0         0        247        46    5.359       8.53          1 8526.25
      L1     2/2         86   1.3      2.6     1.9      0.7       2.6      1.9    2.7   1.3     24.3     24.0       39        19        71        52        109        11    9.938       0.00          0    0.00
      L2    26/0        833   1.3      5.7     1.7      4.0       5.2      1.2    6.3   3.0     15.6     14.2       47       112       147        35        373        44    8.468       0.00          0    0.00
      L3    12/0        505   0.1      0.0     0.0      0.0       0.0      0.0    0.0   0.0      0.0      0.0        0         0         0         0          0         0    0.000       0.00          0    0.00
     Sum    47/7       1778   0.0      8.3     3.6      4.6      10.0      5.4    8.1   4.4     11.6     14.1       86       131       218        87        728       101    7.212       8.53          1 8526.25
     Int     0/0          0   0.0      2.4     0.8      1.6       2.7      1.2   11.5   6.1     12.0     13.6       20        43        63        20        203        23    8.845       0.00          0    0.00
    Flush(GB): accumulative 2.266, interval 0.444
    Stalls(secs): 0.000 level0_slowdown, 0.000 level0_numfiles, 8.526 memtable_compaction, 0.000 leveln_slowdown_soft, 0.000 leveln_slowdown_hard
    Stalls(count): 0 level0_slowdown, 0 level0_numfiles, 1 memtable_compaction, 0 leveln_slowdown_soft, 0 leveln_slowdown_hard

    ** DB Stats **
    Uptime(secs): 336.8 total, 60.4 interval
    Cumulative writes: 61584000 writes, 6480589 batches, 9.5 writes per batch, 1.39 GB user ingest
    Cumulative WAL: 0 writes, 0 syncs, 0.00 writes per sync, 0.00 GB written
    Interval writes: 11235257 writes, 1175050 batches, 9.6 writes per batch, 259.9 MB user ingest
    Interval WAL: 0 writes, 0 syncs, 0.00 writes per sync, 0.00 MB written

To see what happened, go here: 47b452cfcf/db/compaction_picker.cc (L430)
* The for loop started with level 1, because it has the worst score.
* PickCompactionBySize on L429 returned nullptr because all files were being compacted
* ExpandWhileOverlapping(c) returned true (because that's what it does when it gets nullptr!?)
* for loop break-ed, never trying compactions for level 2 :( :(

This bug was present at least since January. I have no idea how we didn't find this sooner.

Test Plan:
Unit testing compaction picker is hard. I tested this by running my service and observing L0->L1 and L2->L3 compactions in parallel. However, for long-term, I opened the task #4968469. @yhchiang is currently refactoring CompactionPicker, hopefully the new version will be unit-testable ;)

Here's how my compactions look like after the patch:

    2014/08/22-08:50:02.166699 7f3400ffb700 ------- DUMPING STATS -------
    2014/08/22-08:50:02.166722 7f3400ffb700
    ** Compaction Stats [default] **
    Level   Files   Size(MB) Score Read(GB)  Rn(GB) Rnp1(GB) Write(GB) Wnew(GB) RW-Amp W-Amp Rd(MB/s) Wr(MB/s)  Rn(cnt) Rnp1(cnt) Wnp1(cnt) Wnew(cnt)  Comp(sec) Comp(cnt) Avg(sec) Stall(sec) Stall(cnt) Avg(ms)
    ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      L0     8/5        404   1.5      0.0     0.0      0.0       4.3      4.3    0.0   0.0      0.0      9.6        0         0         0         0        463        88    5.260       0.00          0    0.00
      L1     2/2         60   0.9      4.8     3.9      0.8       4.7      3.9    2.4   1.2     23.9     23.6       80        23       131       108        204        19   10.747       0.00          0    0.00
      L2    23/3        697   1.0     11.6     3.5      8.1      10.9      2.8    6.4   3.1     17.7     16.6       95       242       317        75        669        92    7.268       0.00          0    0.00
      L3    58/14      2207   0.3      6.2     1.6      4.6       5.9      1.3    7.4   3.6     14.6     13.9       43       121       159        38        436        36   12.106       0.00          0    0.00
     Sum    91/24      3368   0.0     22.5     9.1     13.5      25.8     12.4   11.2   6.0     13.0     14.9      218       386       607       221       1772       235    7.538       0.00          0    0.00
     Int     0/0          0   0.0      3.2     0.9      2.3       3.6      1.3   15.3   8.0     12.4     13.7       24        66        89        23        266        27    9.838       0.00          0    0.00
    Flush(GB): accumulative 4.336, interval 0.444
    Stalls(secs): 0.000 level0_slowdown, 0.000 level0_numfiles, 0.000 memtable_compaction, 0.000 leveln_slowdown_soft, 0.000 leveln_slowdown_hard
    Stalls(count): 0 level0_slowdown, 0 level0_numfiles, 0 memtable_compaction, 0 leveln_slowdown_soft, 0 leveln_slowdown_hard

    ** DB Stats **
    Uptime(secs): 577.7 total, 60.1 interval
    Cumulative writes: 116960736 writes, 11966220 batches, 9.8 writes per batch, 2.64 GB user ingest
    Cumulative WAL: 0 writes, 0 syncs, 0.00 writes per sync, 0.00 GB written
    Interval writes: 11643735 writes, 1206136 batches, 9.7 writes per batch, 269.2 MB user ingest
    Interval WAL: 0 writes, 0 syncs, 0.00 writes per sync, 0.00 MB written

Yay for concurrent L0->L1 and L2->L3 compactions!

Reviewers: sdong, yhchiang, ljin

Reviewed By: yhchiang

Subscribers: yhchiang, leveldb

Differential Revision: https://reviews.facebook.net/D22305
2014-08-22 11:32:40 -07:00
Siying Dong
bb530c0f47 Merge pull request #240 from ShaoYuZhang/master
Fix compilation issue on OSX
2014-08-21 18:16:15 -07:00
Shao Yu Zhang
f76eda74d6 Fix compilation issue on OSX 2014-08-21 18:11:33 -07:00
Radheshyam Balasundaram
08be7f5266 Implement Prepare method in CuckooTableReader
Summary:
- Implement Prepare method
- Rewrite performance tests in cuckoo_table_reader_test to write new file only if one doesn't already exist.
- Add performance tests for batch lookup along with prefetching.

Test Plan:
./cuckoo_table_reader_test --enable_perf
Results (We get better results if we used int64 comparator instead of string comparator (TBD in future diffs)):
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.208us (4.8 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.182us (5.5 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.161us (6.2 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.161us (6.2 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.163us (6.1 Mqps) with batch size of 100

With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.252us (4.0 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.192us (5.2 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.195us (5.1 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.191us (5.2 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.194us (5.1 Mqps) with batch size of 100

With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.228us (4.4 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.185us (5.4 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.186us (5.4 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.188us (5.3 Mqps) with batch size of 100

With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.325us (3.1 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.196us (5.1 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.199us (5.0 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.196us (5.1 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.209us (4.8 Mqps) with batch size of 100

Reviewers: sdong, yhchiang, igor, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22167
2014-08-20 18:35:35 -07:00
Yueh-Hsuan Chiang
47b452cfcf Fix the error of c_test.c
Summary:
Fix the error of c_test.c

Test Plan:
make c_test
./c_test
2014-08-20 17:05:29 -07:00
Yueh-Hsuan Chiang
562b7a1f28 Add missing implementaiton of SanitizeDBOptions in simple_table_db_test.cc
Summary:
Add missing implementaiton of SanitizeDBOptions in simple_table_db_test.cc

Test Plan:
make simple_table_db_test.cc
2014-08-20 16:33:25 -07:00
Yueh-Hsuan Chiang
63a2215c63 Improve Options sanitization and add MmapReadRequired() to TableFactory
Summary:
Currently, PlainTable must use mmap_reads.  When PlainTable is used but
allow_mmap_reads is not set, rocksdb will fail in flush.

This diff improve Options sanitization and add MmapReadRequired() to
TableFactory.

Test Plan:
export ROCKSDB_TESTS=PlainTableOptionsSanitizeTest
make db_test -j32
./db_test

Reviewers: sdong, ljin

Reviewed By: ljin

Subscribers: you, leveldb

Differential Revision: https://reviews.facebook.net/D21939
2014-08-20 15:53:39 -07:00
Jonah Cohen
e173bf9c19 Eliminate VersionSet memory leak
Summary:
ManifestDumpCommand::DoCommand was allocating a VersionSet and never
freeing it.

Test Plan: make

Reviewers: igor

Reviewed By: igor

Differential Revision: https://reviews.facebook.net/D22221
2014-08-20 13:52:03 -07:00
sdong
10720a5587 Revert the unintended change that DestroyDB() doesn't clean up info logs.
Summary: A previous change triggered a change by mistake: DestroyDB() will keep info logs under DB directory. Revert the unintended change.

Test Plan: Add a unit test case to verify it.

Reviewers: ljin, yhchiang, igor

Reviewed By: igor

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22209
2014-08-20 12:07:32 -07:00
Igor Canadi
01cbdd2aae Optimize storage parameters for spatialDB
Summary: We need to start compression at level 1, while OptimizeForLevelComapaction() only sets up rocksdb to start compressing at level 2. I also adjusted some other things.

Test Plan: compiles

Reviewers: yinwang

Reviewed By: yinwang

Differential Revision: https://reviews.facebook.net/D22203
2014-08-20 11:14:01 -07:00