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383 Commits (7d26e4c5a39edb7e805621ccd0b0fec46b9c8f9d)
| Author | SHA1 | Message | Date |
|---|---|---|---|
sdong
|
48fe921754 |
Run clang format against files under tools/ and db_stress_tool/ (#10868)
Summary: Some lines of .h and .cc files are not properly fomatted. Clear them up with clang format. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10868 Test Plan: Watch existing CI to pass Reviewed By: ajkr Differential Revision: D40683485 fbshipit-source-id: 491fbb78b2cdcb948164f306829909ad816d5d0b |
2 years ago |
|
Jay Zhuang
|
8124bc3526 |
Enable preclude_last_level_data_seconds in stress test (#10824)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10824 Reviewed By: siying Differential Revision: D40390535 Pulled By: jay-zhuang fbshipit-source-id: 700803a1aff8a1e77c038740d87931577e79bcf6 |
2 years ago |
|
Peter Dillinger
|
0f91c72adc |
Call experimental new clock cache HyperClockCache (#10684)
Summary: This change establishes a distinctive name for the experimental new lock-free clock cache (originally developed by guidotag and revamped in PR https://github.com/facebook/rocksdb/issues/10626). A few reasons: * We want to make it clear that this is a fundamentally different implementation vs. the old clock cache, to avoid people saying "I already tried clock cache." * We want to highlight the key feature: it's fast (especially under parallel load) * Because it requires an estimated charge per entry, it is not drop-in API compatible with old clock cache. This estimate might always be required for highest performance, and giving it a distinct name should reduce confusion about the distinct API requirements. * We might develop a variant requiring the same estimate parameter but with LRU eviction. In that case, using the name HyperLRUCache should make things more clear. (FastLRUCache is just a prototype that might soon be removed.) Some API detail: * To reduce copy-pasting parameter lists, etc. as in LRUCache construction, I have a `MakeSharedCache()` function on `HyperClockCacheOptions` instead of `NewHyperClockCache()`. * Changes -cache_type=clock_cache to -cache_type=hyper_clock_cache for applicable tools. I think this is more consistent / sustainable for reasons already stated. For performance tests see https://github.com/facebook/rocksdb/pull/10626 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10684 Test Plan: no interesting functional changes; tests updated Reviewed By: anand1976 Differential Revision: D39547800 Pulled By: pdillinger fbshipit-source-id: 5c0fe1b5cf3cb680ab369b928c8569682b9795bf |
2 years ago |
|
Peter Dillinger
|
5724348689 |
Revamp, optimize new experimental clock cache (#10626)
Summary:
* Consolidates most metadata into a single word per slot so that more
can be accomplished with a single atomic update. In the common case,
Lookup was previously about 4 atomic updates, now just 1 atomic update.
Common case Release was previously 1 atomic read + 1 atomic update,
now just 1 atomic update.
* Eliminate spins / waits / yields, which likely threaten some "lock free"
benefits. Compare-exchange loops are only used in explicit Erase, and
strict_capacity_limit=true Insert. Eviction uses opportunistic compare-
exchange.
* Relaxes some aggressiveness and guarantees. For example,
* Duplicate Inserts will sometimes go undetected and the shadow duplicate
will age out with eviction.
* In many cases, the older Inserted value for a given cache key will be kept
(i.e. Insert does not support overwrite).
* Entries explicitly erased (rather than evicted) might not be freed
immediately in some rare cases.
* With strict_capacity_limit=false, capacity limit is not tracked/enforced as
precisely as LRUCache, but is self-correcting and should only deviate by a
very small number of extra or fewer entries.
* Use smaller "computed default" number of cache shards in many cases,
because benefits to larger usage tracking / eviction pools outweigh the small
cost of more lock-free atomic contention. The improvement in CPU and I/O
is dramatic in some limit-memory cases.
* Even without the sharding change, the eviction algorithm is likely more
effective than LRU overall because it's more stateful, even though the
"hot path" state tracking for it is essentially free with ref counting. It
is like a generalized CLOCK with aging (see code comments). I don't have
performance numbers showing a specific improvement, but in theory, for a
Poisson access pattern to each block, keeping some state allows better
estimation of time to next access (Poisson interval) than strict LRU. The
bounded randomness in CLOCK can also reduce "cliff" effect for repeated
range scans approaching and exceeding cache size.
## Hot path algorithm comparison
Rough descriptions, focusing on number and kind of atomic operations:
* Old `Lookup()` (2-5 atomic updates per probe):
```
Loop:
Increment internal ref count at slot
If possible hit:
Check flags atomic (and non-atomic fields)
If cache hit:
Three distinct updates to 'flags' atomic
Increment refs for internal-to-external
Return
Decrement internal ref count
while atomic read 'displacements' > 0
```
* New `Lookup()` (1-2 atomic updates per probe):
```
Loop:
Increment acquire counter in meta word (optimistic)
If visible entry (already read meta word):
If match (read non-atomic fields):
Return
Else:
Decrement acquire counter in meta word
Else if invisible entry (rare, already read meta word):
Decrement acquire counter in meta word
while atomic read 'displacements' > 0
```
* Old `Release()` (1 atomic update, conditional on atomic read, rarely more):
```
Read atomic ref count
If last reference and invisible (rare):
Use CAS etc. to remove
Return
Else:
Decrement ref count
```
* New `Release()` (1 unconditional atomic update, rarely more):
```
Increment release counter in meta word
If last reference and invisible (rare):
Use CAS etc. to remove
Return
```
## Performance test setup
Build DB with
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16
```
Test with
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom -readonly -num=30000000 -bloom_bits=16 -cache_index_and_filter_blocks=1 -cache_size=${CACHE_MB}000000 -duration 60 -threads=$THREADS -statistics
```
Numbers on a single socket Skylake Xeon system with 48 hardware threads, DEBUG_LEVEL=0 PORTABLE=0. Very similar story on a dual socket system with 80 hardware threads. Using (every 2nd) Fibonacci MB cache sizes to sample the territory between powers of two. Configurations:
base: LRUCache before this change, but with db_bench change to default cache_numshardbits=-1 (instead of fixed at 6)
folly: LRUCache before this change, with folly enabled (distributed mutex) but on an old compiler (sorry)
gt_clock: experimental ClockCache before this change
new_clock: experimental ClockCache with this change
## Performance test results
First test "hot path" read performance, with block cache large enough for whole DB:
4181MB 1thread base -> kops/s: 47.761
4181MB 1thread folly -> kops/s: 45.877
4181MB 1thread gt_clock -> kops/s: 51.092
4181MB 1thread new_clock -> kops/s: 53.944
4181MB 16thread base -> kops/s: 284.567
4181MB 16thread folly -> kops/s: 249.015
4181MB 16thread gt_clock -> kops/s: 743.762
4181MB 16thread new_clock -> kops/s: 861.821
4181MB 24thread base -> kops/s: 303.415
4181MB 24thread folly -> kops/s: 266.548
4181MB 24thread gt_clock -> kops/s: 975.706
4181MB 24thread new_clock -> kops/s: 1205.64 (~= 24 * 53.944)
4181MB 32thread base -> kops/s: 311.251
4181MB 32thread folly -> kops/s: 274.952
4181MB 32thread gt_clock -> kops/s: 1045.98
4181MB 32thread new_clock -> kops/s: 1370.38
4181MB 48thread base -> kops/s: 310.504
4181MB 48thread folly -> kops/s: 268.322
4181MB 48thread gt_clock -> kops/s: 1195.65
4181MB 48thread new_clock -> kops/s: 1604.85 (~= 24 * 1.25 * 53.944)
4181MB 64thread base -> kops/s: 307.839
4181MB 64thread folly -> kops/s: 272.172
4181MB 64thread gt_clock -> kops/s: 1204.47
4181MB 64thread new_clock -> kops/s: 1615.37
4181MB 128thread base -> kops/s: 310.934
4181MB 128thread folly -> kops/s: 267.468
4181MB 128thread gt_clock -> kops/s: 1188.75
4181MB 128thread new_clock -> kops/s: 1595.46
Whether we have just one thread on a quiet system or an overload of threads, the new version wins every time in thousand-ops per second, sometimes dramatically so. Mutex-based implementation quickly becomes contention-limited. New clock cache shows essentially perfect scaling up to number of physical cores (24), and then each hyperthreaded core adding about 1/4 the throughput of an additional physical core (see 48 thread case). Block cache miss rates (omitted above) are negligible across the board. With partitioned instead of full filters, the maximum speed-up vs. base is more like 2.5x rather than 5x.
Now test a large block cache with low miss ratio, but some eviction is required:
1597MB 1thread base -> kops/s: 46.603 io_bytes/op: 1584.63 miss_ratio: 0.0201066 max_rss_mb: 1589.23
1597MB 1thread folly -> kops/s: 45.079 io_bytes/op: 1530.03 miss_ratio: 0.019872 max_rss_mb: 1550.43
1597MB 1thread gt_clock -> kops/s: 48.711 io_bytes/op: 1566.63 miss_ratio: 0.0198923 max_rss_mb: 1691.4
1597MB 1thread new_clock -> kops/s: 51.531 io_bytes/op: 1589.07 miss_ratio: 0.0201969 max_rss_mb: 1583.56
1597MB 32thread base -> kops/s: 301.174 io_bytes/op: 1439.52 miss_ratio: 0.0184218 max_rss_mb: 1656.59
1597MB 32thread folly -> kops/s: 273.09 io_bytes/op: 1375.12 miss_ratio: 0.0180002 max_rss_mb: 1586.8
1597MB 32thread gt_clock -> kops/s: 904.497 io_bytes/op: 1411.29 miss_ratio: 0.0179934 max_rss_mb: 1775.89
1597MB 32thread new_clock -> kops/s: 1182.59 io_bytes/op: 1440.77 miss_ratio: 0.0185449 max_rss_mb: 1636.45
1597MB 128thread base -> kops/s: 309.91 io_bytes/op: 1438.25 miss_ratio: 0.018399 max_rss_mb: 1689.98
1597MB 128thread folly -> kops/s: 267.605 io_bytes/op: 1394.16 miss_ratio: 0.0180286 max_rss_mb: 1631.91
1597MB 128thread gt_clock -> kops/s: 691.518 io_bytes/op: 9056.73 miss_ratio: 0.0186572 max_rss_mb: 1982.26
1597MB 128thread new_clock -> kops/s: 1406.12 io_bytes/op: 1440.82 miss_ratio: 0.0185463 max_rss_mb: 1685.63
610MB 1thread base -> kops/s: 45.511 io_bytes/op: 2279.61 miss_ratio: 0.0290528 max_rss_mb: 615.137
610MB 1thread folly -> kops/s: 43.386 io_bytes/op: 2217.29 miss_ratio: 0.0289282 max_rss_mb: 600.996
610MB 1thread gt_clock -> kops/s: 46.207 io_bytes/op: 2275.51 miss_ratio: 0.0290057 max_rss_mb: 637.934
610MB 1thread new_clock -> kops/s: 48.879 io_bytes/op: 2283.1 miss_ratio: 0.0291253 max_rss_mb: 613.5
610MB 32thread base -> kops/s: 306.59 io_bytes/op: 2250 miss_ratio: 0.0288721 max_rss_mb: 683.402
610MB 32thread folly -> kops/s: 269.176 io_bytes/op: 2187.86 miss_ratio: 0.0286938 max_rss_mb: 628.742
610MB 32thread gt_clock -> kops/s: 855.097 io_bytes/op: 2279.26 miss_ratio: 0.0288009 max_rss_mb: 733.062
610MB 32thread new_clock -> kops/s: 1121.47 io_bytes/op: 2244.29 miss_ratio: 0.0289046 max_rss_mb: 666.453
610MB 128thread base -> kops/s: 305.079 io_bytes/op: 2252.43 miss_ratio: 0.0288884 max_rss_mb: 723.457
610MB 128thread folly -> kops/s: 269.583 io_bytes/op: 2204.58 miss_ratio: 0.0287001 max_rss_mb: 676.426
610MB 128thread gt_clock -> kops/s: 53.298 io_bytes/op: 8128.98 miss_ratio: 0.0292452 max_rss_mb: 956.273
610MB 128thread new_clock -> kops/s: 1301.09 io_bytes/op: 2246.04 miss_ratio: 0.0289171 max_rss_mb: 788.812
The new version is still winning every time, sometimes dramatically so, and we can tell from the maximum resident memory numbers (which contain some noise, by the way) that the new cache is not cheating on memory usage. IMPORTANT: The previous generation experimental clock cache appears to hit a serious bottleneck in the higher thread count configurations, presumably due to some of its waiting functionality. (The same bottleneck is not seen with partitioned index+filters.)
Now we consider even smaller cache sizes, with higher miss ratios, eviction work, etc.
233MB 1thread base -> kops/s: 10.557 io_bytes/op: 227040 miss_ratio: 0.0403105 max_rss_mb: 247.371
233MB 1thread folly -> kops/s: 15.348 io_bytes/op: 112007 miss_ratio: 0.0372238 max_rss_mb: 245.293
233MB 1thread gt_clock -> kops/s: 6.365 io_bytes/op: 244854 miss_ratio: 0.0413873 max_rss_mb: 259.844
233MB 1thread new_clock -> kops/s: 47.501 io_bytes/op: 2591.93 miss_ratio: 0.0330989 max_rss_mb: 242.461
233MB 32thread base -> kops/s: 96.498 io_bytes/op: 363379 miss_ratio: 0.0459966 max_rss_mb: 479.227
233MB 32thread folly -> kops/s: 109.95 io_bytes/op: 314799 miss_ratio: 0.0450032 max_rss_mb: 400.738
233MB 32thread gt_clock -> kops/s: 2.353 io_bytes/op: 385397 miss_ratio: 0.048445 max_rss_mb: 500.688
233MB 32thread new_clock -> kops/s: 1088.95 io_bytes/op: 2567.02 miss_ratio: 0.0330593 max_rss_mb: 303.402
233MB 128thread base -> kops/s: 84.302 io_bytes/op: 378020 miss_ratio: 0.0466558 max_rss_mb: 1051.84
233MB 128thread folly -> kops/s: 89.921 io_bytes/op: 338242 miss_ratio: 0.0460309 max_rss_mb: 812.785
233MB 128thread gt_clock -> kops/s: 2.588 io_bytes/op: 462833 miss_ratio: 0.0509158 max_rss_mb: 1109.94
233MB 128thread new_clock -> kops/s: 1299.26 io_bytes/op: 2565.94 miss_ratio: 0.0330531 max_rss_mb: 361.016
89MB 1thread base -> kops/s: 0.574 io_bytes/op: 5.35977e+06 miss_ratio: 0.274427 max_rss_mb: 91.3086
89MB 1thread folly -> kops/s: 0.578 io_bytes/op: 5.16549e+06 miss_ratio: 0.27276 max_rss_mb: 96.8984
89MB 1thread gt_clock -> kops/s: 0.512 io_bytes/op: 4.13111e+06 miss_ratio: 0.242817 max_rss_mb: 119.441
89MB 1thread new_clock -> kops/s: 48.172 io_bytes/op: 2709.76 miss_ratio: 0.0346162 max_rss_mb: 100.754
89MB 32thread base -> kops/s: 5.779 io_bytes/op: 6.14192e+06 miss_ratio: 0.320399 max_rss_mb: 311.812
89MB 32thread folly -> kops/s: 5.601 io_bytes/op: 5.83838e+06 miss_ratio: 0.313123 max_rss_mb: 252.418
89MB 32thread gt_clock -> kops/s: 0.77 io_bytes/op: 3.99236e+06 miss_ratio: 0.236296 max_rss_mb: 396.422
89MB 32thread new_clock -> kops/s: 1064.97 io_bytes/op: 2687.23 miss_ratio: 0.0346134 max_rss_mb: 155.293
89MB 128thread base -> kops/s: 4.959 io_bytes/op: 6.20297e+06 miss_ratio: 0.323945 max_rss_mb: 823.43
89MB 128thread folly -> kops/s: 4.962 io_bytes/op: 5.9601e+06 miss_ratio: 0.319857 max_rss_mb: 626.824
89MB 128thread gt_clock -> kops/s: 1.009 io_bytes/op: 4.1083e+06 miss_ratio: 0.242512 max_rss_mb: 1095.32
89MB 128thread new_clock -> kops/s: 1224.39 io_bytes/op: 2688.2 miss_ratio: 0.0346207 max_rss_mb: 218.223
^ Now something interesting has happened: the new clock cache has gained a dramatic lead in the single-threaded case, and this is because the cache is so small, and full filters are so big, that dividing the cache into 64 shards leads to significant (random) imbalances in cache shards and excessive churn in imbalanced shards. This new clock cache only uses two shards for this configuration, and that helps to ensure that entries are part of a sufficiently big pool that their eviction order resembles the single-shard order. (This effect is not seen with partitioned index+filters.)
Even smaller cache size:
34MB 1thread base -> kops/s: 0.198 io_bytes/op: 1.65342e+07 miss_ratio: 0.939466 max_rss_mb: 48.6914
34MB 1thread folly -> kops/s: 0.201 io_bytes/op: 1.63416e+07 miss_ratio: 0.939081 max_rss_mb: 45.3281
34MB 1thread gt_clock -> kops/s: 0.448 io_bytes/op: 4.43957e+06 miss_ratio: 0.266749 max_rss_mb: 100.523
34MB 1thread new_clock -> kops/s: 1.055 io_bytes/op: 1.85439e+06 miss_ratio: 0.107512 max_rss_mb: 75.3125
34MB 32thread base -> kops/s: 3.346 io_bytes/op: 1.64852e+07 miss_ratio: 0.93596 max_rss_mb: 180.48
34MB 32thread folly -> kops/s: 3.431 io_bytes/op: 1.62857e+07 miss_ratio: 0.935693 max_rss_mb: 137.531
34MB 32thread gt_clock -> kops/s: 1.47 io_bytes/op: 4.89704e+06 miss_ratio: 0.295081 max_rss_mb: 392.465
34MB 32thread new_clock -> kops/s: 8.19 io_bytes/op: 3.70456e+06 miss_ratio: 0.20826 max_rss_mb: 519.793
34MB 128thread base -> kops/s: 2.293 io_bytes/op: 1.64351e+07 miss_ratio: 0.931866 max_rss_mb: 449.484
34MB 128thread folly -> kops/s: 2.34 io_bytes/op: 1.6219e+07 miss_ratio: 0.932023 max_rss_mb: 396.457
34MB 128thread gt_clock -> kops/s: 1.798 io_bytes/op: 5.4241e+06 miss_ratio: 0.324881 max_rss_mb: 1104.41
34MB 128thread new_clock -> kops/s: 10.519 io_bytes/op: 2.39354e+06 miss_ratio: 0.136147 max_rss_mb: 1050.52
As the miss ratio gets higher (say, above 10%), the CPU time spent in eviction starts to erode the advantage of using fewer shards (13% miss rate much lower than 94%). LRU's O(1) eviction time can eventually pay off when there's enough block cache churn:
13MB 1thread base -> kops/s: 0.195 io_bytes/op: 1.65732e+07 miss_ratio: 0.946604 max_rss_mb: 45.6328
13MB 1thread folly -> kops/s: 0.197 io_bytes/op: 1.63793e+07 miss_ratio: 0.94661 max_rss_mb: 33.8633
13MB 1thread gt_clock -> kops/s: 0.519 io_bytes/op: 4.43316e+06 miss_ratio: 0.269379 max_rss_mb: 100.684
13MB 1thread new_clock -> kops/s: 0.176 io_bytes/op: 1.54148e+07 miss_ratio: 0.91545 max_rss_mb: 66.2383
13MB 32thread base -> kops/s: 3.266 io_bytes/op: 1.65544e+07 miss_ratio: 0.943386 max_rss_mb: 132.492
13MB 32thread folly -> kops/s: 3.396 io_bytes/op: 1.63142e+07 miss_ratio: 0.943243 max_rss_mb: 101.863
13MB 32thread gt_clock -> kops/s: 2.758 io_bytes/op: 5.13714e+06 miss_ratio: 0.310652 max_rss_mb: 396.121
13MB 32thread new_clock -> kops/s: 3.11 io_bytes/op: 1.23419e+07 miss_ratio: 0.708425 max_rss_mb: 321.758
13MB 128thread base -> kops/s: 2.31 io_bytes/op: 1.64823e+07 miss_ratio: 0.939543 max_rss_mb: 425.539
13MB 128thread folly -> kops/s: 2.339 io_bytes/op: 1.6242e+07 miss_ratio: 0.939966 max_rss_mb: 346.098
13MB 128thread gt_clock -> kops/s: 3.223 io_bytes/op: 5.76928e+06 miss_ratio: 0.345899 max_rss_mb: 1087.77
13MB 128thread new_clock -> kops/s: 2.984 io_bytes/op: 1.05341e+07 miss_ratio: 0.606198 max_rss_mb: 898.27
gt_clock is clearly blowing way past its memory budget for lower miss rates and best throughput. new_clock also seems to be exceeding budgets, and this warrants more investigation but is not the use case we are targeting with the new cache. With partitioned index+filter, the miss ratio is much better, and although still high enough that the eviction CPU time is definitely offsetting mutex contention:
13MB 1thread base -> kops/s: 16.326 io_bytes/op: 23743.9 miss_ratio: 0.205362 max_rss_mb: 65.2852
13MB 1thread folly -> kops/s: 15.574 io_bytes/op: 19415 miss_ratio: 0.184157 max_rss_mb: 56.3516
13MB 1thread gt_clock -> kops/s: 14.459 io_bytes/op: 22873 miss_ratio: 0.198355 max_rss_mb: 63.9688
13MB 1thread new_clock -> kops/s: 16.34 io_bytes/op: 24386.5 miss_ratio: 0.210512 max_rss_mb: 61.707
13MB 128thread base -> kops/s: 289.786 io_bytes/op: 23710.9 miss_ratio: 0.205056 max_rss_mb: 103.57
13MB 128thread folly -> kops/s: 185.282 io_bytes/op: 19433.1 miss_ratio: 0.184275 max_rss_mb: 116.219
13MB 128thread gt_clock -> kops/s: 354.451 io_bytes/op: 23150.6 miss_ratio: 0.200495 max_rss_mb: 102.871
13MB 128thread new_clock -> kops/s: 295.359 io_bytes/op: 24626.4 miss_ratio: 0.212452 max_rss_mb: 121.109
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10626
Test Plan: updated unit tests, stress/crash test runs including with TSAN, ASAN, UBSAN
Reviewed By: anand1976
Differential Revision: D39368406
Pulled By: pdillinger
fbshipit-source-id: 5afc44da4c656f8f751b44552bbf27bd3ca6fef9
|
2 years ago |
|
Levi Tamasi
|
7dad485278 |
Support JemallocNodumpAllocator for the block/blob cache in db_bench (#10685)
Summary: The patch makes it possible to use the `JemallocNodumpAllocator` with the block/blob caches in `db_bench`. In addition to its stated purpose of excluding cache contents from core dumps, `JemallocNodumpAllocator` also uses a dedicated arena and jemalloc tcaches for cache allocations, which can reduce fragmentation and thus memory usage. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10685 Reviewed By: riversand963 Differential Revision: D39552261 Pulled By: ltamasi fbshipit-source-id: b5c58eab6b7c1baa9a307d9f1248df1d7a77d2b5 |
2 years ago |
|
Akanksha Mahajan
|
7a9ecdac3c |
Add auto prefetching parameters to db_bench and db_stress (#10632)
Summary: Same as title Pull Request resolved: https://github.com/facebook/rocksdb/pull/10632 Test Plan: make crash_test -j32 Reviewed By: anand1976 Differential Revision: D39241479 Pulled By: akankshamahajan15 fbshipit-source-id: 5db5b0c007da786bacc1b30d8926d36d6d029b87 |
2 years ago |
|
Levi Tamasi
|
228f2c5bf5 |
Adjust the blob cache printout in db_bench/db_stress (#10614)
Summary: Currently, `db_bench` and `db_stress` print the blob cache options even if a shared block/blob cache is configured, i.e. when they are not actually in effect. The patch changes this so they are only printed when a separate blob cache is used. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10614 Test Plan: Tested manually using `db_bench` and `db_stress`. Reviewed By: akankshamahajan15 Differential Revision: D39144603 Pulled By: ltamasi fbshipit-source-id: f714304c5d46186f8514746c27ee6f52aa3e4af8 |
2 years ago |
|
Changyu Bi
|
7b9e970042 |
Optionally issue `DeleteRange` in `*whilewriting` benchmarks (#10552)
Summary: Optionally issue DeleteRange in `*whilewriting` benchmarks. This happens in `BGWriter` and uses similar logic as in `DoWrite` to issue DeleteRange operations. I added this when I was benchmarking https://github.com/facebook/rocksdb/issues/10547, but this should be an independent PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10552 Test Plan: ran some benchmarks with various delete range options, e.g. `./db_bench --benchmarks=readwhilewriting --writes_per_range_tombstone=100 --writes=200000 --reads=1000000 --disable_auto_compactions --max_num_range_tombstones=10000` Reviewed By: ajkr Differential Revision: D38927020 Pulled By: cbi42 fbshipit-source-id: 31ee20cb8127f7173f0816ea0cc2a204ec02aad6 |
2 years ago |
|
anand76
|
35cdd3e71e |
MultiGet async IO across multiple levels (#10535)
Summary: This PR exploits parallelism in MultiGet across levels. It applies only to the coroutine version of MultiGet. Previously, MultiGet file reads from SST files in the same level were parallelized. With this PR, MultiGet batches with keys distributed across multiple levels are read in parallel. This is accomplished by splitting the keys not present in a level (determined by bloom filtering) into a separate batch, and processing the new batch in parallel with the original batch. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10535 Test Plan: 1. Ensure existing MultiGet unit tests pass, updating them as necessary 2. New unit tests - TODO 3. Run stress test - TODO No noticeable regression (<1%) without async IO - Without PR: `multireadrandom : 7.261 micros/op 1101724 ops/sec 60.007 seconds 66110936 operations; 571.6 MB/s (8168992 of 8168992 found)` With PR: `multireadrandom : 7.305 micros/op 1095167 ops/sec 60.007 seconds 65717936 operations; 568.2 MB/s (8271992 of 8271992 found)` For a fully cached DB, but with async IO option on, no regression observed (<1%) - Without PR: `multireadrandom : 5.201 micros/op 1538027 ops/sec 60.005 seconds 92288936 operations; 797.9 MB/s (11540992 of 11540992 found) ` With PR: `multireadrandom : 5.249 micros/op 1524097 ops/sec 60.005 seconds 91452936 operations; 790.7 MB/s (11649992 of 11649992 found) ` Reviewed By: akankshamahajan15 Differential Revision: D38774009 Pulled By: anand1976 fbshipit-source-id: c955e259749f1c091590ade73105b3ee46cd0007 |
2 years ago |
|
Akanksha Mahajan
|
5956ef0089 |
Add initial_auto_readahead_size and max_auto_readahead_size to db_bench (#10539)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10539 Reviewed By: anand1976 Differential Revision: D38837111 Pulled By: akankshamahajan15 fbshipit-source-id: eb845c6e15a3c823ff6113395817388ff15a20b1 |
2 years ago |
|
Gang Liao
|
275cd80cdb |
Add a blob-specific cache priority (#10461)
Summary: RocksDB's `Cache` abstraction currently supports two priority levels for items: high (used for frequently accessed/highly valuable SST metablocks like index/filter blocks) and low (used for SST data blocks). Blobs are typically lower-value targets for caching than data blocks, since 1) with BlobDB, data blocks containing blob references conceptually form an index structure which has to be consulted before we can read the blob value, and 2) cached blobs represent only a single key-value, while cached data blocks generally contain multiple KVs. Since we would like to make it possible to use the same backing cache for the block cache and the blob cache, it would make sense to add a new, lower-than-low cache priority level (bottom level) for blobs so data blocks are prioritized over them. This task is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10461 Reviewed By: siying Differential Revision: D38672823 Pulled By: ltamasi fbshipit-source-id: 90cf7362036563d79891f47be2cc24b827482743 |
2 years ago |
|
Changyu Bi
|
fd165c869d |
Add memtable per key-value checksum (#10281)
Summary: Append per key-value checksum to internal key. These checksums are verified on read paths including Get, Iterator and during Flush. Get and Iterator will return `Corruption` status if there is a checksum verification failure. Flush will make DB become read-only upon memtable entry checksum verification failure. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10281 Test Plan: - Added new unit test cases: `make check` - Benchmark on memtable insert ``` TEST_TMPDIR=/dev/shm/memtable_write ./db_bench -benchmarks=fillseq -disable_wal=true -max_write_buffer_number=100 -num=10000000 -min_write_buffer_number_to_merge=100 # avg over 10 runs Baseline: 1166936 ops/sec memtable 2 bytes kv checksum : 1.11674e+06 ops/sec (-4%) memtable 2 bytes kv checksum + write batch 8 bytes kv checksum: 1.08579e+06 ops/sec (-6.95%) write batch 8 bytes kv checksum: 1.17979e+06 ops/sec (+1.1%) ``` - Benchmark on only memtable read: ops/sec dropped 31% for `readseq` due to time spend on verifying checksum. ops/sec for `readrandom` dropped ~6.8%. ``` # Readseq sudo TEST_TMPDIR=/dev/shm/memtable_read ./db_bench -benchmarks=fillseq,readseq"[-X20]" -disable_wal=true -max_write_buffer_number=100 -num=10000000 -min_write_buffer_number_to_merge=100 readseq [AVG 20 runs] : 7432840 (± 212005) ops/sec; 822.3 (± 23.5) MB/sec readseq [MEDIAN 20 runs] : 7573878 ops/sec; 837.9 MB/sec With -memtable_protection_bytes_per_key=2: readseq [AVG 20 runs] : 5134607 (± 119596) ops/sec; 568.0 (± 13.2) MB/sec readseq [MEDIAN 20 runs] : 5232946 ops/sec; 578.9 MB/sec # Readrandom sudo TEST_TMPDIR=/dev/shm/memtable_read ./db_bench -benchmarks=fillrandom,readrandom"[-X10]" -disable_wal=true -max_write_buffer_number=100 -num=1000000 -min_write_buffer_number_to_merge=100 readrandom [AVG 10 runs] : 140236 (± 3938) ops/sec; 9.8 (± 0.3) MB/sec readrandom [MEDIAN 10 runs] : 140545 ops/sec; 9.8 MB/sec With -memtable_protection_bytes_per_key=2: readrandom [AVG 10 runs] : 130632 (± 2738) ops/sec; 9.1 (± 0.2) MB/sec readrandom [MEDIAN 10 runs] : 130341 ops/sec; 9.1 MB/sec ``` - Stress test: `python3 -u tools/db_crashtest.py whitebox --duration=1800` Reviewed By: ajkr Differential Revision: D37607896 Pulled By: cbi42 fbshipit-source-id: fdaefb475629d2471780d4a5f5bf81b44ee56113 |
2 years ago |
|
Jay Zhuang
|
3f763763aa |
Change `bottommost_temperture` to `last_level_temperture` (#10471)
Summary: Change tiered compaction feature from `bottommost_temperture` to `last_level_temperture`. The old option is kept for migration purpose only, which is behaving the same as `last_level_temperture` and it will be removed in the next release. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10471 Test Plan: CI Reviewed By: siying Differential Revision: D38450621 Pulled By: jay-zhuang fbshipit-source-id: cc1cdf8bad409376fec0152abc0a64fb72a91527 |
2 years ago |
|
Jay Zhuang
|
1e86d424e4 |
Tiered storage stress test (#10493)
Summary: Add Tiered storage stress test and db_bench option Pull Request resolved: https://github.com/facebook/rocksdb/pull/10493 Test Plan: new crashtest: https://app.circleci.com/pipelines/github/facebook/rocksdb/16905/workflows/68c2967c-9274-434f-8506-1403cf441ead Reviewed By: ajkr Differential Revision: D38481892 Pulled By: jay-zhuang fbshipit-source-id: 217a0be4acb93d420222e6ede2a1290d9f464776 |
2 years ago |
|
Changyu Bi
|
9d77bf8f7b |
Fragment memtable range tombstone in the write path (#10380)
Summary: - Right now each read fragments the memtable range tombstones https://github.com/facebook/rocksdb/issues/4808. This PR explores the idea of fragmenting memtable range tombstones in the write path and reads can just read this cached fragmented tombstone without any fragmenting cost. This PR only does the caching for immutable memtable, and does so right before a memtable is added to an immutable memtable list. The fragmentation is done without holding mutex to minimize its performance impact. - db_bench is updated to print out the number of range deletions executed if there is any. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10380 Test Plan: - CI, added asserts in various places to check whether a fragmented range tombstone list should have been constructed. - Benchmark: as this PR only optimizes immutable memtable path, the number of writes in the benchmark is chosen such an immutable memtable is created and range tombstones are in that memtable. ``` single thread: ./db_bench --benchmarks=fillrandom,readrandom --writes_per_range_tombstone=1 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=500000 --reads=100000 --max_num_range_tombstones=100 multi_thread ./db_bench --benchmarks=fillrandom,readrandom --writes_per_range_tombstone=1 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=15000 --reads=20000 --threads=32 --max_num_range_tombstones=100 ``` Commit 99cdf16464a057ca44de2f747541dedf651bae9e is included in benchmark result. It was an earlier attempt where tombstones are fragmented for each write operation. Reader threads share it using a shared_ptr which would slow down multi-thread read performance as seen in benchmark results. Results are averaged over 5 runs. Single thread result: | Max # tombstones | main fillrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR | main readrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR | | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- | | 0 |6.68 |6.57 |6.72 |4.72 |4.79 |4.54 | | 1 |6.67 |6.58 |6.62 |5.41 |4.74 |4.72 | | 10 |6.59 |6.5 |6.56 |7.83 |4.69 |4.59 | | 100 |6.62 |6.75 |6.58 |29.57 |5.04 |5.09 | | 1000 |6.54 |6.82 |6.61 |320.33 |5.22 |5.21 | 32-thread result: note that "Max # tombstones" is per thread. | Max # tombstones | main fillrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR | main readrandom micros/op | 99cdf16464a057ca44de2f747541dedf651bae9e | Post PR | | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- | | 0 |234.52 |260.25 |239.42 |5.06 |5.38 |5.09 | | 1 |236.46 |262.0 |231.1 |19.57 |22.14 |5.45 | | 10 |236.95 |263.84 |251.49 |151.73 |21.61 |5.73 | | 100 |268.16 |296.8 |280.13 |2308.52 |22.27 |6.57 | Reviewed By: ajkr Differential Revision: D37916564 Pulled By: cbi42 fbshipit-source-id: 05d6d2e16df26c374c57ddcca13a5bfe9d5b731e |
2 years ago |
|
Andrew Kryczka
|
504fe4de80 |
Avoid allocations/copies for large `GetMergeOperands()` results (#10458)
Summary: This PR avoids allocations and copies for the result of `GetMergeOperands()` when the average operand size is at least 256 bytes and the total operands size is at least 32KB. The `GetMergeOperands()` already included `PinnableSlice` but was calling `PinSelf()` (i.e., allocating and copying) for each operand. When this optimization takes effect, we instead call `PinSlice()` to skip that allocation and copy. Resources are pinned in order for the `PinnableSlice` to point to valid memory even after `GetMergeOperands()` returns. The pinned resources include a referenced `SuperVersion`, a `MergingContext`, and a `PinnedIteratorsManager`. They are bundled into a `GetMergeOperandsState`. We use `SharedCleanablePtr` to share that bundle among all `PinnableSlice`s populated by `GetMergeOperands()`. That way, the last `PinnableSlice` to be `Reset()` will cleanup the bundle, including unreferencing the `SuperVersion`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10458 Test Plan: - new DB level test - measured benefit/regression in a number of memtable scenarios Setup command: ``` $ ./db_bench -benchmarks=mergerandom -merge_operator=StringAppendOperator -num=$num -writes=16384 -key_size=16 -value_size=$value_sz -compression_type=none -write_buffer_size=1048576000 ``` Benchmark command: ``` ./db_bench -threads=$threads -use_existing_db=true -avoid_flush_during_recovery=true -write_buffer_size=1048576000 -benchmarks=readrandomoperands -merge_operator=StringAppendOperator -num=$num -duration=10 ``` Worst regression is when a key has many tiny operands: - Parameters: num=1 (implying 16384 operands per key), value_sz=8, threads=1 - `GetMergeOperands()` latency increases 682 micros -> 800 micros (+17%) The regression disappears into the noise (<1% difference) if we remove the `Reset()` loop and the size counting loop. The former is arguably needed regardless of this PR as the convention in `Get()` and `MultiGet()` is to `Reset()` the input `PinnableSlice`s at the start. The latter could be optimized to count the size as we accumulate operands rather than after the fact. Best improvement is when a key has large operands and high concurrency: - Parameters: num=4 (implying 4096 operands per key), value_sz=2KB, threads=32 - `GetMergeOperands()` latency decreases 11492 micros -> 437 micros (-96%). Reviewed By: cbi42 Differential Revision: D38336578 Pulled By: ajkr fbshipit-source-id: 48146d127e04cb7f2d4d2939a2b9dff3aba18258 |
2 years ago |
|
Peter Dillinger
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65036e4217 |
Revert "Add a blob-specific cache priority (#10309)" (#10434)
Summary:
This reverts commit
|
2 years ago |
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Gang Liao
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8d178090be |
Add a blob-specific cache priority (#10309)
Summary: RocksDB's `Cache` abstraction currently supports two priority levels for items: high (used for frequently accessed/highly valuable SST metablocks like index/filter blocks) and low (used for SST data blocks). Blobs are typically lower-value targets for caching than data blocks, since 1) with BlobDB, data blocks containing blob references conceptually form an index structure which has to be consulted before we can read the blob value, and 2) cached blobs represent only a single key-value, while cached data blocks generally contain multiple KVs. Since we would like to make it possible to use the same backing cache for the block cache and the blob cache, it would make sense to add a new, lower-than-low cache priority level (bottom level) for blobs so data blocks are prioritized over them. This task is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10309 Reviewed By: ltamasi Differential Revision: D38211655 Pulled By: gangliao fbshipit-source-id: 65ef33337db4d85277cc6f9782d67c421ad71dd5 |
2 years ago |
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Yanqin Jin
|
dd759537d0 |
Print perf context for all benchmarks if enabled (#10396)
Summary: If user runs `db_bench` with `-perf_level=2` or higher, db_bench should print perf context after each of all benchmarks. Or make `-perf_level` a per-benchmark switch. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10396 Test Plan: ./db_bench -benchmarks=fillseq,readseq -perf_level=2 Reviewed By: ajkr Differential Revision: D38016324 Pulled By: riversand963 fbshipit-source-id: d83ea4abc34d40ffea394ca6abf0814bc5c0a2e0 |
2 years ago |
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Gang Liao
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0b6bc101ba |
Charge blob cache usage against the global memory limit (#10321)
Summary: To help service owners to manage their memory budget effectively, we have been working towards counting all major memory users inside RocksDB towards a single global memory limit (see e.g. https://github.com/facebook/rocksdb/wiki/Write-Buffer-Manager#cost-memory-used-in-memtable-to-block-cache). The global limit is specified by the capacity of the block-based table's block cache, and is technically implemented by inserting dummy entries ("reservations") into the block cache. The goal of this task is to support charging the memory usage of the new blob cache against this global memory limit when the backing cache of the blob cache and the block cache are different. This PR is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10321 Reviewed By: ltamasi Differential Revision: D37913590 Pulled By: gangliao fbshipit-source-id: eaacf23907f82dc7d18964a3f24d7039a2937a72 |
2 years ago |
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Gang Liao
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ec4ebeff30 |
Support prepopulating/warming the blob cache (#10298)
Summary: Many workloads have temporal locality, where recently written items are read back in a short period of time. When using remote file systems, this is inefficient since it involves network traffic and higher latencies. Because of this, we would like to support prepopulating the blob cache during flush. This task is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10298 Reviewed By: ltamasi Differential Revision: D37908743 Pulled By: gangliao fbshipit-source-id: 9feaed234bc719d38f0c02975c1ad19fa4bb37d1 |
2 years ago |
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Guido Tagliavini Ponce
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9645e66fc9 |
Temporarily return a LRUCache from NewClockCache (#10351)
Summary: ClockCache is still in experimental stage, and currently fails some pre-release fbcode tests. See https://www.internalfb.com/diff/D37772011. API calls to construct ClockCache are done via the function NewClockCache. For now, NewClockCache calls will return an LRUCache (with appropriate arguments), which is stable. The idea that NewClockCache returns nullptr was also floated, but this would be interpreted as unsupported cache, and a default LRUCache would be constructed instead, potentially causing a performance regression that is harder to identify. A new version of the NewClockCache function was created for our internal tests. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10351 Test Plan: ``make -j24 check`` and re-run the pre-release tests. Reviewed By: pdillinger Differential Revision: D37802685 Pulled By: guidotag fbshipit-source-id: 0a8d10612ff21e576f7360cb13e20bc36e244972 |
2 years ago |
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Yanqin Jin
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b283f041f5 |
Stop tracking syncing live WAL for performance (#10330)
Summary: With https://github.com/facebook/rocksdb/issues/10087, applications calling `SyncWAL()` or writing with `WriteOptions::sync=true` can suffer from performance regression. This PR reverts to original behavior of tracking the syncing of closed WALs. After we revert back to old behavior, recovery, whether kPointInTime or kAbsoluteConsistency, may fail to detect corruption in synced WALs if the corruption is in the live WAL. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10330 Test Plan: make check Before https://github.com/facebook/rocksdb/issues/10087 ```bash fillsync : 750.269 micros/op 1332 ops/sec 75.027 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync : 776.492 micros/op 1287 ops/sec 77.649 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync [AVG 2 runs] : 1310 (± 44) ops/sec; 0.1 (± 0.0) MB/sec fillsync : 805.625 micros/op 1241 ops/sec 80.563 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync [AVG 3 runs] : 1287 (± 51) ops/sec; 0.1 (± 0.0) MB/sec fillsync [AVG 3 runs] : 1287 (± 51) ops/sec; 0.1 (± 0.0) MB/sec fillsync [MEDIAN 3 runs] : 1287 ops/sec; 0.1 MB/sec ``` Before this PR and after https://github.com/facebook/rocksdb/issues/10087 ```bash fillsync : 1479.601 micros/op 675 ops/sec 147.960 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync : 1626.080 micros/op 614 ops/sec 162.608 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync [AVG 2 runs] : 645 (± 59) ops/sec; 0.1 (± 0.0) MB/sec fillsync : 1588.402 micros/op 629 ops/sec 158.840 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync [AVG 3 runs] : 640 (± 35) ops/sec; 0.1 (± 0.0) MB/sec fillsync [AVG 3 runs] : 640 (± 35) ops/sec; 0.1 (± 0.0) MB/sec fillsync [MEDIAN 3 runs] : 629 ops/sec; 0.1 MB/sec ``` After this PR ```bash fillsync : 749.621 micros/op 1334 ops/sec 74.962 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync : 865.577 micros/op 1155 ops/sec 86.558 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync [AVG 2 runs] : 1244 (± 175) ops/sec; 0.1 (± 0.0) MB/sec fillsync : 845.837 micros/op 1182 ops/sec 84.584 seconds 100000 operations; 0.1 MB/s (100 ops) fillsync [AVG 3 runs] : 1223 (± 109) ops/sec; 0.1 (± 0.0) MB/sec fillsync [AVG 3 runs] : 1223 (± 109) ops/sec; 0.1 (± 0.0) MB/sec fillsync [MEDIAN 3 runs] : 1182 ops/sec; 0.1 MB/sec ``` Reviewed By: ajkr Differential Revision: D37725212 Pulled By: riversand963 fbshipit-source-id: 8fa7d13b3c7662be5d56351c42caf3266af937ae |
2 years ago |
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Mark Callaghan
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177b2fa341 |
Set the value for --version, add --build_info (#10275)
Summary:
./db_bench --version
db_bench version 7.5.0
./db_bench --build_info
(RocksDB) 7.5.0
rocksdb_build_date: 2022-06-29 09:58:04
rocksdb_build_git_sha:
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2 years ago |
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Guido Tagliavini Ponce
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57a0e2f304 |
Clock cache (#10273)
Summary: This is the initial step in the development of a lock-free clock cache. This PR includes the base hash table design (which we mostly ported over from FastLRUCache) and the clock eviction algorithm. Importantly, it's still _not_ lock-free---all operations use a shard lock. Besides the locking, there are other features left as future work: - Remove keys from the handles. Instead, use 128-bit bijective hashes of them for handle comparisons, probing (we need two 32-bit hashes of the key for double hashing) and sharding (we need one 6-bit hash). - Remove the clock_usage_ field, which is updated on every lookup. Even if it were atomically updated, it could cause memory invalidations across cores. - Middle insertions into the clock list. - A test that exercises the clock eviction policy. - Update the Java API of ClockCache and Java calls to C++. Along the way, we improved the code and comments quality of FastLRUCache. These changes are relatively minor. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10273 Test Plan: ``make -j24 check`` Reviewed By: pdillinger Differential Revision: D37522461 Pulled By: guidotag fbshipit-source-id: 3d70b737dbb70dcf662f00cef8c609750f083943 |
2 years ago |
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Gang Liao
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2352e2dfda |
Add the blob cache to the stress tests and the benchmarking tool (#10202)
Summary: In order to facilitate correctness and performance testing, we would like to add the new blob cache to our stress test tool `db_stress` and our continuously running crash test script `db_crashtest.py`, as well as our synthetic benchmarking tool `db_bench` and the BlobDB performance testing script `run_blob_bench.sh`. As part of this task, we would also like to utilize these benchmarking tools to get some initial performance numbers about the effectiveness of caching blobs. This PR is a part of https://github.com/facebook/rocksdb/issues/10156 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10202 Reviewed By: ltamasi Differential Revision: D37325739 Pulled By: gangliao fbshipit-source-id: deb65d0d414502270dd4c324d987fd5469869fa8 |
2 years ago |
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Hui Xiao
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a5d773e077 |
Add rate-limiting support to batched MultiGet() (#10159)
Summary: **Context/Summary:** https://github.com/facebook/rocksdb/pull/9424 added rate-limiting support for user reads, which does not include batched `MultiGet()`s that call `RandomAccessFileReader::MultiRead()`. The reason is that it's harder (compared with RandomAccessFileReader::Read()) to implement the ideal rate-limiting where we first call `RateLimiter::RequestToken()` for allowed bytes to multi-read and then consume those bytes by satisfying as many requests in `MultiRead()` as possible. For example, it can be tricky to decide whether we want partially fulfilled requests within one `MultiRead()` or not. However, due to a recent urgent user request, we decide to pursue an elementary (but a conditionally ineffective) solution where we accumulate enough rate limiter requests toward the total bytes needed by one `MultiRead()` before doing that `MultiRead()`. This is not ideal when the total bytes are huge as we will actually consume a huge bandwidth from rate-limiter causing a burst on disk. This is not what we ultimately want with rate limiter. Therefore a follow-up work is noted through TODO comments. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10159 Test Plan: - Modified existing unit test `DBRateLimiterOnReadTest/DBRateLimiterOnReadTest.NewMultiGet` - Traced the underlying system calls `io_uring_enter` and verified they are 10 seconds apart from each other correctly under the setting of `strace -ftt -e trace=io_uring_enter ./db_bench -benchmarks=multireadrandom -db=/dev/shm/testdb2 -readonly -num=50 -threads=1 -multiread_batched=1 -batch_size=100 -duration=10 -rate_limiter_bytes_per_sec=200 -rate_limiter_refill_period_us=1000000 -rate_limit_bg_reads=1 -disable_auto_compactions=1 -rate_limit_user_ops=1` where each `MultiRead()` read about 2000 bytes (inspected by debugger) and the rate limiter grants 200 bytes per seconds. - Stress test: - Verified `./db_stress (-test_cf_consistency=1/test_batches_snapshots=1) -use_multiget=1 -cache_size=1048576 -rate_limiter_bytes_per_sec=10241024 -rate_limit_bg_reads=1 -rate_limit_user_ops=1` work Reviewed By: ajkr, anand1976 Differential Revision: D37135172 Pulled By: hx235 fbshipit-source-id: 73b8e8f14761e5d4b77235dfe5d41f4eea968bcd |
2 years ago |
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Peter Dillinger
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126c223714 |
Remove deprecated block-based filter (#10184)
Summary: In https://github.com/facebook/rocksdb/issues/9535, release 7.0, we hid the old block-based filter from being created using the public API, because of its inefficiency. Although we normally maintain read compatibility on old DBs forever, filters are not required for reading a DB, only for optimizing read performance. Thus, it should be acceptable to remove this code and the substantial maintenance burden it carries as useful features are developed and validated (such as user timestamp). This change completely removes the code for reading and writing the old block-based filters, net removing about 1370 lines of code no longer needed. Options removed from testing / benchmarking tools. The prior existence is only evident in a couple of places: * `CacheEntryRole::kDeprecatedFilterBlock` - We can update this public API enum in a major release to minimize source code incompatibilities. * A warning is logged when an old table file is opened that used the old block-based filter. This is provided as a courtesy, and would be a pain to unit test, so manual testing should suffice. Unfortunately, sst_dump does not tell you whether a file uses block-based filter, and the structure of the code makes it very difficult to fix. * To detect that case, `kObsoleteFilterBlockPrefix` (renamed from `kFilterBlockPrefix`) for metaindex is maintained (for now). Other notes: * In some cases where numbers are associated with filter configurations, we have had to update the assigned numbers so that they all correspond to something that exists. * Fixed potential stat counting bug by assuming `filter_checked = false` for cases like `filter == nullptr` rather than assuming `filter_checked = true` * Removed obsolete `block_offset` and `prefix_extractor` parameters from several functions. * Removed some unnecessary checks `if (!table_prefix_extractor() && !prefix_extractor)` because the caller guarantees the prefix extractor exists and is compatible Pull Request resolved: https://github.com/facebook/rocksdb/pull/10184 Test Plan: tests updated, manually test new warning in LOG using base version to generate a DB Reviewed By: riversand963 Differential Revision: D37212647 Pulled By: pdillinger fbshipit-source-id: 06ee020d8de3b81260ffc36ad0c1202cbf463a80 |
2 years ago |
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Peter Dillinger
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94329ae4ec |
Use only ASCII in source files (#10164)
Summary: Fix existing usage of non-ASCII and add a check to prevent future use. Added `-n` option to greps to provide line numbers. Alternative to https://github.com/facebook/rocksdb/issues/10147 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10164 Test Plan: used new checker to find & fix cases, manually check db_bench output is preserved Reviewed By: akankshamahajan15 Differential Revision: D37148792 Pulled By: pdillinger fbshipit-source-id: 68c8b57e7ab829369540d532590bf756938855c7 |
2 years ago |
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Changyu Bi
|
9882652b0e |
Verify write batch checksum before WAL (#10114)
Summary: Context: WriteBatch can have key-value checksums when it was created `with protection_bytes_per_key > 0`. This PR added checksum verification for write batches before they are written to WAL. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10114 Test Plan: - Added new unit tests to db_kv_checksum_test.cc: `make check -j32` - benchmark on performance regression: `./db_bench --benchmarks=fillrandom[-X20] -db=/dev/shm/test_rocksdb -write_batch_protection_bytes_per_key=8` - Pre-PR: ` fillrandom [AVG 20 runs] : 198875 (± 3006) ops/sec; 22.0 (± 0.3) MB/sec ` - Post-PR: ` fillrandom [AVG 20 runs] : 196487 (± 2279) ops/sec; 21.7 (± 0.3) MB/sec ` Mean regressed about 1% (198875 -> 196487 ops/sec). Reviewed By: ajkr Differential Revision: D36917464 Pulled By: cbi42 fbshipit-source-id: 29beb74edf65f04b1a890b4f650d873dc7ed790d |
2 years ago |
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Yanqin Jin
|
ce419c0f10 |
Allow db_bench and db_stress to set `allow_data_in_errors` (#10171)
Summary: There is `Options::allow_data_in_errors` that controls whether RocksDB is allowed to log data, e.g. key, value, etc in LOG files. It is false by default. However, in db_bench and db_stress, it is often ok to log data because there is no concern about privacy. This PR allows db_stress and db_bench to set this option on the command line, while it remains false by default. Furthermore, make crash/recovery test driven by db_crashtest.py to opt-in. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10171 Test Plan: Stress test and db_bench Reviewed By: hx235 Differential Revision: D37163787 Pulled By: riversand963 fbshipit-source-id: 0242f24d292ba15b6faf8ff903963b85d3e011f8 |
2 years ago |
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Hui Xiao
|
d665afdbf3 |
Account memory of FileMetaData in global memory limit (#9924)
Summary: **Context/Summary:** As revealed by heap profiling, allocation of `FileMetaData` for [newly created file added to a Version](https://github.com/facebook/rocksdb/pull/9924/files#diff-a6aa385940793f95a2c5b39cc670bd440c4547fa54fd44622f756382d5e47e43R774) can consume significant heap memory. This PR is to account that toward our global memory limit based on block cache capacity. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9924 Test Plan: - Previous `make check` verified there are only 2 places where the memory of the allocated `FileMetaData` can be released - New unit test `TEST_P(ChargeFileMetadataTestWithParam, Basic)` - db bench (CPU cost of `charge_file_metadata` in write and compact) - **write micros/op: -0.24%** : `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_file_metadata=1 (remove this option for pre-PR) -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 | egrep 'fillseq'` - **compact micros/op -0.87%** : `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_file_metadata=1 -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 -numdistinct=1000 && ./db_bench -benchmarks=compact -db=$TEST_TMPDIR -use_existing_db=1 -charge_file_metadata=1 -disable_auto_compactions=1 | egrep 'compact'` table 1 - write #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 3.9711 | 0.264408 | 3.9914 | 0.254563 | 0.5111933721 20 | 3.83905 | 0.0664488 | 3.8251 | 0.0695456 | -0.3633711465 40 | 3.86625 | 0.136669 | 3.8867 | 0.143765 | 0.5289363078 80 | 3.87828 | 0.119007 | 3.86791 | 0.115674 | **-0.2673865734** 160 | 3.87677 | 0.162231 | 3.86739 | 0.16663 | **-0.2419539978** table 2 - compact #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 2,399,650.00 | 96,375.80 | 2,359,537.00 | 53,243.60 | -1.67 20 | 2,410,480.00 | 89,988.00 | 2,433,580.00 | 91,121.20 | 0.96 40 | 2.41E+06 | 121811 | 2.39E+06 | 131525 | **-0.96** 80 | 2.40E+06 | 134503 | 2.39E+06 | 108799 | **-0.78** - stress test: `python3 tools/db_crashtest.py blackbox --charge_file_metadata=1 --cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D36055583 Pulled By: hx235 fbshipit-source-id: b60eab94707103cb1322cf815f05810ef0232625 |
2 years ago |
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Guido Tagliavini Ponce
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f105e1a501 |
Make the per-shard hash table fixed-size. (#10154)
Summary: We make the size of the per-shard hash table fixed. The base level of the hash table is now preallocated with the required capacity. The user must provide an estimate of the size of the values. Notice that even though the base level becomes fixed, the chains are still dynamic. Overall, the shard capacity mechanisms haven't changed, so we don't need to test this. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10154 Test Plan: `make -j24 check` Reviewed By: pdillinger Differential Revision: D37124451 Pulled By: guidotag fbshipit-source-id: cba6ac76052fe0ec60b8ff4211b3de7650e80d0c |
2 years ago |
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Guido Tagliavini Ponce
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cf85607795 |
Add support for FastLRUCache in db_bench. (#10096)
Summary: db_bench can now run with FastLRUCache. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10096 Test Plan: - Temporarily add an ``assert(false)`` in the execution path that sets up the FastLRUCache. Run ``make -j24 db_bench``. Then test the appropriate code is used by running ``./db_bench -cache_type=fast_lru_cache`` and checking that the assert is called. Repeat for LRUCache. - Verify that FastLRUCache (currently a clone of LRUCache) produces similar benchmark data than LRUCache, by comparing the outputs of ``./db_bench -benchmarks=fillseq,fillrandom,readseq,readrandom -cache_type=fast_lru_cache`` and ``./db_bench -benchmarks=fillseq,fillrandom,readseq,readrandom -cache_type=lru_cache``. Reviewed By: gitbw95 Differential Revision: D36898774 Pulled By: guidotag fbshipit-source-id: f9f6b6f6da124f88b21b3c8dee742fbb04eff773 |
2 years ago |
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Gang Liao
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e6432dfd4c |
Make it possible to enable blob files starting from a certain LSM tree level (#10077)
Summary: Currently, if blob files are enabled (i.e. `enable_blob_files` is true), large values are extracted both during flush/recovery (when SST files are written into level 0 of the LSM tree) and during compaction into any LSM tree level. For certain use cases that have a mix of short-lived and long-lived values, it might make sense to support extracting large values only during compactions whose output level is greater than or equal to a specified LSM tree level (e.g. compactions into L1/L2/... or above). This could reduce the space amplification caused by large values that are turned into garbage shortly after being written at the price of some write amplification incurred by long-lived values whose extraction to blob files is delayed. In order to achieve this, we would like to do the following: - Add a new configuration option `blob_file_starting_level` (default: 0) to `AdvancedColumnFamilyOptions` (and `MutableCFOptions` and extend the related logic) - Instantiate `BlobFileBuilder` in `BuildTable` (used during flush and recovery, where the LSM tree level is L0) and `CompactionJob` iff `enable_blob_files` is set and the LSM tree level is `>= blob_file_starting_level` - Add unit tests for the new functionality, and add the new option to our stress tests (`db_stress` and `db_crashtest.py` ) - Add the new option to our benchmarking tool `db_bench` and the BlobDB benchmark script `run_blob_bench.sh` - Add the new option to the `ldb` tool (see https://github.com/facebook/rocksdb/wiki/Administration-and-Data-Access-Tool) - Ideally extend the C and Java bindings with the new option - Update the BlobDB wiki to document the new option. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10077 Reviewed By: ltamasi Differential Revision: D36884156 Pulled By: gangliao fbshipit-source-id: 942bab025f04633edca8564ed64791cb5e31627d |
2 years ago |
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Changyu Bi
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8515bd50c9 |
Support read rate-limiting in SequentialFileReader (#9973)
Summary: Added rate limiter and read rate-limiting support to SequentialFileReader. I've updated call sites to SequentialFileReader::Read with appropriate IO priority (or left a TODO and specified IO_TOTAL for now). The PR is separated into four commits: the first one added the rate-limiting support, but with some fixes in the unit test since the number of request bytes from rate limiter in SequentialFileReader are not accurate (there is overcharge at EOF). The second commit fixed this by allowing SequentialFileReader to check file size and determine how many bytes are left in the file to read. The third commit added benchmark related code. The fourth commit moved the logic of using file size to avoid overcharging the rate limiter into backup engine (the main user of SequentialFileReader). Pull Request resolved: https://github.com/facebook/rocksdb/pull/9973 Test Plan: - `make check`, backup_engine_test covers usage of SequentialFileReader with rate limiter. - Run db_bench to check if rate limiting is throttling as expected: Verified that reads and writes are together throttled at 2MB/s, and at 0.2MB chunks that are 100ms apart. - Set up: `./db_bench --benchmarks=fillrandom -db=/dev/shm/test_rocksdb` - Benchmark: ``` strace -ttfe read,write ./db_bench --benchmarks=backup -db=/dev/shm/test_rocksdb --backup_rate_limit=2097152 --use_existing_db strace -ttfe read,write ./db_bench --benchmarks=restore -db=/dev/shm/test_rocksdb --restore_rate_limit=2097152 --use_existing_db ``` - db bench on backup and restore to ensure no performance regression. - backup (avg over 50 runs): pre-change: 1.90443e+06 micros/op; post-change: 1.8993e+06 micros/op (improve by 0.2%) - restore (avg over 50 runs): pre-change: 1.79105e+06 micros/op; post-change: 1.78192e+06 micros/op (improve by 0.5%) ``` # Set up ./db_bench --benchmarks=fillrandom -db=/tmp/test_rocksdb -num=10000000 # benchmark TEST_TMPDIR=/tmp/test_rocksdb NUM_RUN=50 for ((j=0;j<$NUM_RUN;j++)) do ./db_bench -db=$TEST_TMPDIR -num=10000000 -benchmarks=backup -use_existing_db | egrep 'backup' # Restore #./db_bench -db=$TEST_TMPDIR -num=10000000 -benchmarks=restore -use_existing_db done > rate_limit.txt && awk -v NUM_RUN=$NUM_RUN '{sum+=$3;sum_sqrt+=$3^2}END{print sum/NUM_RUN, sqrt(sum_sqrt/NUM_RUN-(sum/NUM_RUN)^2)}' rate_limit.txt >> rate_limit_2.txt ``` Reviewed By: hx235 Differential Revision: D36327418 Pulled By: cbi42 fbshipit-source-id: e75d4307cff815945482df5ba630c1e88d064691 |
2 years ago |
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Changyu Bi
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cc23b46da1 |
Support using ZDICT_finalizeDictionary to generate zstd dictionary (#9857)
Summary:
An untrained dictionary is currently simply the concatenation of several samples. The ZSTD API, ZDICT_finalizeDictionary(), can improve such a dictionary's effectiveness at low cost. This PR changes how dictionary is created by calling the ZSTD ZDICT_finalizeDictionary() API instead of creating raw content dictionary (when max_dict_buffer_bytes > 0), and pass in all buffered uncompressed data blocks as samples.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9857
Test Plan:
#### db_bench test for cpu/memory of compression+decompression and space saving on synthetic data:
Set up: change the parameter [here](
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2 years ago |
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Peter Dillinger
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280b9f371a |
Fix auto_prefix_mode performance with partitioned filters (#10012)
Summary: Essentially refactored the RangeMayExist implementation in FullFilterBlockReader to FilterBlockReaderCommon so that it applies to partitioned filters as well. (The function is not called for the block-based filter case.) RangeMayExist is essentially a series of checks around a possible PrefixMayExist, and I'm confident those checks should be the same for partitioned as for full filters. (I think it's likely that bugs remain in those checks, but this change is overall a simplifying one.) Added auto_prefix_mode support to db_bench Other small fixes as well Fixes https://github.com/facebook/rocksdb/issues/10003 Pull Request resolved: https://github.com/facebook/rocksdb/pull/10012 Test Plan: Expanded unit test that uses statistics to check for filter optimization, fails without the production code changes here Performance: populate two DBs with ``` TEST_TMPDIR=/dev/shm/rocksdb_nonpartitioned ./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 -prefix_size=8 TEST_TMPDIR=/dev/shm/rocksdb_partitioned ./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 -prefix_size=8 -partition_index_and_filters ``` Observe no measurable change in non-partitioned performance ``` TEST_TMPDIR=/dev/shm/rocksdb_nonpartitioned ./db_bench -benchmarks=seekrandom[-X1000] -num=10000000 -readonly -bloom_bits=16 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -prefix_size=8 -auto_prefix_mode -cache_index_and_filter_blocks=1 -cache_size=1000000000 -duration 20 ``` Before: seekrandom [AVG 15 runs] : 11798 (± 331) ops/sec After: seekrandom [AVG 15 runs] : 11724 (± 315) ops/sec Observe big improvement with partitioned (also supported by bloom use statistics) ``` TEST_TMPDIR=/dev/shm/rocksdb_partitioned ./db_bench -benchmarks=seekrandom[-X1000] -num=10000000 -readonly -bloom_bits=16 -compaction_style=2 -fifo_compaction_max_table_files_size_mb=10000 -fifo_compaction_allow_compaction=0 -prefix_size=8 -partition_index_and_filters -auto_prefix_mode -cache_index_and_filter_blocks=1 -cache_size=1000000000 -duration 20 ``` Before: seekrandom [AVG 12 runs] : 2942 (± 57) ops/sec After: seekrandom [AVG 12 runs] : 7489 (± 184) ops/sec Reviewed By: siying Differential Revision: D36469796 Pulled By: pdillinger fbshipit-source-id: bcf1e2a68d347b32adb2b27384f945434e7a266d |
3 years ago |
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Hui Xiao
|
3573558ec5 |
Rewrite memory-charging feature's option API (#9926)
Summary: **Context:** Previous PR https://github.com/facebook/rocksdb/pull/9748, https://github.com/facebook/rocksdb/pull/9073, https://github.com/facebook/rocksdb/pull/8428 added separate flag for each charged memory area. Such API design is not scalable as we charge more and more memory areas. Also, we foresee an opportunity to consolidate this feature with other cache usage related features such as `cache_index_and_filter_blocks` using `CacheEntryRole`. Therefore we decided to consolidate all these flags with `CacheUsageOptions cache_usage_options` and this PR serves as the first step by consolidating memory-charging related flags. **Summary:** - Replaced old API reference with new ones, including making `kCompressionDictionaryBuildingBuffer` opt-out and added a unit test for that - Added missing db bench/stress test for some memory charging features - Renamed related test suite to indicate they are under the same theme of memory charging - Refactored a commonly used mocked cache component in memory charging related tests to reduce code duplication - Replaced the phrases "memory tracking" / "cache reservation" (other than CacheReservationManager-related ones) with "memory charging" for standard description of this feature. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9926 Test Plan: - New unit test for opt-out `kCompressionDictionaryBuildingBuffer` `TEST_F(ChargeCompressionDictionaryBuildingBufferTest, Basic)` - New unit test for option validation/sanitization `TEST_F(CacheUsageOptionsOverridesTest, SanitizeAndValidateOptions)` - CI - db bench (in case querying new options introduces regression) **+0.5% micros/op**: `TEST_TMPDIR=/dev/shm/testdb ./db_bench -benchmarks=fillseq -db=$TEST_TMPDIR -charge_compression_dictionary_building_buffer=1(remove this for comparison) -compression_max_dict_bytes=10000 -disable_auto_compactions=1 -write_buffer_size=100000 -num=4000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 3.9711 | 0.264408 | 3.9914 | 0.254563 | 0.5111933721 20 | 3.83905 | 0.0664488 | 3.8251 | 0.0695456 | **-0.3633711465** 40 | 3.86625 | 0.136669 | 3.8867 | 0.143765 | **0.5289363078** - db_stress: `python3 tools/db_crashtest.py blackbox -charge_compression_dictionary_building_buffer=1 -charge_filter_construction=1 -charge_table_reader=1 -cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D36054712 Pulled By: hx235 fbshipit-source-id: d406e90f5e0c5ea4dbcb585a484ad9302d4302af |
3 years ago |
|
sdong
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736a7b5433 |
Remove own ToString() (#9955)
Summary: ToString() is created as some platform doesn't support std::to_string(). However, we've already used std::to_string() by mistake for 16 months (in db/db_info_dumper.cc). This commit just remove ToString(). Pull Request resolved: https://github.com/facebook/rocksdb/pull/9955 Test Plan: Watch CI tests Reviewed By: riversand963 Differential Revision: D36176799 fbshipit-source-id: bdb6dcd0e3a3ab96a1ac810f5d0188f684064471 |
3 years ago |
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sdong
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49628c9a83 |
Use std::numeric_limits<> (#9954)
Summary: Right now we still don't fully use std::numeric_limits but use a macro, mainly for supporting VS 2013. Right now we only support VS 2017 and up so it is not a problem. The code comment claims that MinGW still needs it. We don't have a CI running MinGW so it's hard to validate. since we now require C++17, it's hard to imagine MinGW would still build RocksDB but doesn't support std::numeric_limits<>. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9954 Test Plan: See CI Runs. Reviewed By: riversand963 Differential Revision: D36173954 fbshipit-source-id: a35a73af17cdcae20e258cdef57fcf29a50b49e0 |
3 years ago |
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Mark Callaghan
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bf68d1c93d |
Print elapsed time and number of operations completed (#9886)
Summary: This is inspired by debugging a regression test that runs for ~0.05 seconds and the short running time makes it prone to variance. While db_bench ran for ~60 seconds, 59.95 seconds was spent opening 128 databases (and doing recovery). So it was harder to notice that the benchmark only ran for 0.05 seconds. Normally I add output to the end of the line to make life easier for existing tools that parse it but in this case the output near the end of the line has two optional parts and one of the optional parts adds an extra newline. This is for https://github.com/facebook/rocksdb/issues/9856 Pull Request resolved: https://github.com/facebook/rocksdb/pull/9886 Test Plan: ./db_bench --benchmarks=overwrite,readrandom --num=1000000 --threads=4 old output: DB path: [/tmp/rocksdbtest-2260/dbbench] overwrite : 14.108 micros/op 283338 ops/sec; 31.3 MB/s DB path: [/tmp/rocksdbtest-2260/dbbench] readrandom : 7.994 micros/op 496788 ops/sec; 55.0 MB/s (1000000 of 1000000 found) new output: DB path: [/tmp/rocksdbtest-2260/dbbench] overwrite : 14.117 micros/op 282862 ops/sec 14.141 seconds 4000000 operations; 31.3 MB/s DB path: [/tmp/rocksdbtest-2260/dbbench] readrandom : 8.649 micros/op 458475 ops/sec 8.725 seconds 4000000 operations; 49.8 MB/s (981548 of 1000000 found) Reviewed By: ajkr Differential Revision: D36102269 Pulled By: mdcallag fbshipit-source-id: 5cd8a9e11f5cbe2a46809571afd83335b6b0caa0 |
3 years ago |
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Mark Callaghan
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b6ec3328af |
Make --benchmarks=flush flush the default column family (#9887)
Summary: db_bench --benchmarks=flush wasn't flushing the default column family. This is for https://github.com/facebook/rocksdb/issues/9880 Pull Request resolved: https://github.com/facebook/rocksdb/pull/9887 Test Plan: Confirm that flush works (*.log is empty) when "flush" added to benchmark list Confirm that *.log is not empty otherwise. Repeat for all combinations for: uses column families, uses multiple databases ./db_bench --benchmarks=overwrite --num=10000 ls -lrt /tmp/rocksdbtest-2260/dbbench/*.log -rw-r--r-- 1 me users 1380286 Apr 21 10:47 /tmp/rocksdbtest-2260/dbbench/000004.log ./db_bench --benchmarks=overwrite,flush --num=10000 ls -lrt /tmp/rocksdbtest-2260/dbbench/*.log -rw-r--r-- 1 me users 0 Apr 21 10:48 /tmp/rocksdbtest-2260/dbbench/000008.log ./db_bench --benchmarks=overwrite --num=10000 --num_column_families=4 ls -lrt /tmp/rocksdbtest-2260/dbbench/*.log -rw-r--r-- 1 me users 1387823 Apr 21 10:49 /tmp/rocksdbtest-2260/dbbench/000004.log ./db_bench --benchmarks=overwrite,flush --num=10000 --num_column_families=4 ls -lrt /tmp/rocksdbtest-2260/dbbench/*.log -rw-r--r-- 1 me users 0 Apr 21 10:51 /tmp/rocksdbtest-2260/dbbench/000014.log ./db_bench --benchmarks=overwrite --num=10000 --num_multi_db=2 ls -lrt /tmp/rocksdbtest-2260/dbbench/[01]/*.log -rw-r--r-- 1 me users 1380838 Apr 21 10:55 /tmp/rocksdbtest-2260/dbbench/0/000004.log -rw-r--r-- 1 me users 1379734 Apr 21 10:55 /tmp/rocksdbtest-2260/dbbench/1/000004.log ./db_bench --benchmarks=overwrite,flush --num=10000 --num_multi_db=2 ls -lrt /tmp/rocksdbtest-2260/dbbench/[01]/*.log -rw-r--r-- 1 me users 0 Apr 21 10:57 /tmp/rocksdbtest-2260/dbbench/0/000013.log -rw-r--r-- 1 me users 0 Apr 21 10:57 /tmp/rocksdbtest-2260/dbbench/1/000013.log ./db_bench --benchmarks=overwrite --num=10000 --num_column_families=4 --num_multi_db=2 ls -lrt /tmp/rocksdbtest-2260/dbbench/[01]/*.log -rw-r--r-- 1 me users 1395108 Apr 21 10:52 /tmp/rocksdbtest-2260/dbbench/1/000004.log -rw-r--r-- 1 me users 1380411 Apr 21 10:52 /tmp/rocksdbtest-2260/dbbench/0/000004.log ./db_bench --benchmarks=overwrite,flush --num=10000 --num_column_families=4 --num_multi_db=2 ls -lrt /tmp/rocksdbtest-2260/dbbench/[01]/*.log -rw-r--r-- 1 me users 0 Apr 21 10:54 /tmp/rocksdbtest-2260/dbbench/0/000022.log -rw-r--r-- 1 me users 0 Apr 21 10:54 /tmp/rocksdbtest-2260/dbbench/1/000022.log Reviewed By: ajkr Differential Revision: D36026777 Pulled By: mdcallag fbshipit-source-id: d42d3d7efceea7b9a25bbbc0f04461d2b7301122 |
3 years ago |
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Jaromir Vanek
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fb9a167a55 |
Add 95% confidence intervals to db_bench output (#9882)
Summary: Enhancing `db_bench` output with 95% statistical confidence intervals for better performance evaluation. The goal is to unambiguously separate random variance when running benchmark over multiple iterations. Output enhanced with confidence intervals exposed in brackets: ``` $ ./db_bench --benchmarks=fillseq[-X10] Running benchmark for 10 times fillseq : 4.961 micros/op 201578 ops/sec; 22.3 MB/s fillseq : 5.030 micros/op 198824 ops/sec; 22.0 MB/s fillseq [AVG 2 runs] : 200201 (± 2698) ops/sec; 22.1 (± 0.3) MB/sec fillseq : 4.963 micros/op 201471 ops/sec; 22.3 MB/s fillseq [AVG 3 runs] : 200624 (± 1765) ops/sec; 22.2 (± 0.2) MB/sec fillseq : 5.035 micros/op 198625 ops/sec; 22.0 MB/s fillseq [AVG 4 runs] : 200124 (± 1586) ops/sec; 22.1 (± 0.2) MB/sec fillseq : 4.979 micros/op 200861 ops/sec; 22.2 MB/s fillseq [AVG 5 runs] : 200272 (± 1262) ops/sec; 22.2 (± 0.1) MB/sec fillseq : 4.893 micros/op 204367 ops/sec; 22.6 MB/s fillseq [AVG 6 runs] : 200954 (± 1688) ops/sec; 22.2 (± 0.2) MB/sec fillseq : 4.914 micros/op 203502 ops/sec; 22.5 MB/s fillseq [AVG 7 runs] : 201318 (± 1595) ops/sec; 22.3 (± 0.2) MB/sec fillseq : 4.998 micros/op 200074 ops/sec; 22.1 MB/s fillseq [AVG 8 runs] : 201163 (± 1415) ops/sec; 22.3 (± 0.2) MB/sec fillseq : 4.946 micros/op 202188 ops/sec; 22.4 MB/s fillseq [AVG 9 runs] : 201277 (± 1267) ops/sec; 22.3 (± 0.1) MB/sec fillseq : 5.093 micros/op 196331 ops/sec; 21.7 MB/s fillseq [AVG 10 runs] : 200782 (± 1491) ops/sec; 22.2 (± 0.2) MB/sec fillseq [AVG 10 runs] : 200782 (± 1491) ops/sec; 22.2 (± 0.2) MB/sec fillseq [MEDIAN 10 runs] : 201166 ops/sec; 22.3 MB/s ``` For more explicit interval representation, use `--confidence_interval_only` flag: ``` $ ./db_bench --benchmarks=fillseq[-X10] --confidence_interval_only Running benchmark for 10 times fillseq : 4.935 micros/op 202648 ops/sec; 22.4 MB/s fillseq : 5.078 micros/op 196943 ops/sec; 21.8 MB/s fillseq [CI95 2 runs] : (194205, 205385) ops/sec; (21.5, 22.7) MB/sec fillseq : 5.159 micros/op 193816 ops/sec; 21.4 MB/s fillseq [CI95 3 runs] : (192735, 202869) ops/sec; (21.3, 22.4) MB/sec fillseq : 4.947 micros/op 202158 ops/sec; 22.4 MB/s fillseq [CI95 4 runs] : (194721, 203061) ops/sec; (21.5, 22.5) MB/sec fillseq : 4.908 micros/op 203756 ops/sec; 22.5 MB/s fillseq [CI95 5 runs] : (196113, 203615) ops/sec; (21.7, 22.5) MB/sec fillseq : 5.063 micros/op 197528 ops/sec; 21.9 MB/s fillseq [CI95 6 runs] : (196319, 202631) ops/sec; (21.7, 22.4) MB/sec fillseq : 5.214 micros/op 191799 ops/sec; 21.2 MB/s fillseq [CI95 7 runs] : (194953, 201803) ops/sec; (21.6, 22.3) MB/sec fillseq : 5.260 micros/op 190095 ops/sec; 21.0 MB/s fillseq [CI95 8 runs] : (193749, 200937) ops/sec; (21.4, 22.2) MB/sec fillseq : 5.076 micros/op 196992 ops/sec; 21.8 MB/s fillseq [CI95 9 runs] : (194134, 200474) ops/sec; (21.5, 22.2) MB/sec fillseq : 5.388 micros/op 185603 ops/sec; 20.5 MB/s fillseq [CI95 10 runs] : (192487, 199781) ops/sec; (21.3, 22.1) MB/sec fillseq [AVG 10 runs] : 196134 (± 3647) ops/sec; 21.7 (± 0.4) MB/sec fillseq [MEDIAN 10 runs] : 196968 ops/sec; 21.8 MB/sec ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/9882 Reviewed By: pdillinger Differential Revision: D35796148 Pulled By: vanekjar fbshipit-source-id: 8313712d16728ff982b8aff28195ee56622385b8 |
3 years ago |
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Andrew Kryczka
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690f1edf37 |
Avoid overwriting OPTIONS file settings in db_bench (#9862)
Summary: `InitializeOptionsGeneral()` was overwriting many options that were already configured by OPTIONS file, potentially with the flag default values. This PR changes that function to only overwrite options in limited scenarios, as described at the top of its definition. Block cache is still a violation. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9862 Test Plan: ran under various scenarios (multi-DB, single DB, OPTIONS file, flags) and verified options are set as expected Reviewed By: jay-zhuang Differential Revision: D35736960 Pulled By: ajkr fbshipit-source-id: 75b77740af37e6f5741618f8a8f5685df2417d03 |
3 years ago |
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gitbw95
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f241d082b6 |
Prevent double caching in the compressed secondary cache (#9747)
Summary: ### **Summary:** When both LRU Cache and CompressedSecondaryCache are configured together, there possibly are some data blocks double cached. **Changes include:** 1. Update IS_PROMOTED to IS_IN_SECONDARY_CACHE to prevent confusions. 2. This PR updates SecondaryCacheResultHandle and use IsErasedFromSecondaryCache to determine whether the handle is erased in the secondary cache. Then, the caller can determine whether to SetIsInSecondaryCache(). 3. Rename LRUSecondaryCache to CompressedSecondaryCache. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9747 Test Plan: **Test Scripts:** 1. Populate a DB. The on disk footprint is 482 MB. The data is set to be 50% compressible, so the total decompressed size is expected to be 964 MB. ./db_bench --benchmarks=fillrandom --num=10000000 -db=/db_bench_1 2. overwrite it to a stable state: ./db_bench --benchmarks=overwrite,stats --num=10000000 -use_existing_db -duration=10 --benchmark_write_rate_limit=2000000 -db=/db_bench_1 4. Run read tests with diffeernt cache setting: T1: ./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=520000000 --statistics -db=/db_bench_1 T2: ./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=320000000 -compressed_secondary_cache_size=400000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1 T3: ./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=520000000 -compressed_secondary_cache_size=400000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1 T4: ./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=20000000 -compressed_secondary_cache_size=500000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1 **Before this PR** | Cache Size | Compressed Secondary Cache Size | Cache Hit Rate | |------------|-------------------------------------|----------------| |520 MB | 0 MB | 85.5% | |320 MB | 400 MB | 96.2% | |520 MB | 400 MB | 98.3% | |20 MB | 500 MB | 98.8% | **Before this PR** | Cache Size | Compressed Secondary Cache Size | Cache Hit Rate | |------------|-------------------------------------|----------------| |520 MB | 0 MB | 85.5% | |320 MB | 400 MB | 99.9% | |520 MB | 400 MB | 99.9% | |20 MB | 500 MB | 99.2% | Reviewed By: anand1976 Differential Revision: D35117499 Pulled By: gitbw95 fbshipit-source-id: ea2657749fc13efebe91a8a1b56bc61d6a224a12 |
3 years ago |
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Duncan Bellamy
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25e31d1a94 |
tools/db_bench_tool.cc use uint64_t instead of size_t (#9800)
Summary: to fix compilation for 32bit Pull Request resolved: https://github.com/facebook/rocksdb/pull/9800 Reviewed By: riversand963 Differential Revision: D35404447 fbshipit-source-id: 6a1185bb38f3a718357aa120e3b26a1ea77f023d |
3 years ago |
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Hui Xiao
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49623f9c8e |
Account memory of big memory users in BlockBasedTable in global memory limit (#9748)
Summary: **Context:** Through heap profiling, we discovered that `BlockBasedTableReader` objects can accumulate and lead to high memory usage (e.g, `max_open_file = -1`). These memories are currently not saved, not tracked, not constrained and not cache evict-able. As a first step to improve this, similar to https://github.com/facebook/rocksdb/pull/8428, this PR is to track an estimate of `BlockBasedTableReader` object's memory in block cache and fail future creation if the memory usage exceeds the available space of cache at the time of creation. **Summary:** - Approximate big memory users (`BlockBasedTable::Rep` and `TableProperties` )' memory usage in addition to the existing estimated ones (filter block/index block/un-compression dictionary) - Charge all of these memory usages to block cache on `BlockBasedTable::Open()` and release them on `~BlockBasedTable()` as there is no memory usage fluctuation of concern in between - Refactor on CacheReservationManager (and its call-sites) to add concurrent support for BlockBasedTable used in this PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9748 Test Plan: - New unit tests - db bench: `OpenDb` : **-0.52% in ms** - Setup `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -write_buffer_size=1048576` - Repeated run with pre-change w/o feature and post-change with feature, benchmark `OpenDb`: `./db_bench -benchmarks=readrandom -use_existing_db=1 -db=/dev/shm/testdb -reserve_table_reader_memory=true (remove this when running w/o feature) -file_opening_threads=3 -open_files=-1 -report_open_timing=true| egrep 'OpenDb:'` #-run | (feature-off) avg milliseconds | std milliseconds | (feature-on) avg milliseconds | std milliseconds | change (%) -- | -- | -- | -- | -- | -- 10 | 11.4018 | 5.95173 | 9.47788 | 1.57538 | -16.87382694 20 | 9.23746 | 0.841053 | 9.32377 | 1.14074 | 0.9343477536 40 | 9.0876 | 0.671129 | 9.35053 | 1.11713 | 2.893283155 80 | 9.72514 | 2.28459 | 9.52013 | 1.0894 | -2.108041632 160 | 9.74677 | 0.991234 | 9.84743 | 1.73396 | 1.032752389 320 | 10.7297 | 5.11555 | 10.547 | 1.97692 | **-1.70275031** 640 | 11.7092 | 2.36565 | 11.7869 | 2.69377 | **0.6635807741** - db bench on write with cost to cache in WriteBufferManager (just in case this PR's CRM refactoring accidentally slows down anything in WBM) : `fillseq` : **+0.54% in micros/op** `./db_bench -benchmarks=fillseq -db=/dev/shm/testdb -disable_auto_compactions=1 -cost_write_buffer_to_cache=true -write_buffer_size=10000000000 | egrep 'fillseq'` #-run | (pre-PR) avg micros/op | std micros/op | (post-PR) avg micros/op | std micros/op | change (%) -- | -- | -- | -- | -- | -- 10 | 6.15 | 0.260187 | 6.289 | 0.371192 | 2.260162602 20 | 7.28025 | 0.465402 | 7.37255 | 0.451256 | 1.267813605 40 | 7.06312 | 0.490654 | 7.13803 | 0.478676 | **1.060579461** 80 | 7.14035 | 0.972831 | 7.14196 | 0.92971 | **0.02254791432** - filter bench: `bloom filter`: **-0.78% in ms/key** - ` ./filter_bench -impl=2 -quick -reserve_table_builder_memory=true | grep 'Build avg'` #-run | (pre-PR) avg ns/key | std ns/key | (post-PR) ns/key | std ns/key | change (%) -- | -- | -- | -- | -- | -- 10 | 26.4369 | 0.442182 | 26.3273 | 0.422919 | **-0.4145720565** 20 | 26.4451 | 0.592787 | 26.1419 | 0.62451 | **-1.1465262** - Crash test `python3 tools/db_crashtest.py blackbox --reserve_table_reader_memory=1 --cache_size=1` killed as normal Reviewed By: ajkr Differential Revision: D35136549 Pulled By: hx235 fbshipit-source-id: 146978858d0f900f43f4eb09bfd3e83195e3be28 |
3 years ago |
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Bo Wang
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bcabee737f |
Improve comments for some files (#9793)
Summary: Update the comments, e.g. fixing typo, formatting, etc. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9793 Reviewed By: jay-zhuang Differential Revision: D35323989 Pulled By: gitbw95 fbshipit-source-id: 4a72fc02b67abaae8be0d1439b68f9967a68052d |
3 years ago |
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Andrew Kryczka
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bfea9e7c02 |
Add benchmark for GetMergeOperands() (#9785)
Summary: There's an existing benchmark, "getmergeoperands", but it is unconventional in that it has multiple phases and hardcoded setup parameters. This PR adds a different one, "readrandomoperands", that follows the pattern of other benchmarks of having a single phase and taking its configuration from existing flags. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9785 Test Plan: ``` $ ./db_bench -benchmarks=mergerandom -merge_operator=StringAppendOperator -write_buffer_size=1048576 -max_bytes_for_level_base=4194304 -target_file_size_base=1048576 -compression_type=none -disable_auto_compactions=true $ ./db_bench -use_existing_db=true -benchmarks=readrandomoperands -merge_operator=StringAppendOperator -disable_auto_compactions=true -duration=10 ... readrandomoperands : 542.082 micros/op 1844 ops/sec; 0.2 MB/s (11980 of 18999 found) ``` Reviewed By: jay-zhuang Differential Revision: D35290412 Pulled By: ajkr fbshipit-source-id: fb367ca614b128cef844a75f0e5d9dd7c3328d85 |
3 years ago |