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20 Commits (5fef34fd3a42b31abb0e454d467e0128b115a69c)
| Author | SHA1 | Message | Date |
|---|---|---|---|
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 |
|
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 |
|
Peter Dillinger
|
86a1e3e0e7 |
Derive cache keys from SST unique IDs (#10394)
Summary: ... so that cache keys can be derived from DB manifest data before reading the file from storage--so that every part of the file can potentially go in a persistent cache. See updated comments in cache_key.cc for technical details. Importantly, the new cache key encoding uses some fancy but efficient math to pack data into the cache key without depending on the sizes of the various pieces. This simplifies some existing code creating cache keys, like cache warming before the file size is known. This should provide us an essentially permanent mapping between SST unique IDs and base cache keys, with the ability to "upgrade" SST unique IDs (and thus cache keys) with new SST format_versions. These cache keys are of similar, perhaps indistinguishable quality to the previous generation. Before this change (see "corrected" days between collision): ``` ./cache_bench -stress_cache_key -sck_keep_bits=43 18 collisions after 2 x 90 days, est 10 days between (1.15292e+19 corrected) ``` After this change (keep 43 bits, up through 50, to validate "trajectory" is ok on "corrected" days between collision): ``` 19 collisions after 3 x 90 days, est 14.2105 days between (1.63836e+19 corrected) 16 collisions after 5 x 90 days, est 28.125 days between (1.6213e+19 corrected) 15 collisions after 7 x 90 days, est 42 days between (1.21057e+19 corrected) 15 collisions after 17 x 90 days, est 102 days between (1.46997e+19 corrected) 15 collisions after 49 x 90 days, est 294 days between (2.11849e+19 corrected) 15 collisions after 62 x 90 days, est 372 days between (1.34027e+19 corrected) 15 collisions after 53 x 90 days, est 318 days between (5.72858e+18 corrected) 15 collisions after 309 x 90 days, est 1854 days between (1.66994e+19 corrected) ``` However, the change does modify (probably weaken) the "guaranteed unique" promise from this > SST files generated in a single process are guaranteed to have unique cache keys, unless/until number session ids * max file number = 2**86 to this (see https://github.com/facebook/rocksdb/issues/10388) > With the DB id limitation, we only have nice guaranteed unique cache keys for files generated in a single process until biggest session_id_counter and offset_in_file reach combined 64 bits I don't think this is a practical concern, though. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10394 Test Plan: unit tests updated, see simulation results above Reviewed By: jay-zhuang Differential Revision: D38667529 Pulled By: pdillinger fbshipit-source-id: 49af3fe7f47e5b61162809a78b76c769fd519fba |
2 years ago |
|
Peter Dillinger
|
65036e4217 |
Revert "Add a blob-specific cache priority (#10309)" (#10434)
Summary:
This reverts commit
|
2 years ago |
|
Gang Liao
|
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 |
|
Peter Dillinger
|
01a2e20299 |
Account for DB ID in stress testing block cache keys (#10388)
Summary: I recently discovered that block cache keys are slightly lower quality than previously thought, because my stress testing tool failed to simulate the effect of DB ID differences. This change updates the tool and gives us data to guide future developments. (No changes to production code here and now.) Nevertheless, the following promise still holds ``` // In fact, if our SST files are all < 4TB (see // BlockBasedTable::kMaxFileSizeStandardEncoding), then SST files generated // in a single process are guaranteed to have unique cache keys, unless/until // number session ids * max file number = 2**86 ... ``` because although different DB IDs could cause collision in file number and offset data, that would have to be using the same DB session (lower) to cause a block cache key collision, which is not possible in the same process. (A session is associated with only one DB ID.) This change fixes cache_bench -stress_cache_key to set and reset DB IDs in a parameterized way to evaluate the effect. Previous results assumed to be representative (using -sck_keep_bits=43): ``` 15 collisions after 15 x 90 days, est 90 days between (1.03763e+20 corrected) ``` or expected collision on a single machine every 104 billion billion days (see "corrected" value). After accounting for DB IDs, test never really changing, intermediate, and very frequently changing (using default -sck_db_count=100): ``` -sck_newdb_nreopen=1000000000: 15 collisions after 2 x 90 days, est 12 days between (1.38351e+19 corrected) -sck_newdb_nreopen=10000: 17 collisions after 2 x 90 days, est 10.5882 days between (1.22074e+19 corrected) -sck_newdb_nreopen=100: 19 collisions after 2 x 90 days, est 9.47368 days between (1.09224e+19 corrected) ``` or roughly 10x more often than previously thought (still extremely if not impossibly rare), and better than random base cache keys (with -sck_randomize), though < 10x better than random: ``` 31 collisions after 1 x 90 days, est 2.90323 days between (3.34719e+18 corrected) ``` If we simply fixed this by ignoring DB ID for cache keys, we would potentially have a shortage of entropy for some cases, such as small file numbers and offsets (e.g. many short-lived processes each using SstFileWriter to create a small file), because existing DB session IDs only provide ~103 bits of entropy. We could upgrade the entropy in DB session IDs to accommodate, but it's not known what all would be affected by changing from 20 digit session IDs to something larger. Instead, my plan is to 1) Move to block cache keys derived from SST unique IDs (so that we can derive block cache keys from manifest data without reading file on storage), and show no significant regression in expected collision rate. 2) Generate better SST unique IDs in format_version=6 (https://github.com/facebook/rocksdb/issues/9058), which should have ~100x lower expected/predicted collision rate based on simulations with this stress test: ``` ./cache_bench -stress_cache_key -sck_keep_bits=39 -sck_newdb_nreopen=100 -sck_footer_unique_id ... 15 collisions after 19 x 90 days, est 114 days between (2.10293e+21 corrected) ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/10388 Test Plan: no production changes Reviewed By: jay-zhuang Differential Revision: D37986714 Pulled By: pdillinger fbshipit-source-id: e759b2469e3365cb01c6661a69e0ab849ef4c3df |
2 years ago |
|
Guido Tagliavini Ponce
|
a543773bbc |
Add lean option to cache_bench (#10363)
Summary: Sometimes we may not want to include extra computation in our cache_bench experiments. Here we add a flag to avoid any extra work. We also moved the timer start after the key generation. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10363 Test Plan: Run cache_bench with and without the new flag and check that the appropriate code is being executed. Reviewed By: pdillinger Differential Revision: D37870416 Pulled By: guidotag fbshipit-source-id: f853207b6643b9328e774251c3f679b1fd78a11a |
2 years ago |
|
Guido Tagliavini Ponce
|
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 |
|
Guido Tagliavini Ponce
|
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 |
|
Guido Tagliavini Ponce
|
b52620ab0e |
Fix key size in cache_bench (#10234)
Summary: cache_bench wasn't generating 16B keys, which are necessary for FastLRUCache. Also: - Added asserts in cache_bench, which is assuming that inserts never fail. When they fail (for example, if we used keys of the wrong size), memory allocated to the values will becomes leaked, and eventually the program crashes. - Move kCacheKeySize to the right spot. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10234 Test Plan: ``make -j24 check``. Also, run cache_bench with FastLRUCache and check that memory usage doesn't blow up: ``./cache_bench -cache_type=fast_lru_cache -num_shard_bits=6 -skewed=true \ -lookup_insert_percent=100 -lookup_percent=0 -insert_percent=0 -erase_percent=0 \ -populate_cache=true -cache_size=1073741824 -ops_per_thread=10000000 \ -value_bytes=8192 -resident_ratio=1 -threads=16`` Reviewed By: pdillinger Differential Revision: D37382949 Pulled By: guidotag fbshipit-source-id: b697a942ebb215de5d341f98dc8566763436ba9b |
2 years ago |
|
Peter Dillinger
|
1aac814578 |
Use optimized folly DistributedMutex in LRUCache when available (#10179)
Summary: folly DistributedMutex is faster than standard mutexes though imposes some static obligations on usage. See https://github.com/facebook/folly/blob/main/folly/synchronization/DistributedMutex.h for details. Here we use this alternative for our Cache implementations (especially LRUCache) for better locking performance, when RocksDB is compiled with folly. Also added information about which distributed mutex implementation is being used to cache_bench output and to DB LOG. Intended follow-up: * Use DMutex in more places, perhaps improving API to support non-scoped locking * Fix linking with fbcode compiler (needs ROCKSDB_NO_FBCODE=1 currently) Credit: Thanks Siying for reminding me about this line of work that was previously left unfinished. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10179 Test Plan: for correctness, existing tests. CircleCI config updated. Also Meta-internal buck build updated. For performance, ran simultaneous before & after cache_bench. Out of three comparison runs, the middle improvement to ops/sec was +21%: Baseline: USE_CLANG=1 DEBUG_LEVEL=0 make -j24 cache_bench (fbcode compiler) ``` Complete in 20.201 s; Rough parallel ops/sec = 1584062 Thread ops/sec = 107176 Operation latency (ns): Count: 32000000 Average: 9257.9421 StdDev: 122412.04 Min: 134 Median: 3623.0493 Max: 56918500 Percentiles: P50: 3623.05 P75: 10288.02 P99: 30219.35 P99.9: 683522.04 P99.99: 7302791.63 ``` New: (add USE_FOLLY=1) ``` Complete in 16.674 s; Rough parallel ops/sec = 1919135 (+21%) Thread ops/sec = 135487 Operation latency (ns): Count: 32000000 Average: 7304.9294 StdDev: 108530.28 Min: 132 Median: 3777.6012 Max: 91030902 Percentiles: P50: 3777.60 P75: 10169.89 P99: 24504.51 P99.9: 59721.59 P99.99: 1861151.83 ``` Reviewed By: anand1976 Differential Revision: D37182983 Pulled By: pdillinger fbshipit-source-id: a17eb05f25b832b6a2c1356f5c657e831a5af8d1 |
2 years ago |
|
Guido Tagliavini Ponce
|
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 |
|
Guido Tagliavini Ponce
|
eb99e08076 |
Add support for FastLRUCache in cache_bench (#10095)
Summary: cache_bench can now run with FastLRUCache. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10095 Test Plan: - Temporarily add an ``assert(false)`` in the execution path that sets up the FastLRUCache. Run ``make -j24 cache_bench``. Then test the appropriate code is used by running ``./cache_bench -cache_type=fast_lru_cache`` and checking that the assert is called. Repeat for LRUCache. - Verify that FastLRUCache (currently a clone of LRUCache) has similar latency distribution than LRUCache, by comparing the outputs of ``./cache_bench -cache_type=fast_lru_cache`` and ``./cache_bench -cache_type=lru_cache``. Reviewed By: pdillinger Differential Revision: D36875834 Pulled By: guidotag fbshipit-source-id: eb2ad0bb32c2717a258a6ac66ed736e06f826cd8 |
2 years ago |
|
Andrew Kryczka
|
54fb2a8975 |
Change type of cache buffer passed to `Cache::CreateCallback()` to `const void*` (#9595)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/9595 Reviewed By: riversand963 Differential Revision: D34329906 Pulled By: ajkr fbshipit-source-id: 508601856fa9bee4d40f4a68d14d333ef2143d40 |
3 years ago |
|
Peter Dillinger
|
afc280fdfd |
Enhance new cache key testing & comments (#9329)
Summary: Follow-up to https://github.com/facebook/rocksdb/issues/9126 Added new unit tests to validate some of the claims of guaranteed uniqueness within certain large bounds. Also cleaned up the cache_bench -stress-cache-key tool with better comments and description. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9329 Test Plan: no changes to production code Reviewed By: mrambacher Differential Revision: D33269328 Pulled By: pdillinger fbshipit-source-id: 3a2b684a6b2b15f79dc872e563e3d16563be26de |
3 years ago |
|
Peter Dillinger
|
0050a73a4f |
New stable, fixed-length cache keys (#9126)
Summary: This change standardizes on a new 16-byte cache key format for block cache (incl compressed and secondary) and persistent cache (but not table cache and row cache). The goal is a really fast cache key with practically ideal stability and uniqueness properties without external dependencies (e.g. from FileSystem). A fixed key size of 16 bytes should enable future optimizations to the concurrent hash table for block cache, which is a heavy CPU user / bottleneck, but there appears to be measurable performance improvement even with no changes to LRUCache. This change replaces a lot of disjointed and ugly code handling cache keys with calls to a simple, clean new internal API (cache_key.h). (Preserving the old cache key logic under an option would be very ugly and likely negate the performance gain of the new approach. Complete replacement carries some inherent risk, but I think that's acceptable with sufficient analysis and testing.) The scheme for encoding new cache keys is complicated but explained in cache_key.cc. Also: EndianSwapValue is moved to math.h to be next to other bit operations. (Explains some new include "math.h".) ReverseBits operation added and unit tests added to hash_test for both. Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause) Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126 Test Plan: ### Basic correctness Several tests needed updates to work with the new functionality, mostly because we are no longer relying on filesystem for stable cache keys so table builders & readers need more context info to agree on cache keys. This functionality is so core, a huge number of existing tests exercise the cache key functionality. ### Performance Create db with `TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters` And test performance with `TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4` using DEBUG_LEVEL=0 and simultaneous before & after runs. Before ops/sec, avg over 100 runs: 121924 After ops/sec, avg over 100 runs: 125385 (+2.8%) ### Collision probability I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity over many months, by making some pessimistic simplifying assumptions: * Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys) * All of every file is cached for its entire lifetime We use a simple table with skewed address assignment and replacement on address collision to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output with `./cache_bench -stress_cache_key -sck_keep_bits=40`: ``` Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached) ``` These come from default settings of 2.5M files per day of 32 MB each, and `-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality. More default assumptions, relatively pessimistic: * 100 DBs in same process (doesn't matter much) * Re-open DB in same process (new session ID related to old session ID) on average every 100 files generated * Restart process (all new session IDs unrelated to old) 24 times per day After enough data, we get a result at the end: ``` (keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected) ``` If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data: ``` (keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected) (keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected) ``` The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases: ``` 197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected) ``` I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data. Reviewed By: zhichao-cao Differential Revision: D33171746 Pulled By: pdillinger fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f |
3 years ago |
|
Yanqin Jin
|
42fef0224f |
Fix build for msvc (#9230)
Summary: Test plan With Visual Studio 2017. ``` cd rocksdb mkdir build && cd build cmake -G "Visual Studio 15 Win64" -DWITH_GFLAGS=1 .. MSBuild rocksdb.sln /m /TARGET:cache_bench /TARGET:db_bench /TARGET:db_stress ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/9230 Reviewed By: akankshamahajan15 Differential Revision: D32705095 Pulled By: riversand963 fbshipit-source-id: 101e3533f5178b24c0535ddc47a39347ccfcf92c |
3 years ago |
|
mrambacher
|
570248aeff |
Make SecondaryCache Customizable (#8480)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/8480 Reviewed By: zhichao-cao Differential Revision: D29528740 Pulled By: mrambacher fbshipit-source-id: fd0f70d15f66611c8498257a9973f7e98ca13839 |
3 years ago |
|
anand76
|
13232e11d4 |
Allow cache_bench/db_bench to use a custom secondary cache (#8312)
Summary: This PR adds a ```-secondary_cache_uri``` option to the cache_bench and db_bench tools to allow the user to specify a custom secondary cache URI. The object registry is used to create an instance of the ```SecondaryCache``` object of the type specified in the URI. The main cache_bench code is packaged into a separate library, similar to db_bench. An example invocation of db_bench with a secondary cache URI - ```db_bench --env_uri=ws://ws.flash_sandbox.vll1_2/ -db=anand/nvm_cache_2 -use_existing_db=true -benchmarks=readrandom -num=30000000 -key_size=32 -value_size=256 -use_direct_reads=true -cache_size=67108864 -cache_index_and_filter_blocks=true -secondary_cache_uri='cachelibwrapper://filename=/home/anand76/nvm_cache/cache_file;size=2147483648;regionSize=16777216;admPolicy=random;admProbability=1.0;volatileSize=8388608;bktPower=20;lockPower=12' -partition_index_and_filters=true -duration=1800``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/8312 Reviewed By: zhichao-cao Differential Revision: D28544325 Pulled By: anand1976 fbshipit-source-id: 8f209b9af900c459dc42daa7a610d5f00176eeed |
4 years ago |
|
Peter Dillinger
|
78a309bf86 |
New Cache API for gathering statistics (#8225)
Summary: Adds a new Cache::ApplyToAllEntries API that we expect to use (in follow-up PRs) for efficiently gathering block cache statistics. Notable features vs. old ApplyToAllCacheEntries: * Includes key and deleter (in addition to value and charge). We could have passed in a Handle but then more virtual function calls would be needed to get the "fields" of each entry. We expect to use the 'deleter' to identify the origin of entries, perhaps even more. * Heavily tuned to minimize latency impact on operating cache. It does this by iterating over small sections of each cache shard while cycling through the shards. * Supports tuning roughly how many entries to operate on for each lock acquire and release, to control the impact on the latency of other operations without excessive lock acquire & release. The right balance can depend on the cost of the callback. Good default seems to be around 256. * There should be no need to disable thread safety. (I would expect uncontended locks to be sufficiently fast.) I have enhanced cache_bench to validate this approach: * Reports a histogram of ns per operation, so we can look at the ditribution of times, not just throughput (average). * Can add a thread for simulated "gather stats" which calls ApplyToAllEntries at a specified interval. We also generate a histogram of time to run ApplyToAllEntries. To make the iteration over some entries of each shard work as cleanly as possible, even with resize between next set of entries, I have re-arranged which hash bits are used for sharding and which for indexing within a shard. Pull Request resolved: https://github.com/facebook/rocksdb/pull/8225 Test Plan: A couple of unit tests are added, but primary validation is manual, as the primary risk is to performance. The primary validation is using cache_bench to ensure that neither the minor hashing changes nor the simulated stats gathering significantly impact QPS or latency distribution. Note that adding op latency histogram seriously impacts the benchmark QPS, so for a fair baseline, we need the cache_bench changes (except remove simulated stat gathering to make it compile). In short, we don't see any reproducible difference in ops/sec or op latency unless we are gathering stats nearly continuously. Test uses 10GB block cache with 8KB values to be somewhat realistic in the number of items to iterate over. Baseline typical output: ``` Complete in 92.017 s; Rough parallel ops/sec = 869401 Thread ops/sec = 54662 Operation latency (ns): Count: 80000000 Average: 11223.9494 StdDev: 29.61 Min: 0 Median: 7759.3973 Max: 9620500 Percentiles: P50: 7759.40 P75: 14190.73 P99: 46922.75 P99.9: 77509.84 P99.99: 217030.58 ------------------------------------------------------ [ 0, 1 ] 68 0.000% 0.000% ( 2900, 4400 ] 89 0.000% 0.000% ( 4400, 6600 ] 33630240 42.038% 42.038% ######## ( 6600, 9900 ] 18129842 22.662% 64.700% ##### ( 9900, 14000 ] 7877533 9.847% 74.547% ## ( 14000, 22000 ] 15193238 18.992% 93.539% #### ( 22000, 33000 ] 3037061 3.796% 97.335% # ( 33000, 50000 ] 1626316 2.033% 99.368% ( 50000, 75000 ] 421532 0.527% 99.895% ( 75000, 110000 ] 56910 0.071% 99.966% ( 110000, 170000 ] 16134 0.020% 99.986% ( 170000, 250000 ] 5166 0.006% 99.993% ( 250000, 380000 ] 3017 0.004% 99.996% ( 380000, 570000 ] 1337 0.002% 99.998% ( 570000, 860000 ] 805 0.001% 99.999% ( 860000, 1200000 ] 319 0.000% 100.000% ( 1200000, 1900000 ] 231 0.000% 100.000% ( 1900000, 2900000 ] 100 0.000% 100.000% ( 2900000, 4300000 ] 39 0.000% 100.000% ( 4300000, 6500000 ] 16 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ``` New, gather_stats=false. Median thread ops/sec of 5 runs: ``` Complete in 92.030 s; Rough parallel ops/sec = 869285 Thread ops/sec = 54458 Operation latency (ns): Count: 80000000 Average: 11298.1027 StdDev: 42.18 Min: 0 Median: 7722.0822 Max: 6398720 Percentiles: P50: 7722.08 P75: 14294.68 P99: 47522.95 P99.9: 85292.16 P99.99: 228077.78 ------------------------------------------------------ [ 0, 1 ] 109 0.000% 0.000% ( 2900, 4400 ] 793 0.001% 0.001% ( 4400, 6600 ] 34054563 42.568% 42.569% ######### ( 6600, 9900 ] 17482646 21.853% 64.423% #### ( 9900, 14000 ] 7908180 9.885% 74.308% ## ( 14000, 22000 ] 15032072 18.790% 93.098% #### ( 22000, 33000 ] 3237834 4.047% 97.145% # ( 33000, 50000 ] 1736882 2.171% 99.316% ( 50000, 75000 ] 446851 0.559% 99.875% ( 75000, 110000 ] 68251 0.085% 99.960% ( 110000, 170000 ] 18592 0.023% 99.983% ( 170000, 250000 ] 7200 0.009% 99.992% ( 250000, 380000 ] 3334 0.004% 99.997% ( 380000, 570000 ] 1393 0.002% 99.998% ( 570000, 860000 ] 700 0.001% 99.999% ( 860000, 1200000 ] 293 0.000% 100.000% ( 1200000, 1900000 ] 196 0.000% 100.000% ( 1900000, 2900000 ] 69 0.000% 100.000% ( 2900000, 4300000 ] 32 0.000% 100.000% ( 4300000, 6500000 ] 10 0.000% 100.000% ``` New, gather_stats=true, 1 second delay between scans. Scans take about 1 second here so it's spending about 50% time scanning. Still the effect on ops/sec and latency seems to be in the noise. Median thread ops/sec of 5 runs: ``` Complete in 91.890 s; Rough parallel ops/sec = 870608 Thread ops/sec = 54551 Operation latency (ns): Count: 80000000 Average: 11311.2629 StdDev: 45.28 Min: 0 Median: 7686.5458 Max: 10018340 Percentiles: P50: 7686.55 P75: 14481.95 P99: 47232.60 P99.9: 79230.18 P99.99: 232998.86 ------------------------------------------------------ [ 0, 1 ] 71 0.000% 0.000% ( 2900, 4400 ] 291 0.000% 0.000% ( 4400, 6600 ] 34492060 43.115% 43.116% ######### ( 6600, 9900 ] 16727328 20.909% 64.025% #### ( 9900, 14000 ] 7845828 9.807% 73.832% ## ( 14000, 22000 ] 15510654 19.388% 93.220% #### ( 22000, 33000 ] 3216533 4.021% 97.241% # ( 33000, 50000 ] 1680859 2.101% 99.342% ( 50000, 75000 ] 439059 0.549% 99.891% ( 75000, 110000 ] 60540 0.076% 99.967% ( 110000, 170000 ] 14649 0.018% 99.985% ( 170000, 250000 ] 5242 0.007% 99.991% ( 250000, 380000 ] 3260 0.004% 99.995% ( 380000, 570000 ] 1599 0.002% 99.997% ( 570000, 860000 ] 1043 0.001% 99.999% ( 860000, 1200000 ] 471 0.001% 99.999% ( 1200000, 1900000 ] 275 0.000% 100.000% ( 1900000, 2900000 ] 143 0.000% 100.000% ( 2900000, 4300000 ] 60 0.000% 100.000% ( 4300000, 6500000 ] 27 0.000% 100.000% ( 6500000, 9800000 ] 7 0.000% 100.000% ( 9800000, 14000000 ] 1 0.000% 100.000% Gather stats latency (us): Count: 46 Average: 980387.5870 StdDev: 60911.18 Min: 879155 Median: 1033777.7778 Max: 1261431 Percentiles: P50: 1033777.78 P75: 1120666.67 P99: 1261431.00 P99.9: 1261431.00 P99.99: 1261431.00 ------------------------------------------------------ ( 860000, 1200000 ] 45 97.826% 97.826% #################### ( 1200000, 1900000 ] 1 2.174% 100.000% Most recent cache entry stats: Number of entries: 1295133 Total charge: 9.88 GB Average key size: 23.4982 Average charge: 8.00 KB Unique deleters: 3 ``` Reviewed By: mrambacher Differential Revision: D28295742 Pulled By: pdillinger fbshipit-source-id: bbc4a552f91ba0fe10e5cc025c42cef5a81f2b95 |
4 years ago |
|
storagezhang
|
d9be6556aa |
Include C++ standard library headers instead of C compatibility headers (#8068)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/8068 Reviewed By: zhichao-cao Differential Revision: D27147685 Pulled By: riversand963 fbshipit-source-id: 5428b1c0142ecae17c977fba31a6d49b52983d1c |
4 years ago |
|
mrambacher
|
12f1137355 |
Add a SystemClock class to capture the time functions of an Env (#7858)
Summary: Introduces and uses a SystemClock class to RocksDB. This class contains the time-related functions of an Env and these functions can be redirected from the Env to the SystemClock. Many of the places that used an Env (Timer, PerfStepTimer, RepeatableThread, RateLimiter, WriteController) for time-related functions have been changed to use SystemClock instead. There are likely more places that can be changed, but this is a start to show what can/should be done. Over time it would be nice to migrate most (if not all) of the uses of the time functions from the Env to the SystemClock. There are several Env classes that implement these functions. Most of these have not been converted yet to SystemClock implementations; that will come in a subsequent PR. It would be good to unify many of the Mock Timer implementations, so that they behave similarly and be tested similarly (some override Sleep, some use a MockSleep, etc). Additionally, this change will allow new methods to be introduced to the SystemClock (like https://github.com/facebook/rocksdb/issues/7101 WaitFor) in a consistent manner across a smaller number of classes. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7858 Reviewed By: pdillinger Differential Revision: D26006406 Pulled By: mrambacher fbshipit-source-id: ed10a8abbdab7ff2e23d69d85bd25b3e7e899e90 |
4 years ago |
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Peter Dillinger
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08552b19d3 |
Genericize and clean up FastRange (#7436)
Summary: A generic algorithm in progress depends on a templatized version of fastrange, so this change generalizes it and renames it to fit our style guidelines, FastRange32, FastRange64, and now FastRangeGeneric. Pull Request resolved: https://github.com/facebook/rocksdb/pull/7436 Test Plan: added a few more test cases Reviewed By: jay-zhuang Differential Revision: D23958153 Pulled By: pdillinger fbshipit-source-id: 8c3b76101653417804997e5f076623a25586f3e8 |
4 years ago |
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Peter Dillinger
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079e77ff9e |
Revamp cache_bench to resemble a real workload (#6629)
Summary: I suspect LRUCache could use some optimization, and to support such an effort, a good benchmarking tool is needed. The existing cache_bench was heavily skewed toward insertion and lookup misses, and did not saturate memory with other work. This change should improve those things to better resemble a real workload. (All below using clang compiler, for some consistency, but not necessarily same version and settings.) The real workload is from production MySQL on RocksDB, filtering stacks containing "LRU", "ShardedCache" or "CacheShard." Lookup inclusive: 66% Insert inclusive: 17% Release inclusive: 15% An alternate simulated workload is MySQL running a LinkBench read test: Lookup inclusive: 54% Insert inclusive: 24% Release inclusive: 21% cache_bench default settings, prior to this change: Lookup inclusive: 35.8% Insert inclusive: 63.6% Release inclusive: 0% cache_bench after this change (intended as somewhat "tighter" workload than average production, more like LinkBench): Lookup inclusive: 52% Insert inclusive: 20% Release inclusive: 26% And top exclusive stacks (portion of stack samples as filtered above): Production MySQL: LRUHandleTable::FindPointer: 25.3% rocksdb::operator==: 15.1% <-- Slice == LRUCacheShard::LRU_Remove: 13.8% ShardedCache::Lookup: 8.9% __pthread_mutex_lock: 7.1% LRUCacheShard::LRU_Insert: 6.3% MurmurHash64A: 4.8% <-- Since upgraded to XXH3p ... Old cache_bench: LRUHandleTable::FindPointer: 23.6% __pthread_mutex_lock: 15.0% __pthread_mutex_unlock_usercnt: 11.7% __lll_lock_wait: 8.6% __lll_unlock_wake: 6.8% LRUCacheShard::LRU_Insert: 6.0% ShardedCache::Lookup: 4.4% LRUCacheShard::LRU_Remove: 2.8% ... rocksdb::operator==: 0.2% <-- Slice == ... New cache_bench: LRUHandleTable::FindPointer: 22.8% __pthread_mutex_unlock_usercnt: 14.3% rocksdb::operator==: 10.5% <-- Slice == LRUCacheShard::LRU_Insert: 9.0% __pthread_mutex_lock: 5.9% LRUCacheShard::LRU_Remove: 5.0% ... ShardedCache::Lookup: 2.9% ... So there's a bit more lock contention in the benchmark than in production, but otherwise looks similar enough to me. At least it's a big improvement over the existing code. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6629 Test Plan: No production code changes, ran cache_bench with ASAN Reviewed By: ltamasi Differential Revision: D20824318 Pulled By: pdillinger fbshipit-source-id: 6f8dc5891ead0f87edbed3a615ecd5289d9abe12 |
5 years ago |
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Levi Tamasi
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e6f86cfb36 |
Revert the recent cache deleter change (#6620)
Summary: Revert "Use function objects as deleters in the block cache (https://github.com/facebook/rocksdb/issues/6545)" This reverts commit |
5 years ago |
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Levi Tamasi
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6301dbe7a7 |
Use function objects as deleters in the block cache (#6545)
Summary:
As the first step of reintroducing eviction statistics for the block
cache, the patch switches from using simple function pointers as deleters
to function objects implementing an interface. This will enable using
deleters that have state, like a smart pointer to the statistics object
that is to be updated when an entry is removed from the cache. For now,
the patch adds a deleter template class `SimpleDeleter`, which simply
casts the `value` pointer to its original type and calls `delete` or
`delete[]` on it as appropriate. Note: to prevent object lifecycle
issues, deleters must outlive the cache entries referring to them;
`SimpleDeleter` ensures this by using the ("leaky") Meyers singleton
pattern.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6545
Test Plan: `make asan_check`
Reviewed By: siying
Differential Revision: D20475823
Pulled By: ltamasi
fbshipit-source-id: fe354c33dd96d9bafc094605462352305449a22a
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5 years ago |
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sdong
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fdf882ded2 |
Replace namespace name "rocksdb" with ROCKSDB_NAMESPACE (#6433)
Summary: When dynamically linking two binaries together, different builds of RocksDB from two sources might cause errors. To provide a tool for user to solve the problem, the RocksDB namespace is changed to a flag which can be overridden in build time. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6433 Test Plan: Build release, all and jtest. Try to build with ROCKSDB_NAMESPACE with another flag. Differential Revision: D19977691 fbshipit-source-id: aa7f2d0972e1c31d75339ac48478f34f6cfcfb3e |
5 years ago |
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sdong
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e8263dbdaa |
Apply formatter to recent 200+ commits. (#5830)
Summary: Further apply formatter to more recent commits. Pull Request resolved: https://github.com/facebook/rocksdb/pull/5830 Test Plan: Run all existing tests. Differential Revision: D17488031 fbshipit-source-id: 137458fd94d56dd271b8b40c522b03036943a2ab |
5 years ago |
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Zhongyi Xie
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d68f9f4580 |
simplify include directive involving inttypes (#5402)
Summary: When using `PRIu64` type of printf specifier, current code base does the following: ``` #ifndef __STDC_FORMAT_MACROS #define __STDC_FORMAT_MACROS #endif #include <inttypes.h> ``` However, this can be simplified to ``` #include <cinttypes> ``` as long as flag `-std=c++11` is used. This should solve issues like https://github.com/facebook/rocksdb/issues/5159 Pull Request resolved: https://github.com/facebook/rocksdb/pull/5402 Differential Revision: D15701195 Pulled By: miasantreble fbshipit-source-id: 6dac0a05f52aadb55e9728038599d3d2e4b59d03 |
6 years ago |
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David Lai
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3be9b36453 |
comment unused parameters to turn on -Wunused-parameter flag
Summary: This PR comments out the rest of the unused arguments which allow us to turn on the -Wunused-parameter flag. This is the second part of a codemod relating to https://github.com/facebook/rocksdb/pull/3557. Closes https://github.com/facebook/rocksdb/pull/3662 Differential Revision: D7426121 Pulled By: Dayvedde fbshipit-source-id: 223994923b42bd4953eb016a0129e47560f7e352 |
7 years ago |
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Andrew Kryczka
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63f1c0a57d |
fix gflags namespace
Summary: I started adding gflags support for cmake on linux and got frustrated that I'd need to duplicate the build_detect_platform logic, which determines namespace based on attempting compilation. We can do it differently -- use the GFLAGS_NAMESPACE macro if available, and if not, that indicates it's an old gflags version without configurable namespace so we can simply hardcode "google". Closes https://github.com/facebook/rocksdb/pull/3212 Differential Revision: D6456973 Pulled By: ajkr fbshipit-source-id: 3e6d5bde3ca00d4496a120a7caf4687399f5d656 |
7 years ago |
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Siying Dong
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3c327ac2d0 |
Change RocksDB License
Summary: Closes https://github.com/facebook/rocksdb/pull/2589 Differential Revision: D5431502 Pulled By: siying fbshipit-source-id: 8ebf8c87883daa9daa54b2303d11ce01ab1f6f75 |
7 years ago |
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Siying Dong
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d616ebea23 |
Add GPLv2 as an alternative license.
Summary: Closes https://github.com/facebook/rocksdb/pull/2226 Differential Revision: D4967547 Pulled By: siying fbshipit-source-id: dd3b58ae1e7a106ab6bb6f37ab5c88575b125ab4 |
8 years ago |
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Siying Dong
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d2dce5611a |
Move some files under util/ to separate dirs
Summary: Move some files under util/ to new directories env/, monitoring/ options/ and cache/ Closes https://github.com/facebook/rocksdb/pull/2090 Differential Revision: D4833681 Pulled By: siying fbshipit-source-id: 2fd8bef |
8 years ago |
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Yi Wu
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4cc37f59e5 |
Introduce ClockCache
Summary: Clock-based cache implemenetation aim to have better concurreny than default LRU cache. See inline comments for implementation details. Test Plan: Update cache_test to run on both LRUCache and ClockCache. Adding some new tests to catch some of the bugs that I fixed while implementing the cache. Reviewers: kradhakrishnan, sdong Reviewed By: sdong Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D61647 |
8 years ago |
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Yi Wu
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f71fc77b7c |
Cache to have an option to fail Cache::Insert() when full
Summary: Cache to have an option to fail Cache::Insert() when full. Update call sites to check status and handle error. I totally have no idea what's correct behavior of all the call sites when they encounter error. Please let me know if you see something wrong or more unit test is needed. Test Plan: make check -j32, see tests pass. Reviewers: anthony, yhchiang, andrewkr, IslamAbdelRahman, kradhakrishnan, sdong Reviewed By: sdong Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D54705 |
9 years ago |
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Baraa Hamodi
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21e95811d1 |
Updated all copyright headers to the new format.
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9 years ago |
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Igor Canadi
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68effa0348 |
Fix -Wshadow for tools
Summary: Previously I made `make check` work with -Wshadow, but there are some tools that are not compiled using `make check`. Test Plan: make all Reviewers: yhchiang, rven, ljin, sdong Reviewed By: ljin, sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D28497 |
10 years ago |
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Saghm Rossi
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f9eaaa66e6 |
added include for inttypes.h to fix nonworking printf statements
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10 years ago |
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Feng Zhu
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53404d9fb7 |
add_qps_info_in cache bench
Summary: print qps in summary Test Plan: ./cache_bench Reviewers: yhchiang, ljin, sdong, igor Reviewed By: igor Subscribers: leveldb Differential Revision: https://reviews.facebook.net/D23079 |
10 years ago |
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Feng Zhu
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40ddc3d6c4 |
add cache bench
Summary: 1. A benchmark for cache Test Plan: ./cache_bench Reviewers: yhchiang, dhruba, sdong, igor, ljin Reviewed By: ljin Subscribers: leveldb Differential Revision: https://reviews.facebook.net/D22809 |
10 years ago |