2262 Commits (aa71464410acdfd1f7b33dc034e0886b67bffac0)

Author	SHA1	Message	Date
Levi Tamasi	6d2a9832d9	Clarify API comments for blob_cache/prepopulate_blob_cache (#10723) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10723 Reviewed By: riversand963 Differential Revision: D39749277 Pulled By: ltamasi fbshipit-source-id: 4bda94b4620a0db1fcd4309c7ad03fc23e8718cb	2 years ago
walter	1b351fd9fe	Add C API to set avoid_unnecessary_blocking_io option (#10693) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10693 Reviewed By: riversand963 Differential Revision: D39668399 Pulled By: ajkr fbshipit-source-id: 66d46e5104c49d235a14e8df8eec3af285ab9752	2 years ago
Peter Dillinger	ef443cead4	Refactor to avoid confusing "raw block" (#10408) ... Summary: We have a lot of confusing code because of mixed, sometimes completely opposite uses of of the term "raw block" or "raw contents", sometimes within the same source file. For example, in `BlockBasedTableBuilder`, `raw_block_contents` and `raw_size` generally referred to uncompressed block contents and size, while `WriteRawBlock` referred to writing a block that is already compressed if it is going to be. Meanwhile, in `BlockBasedTable`, `raw_block_contents` either referred to a (maybe compressed) block with trailer, or a maybe compressed block maybe without trailer. (Note: left as follow-up work to use C++ typing to better sort out the various kinds of BlockContents.) This change primarily tries to apply some consistent terminology around the kinds of block representations, avoiding the unclear "raw". (Any meaning of "raw" assumes some bias toward the storage layer or toward the logical data layer.) Preferred terminology: * **Serialized block** - bytes that go into storage. For block-based table (usually the case) this includes the block trailer. WART: block `size` may or may not include the trailer; need to be clear about whether it does or not. * **Maybe compressed block** - like a serialized block, but without the trailer (or no promise of including a trailer). Must be accompanied by a CompressionType. * **Uncompressed block** - "payload" bytes that are either stored with no compression, used as input to compression function, or result of decompression function. * **Parsed block** - an in-memory form of a block in block cache, as it is used by the table reader. Different C++ types are used depending on the block type (see block_like_traits.h). Other refactorings: * Misc corrections/improvements of internal API comments * Remove a few misleading / unhelpful / redundant comments. * Use move semantics in some places to simplify contracts * Use better parameter names to indicate which parameters are used for outputs * Remove some extraneous `extern` * Various clean-ups to `CacheDumperImpl` (mostly unnecessary code) Pull Request resolved: https://github.com/facebook/rocksdb/pull/10408 Test Plan: existing tests Reviewed By: akankshamahajan15 Differential Revision: D38172617 Pulled By: pdillinger fbshipit-source-id: ccb99299f324ac5ca46996d34c5089621a4f260c	2 years ago
Levi Tamasi	12f5a1e35c	Clarify comments for cache priorities and pool options (#10718) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10718 Reviewed By: riversand963 Differential Revision: D39707115 Pulled By: ltamasi fbshipit-source-id: 59aec8c732482f063d0abaad4d9200ba57ebf437	2 years ago
Yanqin Jin	2b6f3510c2	Update version number and HISTORY in main branch (#10694) ... Summary: This PR bumps up version number from 7.7 to 7.8 in main branch, indicating that next release will be 7.8. We are going to release 7.7 soon. Since 7.7.fb branch has been created, we can land this to main. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10694 Reviewed By: gitbw95 Differential Revision: D39581577 Pulled By: riversand963 fbshipit-source-id: 84f3fecf25fd9ac96e46b4cd6d50ddb6edc89427	2 years ago
gitbw95	2cc5b39560	Add enable_split_merge option for CompressedSecondaryCache (#10690) ... Summary: `enable_custom_split_merge` is added for enabling the custom split and merge feature, which split the compressed value into chunks so that they may better fit jemalloc bins. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10690 Test Plan: Unit Tests Stress Tests Reviewed By: anand1976 Differential Revision: D39567604 Pulled By: gitbw95 fbshipit-source-id: f6d1d46200f365220055f793514601dcb0edc4b7	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	87c8bb4bef	Add comments describing {Put,Get}Entity, update/clarify comment for Get and iterator (#10676) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10676 Reviewed By: riversand963 Differential Revision: D39512081 Pulled By: ltamasi fbshipit-source-id: 55704478ceb8081003eceeb0c5a3875cb806587e	2 years ago
anand76	7b11d48444	Change MultiGet multi-level optimization to default on (#10671) ... Summary: Change the ```ReadOptions.optimize_multiget_for_io``` flag to default on. It doesn't impact regular MultiGet users as its only applicable when ```ReadOptions.async_io``` is also set to true. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10671 Reviewed By: akankshamahajan15 Differential Revision: D39477439 Pulled By: anand1976 fbshipit-source-id: 47abcdbfa69f9bc60422ab68a238b232e085d4ba	2 years ago
Levi Tamasi	06ab0a8b40	Add wide-column support to iterators (#10670) ... Summary: The patch extends the iterator API with a new `columns` method which can be used to retrieve all wide columns for the current key. Similarly to the `Get` and `GetEntity` APIs, the classic `value` API returns the value of the default (anonymous) column for wide-column entities, and `columns` returns an entity with a single default column for plain old key-values. (The goal here is to maintain the invariant that `value()` is the same as the value of the default column in `columns()`.) The patch also involves a smaller refactoring: historically, `value()` was implemented using a bunch of conditions, that is, the `Slice` to be returned was decided based on the direction of the iteration, whether a merge had been done etc. when the method was called; with the patch, the value to be exposed is stored in a member `Slice value_` when the iterator lands on a new key, and `value()` simply returns this `Slice`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10670 Test Plan: Ran `make check` and a simple blackbox crash test. Reviewed By: riversand963 Differential Revision: D39475551 Pulled By: ltamasi fbshipit-source-id: 29e7a6ed9ef340841aab36803b832b7c8f668b0b	2 years ago
Changyu Bi	f291eefb02	Cache fragmented range tombstone list for mutable memtables (#10547) ... Summary: Each read from memtable used to read and fragment all the range tombstones into a `FragmentedRangeTombstoneList`. https://github.com/facebook/rocksdb/issues/10380 improved the inefficient here by caching a `FragmentedRangeTombstoneList` with each immutable memtable. This PR extends the caching to mutable memtables. The fragmented range tombstone can be constructed in either read (This PR) or write path (https://github.com/facebook/rocksdb/issues/10584). With both implementation, each `DeleteRange()` will invalidate the cache, and the difference is where the cache is re-constructed.`CoreLocalArray` is used to store the cache with each memtable so that multi-threaded reads can be efficient. More specifically, each core will have a shared_ptr to a shared_ptr pointing to the current cache. Each read thread will only update the reference count in its core-local shared_ptr, and this is only needed when reading from mutable memtables. The choice between write path and read path is not an easy one: they are both improvement compared to no caching in the current implementation, but they favor different operations and could cause regression in the other operation (read vs write). The write path caching in (https://github.com/facebook/rocksdb/issues/10584) leads to a cleaner implementation, but I chose the read path caching here to avoid significant regression in write performance when there is a considerable amount of range tombstones in a single memtable (the number from the benchmark below suggests >1000 with concurrent writers). Note that even though the fragmented range tombstone list is only constructed in `DeleteRange()` operations, it could block other writes from proceeding, and hence affects overall write performance. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10547 Test Plan: - TestGet() in stress test is updated in https://github.com/facebook/rocksdb/issues/10553 to compare Get() result against expected state: `./db_stress_branch --readpercent=57 --prefixpercent=4 --writepercent=25 -delpercent=5 --iterpercent=5 --delrangepercent=4` - Perf benchmark: tested read and write performance where a memtable has 0, 1, 10, 100 and 1000 range tombstones. ``` ./db_bench --benchmarks=fillrandom,readrandom --writes_per_range_tombstone=200 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=200000 --reads=100000 --disable_auto_compactions --max_num_range_tombstones=1000 ``` Write perf regressed since the cost of constructing fragmented range tombstone list is shifted from every read to a single write. 6cbe5d8e172dc5f1ef65c9d0a6eedbd9987b2c72 is included in the last column as a reference to see performance impact on multi-thread reads if `CoreLocalArray` is not used. micros/op averaged over 5 runs: first 4 columns are for fillrandom, last 4 columns are for readrandom. | |fillrandom main | write path caching | read path caching |memtable V3 (https://github.com/facebook/rocksdb/issues/10308) | readrandom main | write path caching | read path caching |memtable V3 | |--- |--- |--- |--- |--- | --- | --- | --- | --- | | 0 |6.35 |6.15 |5.82 |6.12 |2.24 |2.26 |2.03 |2.07 | | 1 |5.99 |5.88 |5.77 |6.28 |2.65 |2.27 |2.24 |2.5 | | 10 |6.15 |6.02 |5.92 |5.95 |5.15 |2.61 |2.31 |2.53 | | 100 |5.95 |5.78 |5.88 |6.23 |28.31 |2.34 |2.45 |2.94 | | 100 25 threads |52.01 |45.85 |46.18 |47.52 |35.97 |3.34 |3.34 |3.56 | | 1000 |6.0 |7.07 |5.98 |6.08 |333.18 |2.86 |2.7 |3.6 | | 1000 25 threads |52.6 |148.86 |79.06 |45.52 |473.49 |3.66 |3.48 |4.38 | - Benchmark performance of`readwhilewriting` from https://github.com/facebook/rocksdb/issues/10552, 100 range tombstones are written: `./db_bench --benchmarks=readwhilewriting --writes_per_range_tombstone=500 --max_write_buffer_number=100 --min_write_buffer_number_to_merge=100 --writes=100000 --reads=500000 --disable_auto_compactions --max_num_range_tombstones=10000 --finish_after_writes` readrandom micros/op: | |main |write path caching |read path caching |memtable V3 | |---|---|---|---|---| | single thread |48.28 |1.55 |1.52 |1.96 | | 25 threads |64.3 |2.55 |2.67 |2.64 | Reviewed By: ajkr Differential Revision: D38895410 Pulled By: cbi42 fbshipit-source-id: 930bfc309dd1b2f4e8e9042f5126785bba577559	2 years ago
gitbw95	0148c4934d	Add PerfContext counters for CompressedSecondaryCache (#10650) ... Summary: Add PerfContext counters for CompressedSecondaryCache. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10650 Test Plan: Unit Tests. Reviewed By: anand1976 Differential Revision: D39354712 Pulled By: gitbw95 fbshipit-source-id: 1b90d3df99d08ddecd351edfd48d1e3723fdbc15	2 years ago
Peter Dillinger	6de7081cf3	Always verify SST unique IDs on SST file open (#10532) ... Summary: Although we've been tracking SST unique IDs in the DB manifest unconditionally, checking has been opt-in and with an extra pass at DB::Open time. This changes the behavior of `verify_sst_unique_id_in_manifest` to check unique ID against manifest every time an SST file is opened through table cache (normal DB operations), replacing the explicit pass over files at DB::Open time. This change also enables the option by default and removes the "EXPERIMENTAL" designation. One possible criticism is that the option no longer ensures the integrity of a DB at Open time. This is far from an all-or-nothing issue. Verifying the IDs of all SST files hardly ensures all the data in the DB is readable. (VerifyChecksum is supposed to do that.) Also, with max_open_files=-1 (default, extremely common), all SST files are opened at DB::Open time anyway. Implementation details: * `VerifySstUniqueIdInManifest()` functions are the extra/explicit pass that is now removed. * Unit tests that manipulate/corrupt table properties have to opt out of this check, because that corrupts the "actual" unique id. (And even for testing we don't currently have a mechanism to set "no unique id" in the in-memory file metadata for new files.) * A lot of other unit test churn relates to (a) default checking on, and (b) checking on SST open even without DB::Open (e.g. on flush) * Use `FileMetaData` for more `TableCache` operations (in place of `FileDescriptor`) so that we have access to the unique_id whenever we might need to open an SST file. **There is the possibility of performance impact because we can no longer use the more localized `fd` part of an `FdWithKeyRange` but instead follow the `file_metadata` pointer. However, this change (possible regression) is only done for `GetMemoryUsageByTableReaders`.** * Removed a completely unnecessary constructor overload of `TableReaderOptions` Possible follow-up: * Verification only happens when opening through table cache. Are there more places where this should happen? * Improve error message when there is a file size mismatch vs. manifest (FIXME added in the appropriate place). * I'm not sure there's a justification for `FileDescriptor` to be distinct from `FileMetaData`. * I'm skeptical that `FdWithKeyRange` really still makes sense for optimizing some data locality by duplicating some data in memory, but I could be wrong. * An unnecessary overload of NewTableReader was recently added, in the public API nonetheless (though unusable there). It should be cleaned up to put most things under `TableReaderOptions`. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10532 Test Plan: updated unit tests Performance test showing no significant difference (just noise I think): `./db_bench -benchmarks=readwhilewriting[-X10] -num=3000000 -disable_wal=1 -bloom_bits=8 -write_buffer_size=1000000 -target_file_size_base=1000000` Before: readwhilewriting [AVG 10 runs] : 68702 (± 6932) ops/sec After: readwhilewriting [AVG 10 runs] : 68239 (± 7198) ops/sec Reviewed By: jay-zhuang Differential Revision: D38765551 Pulled By: pdillinger fbshipit-source-id: a827a708155f12344ab2a5c16e7701c7636da4c2	2 years ago
Bo Wang	d490bfcdb6	Avoid recompressing cold block in CompressedSecondaryCache (#10527) ... Summary: **Summary:** When a block is firstly `Lookup` from the secondary cache, we just insert a dummy block in the primary cache (charging the actual size of the block) and don’t erase the block from the secondary cache. A standalone handle is returned from `Lookup`. Only if the block is hit again, we erase it from the secondary cache and add it into the primary cache. When a block is firstly evicted from the primary cache to the secondary cache, we just insert a dummy block (size 0) in the secondary cache. When the block is evicted again, it is treated as a hot block and is inserted into the secondary cache. **Implementation Details** Add a new state of LRUHandle: The handle is never inserted into the LRUCache (both hash table and LRU list) and it doesn't experience the above three states. The entry can be freed when refs becomes 0. (refs >= 1 && in_cache == false && IS_STANDALONE == true) The behaviors of `LRUCacheShard::Lookup()` are updated if the secondary_cache is CompressedSecondaryCache: 1. If a handle is found in primary cache: 1.1. If the handle's value is not nullptr, it is returned immediately. 1.2. If the handle's value is nullptr, this means the handle is a dummy one. For a dummy handle, if it was retrieved from secondary cache, it may still exist in secondary cache. - 1.2.1. If no valid handle can be `Lookup` from secondary cache, return nullptr. - 1.2.2. If the handle from secondary cache is valid, erase it from the secondary cache and add it into the primary cache. 2. If a handle is not found in primary cache: 2.1. If no valid handle can be `Lookup` from secondary cache, return nullptr. 2.2. If the handle from secondary cache is valid, insert a dummy block in the primary cache (charging the actual size of the block) and return a standalone handle. The behaviors of `LRUCacheShard::Promote()` are updated as follows: 1. If `e->sec_handle` has value, one of the following steps can happen: 1.1. Insert a dummy handle and return a standalone handle to caller when `secondary_cache_` is `CompressedSecondaryCache` and e is a standalone handle. 1.2. Insert the item into the primary cache and return the handle to caller. 1.3. Exception handling. 3. If `e->sec_handle` has no value, mark the item as not in cache and charge the cache as its only metadata that'll shortly be released. The behavior of `CompressedSecondaryCache::Insert()` is updated: 1. If a block is evicted from the primary cache for the first time, a dummy item is inserted. 4. If a dummy item is found for a block, the block is inserted into the secondary cache. The behavior of `CompressedSecondaryCache:::Lookup()` is updated: 1. If a handle is not found or it is a dummy item, a nullptr is returned. 2. If `erase_handle` is true, the handle is erased. The behaviors of `LRUCacheShard::Release()` are adjusted for the standalone handles. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10527 Test Plan: 1. stress tests. 5. unit tests. 6. CPU profiling for db_bench. Reviewed By: siying Differential Revision: D38747613 Pulled By: gitbw95 fbshipit-source-id: 74a1eba7e1957c9affb2bd2ae3e0194584fa6eca	2 years ago
Changyu Bi	30bc495c03	Skip swaths of range tombstone covered keys in merging iterator (2022 edition) (#10449) ... Summary: Delete range logic is moved from `DBIter` to `MergingIterator`, and `MergingIterator` will seek to the end of a range deletion if possible instead of scanning through each key and check with `RangeDelAggregator`. With the invariant that a key in level L (consider memtable as the first level, each immutable and L0 as a separate level) has a larger sequence number than all keys in any level >L, a range tombstone `[start, end)` from level L covers all keys in its range in any level >L. This property motivates optimizations in iterator: - in `Seek(target)`, if level L has a range tombstone `[start, end)` that covers `target.UserKey`, then for all levels > L, we can do Seek() on `end` instead of `target` to skip some range tombstone covered keys. - in `Next()/Prev()`, if the current key is covered by a range tombstone `[start, end)` from level L, we can do `Seek` to `end` for all levels > L. This PR implements the above optimizations in `MergingIterator`. As all range tombstone covered keys are now skipped in `MergingIterator`, the range tombstone logic is removed from `DBIter`. The idea in this PR is similar to https://github.com/facebook/rocksdb/issues/7317, but this PR leaves `InternalIterator` interface mostly unchanged. **Credit**: the cascading seek optimization and the sentinel key (discussed below) are inspired by [Pebble](https://github.com/cockroachdb/pebble/blob/master/merging_iter.go) and suggested by ajkr in https://github.com/facebook/rocksdb/issues/7317. The two optimizations are mostly implemented in `SeekImpl()/SeekForPrevImpl()` and `IsNextDeleted()/IsPrevDeleted()` in `merging_iterator.cc`. See comments for each method for more detail. One notable change is that the minHeap/maxHeap used by `MergingIterator` now contains range tombstone end keys besides point key iterators. This helps to reduce the number of key comparisons. For example, for a range tombstone `[start, end)`, a `start` and an `end` `HeapItem` are inserted into the heap. When a `HeapItem` for range tombstone start key is popped from the minHeap, we know this range tombstone becomes "active" in the sense that, before the range tombstone's end key is popped from the minHeap, all the keys popped from this heap is covered by the range tombstone's internal key range `[start, end)`. Another major change, *delete range sentinel key*, is made to `LevelIterator`. Before this PR, when all point keys in an SST file are iterated through in `MergingIterator`, a level iterator would advance to the next SST file in its level. In the case when an SST file has a range tombstone that covers keys beyond the SST file's last point key, advancing to the next SST file would lose this range tombstone. Consequently, `MergingIterator` could return keys that should have been deleted by some range tombstone. We prevent this by pretending that file boundaries in each SST file are sentinel keys. A `LevelIterator` now only advance the file iterator once the sentinel key is processed. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10449 Test Plan: - Added many unit tests in db_range_del_test - Stress test: `./db_stress --readpercent=5 --prefixpercent=19 --writepercent=20 -delpercent=10 --iterpercent=44 --delrangepercent=2` - Additional iterator stress test is added to verify against iterators against expected state: https://github.com/facebook/rocksdb/issues/10538. This is based on ajkr's previous attempt https://github.com/facebook/rocksdb/pull/5506#issuecomment-506021913. ``` python3 ./tools/db_crashtest.py blackbox --simple --write_buffer_size=524288 --target_file_size_base=524288 --max_bytes_for_level_base=2097152 --compression_type=none --max_background_compactions=8 --value_size_mult=33 --max_key=5000000 --interval=10 --duration=7200 --delrangepercent=3 --delpercent=9 --iterpercent=25 --writepercent=60 --readpercent=3 --prefixpercent=0 --num_iterations=1000 --range_deletion_width=100 --verify_iterator_with_expected_state_one_in=1 ``` - Performance benchmark: I used a similar setup as in the blog [post](http://rocksdb.org/blog/2018/11/21/delete-range.html) that introduced DeleteRange, "a database with 5 million data keys, and 10000 range tombstones (ignoring those dropped during compaction) that were written in regular intervals after 4.5 million data keys were written". As expected, the performance with this PR depends on the range tombstone width. ``` # Setup: TEST_TMPDIR=/dev/shm ./db_bench_main --benchmarks=fillrandom --writes=4500000 --num=5000000 TEST_TMPDIR=/dev/shm ./db_bench_main --benchmarks=overwrite --writes=500000 --num=5000000 --use_existing_db=true --writes_per_range_tombstone=50 # Scan entire DB TEST_TMPDIR=/dev/shm ./db_bench_main --benchmarks=readseq[-X5] --use_existing_db=true --num=5000000 --disable_auto_compactions=true # Short range scan (10 Next()) TEST_TMPDIR=/dev/shm/width-100/ ./db_bench_main --benchmarks=seekrandom[-X5] --use_existing_db=true --num=500000 --reads=100000 --seek_nexts=10 --disable_auto_compactions=true # Long range scan(1000 Next()) TEST_TMPDIR=/dev/shm/width-100/ ./db_bench_main --benchmarks=seekrandom[-X5] --use_existing_db=true --num=500000 --reads=2500 --seek_nexts=1000 --disable_auto_compactions=true ``` Avg over of 10 runs (some slower tests had fews runs): For the first column (tombstone), 0 means no range tombstone, 100-10000 means width of the 10k range tombstones, and 1 means there is a single range tombstone in the entire DB (width is 1000). The 1 tombstone case is to test regression when there's very few range tombstones in the DB, as no range tombstone is likely to take a different code path than with range tombstones. - Scan entire DB | tombstone width | Pre-PR ops/sec | Post-PR ops/sec | ±% | | ------------- | ------------- | ------------- | ------------- | | 0 range tombstone |2525600 (± 43564) |2486917 (± 33698) |-1.53% | | 100 |1853835 (± 24736) |2073884 (± 32176) |+11.87% | | 1000 |422415 (± 7466) |1115801 (± 22781) |+164.15% | | 10000 |22384 (± 227) |227919 (± 6647) |+918.22% | | 1 range tombstone |2176540 (± 39050) |2434954 (± 24563) |+11.87% | - Short range scan | tombstone width | Pre-PR ops/sec | Post-PR ops/sec | ±% | | ------------- | ------------- | ------------- | ------------- | | 0 range tombstone |35398 (± 533) |35338 (± 569) |-0.17% | | 100 |28276 (± 664) |31684 (± 331) |+12.05% | | 1000 |7637 (± 77) |25422 (± 277) |+232.88% | | 10000 |1367 |28667 |+1997.07% | | 1 range tombstone |32618 (± 581) |32748 (± 506) |+0.4% | - Long range scan | tombstone width | Pre-PR ops/sec | Post-PR ops/sec | ±% | | ------------- | ------------- | ------------- | ------------- | | 0 range tombstone |2262 (± 33) |2353 (± 20) |+4.02% | | 100 |1696 (± 26) |1926 (± 18) |+13.56% | | 1000 |410 (± 6) |1255 (± 29) |+206.1% | | 10000 |25 |414 |+1556.0% | | 1 range tombstone |1957 (± 30) |2185 (± 44) |+11.65% | - Microbench does not show significant regression: https://gist.github.com/cbi42/59f280f85a59b678e7e5d8561e693b61 Reviewed By: ajkr Differential Revision: D38450331 Pulled By: cbi42 fbshipit-source-id: b5ef12e8d8c289ed2e163ccdf277f5039b511fca	2 years ago
Akanksha Mahajan	4cd16d65ae	Add new option num_file_reads_for_auto_readahead in BlockBasedTableOptions (#10556) ... Summary: RocksDB does auto-readahead for iterators on noticing more than two reads for a table file if user doesn't provide readahead_size and reads are sequential. A new option num_file_reads_for_auto_readahead is added which can be configured and indicates after how many sequential reads prefetching should be start. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10556 Test Plan: Existing and new unit test Reviewed By: anand1976 Differential Revision: D38947147 Pulled By: akankshamahajan15 fbshipit-source-id: c9eeab495f84a8df7f701c42f04894e46440ad97	2 years ago
sdong	9509003503	Option migration tool to break down files for FIFO compaction (#10600) ... Summary: Right now, when the option migration tool migrates to FIFO compaction, it compacts all the data into one single SST file and move to L0. Although it creates a valid LSM-tree for FIFO, for any data to be deleted for FIFO, the giant file will be deleted, which might make the DB almost empty. There is not good solution for it, because usually we don't have enough information to reconstruct the FIFO LSM-tree. This change changes to a solution that compromises the FIFO condition. We hope the solution is more useable. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10600 Test Plan: Add unit tests for that. Reviewed By: jay-zhuang Differential Revision: D39106424 fbshipit-source-id: bdfd852c3b343373765b8d9716fefc08fd27145c	2 years ago
Levi Tamasi	7818560194	Add a dedicated cache entry role for blobs (#10601) ... Summary: The patch adds a dedicated cache entry role for blob values and switches to a registered deleter so that blobs show up as a separate bucket (as opposed to "Misc") in the cache occupancy statistics, e.g. ``` Block cache entry stats(count,size,portion): DataBlock(133515,531.73 MB,13.6866%) BlobValue(1824855,3.10 GB,81.7071%) Misc(1,0.00 KB,0%) ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/10601 Test Plan: Ran `make check` and tested the cache occupancy statistics using `db_bench`. Reviewed By: riversand963 Differential Revision: D39107915 Pulled By: ltamasi fbshipit-source-id: 8446c3b190a41a144030df73f318eeda4398c125	2 years ago
anand76	72a3fb3424	Update statistics for async scan readaheads (#10585) ... Summary: Imported a fix to "rocksdb.prefetched.bytes.discarded" stat from https://github.com/facebook/rocksdb/issues/10561, and added a new stat "rocksdb.async.prefetch.abort.micros" to measure time spent waiting for async reads to abort. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10585 Reviewed By: akankshamahajan15 Differential Revision: D39067000 Pulled By: anand1976 fbshipit-source-id: d7cda71abb48017239bd5fd832345a16c7024faf	2 years ago
Peter Dillinger	c5afbbfe4b	Don't wait for indirect flush in read-only DB (#10569) ... Summary: Some APIs for getting live files, which are used by Checkpoint and BackupEngine, can optionally trigger and wait for a flush. These would deadlock when used on a read-only DB. Here we fix that by assuming the user wants the overall operation to succeed and is OK without flushing (because the DB is read-only). Follow-up work: the same or other issues can be hit by directly invoking some DB functions that are clearly not appropriate for read-only instance, but are not covered by overrides in DBImplReadOnly and CompactedDBImpl. These should be fixed to avoid similar problems on accidental misuse. (Long term, it would be nice to have a DBReadOnly class without those members, like BackupEngineReadOnly.) Pull Request resolved: https://github.com/facebook/rocksdb/pull/10569 Test Plan: tests updated to catch regression (hang before the fix) Reviewed By: riversand963 Differential Revision: D38995759 Pulled By: pdillinger fbshipit-source-id: f5f8bc7123e13cb45bd393dd974d7d6eda20bc68	2 years ago
muthukrishnan.s	79ed4be80f	Add get_name, get_id for column family handle in C API (#10499) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10499 Reviewed By: hx235 Differential Revision: D38523859 Pulled By: ajkr fbshipit-source-id: 268bba1fcce4a3e20c51e498a79d7b476f663aea	2 years ago
EdvardD	6e93d24935	Expose set_checksum function to C api (#10537) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10537 Reviewed By: hx235 Differential Revision: D38797662 Pulled By: ajkr fbshipit-source-id: a8db723c3eb9d5592cd78f8be7e442e4826686ad	2 years ago
Bo Wang	b0048b673c	Post 7.6 branch cut changes (#10546) ... Summary: After branch 7.6.fb branch is cut, following release process, upgrade version number to 7.7 and add 7.6.fb to format compatibility check. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10546 Test Plan: Watch CI Reviewed By: ajkr Differential Revision: D38892023 Pulled By: gitbw95 fbshipit-source-id: 94e96dedbd973f5f9713e73d3bed336e4678565b	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
Levi Tamasi	81388b36e0	Add support for wide-column point lookups (#10540) ... Summary: The patch adds a new API `GetEntity` that can be used to perform wide-column point lookups. It also extends the `Get` code path and the `MemTable` / `MemTableList` and `Version` / `GetContext` logic accordingly so that wide-column entities can be served from both memtables and SSTs. If the result of a lookup is a wide-column entity (`kTypeWideColumnEntity`), it is passed to the application in deserialized form; if it is a plain old key-value (`kTypeValue`), it is presented as a wide-column entity with a single default (anonymous) column. (In contrast, regular `Get` returns plain old key-values as-is, and returns the value of the default column for wide-column entities, see https://github.com/facebook/rocksdb/issues/10483 .) The result of `GetEntity` is a self-contained `PinnableWideColumns` object. `PinnableWideColumns` contains a `PinnableSlice`, which either stores the underlying data in its own buffer or holds on to a cache handle. It also contains a `WideColumns` instance, which indexes the contents of the `PinnableSlice`, so applications can access the values of columns efficiently. There are several pieces of functionality which are currently not supported for wide-column entities: there is currently no `MultiGetEntity` or wide-column iterator; also, `Merge` and `GetMergeOperands` are not supported, and there is no `GetEntity` implementation for read-only and secondary instances. We plan to implement these in future PRs. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10540 Test Plan: `make check` Reviewed By: akankshamahajan15 Differential Revision: D38847474 Pulled By: ltamasi fbshipit-source-id: 42311a34ccdfe88b3775e847a5e2a5296e002b5b	2 years ago
Andrew Kryczka	91166012c8	Prevent a case of WriteBufferManager flush thrashing (#6364) ... Summary: Previously, the flushes triggered by `WriteBufferManager` could affect the same CF repeatedly if it happens to get consecutive writes. Such flushes are not particularly useful for reducing memory usage since they switch nearly-empty memtables to immutable while they've just begun filling their first arena block. In fact they may not even reduce the mutable memory count if they involve replacing one mutable memtable containing one arena block with a new mutable memtable containing one arena block. Further, if such switches happen even a few times before a flush finishes, the immutable memtable limit will be reached and writes will stall. This PR adds a heuristic to not switch memtables to immutable for CFs that already have one or more immutable memtables awaiting flush. There is a memory usage regression if the user continues writing to the same CF, that DB does not have any CFs eligible for switching, flushes are not finishing, and the `WriteBufferManager` was constructed with `allow_stall=false`. Before, it would grow by switching nearly empty memtables until writes stall. Now, it would grow by filling memtables until writes stall. This feels like an acceptable behavior change because users who prefer to stall over violate the memory limit should be using `allow_stall=true`, which is unaffected by this PR. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6364 Test Plan: - Command: `rm -rf /dev/shm/dbbench/ && TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num_multi_db=8 -num_column_families=2 -write_buffer_size=4194304 -db_write_buffer_size=16777216 -compression_type=none -statistics=true -target_file_size_base=4194304 -max_bytes_for_level_base=16777216` - `rocksdb.db.write.stall` count before this PR: 175 - `rocksdb.db.write.stall` count after this PR: 0 Reviewed By: jay-zhuang Differential Revision: D20167197 Pulled By: ajkr fbshipit-source-id: 4a64064e9bc33d57c0a35f15547542d0191d0cb7	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	5d3aefb682	Migrate to docker for CI run (#10496) ... Summary: Moved linux builds to using docker to avoid CI instability caused by dependency installation site down. Added the `Dockerfile` which is used to build the image. The build time is also significantly reduced, because no dependencies installation and with using 2xlarge+ instance for slow build (like tsan test). Also fixed a few issues detected while building this: * `DestoryDB()` Status not checked for a few tests * nullptr might be used in `inlineskiplist.cc` Pull Request resolved: https://github.com/facebook/rocksdb/pull/10496 Test Plan: CI Reviewed By: ajkr Differential Revision: D38554200 Pulled By: jay-zhuang fbshipit-source-id: 16e8fb2bf07b9c84bb27fb18421c4d54f2f248fd	2 years ago
Levi Tamasi	24bcab7d5d	Make queries return the value of the default column for wide-column entities (#10483) ... Summary: The patch adds support for wide-column entities to the existing query APIs (`Get`, `MultiGet`, and iterator). Namely, when during a query a wide-column entity is encountered, we will return the value of the default (anonymous) column as the result. Later, we plan to add wide-column specific query APIs which will enable retrieving entire wide-column entities or a subset of their columns. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10483 Test Plan: `make check` Reviewed By: riversand963 Differential Revision: D38441881 Pulled By: ltamasi fbshipit-source-id: 6444e79a31aff2470e866698e3a97985bc2b3543	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	375534752a	Improve universal compaction picker for tiered compaction (#10467) ... Summary: Current universal compaction picker may cause extra size amplification compaction if there're more hot data on penultimate level. Improve the picker to skip the last level for size amp calculation if tiered compaction is enabled, which can 1. avoid extra unnecessary size amp compaction; 2. typically cold tier (the last level) is not size constrained, so skip size amp for cold tier is intended; Pull Request resolved: https://github.com/facebook/rocksdb/pull/10467 Test Plan: CI and added unittest Reviewed By: siying Differential Revision: D38391350 Pulled By: jay-zhuang fbshipit-source-id: 103c0731c05e0a7e8f267e9e829d022328be25d2	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
sdong	cc2099803a	Use EnvLogger instead of PosixLogger (#10436) ... Summary: EnvLogger was built to replace PosixLogger that supports multiple Envs. Make FileSystem use EnvLogger by default, remove Posix FS specific implementation and remove PosixLogger code, Some hacky changes are made to make sure iostats are not polluted by logging, in order to pass existing unit tests. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10436 Test Plan: Run db_bench and watch info log files. Reviewed By: anand1976 Differential Revision: D38259855 fbshipit-source-id: 67d65874bfba7a33535b6d0dd0ed92cbbc9888b8	2 years ago
Akanksha Mahajan	56463d443d	Provide support for subcompactions with user-defined timestamps (#10344) ... Summary: The subcompaction logic currently picks file boundaries as subcompaction boundaries. This is not compatible with user-defined timestamps because of two issues. Issue1: ReadOptions.iterate_lower_bound and ReadOptions.iterate_upper_bound contains timestamps which results in assertion failure as BlockBasedTableIterator expects bounds to be without timestamps. As result, because of wrong comparison end key is returned as user_key resulting in assertion failure. Issue2: Since it might result in two keys that only differ by user timestamp getting processed by two different subcompactions (and thus two different CompactionIterator state machines), which in turn can cause data correction issues. This PR provide support to reenable subcompactions with user-defined timestamps. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10344 Test Plan: Added new unit test - Without fix for Issue1 unit test MultipleSubCompactions fails with error: ``` db_with_timestamp_compaction_test: ./db/compaction/clipping_iterator.h:247: void rocksdb::ClippingIterat│ or::AssertBounds(): Assertion `!valid_ || !end_ || cmp_->Compare(key(), *end_) < 0' failed. Received signal 6 (Aborted) │ #0 /usr/local/fbcode/platform009/lib/libc.so.6(gsignal+0x100) [0x7f8fbbbfe530] db_with_timestamp_compaction_test: ./db/compaction/clipping_iterator.h:247: void rocksdb::ClippingIterator::AssertBounds(): Assertion `!valid_ || !end_ || cmp_->Compare(key(), *end_) < 0' failed. Aborted (core dumped) ``` Ran stress test `make crash_test_with_ts -j32` Reviewed By: riversand963 Differential Revision: D38220841 Pulled By: akankshamahajan15 fbshipit-source-id: 5d5cae2bd37fcaeba1e77fce0a69070ad4158ccb	2 years ago
Peter Dillinger	65036e4217	Revert "Add a blob-specific cache priority (#10309)" (#10434) ... Summary: This reverts commit 8d178090be because of a clear performance regression seen in internal dashboard https://fburl.com/unidash/tpz75iee Pull Request resolved: https://github.com/facebook/rocksdb/pull/10434 Reviewed By: ltamasi Differential Revision: D38256373 Pulled By: pdillinger fbshipit-source-id: 134aa00f50dd7b1bbe037c227884a351342ec44b	2 years ago
Andrew Kryczka	c7ccbb33a6	Allow manual compactions to run in parallel by default (#10317) ... Summary: This PR changes the default value of `CompactRangeOptions::exclusive_manual_compaction` from true to false so manual `CompactRange()`s can run in parallel with other compactions. I believe no artificial parallelism restriction is the intuitive behavior so feel the old default value is a trap, which I have fallen into several times, including yesterday. `CompactRangeOptions::exclusive_manual_compaction == false` has been used in both our correctness test and in production for years so should be reasonably safe. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10317 Reviewed By: jay-zhuang Differential Revision: D37659392 Pulled By: ajkr fbshipit-source-id: 504915e978bbe300b79483d064070c75e93d91e5	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
Jay Lee	84e9b6ee2d	full_history_ts_low should be const (#10411) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10411 Reviewed By: jay-zhuang Differential Revision: D38131644 Pulled By: riversand963 fbshipit-source-id: d241521dccff1ab8882ae0726ec368f84b7e8311	2 years ago
Gang Liao	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
Andrew Kryczka	25cc564ff7	Make RateLimiter not Customizable (#10378) ... Summary: (PR created for informational/testing purposes only.) - Fixes lost dynamic updates to GenericRateLimiter bandwidth using `SetBytesPerSecond()` - Benefit over #10374 is eliminating race conditions with Configurable framework. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10378 Reviewed By: pdillinger Differential Revision: D37914865 fbshipit-source-id: d4f566d60ec9726d26932388c61671adf0ee0f30	2 years ago
sdong	d9deffba57	Post 7.5 branch cut changes (#10376) ... Summary: After branch 7.5.fb branch is cut, following release process, upgrade version number to 7.6 and add 7.5.fb to format compatibility check. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10376 Test Plan: Watch CI Reviewed By: ajkr Differential Revision: D37927694 fbshipit-source-id: 71b37ae55ebb7c95a1bcc0d7eee643d6ba5f8461	2 years ago
Gang Liao	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
sg20180546	f5ef36a29a	add sstfilewriter_delete_range (#10314) ... Summary: I add C API db/c.cc rocksdb_sstfilewriter_delete_range and test it , PASS. can you review it ? ajkr Pull Request resolved: https://github.com/facebook/rocksdb/pull/10314 Reviewed By: riversand963 Differential Revision: D37657236 Pulled By: ajkr fbshipit-source-id: c3b758daa36fbd9133210b011716914dff311278	2 years ago
Jay Zhuang	dcb6a3be4e	Add helper function to get debug type name (#10243) ... Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/10243 Reviewed By: riversand963 Differential Revision: D37370236 Pulled By: jay-zhuang fbshipit-source-id: 6e7a6fadf45fdfb5afe97b3f6fe4acf1260d4a86	2 years ago
sdong	00e68e7a30	DB::PutEntity() shouldn't be defined as =0 (#10364) ... Summary: DB::PutEntity() is defined as 0, but it is actually implemented in db/db_impl/db_impl_write.cc. It is incorrect, and might cause problems when users implement class DB themselves. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10364 Test Plan: See existing tests pass Reviewed By: riversand963 Differential Revision: D37874886 fbshipit-source-id: b81713ddb707720b52d57a15de56a59414c24f66	2 years ago
Jay Zhuang	a3acf2ef87	Add seqno to time mapping (#10338) ... Summary: Which will be used for tiered storage to preclude hot data from compacting to the cold tier (the last level). Internally, adding seqno to time mapping. A periodic_task is scheduled to record the current_seqno -> current_time in certain cadence. When memtable flush, the mapping informaiton is stored in sstable property. During compaction, the mapping information are merged and get the approximate time of sequence number, which is used to determine if a key is recently inserted or not and preclude it from the last level if it's recently inserted (within the `preclude_last_level_data_seconds`). Pull Request resolved: https://github.com/facebook/rocksdb/pull/10338 Test Plan: CI Reviewed By: siying Differential Revision: D37810187 Pulled By: jay-zhuang fbshipit-source-id: 6953be7a18a99de8b1cb3b162d712f79c2b4899f	2 years ago
sdong	c8b20d469d	Make InternalKeyComparator not configurable (#10342) ... Summary: InternalKeyComparator is an internal class which is a simple wrapper of Comparator. https://github.com/facebook/rocksdb/pull/8336 made Comparator customizeable. As a side effect, internal key comparator was made configurable too. This introduces overhead to this simple wrapper. For example, every InternalKeyComparator will have an std::vector attached to it, which consumes memory and possible allocation overhead too. We remove InternalKeyComparator from being customizable by making InternalKeyComparator not a subclass of Comparator. Pull Request resolved: https://github.com/facebook/rocksdb/pull/10342 Test Plan: Run existing CI tests and make sure it doesn't fail Reviewed By: riversand963 Differential Revision: D37771351 fbshipit-source-id: 917256ee04b2796ed82974549c734fb6c4d8ccee	2 years ago
Jay Zhuang	6ce0b2ca34	Tiered Compaction: per key placement support (#9964) ... Summary: Support per_key_placement for last level compaction, which will be used for tiered compaction. * compaction iterator reports which level a key should output to; * compaction get the output level information and check if it's safe to output the data to penultimate level; * all compaction output files will be installed. * extra internal compaction stats added for penultimate level. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9964 Test Plan: * Unittest * db_bench, no significate difference: https://gist.github.com/jay-zhuang/3645f8fb97ec0ab47c10704bb39fd6e4 * microbench manual compaction no significate difference: https://gist.github.com/jay-zhuang/ba679b3e89e24992615ee9eef310e6dd * run the db_stress multiple times (not covering the new feature) looks good (internal: https://fburl.com/sandcastle/9w84pp2m) Reviewed By: ajkr Differential Revision: D36249494 Pulled By: jay-zhuang fbshipit-source-id: a96da57c8031c1df83e4a7a8567b657a112b80a3	2 years ago