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
Summary:
**NOTE**: this also needs to be back-ported to 6.4.6 and possibly older branches if further releases from them is envisaged.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6081
Differential Revision: D18710107
Pulled By: zhichao-cao
fbshipit-source-id: 03260f9316566e2bfc12c7d702d6338bb7941e01
Summary:
This PR adds support in block cache trace analyzer to read from human readable trace file. This is needed when a user does not have access to the binary trace file.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5679
Test Plan: USE_CLANG=1 make check -j32
Differential Revision: D16697239
Pulled By: HaoyuHuang
fbshipit-source-id: f2e29d7995816c389b41458f234ec8e184a924db
Summary:
This PR adds four more eviction policies.
- OPT [1]
- Hyperbolic caching [2]
- ARC [3]
- GreedyDualSize [4]
[1] L. A. Belady. 1966. A Study of Replacement Algorithms for a Virtual-storage Computer. IBM Syst. J. 5, 2 (June 1966), 78-101. DOI=http://dx.doi.org/10.1147/sj.52.0078
[2] Aaron Blankstein, Siddhartha Sen, and Michael J. Freedman. 2017. Hyperbolic caching: flexible caching for web applications. In Proceedings of the 2017 USENIX Conference on Usenix Annual Technical Conference (USENIX ATC '17). USENIX Association, Berkeley, CA, USA, 499-511.
[3] Nimrod Megiddo and Dharmendra S. Modha. 2003. ARC: A Self-Tuning, Low Overhead Replacement Cache. In Proceedings of the 2nd USENIX Conference on File and Storage Technologies (FAST '03). USENIX Association, Berkeley, CA, USA, 115-130.
[4] N. Young. The k-server dual and loose competitiveness for paging. Algorithmica, June 1994, vol. 11,(no.6):525-41. Rewritten version of ''On-line caching as cache size varies'', in The 2nd Annual ACM-SIAM Symposium on Discrete Algorithms, 241-250, 1991.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5644
Differential Revision: D16548817
Pulled By: HaoyuHuang
fbshipit-source-id: 838f76db9179f07911abaab46c97e1c929cfcd63
Summary:
This PR implements cache eviction using reinforcement learning. It includes two implementations:
1. An implementation of Thompson Sampling for the Bernoulli Bandit [1].
2. An implementation of LinUCB with disjoint linear models [2].
The idea is that a cache uses multiple eviction policies, e.g., MRU, LRU, and LFU. The cache learns which eviction policy is the best and uses it upon a cache miss.
Thompson Sampling is contextless and does not include any features.
LinUCB includes features such as level, block type, caller, column family id to decide which eviction policy to use.
[1] Daniel J. Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, and Zheng Wen. 2018. A Tutorial on Thompson Sampling. Found. Trends Mach. Learn. 11, 1 (July 2018), 1-96. DOI: https://doi.org/10.1561/2200000070
[2] Lihong Li, Wei Chu, John Langford, and Robert E. Schapire. 2010. A contextual-bandit approach to personalized news article recommendation. In Proceedings of the 19th international conference on World wide web (WWW '10). ACM, New York, NY, USA, 661-670. DOI=http://dx.doi.org/10.1145/1772690.1772758
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5610
Differential Revision: D16435067
Pulled By: HaoyuHuang
fbshipit-source-id: 6549239ae14115c01cb1e70548af9e46d8dc21bb
Summary:
- Compute correlation between a few features and predictions, e.g., number of accesses since the last access vs number of accesses till the next access on a block.
- Output human readable trace file so python can consume it.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5596
Test Plan: make clean && USE_CLANG=1 make check -j32
Differential Revision: D16373200
Pulled By: HaoyuHuang
fbshipit-source-id: c848d26bc2e9210461f317d7dbee42d55be5a0cc
Summary:
This PR traces the referenced key for Get for all types of blocks. This is useful when evaluating hybrid row-block caches.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5548
Test Plan: make clean && USE_CLANG=1 make check -j32
Differential Revision: D16157979
Pulled By: HaoyuHuang
fbshipit-source-id: f6327411c9deb74e35e22a35f66cdbae09ab9d87
Summary:
This PR creates cache_simulator.h file. It contains a CacheSimulator that runs against a block cache trace record. We can add alternative cache simulators derived from CacheSimulator later. For example, this PR adds a PrioritizedCacheSimulator that inserts filter/index/uncompressed dictionary blocks with high priority.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5517
Test Plan: make clean && COMPILE_WITH_ASAN=1 make check -j32
Differential Revision: D16043689
Pulled By: HaoyuHuang
fbshipit-source-id: 65f28ed52b866ffb0e6eceffd7f9ca7c45bb680d
Summary:
This PR adds a feature in block cache trace analysis tool to write statistics into csv files.
1. The analysis tool supports grouping the number of accesses per second by various labels, e.g., block, column family, block type, or a combination of them.
2. It also computes reuse distance and reuse interval.
Reuse distance: The cumulated size of unique blocks read between two consecutive accesses on the same block.
Reuse interval: The time between two consecutive accesses on the same block.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5490
Differential Revision: D15901322
Pulled By: HaoyuHuang
fbshipit-source-id: b5454fea408a32757a80be63de6fe1c8149ca70e
Summary:
This PR adds more callers for table readers. These information are only used for block cache analysis so that we can know which caller accesses a block.
1. It renames the BlockCacheLookupCaller to TableReaderCaller as passing the caller from upstream requires changes to table_reader.h and TableReaderCaller is a more appropriate name.
2. It adds more table reader callers in table/table_reader_caller.h, e.g., kCompactionRefill, kExternalSSTIngestion, and kBuildTable.
This PR is long as it requires modification of interfaces in table_reader.h, e.g., NewIterator.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5454
Test Plan: make clean && COMPILE_WITH_ASAN=1 make check -j32.
Differential Revision: D15819451
Pulled By: HaoyuHuang
fbshipit-source-id: b6caa704c8fb96ddd15b9a934b7e7ea87f88092d
Summary:
This PR adds a BlockCacheTraceSimulator that reports the miss ratios given different cache configurations. A cache configuration contains "cache_name,num_shard_bits,cache_capacities". For example, "lru, 1, 1K, 2K, 4M, 4G".
When we replay the trace, we also perform lookups and inserts on the simulated caches.
In the end, it reports the miss ratio for each tuple <cache_name, num_shard_bits, cache_capacity> in a output file.
This PR also adds a main source block_cache_trace_analyzer so that we can run the analyzer in command line.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5449
Test Plan:
Added tests for block_cache_trace_analyzer.
COMPILE_WITH_ASAN=1 make check -j32.
Differential Revision: D15797073
Pulled By: HaoyuHuang
fbshipit-source-id: aef0c5c2e7938f3e8b6a10d4a6a50e6928ecf408
Summary:
This PR integrates the block cache tracer into block based table reader. The tracer will write the block cache accesses using the trace_writer. The tracer is null in this PR so that nothing will be logged.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5441
Differential Revision: D15772029
Pulled By: HaoyuHuang
fbshipit-source-id: a64adb92642cd23222e0ba8b10d86bf522b42f9b
Summary:
This PR contains the first commit for block cache trace analyzer. It reads a block cache trace file and prints statistics of the traces.
We will extend this class to provide more functionalities.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5425
Differential Revision: D15709580
Pulled By: HaoyuHuang
fbshipit-source-id: 2f43bd2311f460ab569880819d95eeae217c20bb
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