e532877940
Summary: With `table_options.cache_index_and_filter_blocks = true`, index and filter blocks are stored in block cache. Then people are curious how much of the block cache total size is used by indexes and bloom filters. It will be nice we have a way to report that. It can help people tune performance and plan for optimized hardware setting. We add several enum values for db Statistics. BLOCK_CACHE_INDEX/FILTER_BYTES_INSERT - BLOCK_CACHE_INDEX/FILTER_BYTES_ERASE = current INDEX/FILTER total block size in bytes. Test Plan: write a test case called `DBBlockCacheTest.IndexAndFilterBlocksStats`. The result is: ``` [gzh@dev9927.prn1 ~/local/rocksdb] make db_block_cache_test -j64 && ./db_block_cache_test --gtest_filter=DBBlockCacheTest.IndexAndFilterBlocksStats Makefile:101: Warning: Compiling in debug mode. Don't use the resulting binary in production GEN util/build_version.cc make: `db_block_cache_test' is up to date. Note: Google Test filter = DBBlockCacheTest.IndexAndFilterBlocksStats [==========] Running 1 test from 1 test case. [----------] Global test environment set-up. [----------] 1 test from DBBlockCacheTest [ RUN ] DBBlockCacheTest.IndexAndFilterBlocksStats [ OK ] DBBlockCacheTest.IndexAndFilterBlocksStats (689 ms) [----------] 1 test from DBBlockCacheTest (689 ms total) [----------] Global test environment tear-down [==========] 1 test from 1 test case ran. (689 ms total) [ PASSED ] 1 test. ``` Reviewers: IslamAbdelRahman, andrewkr, sdong Reviewed By: sdong Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D58677
RocksDB: A Persistent Key-Value Store for Flash and RAM Storage
RocksDB is developed and maintained by Facebook Database Engineering Team. It is built on earlier work on LevelDB by Sanjay Ghemawat (sanjay@google.com) and Jeff Dean (jeff@google.com)
This code is a library that forms the core building block for a fast key value server, especially suited for storing data on flash drives. It has a Log-Structured-Merge-Database (LSM) design with flexible tradeoffs between Write-Amplification-Factor (WAF), Read-Amplification-Factor (RAF) and Space-Amplification-Factor (SAF). It has multi-threaded compactions, making it specially suitable for storing multiple terabytes of data in a single database.
Start with example usage here: https://github.com/facebook/rocksdb/tree/master/examples
See the github wiki for more explanation.
The public interface is in include/. Callers should not include or
rely on the details of any other header files in this package. Those
internal APIs may be changed without warning.
Design discussions are conducted in https://www.facebook.com/groups/rocksdb.dev/