1f0142ce19
Summary:
We expect the persistent read cache to perform at speeds upto 8 GB/s. In order
to accomplish that, we need build a index mechanism which operate in the order
of multiple millions per sec rate.
This patch provide the basic data structure to accomplish that:
(1) Hash table implementation with lock contention spread
It is based on the StripedHashSet<T> implementation in
The Art of multiprocessor programming by Maurice Henry & Nir Shavit
(2) LRU implementation
Place holder algorithm for further optimizing
(3) Evictable Hash Table implementation
Building block for building index data structure that evicts data like files
etc
TODO:
(1) Figure if the sharded hash table and LRU can be used instead
(2) Figure if we need to support configurable eviction algorithm for
EvictableHashTable
Test Plan: Run unit tests
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D55785
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/