Summary:
The tsan error was because the random implementation we have is not
thread safe, using Random::GetTLSInstance
Test Plan: Run tests in Linux
Reviewers: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D59559
Summary:
This provides provides an implementation of PersistentCacheTier that is
specialized for RAM. This tier does not persist data though.
Why do we need this tier ?
This is ideal as tier 0. This tier can host data that is too hot.
Why can't we use Cache variants ?
Yes you can use them instead. This tier can potentially outperform BlockCache
in RAW mode by virtue of compression and compressed cache in block cache doesn't
seem very popular. Potentially this tier can be modified to under stand the
disadvantage of the tier below and retain data that the tier below is bad at
handling (for example index and bloom data that is huge in size)
Test Plan: Run unit tests added
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D57069
Summary: Add hash table (under persistent cache) to CMake list
Test Plan: Run hash_test in windows and make check in Linux
Reviewers: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D59151
Summary:
Persistent read cache isn't very applicable for lite builds. Wrapping
the code with #ifndef ROCKSDB_LITE .. #endif
Test Plan: Run unit, lite, lite_test
Reviewers: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D58563
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
