A library that provides an embeddable, persistent key-value store for fast storage.
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krad d4540654e9 Optimize GetApproximateSizes() to use lesser CPU cycles.
Summary:
CPU profiling reveals GetApproximateSizes as a bottleneck for performance. The current implementation is sub-optimal, it scans every file in every level to compute the result.

We can take advantage of the fact that all levels above 0 are sorted in the increasing order of key ranges and use binary search to locate the starting index. This can reduce the number of comparisons required to compute the result.

Test Plan: We have good test coverage. Run the tests.

Reviewers: sdong, igor, rven, dynamike

Subscribers: dynamike, maykov, dhruba, leveldb

Differential Revision: https://reviews.facebook.net/D37755
2015-04-30 10:55:03 -07:00
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db Optimize GetApproximateSizes() to use lesser CPU cycles. 2015-04-30 10:55:03 -07:00
doc Remove seek compaction 2014-06-20 10:23:02 +02:00
examples Fix formatting 2015-02-09 09:53:30 -08:00
hdfs Remove unused parameter in CancelAllBackgroundWork 2015-03-16 21:07:54 -07:00
include Making GetOptions() comment better (#597) 2015-04-30 09:29:51 -07:00
java [RocksJava] Remove deprecated methods 2015-04-16 00:31:43 +02:00
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HISTORY.md Task 6532943: Rocksdb - SetCapacity() can dynamically change cache capacity if feasible 2015-04-24 14:12:58 -07:00
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README.md Replaced "built on on earlier work" by "built on earlier work" in README.md 2014-09-17 01:16:17 -07:00
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Vagrantfile RocksDB on FreeBSD support 2015-02-26 15:19:17 -08:00

RocksDB: A Persistent Key-Value Store for Flash and RAM Storage

Build Status

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/