Shu Zhang 8dee8cad9e Enable fifo compaction benchmark to db_bench
Summary:
Added fifo benchmark to db_bench.
One thing i am not sure is that i am using CompactRange() instead of CompactFiles(). (may cause performance skew because CompactionRange() is not happening in current thread?)  For CompactFiles(), for some reason FIFO compaction doesn't work as expected. More insight is welcomed. I guess FIFO compaction doesn't work with file names? igorcanadi

test cmd:
./db_bench --compaction_style=2 --benchmarks=fillseqdeterministic --disable_auto_compactions --num_levels=1 --fifo_compaction_max_table_files_size_mb=10

---------------------- DB 0 LSM ---------------------
Level[0]: /000014.sst(size: 4211014 bytes)
fillseqdeterministic :       4.731 micros/op 211381 ops/sec;   23.4 MB/s
Closes https://github.com/facebook/rocksdb/pull/1734

Differential Revision: D4774964

Pulled By: siying

fbshipit-source-id: 9d08df6
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RocksDB: A Persistent Key-Value Store for Flash and RAM Storage

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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/

Description
A library that provides an embeddable, persistent key-value store for fast storage.
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