A library that provides an embeddable, persistent key-value store for fast storage.
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Yueh-Hsuan Chiang 3f0867c0fe Allow GetThreadList to report Flush properties.
Summary:
Allow GetThreadList to report Flush properties, which includes:
* job id
* number of bytes that has been written since flush started.
* total size of input mem-tables

Test Plan:
./db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=100 --value_size=1000

Sample output from db_bench which tracks same flush job

          ThreadID ThreadType       cfName            Operation   ElapsedTime                                         Stage        State OperationProperties
   140213879898240   High Pri      default                Flush       5789 us                    FlushJob::WriteLevel0Table              BytesMemtables 4112835 | BytesWritten 577104 | JobID 8 |

          ThreadID ThreadType       cfName            Operation   ElapsedTime                                         Stage        State OperationProperties
   140213879898240   High Pri      default                Flush     30.634 ms                    FlushJob::WriteLevel0Table              BytesMemtables 4112835 | BytesWritten 1734865 | JobID 8 |

Reviewers: rven, igor, sdong

Reviewed By: sdong

Subscribers: dhruba, leveldb

Differential Revision: https://reviews.facebook.net/D38505
2015-05-15 23:22:22 -07:00
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db Allow GetThreadList to report Flush properties. 2015-05-15 23:22:22 -07:00
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java Bugfix remove deprecated option use which was removed in previous commit 019ecd1932 2015-04-30 23:16:04 +01:00
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utilities API to fetch from both a WriteBatchWithIndex and the db 2015-05-11 14:51:51 -07:00
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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/