基于闪存数据库系统调研报告.ppt

1、Some key-value stores using log-structure,Zhichao L,LevelDB,Riak,Outline,Why log structure?Riak: log-structure hash tableRethinkdb: log-structure b-treeLeveldb: log-structure merge treeConclusion,Outline,Why log structure?Riak: log-structure hash tableRethinkdb: log-structure b-treeLeveldb: log-stru

2、cture merge treeConclusion,Log Structure,Alog-structured file systemis a file system design first proposed in 1988 by John K. Ousterhout and Fred Douglis.Design for high write throughput, all updates to data and metadata are written sequentially to a continuous stream, called a log.Conventional file

3、 systems tend to lay out files with great care for spatial locality and make in-place changes to their data structures.,Log Structure for SSD,Random write degrades the system performance and shrinks the lifetime of ssd.Log structure is ssd-friendly natively!,Magnetic Disk,SSD,free,free,free,free,fre

4、e,free,free,free,free,free,free,free,data 1,new data 1,data 2,data 3,data 4,new data 3,block,block,data 3,data 2,data 1,RAM,free,free,free,data 2,erased,erased,erased,new data 1,data 2,data 3,data 3,Outline,Why log structure?Riak: log-structure hash tableRethinkdb: log-structure b-treeLeveldb: log-s

5、tructure merge treeConclusion,Riak ?,Riak is an open source, highly scalable, fault-tolerant distributed database.Supported core features:- operate in highly distributed environments- no single point of failure- highly fault-tolerant- scales simply and intelligently- highly data available- low cost

6、of operations,Bitcask,A Bitcask instance is a directory, and only one operating system process will open that Bitcask for writing at a given time.The active file is only written by appending, which means that sequential writes do not require disk seeking.,Hash Index: keydir,A keydir is simply a hash

7、 table that maps every key in a Bitcask to a fixed-size structure giving the file, offset and size of the most recently written entry for that key .,Merge,The merge process iterates over all non-active file and produces as output a set of data files containing only the “live” or latest versions of e

8、ach present key.,Outline,Why log structure?Riak: log-structure hash tableRethinkdb: log-structure b-treeLeveldb: log-structure merge treeConclusion,RethinkDB ?,RethinkDB is a persistent, industrial-strength key-value store with full support for the Memcached protocol.Powerful technology:- Linear sca

9、ling across cores- Fine-grained durability control- Instantaneous recovery on power failureSupported core features:- Atomic increment/decrement- Values up to 10MB in size- Multi-GET support- Up to one million transactions per second on commodity hardware,Installation & usage,RethinkDB works on moder

10、n 64-bit distributions of Linux.Running the rethinkdb server:,Ubuntu 10.04.1 x86_64 Ubuntu 10.10 x86_64Red Hat Enterprise Linux 5 x86_64 CentOS 5 x86_64SUSE Linux 10,Default installation path: /usr/bin/rethinkdb-1.0./rethinkdb-1.0 -f /u01/rethinkdb_data./rethinkdb-1.0 -f /u01/rethinkdb_data -c 4 -p

11、11500./rethinkdb-1.0 -f /u01/rethinkdb_data -f /u03/rethinkdb_data -c 4 -p 11500,The methodology,Firstly, lack of mechanical parts makes random reads on SSD are significantly efficient!Secondly, random writes trigger more erases, making these operations expensive, and decreasing the drive lifetime!R

12、ethinkDB takes an append-only approach to storing data, pioneered by log-structured file system!,What are the consequences of appen-only ?,Append-only consequences,Data Consistency,Hot Backups,Instantaneous Recovery,Easy Replication,Lock-Free Concurrency,Live Schema Changes,Database Snapshots,2) lar

13、ge amount of data that quickly becomes obsolete in an environment with a heavy insert or update workload,1) eliminating data locality requires a larger number of disk access,Append-only B-tree,15,Outline,Why log structure?Riak: log-structure hash tableRethinkdb: log-structure b-treeLeveldb: log-stru

14、cture merge treeConclusion,LevelDB ?,LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.Supported core features:- Data is stored sorted by key- Multiple changes can be made in one atomic batch- Users can create a transient

15、 snapshot to get a consistent view of data- Data is automatically compressed using the Snappy compression library,Installation & usage,LevelDB works with snappy, which is a compression /decompression library.It is a library, no database server!,svn checkout http:/ leveldb-read-onlymake & cp liblevel

16、db.a /usr/local/lib &cp -r include/leveldb /usr/local/include,download snappy from http:/ cd snappy-1.0.4./configure & make & make install,libleveldb.a,Log-structure merge tree,LevelDB,Outline,Why log structure?Riak: log-structure hash tableRethinkdb: log-structure b-treeLeveldb: log-structure merge treeConclusion,Conclusion,Log-structure,