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Published byAlexys Addis Modified over 9 years ago
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HBase
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OUTLINE Basic Data Model Implementation – Architecture of HDFS Hbase Server HRegionServer 2
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Basic HBase directly uses or subclasses the parent Hadoop implementation
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Basic 4 Linux
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Basic DataBase of problem: – Grown of Data – Complexity of install and maintain Mutil-RDBMS of poblem:(for nodes ) – JOIN – not effective – rebalance Solution : Relational DataBase Management System(RDBMS) Solution : NoSQL DataBase
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Basic NoSQL DataBase : – Distributed – Scalability – Easy to use (EX:put, get,alter etc.)
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Basic List of NoSQL: – OpenSource HBase (Yahoo!) Cassandra (Facebook) SimpleDB (Amazon) – Commercial BigTable (Google)
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Basic Hbase: – Hadoop’s DataBase. – Reversion of 0.20.6 released – Usage with Map/Reduce
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OUTLINE Basic Data Model Implementation – Architecture of HDFS Hbase Server HRegionServer 9
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Table member : Row, Column, TimeStamp Row key Time Stamep Column”Contents” “com.yahoo.news.tw” t3 “ 我研發水下 6 千公尺機器人 ” t2 “ 蚊子怎麼搜尋人肉 ” t1 “… Wang 40…” “com.cnn.www”t1 “ 用腦波「發聲」 ”
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Table Add column ” Anchor ” Row key Time Stamep ”Contents” “com.yahoo. news.tw” t3 “ 我研發水下 6 千公尺 機器人 ” t2 “ 蚊子怎麼搜尋人肉 ” t1 “… Wang 40…” “com.cnn.w ww” t1 “ 用腦波「發聲」 ” Add
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Table Row key Time Stamep ”Contents”‘’ Anchor ’’ “com.yahoo.ne ws.tw” t5 “Anchor:tech” “Silvia” t4 “Anchor:sports” “Eric” t3 “ 我研發水下 6 千公尺機器 人 ” t2 “ 蚊子怎麼搜尋人肉 ” t1“… Wang 40…” “com.cnn.ww w”t1 “ 用腦波「發聲」 ” ‘’ Anchor_tech ’’‘’ Anchor_sports ’’ Silva Eric
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Region Row key Time Stamep ”Contents”‘’ Anchor ’’ “com.ya hoo.new s.tw” t5 “Anchor:tech” “Silvia” t4“Anchor:sports”“Eric” t3 “ 我研發水下 6 千公 尺機器人 ” t2 “ 蚊子怎麼搜尋人肉 ” t1“… Wang 40…” “com.cn n.www”t1 “ 用腦波「發聲」 ” “com.ab c.www” “com.de f.www” region1region1 region2region2 Region1(com.yahoo.ne w.tw,com.def.www>,ID Express: Region(start row key, end row key>& identifier
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Sort Sort by row key – byte-ordered Add label on family column
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Locking Row key Time Stamep ”Contents”‘’ Anchor ’’ “com.ya hoo.new s.tw” t5 “Anchor:tech” “Silvia” t4“Anchor:sports”“Eric” t3 “ 我研發水下 6 千公 尺機器人 ” t2 “ 蚊子怎麼搜尋人肉 ” t1“… Wang 40…” “com.cn n.www”t1 “ 用腦波「發聲」 ” “com.ab c.www” “com.de f.www” User1 update User2 update User3 update User4 update
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OUTLINE Basic Data Model Implementation – Architecture of Hbase Hbase Server HRegionServer 16
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Architecture of Hbase NN: NameNode DN: DataNode HM: Hmaster HR:HRegion Cluster HDFS Client NNDN HMHR ZooKeeper
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rebalance a single host grows the regions – it split a row into two new regions of approximately equal size. Until not across threshold automatic
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Hbase Master The master node is lightly loaded. assignment of the replacement daughters Recovering regionserver failures.
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RegionServer carry zero or more regions client read/write/scan requests – Random access Automatic split regions Send HeartBeat to Master
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RegionInfo. Region of metadata – the current list, state, recent history, and location of all regions afloat on the cluster. {NAME => ‘docs’, FAMILIES => [{NAME => ‘cache’, COMPRESSION => ‘NONE’, VERSIONS => ’3′, TTL => ′ 2147483647′, BLOCKSIZE => ’65536′, IN_MEMORY => ‘false’, BLOCKCACHE => ‘false’}
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.MATA.
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HBase in operation memory size of 256MB and each row is 1KB size -ROOT-.META. useregion 1.8 x 10 19 (2 64 ) bytes of user data 2.6 x 10 5 META regions 6.9 x 10 10 user regions
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HBase in operation NN: NameNode DN: DataNode HM: Hmaster HR:Regionsever Cluster HBase Client NNDN HMRR RRR ZooKeeper ROOTMETA Request consult Step 3. User region Step 1. Step 2 Read Requests - Step 1.location of -ROOT- - Step 2.location of the.META. Region - Step3.user region space
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HBase in operation NN: NameNode DN: DataNode HM: Hmaster HR:Regionsever Cluster HBase Client NNDN HMRR RRR ZooKeeper Interacts with RegionServer Read Requests -clients cache save information of ROOT, META and User Region
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HBase in operation Interacts with RegionServer HBase Client HLog table Region server of state Region Serser Region Serser Hstore Region Hstore HFile Hfile Mem Store
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HBase in operation RegionServer HBase Client HLog Client request to save data in table Region Serser Region Serser Hstore Region Hstore HFile Hfile Mem Store
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Hbase of characteristic Fault tolerance Batch processing Automatic partitioning Scale linearly with new nodes
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