Gowtham Rajappan
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HDFS – Hadoop Distributed File System modeled on Google GFS.
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Hadoop MapReduce – Similar to Google MapReduce
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Hbase – Similar to Google Bigtable
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Master: hadoop01.cselabs.umn.edu
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Slaves: hadoop02 – hadoop05.cselabs.umn.edu
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You will require cselabs account to access this cluster. You can
login to any of these machines from any cs/cselabs machine.
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Data is divided into various tables
Table is composed of columns, columns are grouped into columnfamilies
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Partitioning
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A table is horizontally partitioned into regions, each region is
composed of sequential range of keys
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Each region is managed by a RegionServer, a single
RegionServer may hold multiple regions
Persistence and data availability
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HBase stores its data in HDFS, it doesn't replicate
RegionServers and relies on HDFS replication for data
availability.
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Region data is cached in-memory
 Updates and reads are served from in-memory cache
(MemStore)
 MemStore is flushed periodically to HDFS
 Write Ahead Log (stored in HDFS) is used for durability of
updates
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HBase shell provides interactive commands for manipulating
database
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Create/delete tables
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Insert/update/read from tables
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Manage regions
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Hbase provides single row atomic operations
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CheckAndPut – Similar to test-and-set
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CheckAndDelete
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All row operations are atomic no matter how many columns are
involved.
Hbase also provides row level exclusive locks
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You can use these locks to implement single row level
transactions
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HBase stores multiple versions of a column in a row. Each version
is identified by a integer timestamp
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By default system time is used as version timestamps. However
user can specify a logical timestamp for versioning
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Each update to a row creates a new version, for the specified
column.
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A version can be accessed or deleted using its timestamp.
HBase allows to obtain list of all the versions.
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Hadoop Home - http://hadoop.apache.org/
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Hbase - http://hbase.apache.org/
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API
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http://hbase.apache.org/apidocs/
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http://hadoop.apache.org/