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HBase. Presented by Chintamani Siddeshwar Swathi Selvavinayakam. http:// www.slideshare.net / amansk /hbase-hadoop-day-seattle-4987041. HBase. Open source BigTable HDFS as underlying DFS ZooKeeper as lock service Tight integration with Hadoop MapReduce. Why HBase ?.

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hbase

HBase

Presented by

ChintamaniSiddeshwar

SwathiSelvavinayakam

http://www.slideshare.net/amansk/hbase-hadoop-day-seattle-4987041

hbase1
HBase
  • Open source BigTable
  • HDFS as underlying DFS
  • ZooKeeperas lock service
  • Tight integration with HadoopMapReduce
why hbase
Why HBase ?
  • Scales out to thousands of nodes
  • Access granularity is a row – read/write to a single row is atomic
  • Designed for workloads consisting of simple operations on individual items
  • Provides efficient access to random rows
  • Allows dynamic repartitioning of data
data model
Data Model
  • Sparse
  • Distributed
  • multi dimensional
  • persistent
  • Sorted
  • map
  • (row, column, timestamp) -> cell
  • Column = Column Family : Column Qualifier
other features
Other Features
  • Compression
  • In memory column families
  • Multiple masters
  • Rolling restart
  • Bloom filters
  • Efficient bulk loads
  • Source and sink for Hive, Pig, Cascading
use cases
Use Cases
  • Mozilla
  • Yahoo!
  • Twitter
  • Facebook
  • Adobe
hbase v s rdbms
HBase v/s RDBMS
  • Column Oriented
  • Flexible schema, add columns on the fly
  • Good with sparse tables
  • No query language
  • De-normalize your data
  • No transactions
  • Row Oriented ( mostly)
  • Fixed schema
  • Not optimized for sparse tables
  • SQL
  • Normalize as you can
  • Transactional
related chapters
Related Chapters
  • Big Data
  • Data Modelling
references
References
  • http://ofps.oreilly.com/titles/9781449396107/intro.html
  • http://wiki.apache.org/hadoop/Hbase/DataModel
  • http://www.slideshare.net/amansk/hbase-hadoop-day-seattle-4987041
  • http://static.googleusercontent.com/external_content/untrusted_dlcp/labs.google.com/en/us/papers/bigtable-osdi06.pdf