This document provides an overview of HBase, describing it as a non-relational, distributed, column-oriented database that provides high availability and high performance. It discusses HBase's implementation with a master node and region servers, and how to install, configure, and start HBase. It also summarizes how HBase differs from HDFS, how to program with HBase using its shell and APIs, its data storage model, and provides examples of organizations using HBase at large scales.

1. A Soft Introduction

2. What is Hbase
 Non-relational, distributed database
 Column‐Oriented
 Multi‐Dimensional
 High Availability
 High Performance
 open source

3. Implementation
 HBase modeled with an HBase master node
orchestrating a cluster of one or more regionserver
slaves.
 The HBase master is responsible for bootstrapping a
virgin install, for assigning regions to registered region
servers, and for recovering region server failures. The
master node is lightly loaded.

5. Installation
 Download a stable release from an Apache Download
Mirror and unpack it on your local filesystem.
 you first need to tell HBase where Java is located on
your system. i.e JAVA_HOME environment variable
 you can set the Java installation that HBase uses by
editing HBase’s conf/hbaseenv.sh, and specifying the
JAVA_HOME

6. Continue
 Add the HBase binary directory to your command-line
path. For example:
% exportHBASE_HOME=/home/hbase/hbase-x.y.z
% export PATH=$PATH:$HBASE_HOME/bin
 To get the list of HBase options, type: % hbase
 To start a temporary instance of HBase
% start-hbase.sh
 launch the HBase shell by typing: % hbase shell
type:

7. Difference Between Hadoop/HDFS
and Hbase
 HDFS is a distributed file system that is well suited for
the storage of large files.
 HBase, on the other hand, is built on top of HDFS and
provides fast record lookups (and updates) for large
tables.
 HDFS has based on GFS file system.
 Hbase is Distributed – uses HDFS for storage ,Column
– Oriented , Multi Dimensional( Versions) , Storage
System

8. Hbase is NOT
 A sql Database – No Joins,
datatypes , no (damn) sql
 No Schema
 No DBA needed
no query engine, no

9. Programming with HBase
 HBase shell
 Scan, List, Create, Get, Put, Delete
 Java API
 Get, Put, Delete, Scan,…
 Non-Java Clients
 Thrift
 REST
 HBase MapReduce API
 hbase.mapreduce.TableMapper;
 hbase.mapreduce.TableReducer;
 High Level Interface
 Pig, Hive

10. Storage Model
 Column – oriented database (column families)
 Table consists of Rows, each which has a
primary
key(row key)
 Each Row may have any number of columns
 Table schema only defines Column familes(column
family can have any number of columns)
 Each cell value has a timestamp

11. Hbase shell
 hbase(main):003:0> create 'test', 'cf'
 0 row(s) in 1.2200 seconds
 hbase(main):004:0> put 'test', 'row1', 'cf:a', 'value1'
 0 row(s) in 0.0560 seconds
 0 hbase(main):005:0> put 'test', 'row2', 'cf:b', 'value2'
 0 row(s) in 0.0370 seconds
 hbase(main):006:0> put 'test', 'row3', 'cf:c', 'value3'
 0 row(s) in 0.0450 seconds

12. Hbase vs RDBMS
RDBMS Hbase
 Data layout: Row-oriented Column family oriented
 Query language SQL Get/put/scan/etc *
 Security
 Max data size
 Read/write
Authentication/Authorization Work in Progress
TBs
1000s queries/second
Hundrends of PBs
Millions of queries /second

13. Use Cases
 Facebook Analytics
 Real-time counters of URLs shared, preferred links
 Twitter
 25 TB of message every month
 Mozilla
 Store crashes report, 2.5 million per day.