Hbase-A Soft Introduction & Quickstart

After understanding whats is Hadoop, and after deploying hadoop , lets’ start understanding HBase. This tutorial explains basics of HBase, and its features. Here I tried to explain functionality HBase provides and a quick start about HBase, a Basic tutorial for beginners. You will get to know where to use HBase, in which situation HBase can be useful.

Apache HBase
Source: Apache
Understanding What is HBase
HBase is an open source, distributed, versioned, column-oriented, No-SQL / Non-relational database management system that runs on the top of Hadoop. It adds transactional capability to hadoop, allowing users to update data records. Hadoop is designed for batch processing of large dataset, but with HBase on the top of Hadoop we can process real time dataset.

Optimize Map Reduce Job Performance

Optimize Hadoop Performance. To improve Hadoop performance, you need to change various configuration parameter in core-site.xml, hdfs-site.xml, mapred-site.xml. The configuration / optimization of parameter to improve performance depends on the type of processing, it depends on case to case, there is no hard and fast rule.

To install Hadoop on ubuntu cluster you can refer this post

We can change block size, number of mappers and reducers, sort factor, jvm reuse, memory for java process, enable compression, map output compression, use combiner, etc.
I found a very nice description given by Cloudera

Deploy Apache Flume NG (1.x.x)

In this tutorial I have explained how to install / deploy / configure Flume NG on single system, and how to configure Flume NG to copy data to HDFS, then configuration for copying data to HBase

Before going to configurations let’s understand what Flume NG (1.x.x) is:
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. The system is centrally managed and allows for intelligent dynamic management. It uses a simple extensible data model that allows for online analytic application.