This article attempts to give a step by step walk through for creating a single Node Hadoop Cluster. It is an hands on tutorial so that even a novice user can follow the steps and create the Hadoop Cluster.
This tutorial talks about Map reduce programming paradigm used widely in the Big Data analytics arena. We will also run through an example step by step to understand various mechanisms involved.
This was a research paper that we submitted to ICAPADS-2012 an IEEE – Institute of High performance distributed computing conference . It talks about a map reduce based solution to maze traversal problem which is applicable in many practical problems.
This tutorial talks about various resources that you can use to leard about hadoop and map reduce. It also talks about how you can think about learning about Big data as a subject in totality
In this article we will go through a very important technique – importing data from SQL table to HDFS. We will do so on a sample database say ‘bigdata’ and a sample table say ’employee’ containing employee data.
We will do this in 3 parts. Part 1 will be in scope of this article. We will look at the next parts in subsequent article
In this hadoop tutorial we will have a look at the modification to our previous program wordcount with our own custom mapper and reducer by implementing a concept called as custom record reader. Before we attack the problem let us look at some theory required to understand the topic.
So here is the next article in series. In the last post we learnt how to write wordcount without using explicit custom mappers or reducers. You can find the post here
Today we will go a step ahead and we will rewrite the same wordcount program by writing our own custom mappers as well as reducers.
We will use 2 classes in addition to our wordcount class.