This chapter explains Hadoop administration which includes both HDFS and MapReduce administration. HDFS administration includes monitoring the HDFS file structure, locations, and the updated files.MapReduce administration includes monitoring the list…
A Combiner, also known as a semi-reducer, is an optional class that operates by accepting the inputs from the Map class and thereafter passing the output key-value pairs to the Reducer class.…
A partitioner works like a condition in processing an input dataset. The partitioning phase takes place after the Map phase and before the Reduce phase. The number of partitioners is…
MapReduce is a framework that is used for writing applications to process huge volumes of data on large clusters of commodity hardware in a reliable manner. This chapter takes you…
MapReduce works only on Linux flavored operating systems and it comes inbuilt with a Hadoop Framework. We need to perform the following steps in order to install the Hadoop framework.…
The MapReduce algorithm contains two important tasks, namely Map and Reduce. The map task is done by means of Mapper ClassThe reduce task is done by means of Reducer Class.…
MapReduce is a programming model for writing applications that can process Big Data in parallel on multiple nodes. MapReduce provides analytical capabilities for analyzing huge volumes of complex data. What…
MapReduce is a programming paradigm that runs in the background of Hadoop to provide scalability and easy data-processing solutions. This tutorial explains the features of MapReduce and how it works…