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.…
Let us now see how to install Apache Storm framework on your machine. There are three majo steps here − Install Java on your system, if you don’t have it…
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…
Apache Storm processes real-time data and the input normally comes from a message queuing system. An external distributed messaging system will provide the input necessary for the realtime computation. Spout…
A working Storm cluster should have one nimbus and one or more supervisors. Another important node is Apache ZooKeeper, which will be used for the coordination between the nimbus and…
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…
One of the main highlight of the Apache Storm is that it is a fault-tolerant, fast with no “Single Point of Failure” (SPOF) distributed application. We can install Apache Storm…
Apache Storm reads raw stream of real-time data from one end and passes it through a sequence of small processing units and output the processed / useful information at the…
In this chapter, we will take a close look at the classes and their methods that are involved in the operations of MapReduce programming. We will primarily keep our focus…