Hadoop MapReduce Applications With Combiners

In this Skillsoft Aspire course explore the use of Combiners to make MapReduce applications more efficient by minimizing data transfers. Start by learning about the need for Combiners to optimize the execution of a MapReduce application by minimizing data transfers within a cluster. Recall the steps to process data in a MapReduce application and look at using a Combiner to perform partial reduction of data output from the Mapper. Then create a new project to calculate average automobile prices using Maven for a MapReduce application. Next develop the Mapper and Reducer to calculate the average price for automobile makes in the input data set. Create a driver program for the MapReduce application run it and check output to get the average price per automobile. Learn how to code up a Combiner for a MapReduce application fix the bug in the application so it can be used to correctly calculate the average price then run the fixed application to verify that the prices are being calculated correctly. The concluding exercise concerns optimizing MapReduce with Combiners.