A MapReduce Example
Understand how to implement a MapReduce job within Hadoop using Python and Hadoop Streaming. Learn to interact with HDFS, run commands, and process data files to count items efficiently. This hands-on example helps beginners grasp the practical workflow of big data processing with Hadoop.
We'll cover the following...
MapReduce in practice
To understand MapReduce, we first need to understand its importance. Suppose we have a vast dataset of the text files. Each file has multiple lines and is separated into numerous nodes.
For this lesson, we will continue with the tennis ball example discussed in an earlier lesson.
Due to lack of infrastructure, in our example, we will do the processing in one node. However, this will make no difference in our interaction, at least from a development perspective. Infrastructure administration has some overhead, of course.
First, we store information about our products in various files in HDFS.
Those files contain the name of the color of each tennis ball that matches the criteria.
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