In this Hadoop Java Programming course, you will implement a strategy for developing Hadoop jobs and extracting business value from large and varied data sets. This Apache Hadoop development training is essential for programmers who want to augment their programming skills to use Hadoop for a variety of big data solutions. You will learn to write, customize and deploy MapReduce jobs to summarize data, load and retrieve unstructured data from HDFS and HBase. In addition, you will develop Hive and Pig queries to simplify data analysis, as well as test and debug jobs using MRUnit.
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Meeting the challenges of parallel programming
Parallel programming with MapReduce
Applying the Hadoop MapReduce paradigm
Building complex MapReduce jobs
Solving common data manipulation problems
Implementing partitioners and comparators
Making the case for distributed data
Interfacing with Hadoop Distributed File System (HDFS)
Structuring data with HBase
Unleashing the power of SQL with Hive
Executing workflows with Pig
Testing and debugging Hadoop code
Deploying, monitoring and tuning performance
Exam preparation through fact-based questions and case-study questions.
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