Hadoop Ecosystem Masterclass - MapReduce

Through this course we are going to learn about the Choosing appropriate Hadoop data types, Implementing a custom Hadoop Writable data type, Implementing a custom Hadoop key type, Emitting data of different value types from a mapper, Choosing a suitable Hadoop Input Format for your input data format, Adding support for new input data formats – implementing a custom Input Format, Formatting the results of MapReduce computations – using Hadoop Output Formats. Next we focus on the data partitioning, , Broadcasting and distributing shared resources to tasks in a MapReduce job – Hadoop Distributed Cache, Using Hadoop with legacy applications – Hadoop Streaming, Adding dependencies between MapReduce jobs and using Hadoop counters for reporting custom metrics.