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Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? Distribution systems. What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco System HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Developing the Map Reduce Application Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster MapReduce workflows How MapReduce Works Anatomy of a MapReduce job run Failures Job Scheduling Shuffle and Sort Task Execution MapReduce Types and Formats MapReduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output MapReduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hive and PIG Fundamentals When to Use PIG and HIVE Concepts HBASE CAP Theorem Hbase Architecture and concepts Programming

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