This is the series of blog posts to cover the core Map Reduce Programming. It also covers the job execution phases.
- Map Reduce 1 – Insight
- Lab 02 – A Simple Hadoop Mapper with Eclipse and Maven
- Lab 03 – A Hadoop Mapper to get the category of an RSS feed with Eclipse and Maven
- Lab 04 – A Hadoop Reducer demo
- Lab 05 – A hadoop combiner demo
- Lab 06 – A simple hadoop partitioner
- java.io.IOException: Illegal partition for Big Data (3)
- Lab 07 – A mini MR project with mapper, reducer and partitioner
- Lab 08 – MapReduce using custom class as Key
- Lab 09 – Identity Mapper & Reducer
- Lab 10 – Make use of MapReduce Counter
- Lab11 – Reading from HDFS & charting
- Lab12 – Writing local file to HDFS
- Lab 13 – Working with Hadoop serialization – MapReduce with custom key and custom value
- Lab 14: Sending MapReduce output to JDBC
- Lab 15: Writing unit test cases for MapReduce
- MapReduce Job Execution Process – Job Submission
- MapReduce Job Execution Process – Job initialization
- MapReduce Job Execution Process – Job scheduling
- MapReduce Job Execution Process – Sort & Spill
- MapReduce Job Execution Process – Reduce Function
- MapReduce Job Execution Process – Job Cleanup
- java.io.IOException: Filesystem closed
- Lab 17 – Adding custom jars to MapReduce using Distributed Cache
- Lab 18: Map Side Join with DistributedCache
- Lab 19: Reducer side join
- Lab 20: Sequential File Creation
- Lab 21: MapReduce with Sequence File