Section 1: Introduction to Hadoop 

hadoop history, concepts,eco system, distributions, high level architecture, hadoop myths, hadoop challenges, hardware / software

Section 2: HDFS 

concepts (horizontal scaling, replication, data locality, rack awareness), architecture, Namenode, Secondary namenode, Data node, communications / heart-beats block manager / balancer, health check / safemode, read / write path, file systems abstractions, data integrity, future of HDFS : Namenode HA, Federation, lab exercises

Section 3: Map Reduce

mapreduce concepts, daemons : jobtracker / tasktracker, phases : driver, mapper, shuffle/sort, reducer, counters, distributed cache, combiners, mapreduce configuration, MR types and formats, sorting,Joins (map side & reduce side),job schedulers,unit testing,Thinking in map reduce, Future of mapreduce (yarn), lab exercises 

Section 4: Pig 

pig vs java map reduce, pig job flow, pig latin language, lab exercises

Section 5: Hive 

hive concepts, architecture, data types, hive vs sql, lab exercises 

Section 6: HBase 

Intro, concepts, architecture, hbase vs RDBMS, read path / write path, schema design, lab exercises