• Students and Freshers.
• Professionals willing to switch to Big Data / Hadoop developer stream.

• Core Java programming skills
• Any RDBMS (like Oracle or MySQL)
• XML awareness, Linux commands familiarity

• Work in clustered Hadoop environment.
• Get pre-installed VM with Hadoop & Eco system setup.
• Get in-depth understanding of Hadoop internals/core.
• Learn with plenty of demo codes/programs.
• Focus on core features of Hadoop and eco-system, than touching various features.
• Quality is having higher weightage than the quantity.

• Core i3 (64-bit) and above
• RAM min 8 GB. Recommended: 16 GB+.
• 64-bit Linux – Ubuntu or CentOS – Java 8.0 JDK installed.

• Data science (math/stat) - However implementation of stats formulae in MR job will be covered.
• Hadoop administration - However some basic config and performance related config will be discussed.
• Reporting and visualization tools.
• Hadoop cluster on cloud - However multi-node cluster with minimal configuration will be taught.

Java Revision for Hadoop
JVM, JRE, JDK, Packaging jar, Execution
Wrapper classes, inheritance, abstract class
Interfaces, Method overriding, Reflection
Java generics, Collection framework,
IO framework, Garbage collection, Member class

Hadoop Basics
Big Data intro – What & Why?
BigData vs. RDBMS
Hadoop2 architecture, daemons
Hadoop2 installation in modes
File System, Distributed FS & HDFS
HDFS: namenode, sec namenode, data node
Replica mechanism, FS shell cmds, Web UI
MapReduce (MR) & alternatives, YARN
Hadoop eco-systems, applications/use cases

Hadoop Programming
Hadoop FS apis, dealing with local/HDFS files
Hadoop data types, Parsing MR job args
MR programming: Mapper & Reducer impl
Input splits, Input/Output formats
Job execution on YARN, Understanding logs
AppMaster, ResourceManager & NodeManager
Partitioner & Combiners, Custom Writables
Counters, Testing, Analyzing execution
Inner/Outer Joins in MR, Cartesian product,
Hadoop streaming, SequenceFiles

NoSQL database - HBase

RDBMS vs NoSQL databases, NoSQL db types 
ACID vs BASE, CAP theorm, 
HBase introduction, Column oriented Db
HBase vs RDBMS, HBase installation
HBase architecture, Master & Region servers
HBase column schema, Internal storage
Hbase Shell, commands, Java client APIs
Distribution system coordination, Zookeeper
MapReduce & HBase integration

Hive
Hive introduction, architecture, installation
Hive CLI, Security, Beeline, Metastore & Derby
Hive managed & external tables,
Hive QL: Loading, Filtering, Grouping, Joins
Hive simple & complex types, DDL, DML, DQL
Hive indexes, views, query optimizations
Hive serialization / deserialization, Loading data
Partitioning: static & dynamic – use cases
Bucketing, use cases of Partitions & Buckets
Hive functions, operators and Hive UDF impl.
Thrift server, Java connectivity, Hive vs Impala

Sqoop & Flume
Sqoop intro, use cases, sqoop execution,
Import data into Hadoop, Export from Hadoop
Sqoop for importing in Hive or HBase
Flume intro, flume architecture, applications
Events, source, channel and sink
Capturing logs data, IoT data