ABOUT HADOOP TRAINING

Prince Tech Solutions Big Data and Hadoop Online Training will clearly explains MapReduce Concepts with the help of industry Experts. Our Trainer’s will also teach you how to handle Apache Hadoop ecosystems like Hive, Pig, and HBase with live Project’s.This course gives you a clear understanding about how to build a Hadoop application using the relevant frameworks under the suitable Apache Project ecosystem in a real time scenario and that will help you to build a custom application by yourself. We customized this course curriculum to meet the current industry standards. We guarantee that even any participant who is not familiar with much technical background, can easily learn & excel this Hadoop training and build an application at the end of this course completion.

Objective of this course:

At end of this Hadoop training by Prance Tech Solutions, you will be able to,

  • Learn how to write HDFS/Mapreduce programs
  • Learn how to write & utilize effectively Hive & Pig Scripts
  • Understand basically how the administration part is even handled for a cluster setup
  • Learn how to write & utilize effectively Flume & Zookeeper mechanisms
  • Understand better on the internal architecture/design involved on all the Hadoop platforms
  • Understand how to enhance your coding skills using Hbase & Sqoop tools
  • To understand better on how a real time projects fit into the big data platform

Hadoop – Course Content

Apache Hadoop
  • Introduction to Big Data & Hadoop Fundamentals
  • Dimensions of Big data
  • Type of Data generation
  • Apache ecosystem & its projects
  • Hadoop distributors
  • HDFS core concepts
  • Modes of Hadoop employment
  • HDFS Flow architecture
  • HDFS MrV1 vs MrV2 architecture
  • Types of Data compression techniques
  • Rack topology
  • HDFS utility commands
  • Min h/w requirements for a cluster & property files changes
Mapreduce Framework
  • Introduction to Mapreduce
  • Mapreduce Design flow
  • Mapreduce Program (Job) execution
  • Types of Inputformats & Outputformats
  • Mapreduce Datatypes
  • Performance tuning of a Mapreduce jobs
  • Counters techniques
Apache Hive
  • Introduction to Hive & features
  • Hive architecture flow
  • Types of hive tables flow
  • DML/DDL commands explanation
  • Partitioning logic
  • Bucketing logic
  • Hive script execution in shell & HUE
Apache Hbase
  • Introduction to Hbase concepts
  • Introdcution to NoSQL/CAP theorem concepts
  • Hbase design/architecture flow
  • Hbase table commands
  • Hive + Hbase integration module/jars deployment
  • Hbase execution in shell/HUE
Apache Pig
  • Introduction to Pig concepts
  • Pig modes of execution/storage concepts
  • Pig program logics explanation
  • Pig basic commands
  • Pig script execution in shell/HUE
Apache Sqoop
  • Introduction to Sqoop concepts
  • Sqoop internal design/architecture
  • Sqoop Import statements concepts
  • Sqoop Export Statements concepts
  • Quest Data connectors flow
  • Incremental updating concepts
  • Creating a database in MySQL for importing to HDFS
  • Sqoop commands execution in shell/HUE
Apache HUE
  • Introduction to Hue design
  • Hue architecture flow/UI interface
Apache Zookeeper
  • Introduction to zookeeper concepts
  • Zookeeper principles & usage in Hadoop framework
  • Basics of Zookeeper
Apache Flume
  • Introduction to Flume & features
  • Flume topology & core concepts
  • Property file parameters logic
Hadoop Administration
  • Principles of Hadoop administration & its importance
  • Hadoop admin commands explanation
  • Balancer concepts
  • Rolling upgrade mechanism explanation