Hadoop Training In Chennai Adyar - Greens

20/11/2014 Language Classes

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Description

HADOOP Training 


Course Objective Summary
During this course, you will learn:
• Introduction to Big Data and Analytics
• Introduction to Hadoop
• Hadoop ecosystem - Concepts
• Hadoop Map-reduce concepts and features
• Developing the map-reduce Applications
• Pig concepts
• Hive concepts
• Sqoop concepts
• Flume Concepts
• Oozie workflow concepts
• Impala Concepts
• Hue Concepts
• HBASE Concepts
• ZooKeeper Concepts
• Real Life Use Cases
Reporting Tool
• Tableau
1. Virtualbox/VM Ware
• Basics
• Installations
• Backups
• Snapshots
2. Linux
• Basics
• Installations
• Commands
3. Hadoop
• Why Hadoop?
• Scaling
• Distributed Framework
• Hadoop v/s RDBMS
• Brief history of hadoop
4. Setup hadoop
• Pseudo mode
• Cluster mode
• Ipv6
• Ssh
• Installation of java, hadoop
• Configurations of hadoop
• Hadoop Processes ( NN, SNN, JT, DN, TT)
• Temporary directory
• UI
• Common errors when running hadoop cluster, solutions
5. HDFS- Hadoop distributed File System
• HDFS Design and Architecture
• HDFS Concepts
• Interacting HDFS using command line
• Interacting HDFS using Java APIs
• Dataflow
• Blocks
• Replica
6. Hadoop Processes
• Name node
• Secondary name node
• Job tracker
• Task tracker
• Data node
7. Map Reduce
• Developing Map Reduce Application
• Phases in Map Reduce Framework
• Map Reduce Input and Output Formats
• Advanced Concepts
• Sample Applications
• Combiner
8. Joining datasets in Mapreduce jobs
• Map-side join
• Reduce-Side join
9. Map reduce – customization
• Custom Input format class
• Hash Partitioner
• Custom Partitioner
• Sorting techniques
• Custom Output format class
10. Hadoop Programming Languages :-
I.HIVE
• Introduction
• Installation and Configuration
• Interacting HDFS using HIVE
• Map Reduce Programs through HIVE
• HIVE Commands
• Loading, Filtering, Grouping….
• Data types, Operators…..
• Joins, Groups….
• Sample


 


 

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