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Big data hadoop online training in India | Bangalore, Hyderabad and Pune

Real time trainer with limited students in a batch

Hadoop Online Training in India

Hadoop Online Training in India

CRS Info solutions is one of the best institute with good repetition for online training. We are happy to provide big data hadoop online training to our students from all over the world. Our students are from United States of America, UK, Europe, Dubai, Singapore, Australia like wise from all parts of the globe students are attending to our demos and joining in our hadoop coaching without delay.

We want to keep it simple and professional, our trainers are also follows same principles. They are friendly, having real time experience and they will spend time to clarify your doubts. That is only we expect first priority is to provide professional online training and second thing is friendly support throughout the course duration.

So if you are interested to join in our hadoop online training, please fill the contact form. We will get back to you within no time.


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 Tool1. Virtualbox/VM Ware
Snapshots2. Linux
Commands3. Hadoop
Why Hadoop?
Distributed Framework
Hadoop v/s RDBMS
Brief history of hadoop

4. Setup hadoop
Pseudo mode
Cluster mode
Installation of java, hadoop
Configurations of hadoop
Hadoop Processes ( NN, SNN, JT, DN, TT)
Temporary directory
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

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

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
Installation and Configuration
Interacting HDFS using HIVE
Map Reduce Programs through HIVE
HIVE Commands
Loading, Filtering, Grouping….
Data types, Operators…..
Joins, Groups….
Sample programs in HIVE

Installation and Configurations

11. Introduction

12. The Motivation for Hadoop

Problems with traditional large-scale systems
Requirements for a new approach

13. Hadoop: Basic Concepts
An Overview of Hadoop
The Hadoop Distributed File System
Hands-On Exercise
How MapReduce Works
Hands-On Exercise
Anatomy of a Hadoop Cluster
Other Hadoop Ecosystem Components

14. Writing a MapReduce Program
The MapReduce Flow
Examining a Sample MapReduce Program
Basic MapReduce API Concepts
The Driver Code
The Mapper
The Reducer
Hadoop’s Streaming API
Using Eclipse for Rapid Development
Hands-on exercise
The New MapReduce API

15. Common MapReduce Algorithms
Sorting and Searching
Machine Learning With Mahout
Term Frequency – Inverse Document Frequency
Word Co-Occurrence
Hands-On Exercise

16. PIG Concepts..
Data loading in PIG
Data Extraction in PIG
Data Transformation in PIG
Hands on exercise on PIG

17. Hive Concepts.
Hive Query Language
Alter and Delete in Hive
Partition in Hive
Joins in Hive.Unions in hive
Industry specific configuration of hive parameters
Authentication & Authorization
Statistics with Hive
Archiving in Hive
Hands-on exercise

18. Working with Sqoop
Import Data
Export Data
Sqoop Syntaxs
Databases connection
Hands-on exercise

19. Working with Flume
Configuration and Setup
Flume Sink with example
Flume Source with example
Complex flume architecture

20. OOZIE Concepts

21. IMPALA Concepts

22. HUE Concepts

23. HBASE Concepts

24. ZooKeeper Concepts

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