About The Course

Hadoop Online coaching in ameerpet Hyderabad and marathahalli Bangalore, India providing professional course in Hadoop Technology.
The growing, data vows cannot be met by conventional technologies and need some really organized and automated technology.
Big data and Hadoop are the two kinds of the promising technologies that can analyze, curate, and manage the data.
The course on Hadoop and Big data is to provide enhanced knowledge and technical skills needed to become an efficient developer in Hadoop technology.
Along with learning, there is virtual implementation using the core concepts of the subject upon live industry based applications.
With the simple programming modules, large clusters of data can be managed into simpler versions for ease of accessibility and management.
Best hadoop Online Training India has the best expertise to handle the Hadoop Online training in India.

Course Objectives

The Course goes with the aim to understand key concepts about:

  • HDFS and MapReduce Framework
  • Architecture of Hadoop 2.x
  • To write Complex MapReduce Programs and Set Up Hadoop Cluster
  • Making Data Analytics by using Pig, Hive and Yarn
  • Sqoop and Flume for learning Data Loading Techniques
  • Implementation of integration by HBase and MapReduce
  • To implement Indexing and Advanced Usage
  • To Schedule jobs with the use of Oozie application
  • To implement best practices for Hadoop Development Program
  • Working on Real Life Projects basing on Big Data Analytics
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
1. Virtualbox/VM Ware

2. Linux


3. 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


Course Details:

Duration : 45-50 hours(Daily 1hr to 1 hr 30 minutes)
System Access: 5 months
Session Timings: As per participant convenience
Payment Options: Online


About Trainer:

CRS Info Solutions trainers are passionate and focused in quality and accuracy for delivering the best services for our clients. Our trainers are from top MNCs and carry years of experience. The training methodology is not just walking through people with PPTs, rather it is way to share experienced they gain over many years. Our trainer evaluation method is very rigorous and people qualify with predefined parameters are only eligible to train and associate with CRS Info Solutions. CRS Info Solutions training quality parameters are very high and we are very concern about the quality delivery. Our trainers are educated with CRS Info Solutions training standard and ensure that there is no way we compromise with quality at any point.