Join Our Hadoop Course in Bangalore

  • Course Summary

Hadoop Training in Marathahalli, Bangalore by RIA classroomoffers students an imaginative approach to learn Hadoop in Bangalore. With experienced Hadoop proficient trainers and advanced lab Facilities to practice Hadoop, students can finish Hadoop training on real time situation. Our Hadoop Training Institute in Bangalore is appraised as one of the Best Hadoop Learning Center on Google.

Training system utilized for directing Hadoop course incorporates simplicity of understanding Hadoop ideas, most recent examples in Hadoop classes and real time commonsense presentation. This guarantees students deciding on Hadoop training in Marathahalli, Bangalore get value for money. Our Hadoop course content is organized to cover all ideas under Hadoop Training

Hadoop Training Facilities

Coaching facilities for Hadoop Training in Marathahalli, Bangalore are best suited for Freshers as well as experienced professionals who are actively looking for upgrading skills in Hadoop. From Hadoop training consultation to Hadoop course completion we offer complete support to students. Regular reviews are conducted to ensure that Hadoop Training is being conducted in a structured manner and the students are able to understand all the Hadoop Training concepts.

Hadoop Training Batch Timings

We offer flexible batch timings for Hadoop Training in Bangalore. Students can choose to join our weekday batches for Hadoop course and IT professionals looking for Hadoop Training to advance in their career can join our Weekend classes based on their convenience. We also offer Fast Track Training for students who want to complete Hadoop course in detail in a short span.

Hadoop Course Content

Our Hadoop Course content is structured to cover all the modules within Hadoop. From basic to advance, we give Hadoop training in Bangalore in a manner that is easy to understand.

Below is the detailed course content for Hadoop Training

  • What is Big Data
  • What is Hadoop
  • Why Hadoop and its use cases
  • Different Componets of Hadoop

HDFS (Hadoop Distributed File System)

  • Significance of HDFS in Hadoop
  • Features of HDFS

5 daemons of Hadoop

  • Name Node and its functionality
  • Data Node and its functionality
  • Job Tracker and its functionality
  • Task Track and its functionality
  • Secondary Name Node and its functionality.

Data Storage in HDFS

  • Introduction about Blocks
  • Data Replication

Accessing HDFS

  • CLI (Command Line Interface) and Admin commands
  • DataNode Recommendations
  • NameNode Recommendations
  • Hadoop Archives

Hadoop Installation

  • MapReduce
  • MapReduce architecture
  • Map Reduce Programming Model
  • Different phases of Map Reduce Algorithm
  • Different Data types in Map Reduce

How to write a basic Map Reduce Program

  • The Mapper
  • The Reducer
  • The Driver Code
  • Creating Input and Output Formats in Map Reduce Jobs
  • Text Input Format
  • Key Value Input Format
  • Introduction to Map Reduce Pipeline
  • Combiner and Partioner
  • YARN and Map Reducev2

Apache PIG

  • Introduction to Apache Pig
  • Map Reduce Vs Apache Pig
  • SQL Vs Apache Pig
  • Different datatypes in Pig

Modes Of Execution in Pig

  • Local Mode
  • Map Reduce

Execution Mechanism

  • Grunt Shell
  • Script
  • Transformations in Pig
  • How to write a simple pig script
  • UDFs in Pig


  • Hive Introduction
  • Difference between Pig and Hive
  • Difference between Hive and RDBMS
  • Hive Integration with Hadoop
  • Hive Query Language(Hive QL)
  • Internal and External Table
  • Partition and Bucketing
  • Tuning of Hive
  • Authentication in Hive
  • Authorization in Hive
  • Speculative execution in Hive
  • Hive UDF


  • Introduction to Sqoop.
  • MySQL client and Server Installation
  • How to connect to Relational Database using Sqoop
  • Different Sqoop Commands
  • Import (MySQL data import to HDFS)
  • Export


  • Flume Introduction
  • Different components of Flume
  • Twitter data collection using Flume


  • Introduction
  • Requirements of Cassandra
  • Cassandra Architecture
  • Write Operation
  • KeySpace and ColumnFamily
  • Storing and Reading data in Columnfamily
  • Datatypes in Cassandra
  • CQL and CLI Utility
  • CAP Theorem
  • Difference between HBase and Cassandra
  • Introduction to Splunk and Tableau
NOTE: Mock Interviews will be conducted on a one-to-one basis after the course duration. Real time project explanation. Interview Questions discussion

Best Hadoop Training institute in Bangalore

  • Trained over 2000 students
  • Over a Decade of experience in Training industry
  • Experienced and Certified trainers
  • Practical and Theory training
  • Flexible Batch timings

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