Hadoop Training – Best Hadoop Training Institute in Chennai

If you are searching for the best Hadoop training in Chennai then you have come to the correct place, Upshot technologies in Chennai. Because, we are the Best training centre in teaching Hadoop in Chennai.

About Hadoop:

  Open source framework used to store, process and analyse Big Data.
  Big Data is nothing but a huge volume of data including structured and unstructured data.
  Created by Doug Cutting and Mike Cafarella in 2011 and released in 2012.
  Part of Apache project by Apache Software Foundation (ASF).
  Uses distributed and parallel computing to perform all its tasks successfully.
  Its distributed file system allows high data transfer rate and thus enabling faster and efficient processing.
  In recent years, Hadoop has emerged as one of the important pillars for Big Data analytics.


Upshot Technologies is the one of the premier training institutes in Bangalore with huge expertise and experience in teaching Hadoop. Due to our experience, we are now providing the best Hadoop training in Bangalore. Some of the benefits of joining the best training institute are given below:

  Specially designed considering the requirements of the IT industry.
  Extensive including Big Data, Data analytics and hosting on different clouds.
  Prepared by a team of Hadoop experts who prepare the study materials.
  Consists of two parts namely Theoretical basis (classroom) and Practical sessions.
  Includes many case studies and real-time projects.

  Working Professionals with superior skills and in-depth knowledge.
  Have extensive experience in Hadoop and are committers in ASF for Hadoop.
  Compassionate teachers who cares for the education and welfare of the students.
  Provides counselling and advices to our students whenever required.

  State-of-the-art computer lab with Hadoop being installed in all the systems.
  Smart classrooms with projectors and video-conferencing kits.
  Spacious and calm study halls and libraries for our students.
  Lab assistants are always available to support the students to practice.
  Free Wi-fi connectivity to help our students stay up-to-date.

Placement care
  100% placement guarantee for all successful students.
  A dedicated team to ensure that all of our students got a job after completing the course.
  Help to prepare an impressive Resume.
  Provide a lot of interview preparation study materials.
  Conduct mock tests and interviews to familiarize our students.

There are also other perks in choosing the Best Hadoop training institute such as

  Flexible batch timings to admit students, freshers and employed professionals.
  Affordable fees structure to help the as many students as possible.
  Access to a huge repository containing information about Hadoop.
  1-to-1 training and Corporate training can be arranged if informed earlier.

Hadoop Training Syllabus

Module 1 : Fundamental of Core Java

Module 2 : Fundamental of Basic SQL

Module 3: Introduction to BigData, Hadoop (HDFS and MapReduce) :
  BigData Introduction
  Hadoop Introduction
  HDFS Introduction
  MapReduce Introduction

Module 4 : Deep Dive in HDFS
  HDFS Design
  Fundamental of HDFS (Blocks, NameNode, DataNode, Secondary Name Node)
  Read/Write from HDFS
  HDFS Federation and High Availability
  Parallel Copying using DistCp
  HDFS Command Line Interface

Module 4A : HDFS File Operation Lifecycle (Supplementary)
  1. File Read Cycel from HDFS
– DistributedFileSystem
– FSDataInputStream
  2. Failure or Error Handling When File Reading Fails
  3. File Write Cycle from HDFS
– FSDataOutputStream
  4. Failure or Error Handling while File write fails

Module 5 : Understanding MapReduce :
  JobTracker and TaskTracker
  Topology Hadoop cluster
  Example of MapReduce
– Map Function
– Reduce Function
  Java Implementation of MapReduce
  DataFlow of MapReduce
  Use of Combiner

Module 6 : MapReduce Internals -1 (In Detail)
  How MapReduce Works
  Anatomy of MapReduce Job (MR-1)
  Submission & Initialization of MapReduce Job (What Happen ?)
  Assigning & Execution of Tasks
  Monitoring & Progress of MapReduce Job
  Completion of Job

Module 7 : Advanced MapReduce Algorithm
  File Based Data Structure
– Sequence File
– MapFile
  Default Sorting In MapReduce
– Data Filtering (Map-only jobs)
– Partial Sorting
  Data Lookup Stratgies
– In MapFiles
  Sorting Algorithm
– Total Sort (Globally Sorted Data)
– InputSampler
– Secondary Sort

Module 8 : Advanced MapReduce Algorithm -2
  MapReduce Joining
– Reduce Side Join
– MapSide Join
– Semi Join
  2. MapReduce Job Chaining
– MapReduce Sequence Chaining
– MapReduce Complex Chaining

Module 9 : Apache Pig
  What is Pig ?
  Introduction to Pig Data Flow Engine
  Pig and MapReduce in Detail
  When should Pig Used ?
  Pig and Hadoop Cluster
  Pig Interpreter and MapReduce
  Pig Relations and Data Types
  PigLatin Example in Detail
  Debugging and Generating Example in Apache Pig

Module 9A : Apache Pig Coding
  Working with Grunt shell
  Create word count application
  Execute word count application
  Accessing HDFS from grunt shell

Module 9B : Apache Pig Complex Datatypes
  Understand Map, Tuple and Bag
  Create Outer Bag and Inner Bag
  Defining Pig Schema

Module 9C : Apache Pig Data loading
  Understand Load statement
  Loading csv file
  Loading csv file with schema
  Loading Tab separated file
  Storing back data to HDFS.

Module 9D : Apache Pig Statements

  ForEach statement
  Example 1 : Data projecting and foreach statement
  Example 2 : Projection using schema
  Example 3 : Another way of selecting columns using two dots ..

Module 9E : Apache Pig Complex Datatype practice
  Example 1 : Loading Complex Datatypes
  Example 2 : Loading compressed files
  Example 3 : Store relation as compressed files
  Example 4 : Nested FOREACH statements to solved same problem.

Module 10 : Fundamental of Apache Hive Part-1
  What is Hive ?
  Architecture of Hive
  Hive Services
  Hive Clients
  how Hive Differs from Traditional RDBMS
  Introduction to HiveQL
  Data Types and File Formats in Hive
  File Encoding
  Common problems while working with Hive

Module 10A : Apache Hive
  Managed and External Tables
  Understand Storage Formats
  Querying Data
– Sorting and Aggregation
– MapReduce In Query
– Joins, SubQueries and Views
  5. Writing User Defined Functions (UDFs)
  6. Data types and schemas
  7. Querying Data
  8. HiveODBC
  9. User-Defined Functions

Module 11 : Step by Step Process creating and Configuring eclipse for writing MapReduce
Module 12 : NOSQL Introduction and Implementation
  What is NoSQL ?
  NoSQL Characterise or Common Traits
  Categories of NoSQL DataBases
– Key-Value Database
– Document DataBase
– Column Family DataBase
– Graph DataBase
  4. Aggregate Orientation : Perfect fit for NoSQl
  5. NOSQL Implementation
  6. Key-Value Database Example and Use
  7. Document DataBase Example and Use
  8. Column Family DataBase Example and Use
  9. What is Polyglot persistence ?

Module 12A : HBase Introduction
  Fundamentals of HBase
  Usage Scenerio of HBase
  Use of HBase in Search Engine
  HBase DataModel
– Table and Row
– Column Family and Column Qualifier
– Cell and its Versioning
– Regions and Region Server
  5. HBase Designing Tables
  6. HBase Data Coordinates
  7. Versions and HBase Operation
– Get/Scan
– Put
– Delete

Module 13 : Apache Sqoop (SQL To Hadoop)
  Sqoop Tutorial
  How does Sqoop Work
  Sqoop JDBCDriver and Connectors
  Sqoop Importing Data
  Various Options to Import Data
– Table Import
– Binary Data Import
– SpeedUp the Import
– Filtering Import
– Full DataBase Import Introduction to Sqoop

Module 14 : Apache Flume
  Data Acquisition : Apache Flume Introduction
  Apache Flume Components
  POSIX and HDFS File Write
  Flume Events
  Interceptors, Channel Selectors, Sink Processor

Module 14A : Advanced Apache Flume
  Sample Twiteer Feed Configuration
  Flume Channel
– Memory Channel
– File Channel
  3. Sinks and Sink Processors
  4. Sources
  5. Channel Selectors
  6. Interceptors

Module 15 : Apache Spark : Introduction to Apache Spark
  Introduction to Apache Spark
  Features of Apache Spark
  Apache Spark Stack
  Introduction to RDD’s
  RDD’s Transformation
  What is Good and Bad In MapReduce
  Why to use Apache Spark

Module 16 : Load data in HDFS using the HDFS commands

Module 17 : Importing Data from RDBMS to HDFS
  Without Specifying Directory
  With target Directory
  With warehouse directory

Module 18 : Sqoop Import & Export Module
  Importing Subset of data from RDBMS
  Changing the delimiter during Import
  Encoding Null values
  Importing Entire schema or all tables


Hadoop is an open source framework developed by a non-profit corporation (ASF). So, it has no official certification available but there are some other private Certifications available right now. These are accepted by lot of companies. For example, CCA Spark and Hadoop Developer Certification by Cloudera Inc. and HDP Certified Developer and HDP Certified Java Developer Certifications by Hortonworks. Our Hadoop training covers the basics of all these exams and you can easily clear the certification exams with the knowledge you learned and the guidance of our placement cell. But you won’t need these certifications to get a job because you would be placed as soon as you had successfully completed our Hadoop training.

After the completion of our Hadoop training, you will have numerous job opportunities from all over the world. Some of the designations you will be recruited for, are listed below:

  Hadoop Developer
  Technical Consultant – Hadoop
  Software Development Engineer – Hadoop
  BigData Hadoop Consultant

Apart from these, there are other career options such as promotions, switching job to a MNC and even teaching Hadoop at institutes or online platforms based on your availability.

            Best IT training institute in Chennai with Placement

“You don’t have to believe our words that name Upshot technologies as the Best IT training institute in Chennai but you have to believe the words of our students which are spoken from the experience they had from our training.  ”


We are glad that you preferred to contact us. Please fill our short form and one of our friendly team members will contact you back.


Quick Enquiry