Big Data & Hadoop Training in Chennai

Big Data & Hadoop Training in Chennai
Big Data & Hadoop Training in Chennai

Big Data & Hadoop Training in Chennai – Student Testimonial

I learnt the Big Data Hadoop course from Web D School recently & I must say that the teaching was much greater than my expectation.

Keerthi Rajesh ( Big Data & Hadoop Course )

Big Data & Hadoop Course Details

Data is the most important component of any business success in today’s digital world & learning the Big data & Hadoop course from a reputed training institute like Web D School would ensure a wonderful career for you.

Few things about us that you should know

The WEB D ADVANTAGE

Unlimited Lab Hours - No restrictions on lab hours as we allow you to practice for long hours on all 7 days in a week.

eBooks / Library Videos - Exclusive reference material for our students (only for select courses).

Student Assessment - We conduct regular assessment of Students works to understand their progress. Check our student works here to know our training standards.

Exclusive Job Portal - We have our own job portal, where the students can see all the current openings from different companies before applying for the suitable jobs. Check our job portal here.

Dedicated Placement Cell - It takes care of everything related to placement like Creating a good resume, Sharing interview tips, Conducting mock-up interviews, Scheduling interviews etc. Check our placement record here.

Saturday events - We conduct a seminar / contest / workshop every Saturday to increase the all-round knowledge of our students. Check our recent events here.

Portfolio Development - An excellent final project helps in securing a good job, & we provide our fullest support to the students in developing a fine portfolio.

Excellent Experience - We strive for excellence in everything we do & want all our students to have a delightful experience studying with us. Check their experience at Web D School here.


Big Data & Hadoop Course Module

  • Introduction to Big Data and Hadoop
  • Hadoop Architecture
  • Hadoop Ecosystem
  • Cluster Architecture and block placement
  • Common Hadoop shell commands
  • Modes in Hadoop
  • Hadoop Daemon
  • Task Instance
  • Hadoop HDFS Commands
  • Hadoop Storage
  • Accessing HDFS - CLI Approach & Java Approach
  • Hadoop Processing
  • MapReduce Framework
  • Hadoop Different distributions
  • Traditional way vs Map - Reduce way
  • Hadoop 2.x MapReduce Architecture
  • Hadoop 2.x MapReduce Components
  • YARN MR Application Execution Flow
  • YARN Workflow
  • Inspiration to Word-Count Example
  • Developing Map - Reduce Program using Eclipse Luna
  • HDFS Read - Write Process
  • Map-Reduce Life Cycle Method
  • Serialization (Java)
  • Datatypes
  • Custom Output File
  • Analysing Temperature data set using Map - Reduce
  • Custom Partitioner & Combiner
  • Custom and Dynamic Counters
  • Running Map - Reduce in Multi-node Hadoop Cluster
  • Custom Writable
  • Site Data Distribution
  • Input Formatters
  • Sorting
  • Compression Technique
  • Working with Sequence File Format
  • Working with AVRO File Format
  • Testing Map - Reduce with MR Unit
  • Xml file Parsing using Map - Reduce
  • Installation and Introduction
  • Map-reduce vs Pig
  • WordCount in Pig
  • Programming structure
  • Pig running modes
  • Pig components
  • Pig execution
  • Working With Complex Datatypes
  • Pig Schema
  • Miscellaneous Command
  • Group
  • Built in functions
  • Parameter Substitution
  • Pig streaming

  • Pig Macros
  • Testing pigscripts
  • Hive Introduction & Installation
  • Hive vs Pig
  • Hive architecture & components
  • Data Types in Hive
  • Commands in Hive
  • Exploring Internal and External Table
  • Partitions
  • Complex data types
  • Importing & Querying data
  • UDF in Hive
  • Thrift Server
  • Java to Hive Connection
  • Joins in Hive
  • Working with HWI
  • Bucket Map-side Join
  • Managing outputs
  • HBase Introduction & Installation
  • Custom Map-Reduce scripts
  • Exploring HBase Shell
  • HBase vs RDBMS
  • HBase components
  • HBase Storage Technique
  • HBasing with Java
  • CRUD with HBase
  • HBase cluster deployment
  • Hive HBase Integration
  • What is Apache Spark
  • Spark Ecosystem
  • Spark Components
  • History of Spark and Spark Versions/Releases
  • Spark a Polyglot
  • What is Scala?
  • Why Scala?
  • SparkContext
  • RDD
  • Flume and Sqoop Demo
  • Installing Oozie
  • Oozie Components & Workflow
  • Scheduling with Oozie
  • Oozie Co-ordinator
  • Oozie Commands
  • Oozie Web Console
  • Oozie for MapReduce
  • Combine flow of MR, PIG, Hive in Oozie
  • Hadoop Project Demo
  • Duration: 2 Months

So, if you have decided to pursue a Big Data Hadoop Course in Chennai, then Web D School, with its excellent track record, could be an ideal choice.

Please call us at 9791333350 to get more details about our Hadoop Training Course


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