Bigdata Training

by Dev Technology Claim Listing

Every company, every organization and every team has to process large amounts of data. Analysis and structuring can take a lot of time and hamper the progress of work.Hadoop or Big Data is a tool by Apache which helps structure this data and bring it into a format which can be analyzed easily.

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Every company, every organization and every team has to process large amounts of data. Analysis and structuring can take a lot of time and hamper the progress of work.Hadoop or Big Data is a tool by Apache which helps structure this data and bring it into a format which can be analyzed easily.

This can be a really good way for developers to increase their salary rate and for freshers to find better job opportunities.

We provide one of the most sophisticated training for Hadoop (Big Data) in Chennai. Our real time implementation classes combined with our fun learning experience methods provide an environment where students can practice the knowledge they receive.

 

Bigdata Training Syllabus:

  • Overview of Big Data & Hadoop
  • What is High Availability
  • Introduction to Big data
  • Introduction to What is Hadoop
  • Discuss about Storage & Processing Challenges
  • Explain about Bigdata technologies(Hadoop & Database)
  • Introduction to Hadoop
  • Architecture of Hadoop
  • Setup a production cluster in Hadoop
  • Discuss about various shell commands
  • Configuration of files in Hadoop
  • Installation of single node cluster
  • Overview of Spark, Scala, Sqoop, Pig and Flume
  • Hadoop Distributed File System (HDFS)
  • Introduction to HDFS Design
  • Architecture of HDFS & Components
  • Discuss about High Availability Cluster
  • Difference between Normal File System & HDFS
  • Configuration of Command-Line Interface in HDFS
  • Working with Common HDFS Commands
  • Configuration of Block size and design Principles
  • Explain about Name nodes and Data nodes
  • Map Reduce Programming
  • Introduction to Map Reduce Programming Basics
  • Discuss about Map & Reduce
  • Map Reduce Life Cycle
  • Working with Map Reduce Job Run
  • Explain about Job Submission & Initialization, Task Assignment & Execution and Status
  • Discuss about Shuffling and Sorting using Map Reduce
  • HDFS data load from RDBMS
  • Discuss about YARN (Resource Manager, Application Master and Node Manager)
  • Explain about Splits, Record reader, Partition and types
  • Working with Input Split & Driver code
  • Discuss about Text lnput Format, DB Input Format & Sequence File Input Format
  • Explain about Map & Reduce Side Join
  • Overview of Distributed cache
  • NOSQL & HBase
  • NoSQL Introduction
  • Explain about NoSQL concepts
  • Overview & Architecture of HBase
  • Installation of HBase
  • Working with DDL and DML HBase Operations
  • Discuss about Catalog Tables & Block Cache
  • Explain about SPLITS
  • HBase Scans & HBase Filters
  • Hive & Pig
  • Installation of Hive & Pig
  • Architecture of HIVE
  • Explain about HIVE query language (HIVE QL)
  • Configuration of HIVE with MySQL
  • Meta store & Data slicing mechanism in HIVE
  • Collection Data types(Array, Struct & Map) in HIVE
  • Discuss about Hive serializer or Deserializer
  • Installation of Pig
  • Discuss about Pig data types
  • Working with Tuple schema, BAG Schema and MAP Schema
  • Pig Filtering, Grouping and Joining
  • Pig Validations and Type casting
  • Working with Pig User Defined Functions
  • Write a simple pig script
  • And more.
  • Salem Branch

    No:T4, RBT Mall, First Floor, Meyyanur Bypass Road, Salem

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