Tryst-2017 IIT Delhi

Big Data and Hadoop Workshop

 

Eager to learn Big Data and Hadoop just in 1 Day!!!

We have come with Workshop based on Big Data and Hadoop.

For Assistance Call

Ratika +91-9990203445
Anupama +91-8744059531
Ankit Kumar Jain +91-7065174555
Vivek Kumar Singh +91-8744059520
  • Big Data and Hadoop workshop
  • Big Data and Hadoop training

Course Description

OVERVIEW

Big data means really a big data, it is a collection of large datasets that cannot be processed using traditional computing techniques. Big data is not merely a data, rather it has become a complete subject, which involves various tools, technqiues and frameworks.
Big data technologies are important in providing more accurate analysis, which may lead to more concrete decision-making resulting in greater operational efficiencies, cost reductions, and reduced risks for the business.

The duration of this workshop will be 1 day, with Ten hours session , properly divided into theory and hand on practical sessions.Certificate of participation will be provided by RoboTryst 2017 in association with Tryst IIT Delhi.


Best Suited for : All B.Tech/B.E./BCA/BSc Students

Day 1 (Session 1)

Big-Data and Hadoop
  • Introduction to big data and Hadoop
  • Hadoop Architecture
  • Installing Hadoop
  • Single Node Hadoop installation
  • Multi Node Hadoop installation
  • Linux commands and Hadoop commands
  • Cluster architecture and block placement
  • Modes in Hadoop
    • Local Mode
    • Pseudo Distributed Mode
    • Fully Distributed Mode
  • Hadoop Daemon
    • Master Daemons(Name Node, Secondary Name Node, Job Tracker)
    • Slave Daemons(Job tracker, Task tracker)
  • Task Instance
  • Hadoop HDFS Commands
  • Modes in Hadoop
    • Accessing HDFS
    • CLI Approach
    • Java Approach
Map-Reduce
  • Understanding Map Reduce Framework
  • Inspiration to Word-Count Example
  • Developing Map-Reduce Program using Eclipse Luna
  • HDFS Read-Write Process
  • Map-Reduce Life Cycle Method
  • Serialization(Java)
  • Datatypes
  • Comparator and Comparable(Java)
  • Custom Output File
  • Analysing Temperature dataset using Map-Reduce
  • Custom Partitioner & Combiner
  • Running Map-Reduce in Local and Pseudo Distributed Mode

Day 1 (Session 2)

Advanced Map-Reduce
  • Enum(Java)
  • Custom and Dynamic Counters
  • Running Map-Reduce in Multi-node Hadoop Cluster
  • Custom Writable
  • Site Data Distribution
    • Using Configuration
    • Using DistributedCache
    • Using stringifie
  • Input Formatters
    • NLine Input Formatter
    • XML Input Formatter
  • Sorting
    • Primary Reverse Sorting
    • Secondary Sorting
  • Compression Technique
  • Working with Sequence File Format
  • Working with AVRO File Format
  • Testing MapReduce with MR Unit
HIVE
  • Hive Introduction & Installation
  • Data Types in Hive
  • Commands in Hive
  • Exploring Internal and External Table
  • Partitions
  • Complex data types
  • UDF in Hive
    • Built-in UDF
    • Custom UDF
  • Thrift Server
  • Java to Hive Connection
  • Joins in Hive
  • Working with HWI
  • Bucket Map-side Join
SQOOP
  • Sqoop Installations and Basics
  • Importing Data from Oracle to HDFS
  • Advance Imports
  • Real Time UseCase
  • Exporting Data from HDFS to Oracle
  • Running Sqoop in Cloudera

Day 1 (Session 3)

PIG
  • Installation and Introduction
  • WordCount in Pig
  • NYSE in Pig
  • Working With Complex Datatypes
  • Pig Schema
  • Misc Commands
HBase
  • HBase Introduction & Installation
  • Exploring HBase Shell
  • HBase Storage Techinique
  • HBasing with Java
  • CRUD with HBase
  • Hive HBase Integration
OOZIE
  • Installing Oozie
  • Running Map-Reduce with Oozie
  • Running Pig and Sqoop with Oozie

Project to be Covered Coming Soon

Photo Gallery

Video Gallery

required Tools and accessories etc

Overview

OVERVIEW

Big data means really a big data, it is a collection of large datasets that cannot be processed using traditional computing techniques. Big data is not merely a data, rather it has become a complete subject, which involves various tools, technqiues and frameworks.
Big data technologies are important in providing more accurate analysis, which may lead to more concrete decision-making resulting in greater operational efficiencies, cost reductions, and reduced risks for the business.

The duration of this workshop will be 1 day, with Ten hours session , properly divided into theory and hand on practical sessions.Certificate of participation will be provided by RoboTryst 2017 in association with Tryst IIT Delhi.


Best Suited for : All B.Tech/B.E./BCA/BSc Students

Course

Day 1 (Session 1)

Big-Data and Hadoop
  • Introduction to big data and Hadoop
  • Hadoop Architecture
  • Installing Hadoop
  • Single Node Hadoop installation
  • Multi Node Hadoop installation
  • Linux commands and Hadoop commands
  • Cluster architecture and block placement
  • Modes in Hadoop
    • Local Mode
    • Pseudo Distributed Mode
    • Fully Distributed Mode
  • Hadoop Daemon
    • Master Daemons(Name Node, Secondary Name Node, Job Tracker)
    • Slave Daemons(Job tracker, Task tracker)
  • Task Instance
  • Hadoop HDFS Commands
  • Modes in Hadoop
    • Accessing HDFS
    • CLI Approach
    • Java Approach
Map-Reduce
  • Understanding Map Reduce Framework
  • Inspiration to Word-Count Example
  • Developing Map-Reduce Program using Eclipse Luna
  • HDFS Read-Write Process
  • Map-Reduce Life Cycle Method
  • Serialization(Java)
  • Datatypes
  • Comparator and Comparable(Java)
  • Custom Output File
  • Analysing Temperature dataset using Map-Reduce
  • Custom Partitioner & Combiner
  • Running Map-Reduce in Local and Pseudo Distributed Mode

Day 1 (Session 2)

Advanced Map-Reduce
  • Enum(Java)
  • Custom and Dynamic Counters
  • Running Map-Reduce in Multi-node Hadoop Cluster
  • Custom Writable
  • Site Data Distribution
    • Using Configuration
    • Using DistributedCache
    • Using stringifie
  • Input Formatters
    • NLine Input Formatter
    • XML Input Formatter
  • Sorting
    • Primary Reverse Sorting
    • Secondary Sorting
  • Compression Technique
  • Working with Sequence File Format
  • Working with AVRO File Format
  • Testing MapReduce with MR Unit
HIVE
  • Hive Introduction & Installation
  • Data Types in Hive
  • Commands in Hive
  • Exploring Internal and External Table
  • Partitions
  • Complex data types
  • UDF in Hive
    • Built-in UDF
    • Custom UDF
  • Thrift Server
  • Java to Hive Connection
  • Joins in Hive
  • Working with HWI
  • Bucket Map-side Join
SQOOP
  • Sqoop Installations and Basics
  • Importing Data from Oracle to HDFS
  • Advance Imports
  • Real Time UseCase
  • Exporting Data from HDFS to Oracle
  • Running Sqoop in Cloudera

Day 1 (Session 3)

PIG
  • Installation and Introduction
  • WordCount in Pig
  • NYSE in Pig
  • Working With Complex Datatypes
  • Pig Schema
  • Misc Commands
HBase
  • HBase Introduction & Installation
  • Exploring HBase Shell
  • HBase Storage Techinique
  • HBasing with Java
  • CRUD with HBase
  • Hive HBase Integration
OOZIE
  • Installing Oozie
  • Running Map-Reduce with Oozie
  • Running Pig and Sqoop with Oozie

Project

Project to be Covered Coming Soon

Kit

required Tools and accessories etc

Video Gallery

Video Gallery

Coming soon...