Hadoop Development Course

Hadoop Development Course

  • Introduction to big data and Hadoop
  • Hadoop Distributed File System Architecture
  • Installing Ubuntu with Java 1.8 on VM Workstation 11
  • Hadoop Versioning and Configuration
  • Single Node Hadoop 1.2.1 installation on Ubuntu 14.4.1
  • Multi Node Hadoop 1.2.1 installation on Ubuntu 14.4.1
  • Linux commands and Hadoop commands
  • Cluster architecture and block placement
  • Modes in Hadoop
  • 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

  • Accessing HDFS
  • CLI Approach

  • Java Approach

  • 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)
  • HEADLINE
  • Data types
  • Comparator and Comparable (Java)
  • Custom Output File
  • Analyzing Temperature dataset using Map-Reduce
  • Custom Practitioner & Combiner
  • Running Map-Reduce in Local and Pseudo Distributed Mode
  • Enum (Java)
  • Custom and Dynamic Counters
  • Running Map-Reduce in Multi-node Hadoop Cluster
  • Custom Writable
  • Site Data Distribution
  • Using Configuration
  • Using Distributed Cache
  • 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 Map Reduce with MR Unit
  • Working with NYSE Datasets
  • Working with Million Song Datasets
  • Working with Million Song Datasets
  • Hive Introduction & Installation

  • Data Types in Hive

  • Commands in Hive

  • Exploring Internal and External Table

  • Partitions

  • Complex data types

  • UDF in Hive 4.7.1. Built-in UDF 4.7.2. Custom UDF

    Thrift Server

  • Java to Hive Connection

  • Joins in Hive

  • Working with HWI

  • Bucket Map-side Join

  • More commands

  • View

  • Sort By

  • Distribute By

  • Lateral View

  • Sqoop Installations and Basics

  • Advance Imports

  • Real Time Use Case

  • Exporting Data from HDFS to Oracle

  • Running Sqoop in Cloud era

  • PIG

  • Installation and Introduction

  • Word Count in Pig

  • NYSE in Pig

  • Working With Complex Datatypes

  • Pig Schema

  • Miscellaneous Command

  • Group

  • Filter

  • Order

  • Distinct

  • Join

  • Flatten

  • Co-group

  • Union

  • Illustrate

  • Explain

  • UDFs in Pig

  • Parameter Substitution and Dry Run

  • Pig Macros

  • Running Pig in Cloud era

  • HBase Introduction & Installation

  • Exploring HBase Shell

  • HBase Storage Technique

  • HBasing with Java

  • CRUD with HBase

  • Hive HBase Integration

  • Installing Oozie

  • Running Map-Reduce with Oozie

  • Running Pig and Sqoop with Oozie


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Benefits of Aspire Techsoft training

  • ASAP methodology

  • 24 HOURS LAB

  • MATERIAL SOFT COPY& HARD COPY

  • 100% PLACEMENT ASSISTANCE

  • RESUME PREPARATION

  • SOFT SKILLS& HR TIPS

  • PERSONALITY DEVELOPMENT

  • MOCK INTERVIEWS

Reviews

  • Kanchan Warghade

    2016-12-24

    Training is good for Big Data.Faculty is also good.More focus is on practicals.

    • raj patil

      2016-12-24

      I would like to thanks to Aspire Hadoop development training.I got good training. tutor was very good, Thanks to Aspire. Helpful?

      • Kanchan Warghade

        2016-12-24

        Training is good for Big Data.Faculty is also good.More focus is on practicals.

      Your Rating :

53618 Students applied

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  • John Doe

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