WHY ASPIRE ?

We are the Information Technology training division of Aspire Techsoft Pvt Ltd, an IT company founded in 2011.We are ranked among the software training institutes in the india. We are specialized in ERP, SAP, SAS, JAVA, Data Warehousing,Hadoop etc.

Kothrud Branch (Head Office)
  • Address: Malhar Building, Plot No 2, H. A. Colony,
    Paud Phata, Eardawana, Pune 38.
  • Phone:7058-198-728 / 7058-733-423
  • Email:info@aspireit.net
Dange Chowk Branch
  • Address: Office No 108, 1st Floor, ABC Nirman Complex,
    Opp Macdonald, 16 No Stop, Near Dange Chowk, Pimpri Chinchwad, Pune - 33.
  • Phone:8856-033-664
  • Email:aspiretech.erpsolution@gmail.com
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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

  • 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

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Kanchan Warghade

  • 2016-12-24

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

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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?

candidate_photo

Kanchan Warghade

  • 2016-12-24

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

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