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Course Overview:

Companies around the world today find it increasingly difficult to organize and manage large vol

Bigdata and Hadoop (2.0) Development Training in Pune


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About The Event

3 Day Workshop:



Course Overview:


Companies around the world today find it increasingly difficult to organize and manage large volumes of data. Hadoop has emerged as the most efficient data platform for companies working with big data, and is an integral part of storing, handling and retrieving enormous amounts of data in a variety of applications. Hadoop helps to run deep analytics which cannot be effectively handled by a database engine.

Big enterprises around the world have found Hadoop to be a game changer in their Big Data management, and as more companies embrace this powerful technology the demand for Hadoop Developers is also growing. By learning how to harness the power of Hadoop 2.0 to manipulate, analyse and perform computations on Big Data, you will be paving the way for an enriching and financially rewarding career as an expert Hadoop developer.

Our three day course in Hadoop 2.0 Developer training will teach you the technical aspects of Apache Hadoop, and you will obtain a deeper understanding of the power of Hadoop. Our experienced trainers will handhold you through the development of applications and analyses of Big Data, and you will be able to comprehend the key concepts required to create robust big data processing applications. Successful candidates will earn the credential of Hadoop Professional, and will be capable of handling and analysing Terabyte scale of data successfully using MapReduce.


Course Agenda:



Phase 1: Hadoop 2.0 Fundamentals (12 Hours)

Big Data

  • What is Big Data
  • Dimensions of Big Data
  • Big Data in Advertising
  • Big Data in Banking
  • Big Data in Telecom
  • Big Data in eCommerce
  • Big Data in Healthcare
  • Big Data in Defense
  • Processing options of Big Data
  • Hadoop as an option


  • What is Hadoop
  • How Hadoop 1.0 Works
  • How Hadoop 2.0 Works
  • HDFS
  • MapReduce
  • What is YARN
  • How YARN Works
  • Advantages of YARN
  • How Hadoop has an edge

Hadoop Ecosystem

  • Sqoop
  • Oozie
  • Pig
  • Hive
  • Flume

Hadoop Hands On

  • Running HDFS commands
  • Running your MapReduce program on Hadoop 1.0
  • Running your MapReduce Program on Hadoop 2.0
  • Running Sqoop Import and Sqoop Export
  • Creating Hive tables directly from Sqoop
  • Creating Hive tables
  • Querying Hive tables

Evaluation Test
Setting up Hadoop 1.0 on a single node cluster manual
Setting up Hadoop 2.0 on a single node setup manual
Multinode setup walkthrough manual

Phase 2: Hadoop Development (8 hours)

Advanced MapReduce

  • MapReduce Code Walkthrough
  • ToolRunner
  • MR Unit
  • Distributed Cache
  • Combiner
  • Partitioner
  • Setup and Cleanup methods
  • Using Java API to access HDFS

Joins Using MapReduce

  • Map Side joins
  • Reduce side joins

Custom Types

  • Input Types in MapReduce
  • Output Types in MapReduce
  • Custom Input Data types
  • Custom Output Data types
  • Multiple Reducer MR program
  • Zero Reducer Mapper Program

Advanced MapReduce Hands On

  • MR Unit hands on
  • Distributed Cache hands on
  • Partitioner hands on
  • Combiner hands on
  • Accessing files using HDFS API hands on
  • Map Side joins hands on
  • Reduce side joins hands on

MapReduce Design Patterns :

  • Searching
  • Sorting
  • Filtering
  • Inverted Index
  • TF-IDF
  • Word Co-occurrence

MapReduce Design Patterns Hands On :

  • Distributed Grep
  • Bloom Filters
  • Average Calculation
  • Standard Deviation
  • MapSide joins
  • Reduce Side joins

Evaluation Test (30 marks)

Phase 3: Other Hadoop Development Aspects- Pig, Hive, Oozie and Impala (8 hours)


  • What is Pig
  • How Pig Works
  • Simple processing using Pig
  • Advanced Processing Using Pig
  • Pig Hands On


  • What is Hive
  • How Hive Works
  • Simple processing using Hive
  • Advanced processing using Hive
  • Hive Hands on


  • What is Oozie
  • How Oozie Works
  • Oozie Hands on


  • What is Impala
  • How Impala Works
  • Where Impala is better than Hive
  • Impala's shortcomings
  • Impala Hands on

Evaluation Test





From the course :

  • Understand Big Data and the various types of data stored in Hadoop
  • Understand the fundamentals of MapReduce, Hadoop Distributed File System (HDFS), YARN, and how to write MapReduce code
  • Learn best practices and considerations for Hadoop development, debugging techniques and implementation of workflows and common algorithms
  • Learn how to leverage Hadoop frameworks like ApachePig™, ApacheHive™, Sqoop, Flume, Oozie and other projects from the Apache Hadoop Ecosystem
  • Understand optimal hardware configurations and network considerations for building out, maintaining and monitoring your Hadoop cluster
  • Learn advanced Hadoop API topics required for real-world data analysis
  • Understand the path to ROI with Hadoop

From the workshop :

  • High quality training from an industry expert
  • 3 Days of hands-on experience and practical exercises
  • Earn 24 PDUs
  • Hard copy of courseware
  • 50% interactive and hands-on training exercises using HDFS, Pig, Hive, HBase, key MapReduce components and features, and more




Venue for Pune - 26th - 28th Feb 2015

The Coronet Hotel
1205 / 4, Apte Road , Deccan Gymkhana,
Opposite Santosh Bakery
Pune 411004.

Timing: 9:00AM to 6:00PM

Venue Map