Hadoop Jump Start

This course provides a well grounded introduction to Hadoop and its building blocks – HDFS, Map/Reduce, Pig, Hive, HBase, Sqoop and Flume. Anyone with a basic understanding of programming and databases (SQL) can benefit from this course. Prior knowledge of Java is not essential, although it is useful. As part of lab work, students build their own development cluster and implement a wide range of technical use cases.

The environment can be used for further learning and experimentation after the course as well. Students should be able to perform basic tasks on a Hadoop project, based upon their prior background and experience.

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​Highlights of Blockchain Certification Training

  • 32 Hours of top quality Instructor-led training(16 hours theory and 16 hours of lab work)
  • 25+ years experienced Instructor
  • 100+ Hadoop workshops completed
  • 2000+ professionals trained
  • 20+ hand-on exercises, culled from real-world examples
  • Set up own cluster as well as work on a production-grade 7-node cluster.
  • Ideal groundwork for professionals aiming for Hadoop certifications
  • Course covers 50 top interview questions and one practical exam.

Who Should Attend

  • Senior Managers, Managers and Team Leaders tasked with the responsibility of Big Data data analytics
  • Professionals who intend to seriously consider Data Analytics as their career option
  • Project Managers who would like to bid for Data Analytics projects and lead the delivery teams
  • IT administrators likely to be tasked with the responsibility of Hadoop installation and maintenance.
  • Marketing and Sales professionals who would like to understand what Big Data, Data Analytics and Machine Learning is all about – and package such offerings

Exercises

  • Setting up a multi-node Apache Hadoop cluster from scratch
  • Performing file I/O using HDFS
  • Implementing an end-to-end data pipeline with Hive
  • Creating User Defined Functions in Hive
  • Working with HBase Shell and loading data from Hive
  • Ingesting sensor data and log files using Flume
  • Import/Export data from various RDBMS’s using Sqoop

Training Benefits

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BENEFITS FOR INDIVIDUALS

  • Get a good grip on Big Data and Data Analytics
  • Gain the ability to identify and classify data analysis problems – and identify solutions
  • Hands-on introduction to Hadoop Software – and their applications
  • Apply the acquired concepts to practical situations – such as Business Data Analysis – to support decision making
  • Get a practical introduction to the Hadoop eco-system components.
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BENEFITS FOR ORGANIZATIONS

  • Build a team with a view to harness availability of data for business growth
  • Offer data oriented products and services
  • Create experts who can further spread their learning into the organisation

Curriculum

Day 1
    • Introduction to Big Data Analytics
      • What is Big Data? – The 3V Paradigm
      • Limitations of Conventional Technologies
      • Essentials of Distributed Computing
      • Introduction to Hadoop & Its Ecosystem
      • Hadoop Distributed File System (HDFS)
    • HDFS Architecture
      • Anatomy of file Read / Write
      • Fault Tolerance in HDFS
      • Setting Up a Hadoop Cluster
    • Setting Up a Hadoop Cluster
      • Exercise : Installing & Configuring Hadoop 2.7.1 Cluster
      • Exercise : Working with HDFS through Shell & Web UI
Day 2
  • Map / Reduce
    • Map Reduce Concepts
    • Map Reduce Job Execution LifeCycle
    • Exercise : Running a Map/ Reduce Job – Word Count
    • Example Map/Reduce API Overview
    • Exercise : Using EcListItempse to build Map/Reduce AppListItemcations
    • Exercise : Deploying Map/Reduce Jobs on Cluster
    • Advanced Map/Reduce Examples
Day 3
  • Pig
    • Pig Introduction & Basic Concepts
    • Pig / Latin Language Overview
    • Exercises : Analyzing Stock Market Data using Pig/Latin
    • Exercises : Working With Complex Data Types
    • Hive Basics & Architecture
    • Hive Query Language . Exercise – Working with Hive
    • Exercise: Analyzing weather data using Hive QL
Day 4

  • Advanced Hive

    • Hive Formats & SerDes

    • Exercise: Working with ORC, XML & RegEx SerDes

    • Exercise: Optimizing Hive Queries using Partitions & Clusters

    • Overview of Hive Functions

    • Exercise : Creating User Defined functions(UDF)

    • Introduction to Hbase

  • Need for Low Latency Queries

    • Introduction to Hbase & NoSQL

    • Database

  • Hbase Data Model & Architecture

    • Exercise : Working with Hbase Shell

    • Role of Zookeeper

Day 5

  • Sqoop

    • Using Sqoop to Extract data from MySQL

    • Exercises: Loading Data in HDFS, Hive & Hbase in Various formats

    • Flume

  • Flume Architecture & Data Model

    • Configuring Flume Agents to build custom data flows

    • Exercise: Ingesting Sensor Data into HDFS

    • Exercise: Aggregating Weblogs into HDFS

    • Building An End to End Hadoop AppListItemcation

  • Exercise: Running HQL Queries through a JDBC Client

    • Exercise: Reading and Writing to Hbase

    • Exercise: HiveBase Integration

    • Exercise: Displaying the results on a Dashboard

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