Hadoop Development


INTRODUCTION

Hadoop may be a distributed computing system that works on commodity hardware on a scale and speed that's simply impractical for alternative database processing systems to match. due to this there's a large demand for Hadoop Developers who will deploy Hadoop on a massive scale. This Hadoop Developer training equips you with the proper skill sets required to take the skilled Hadoop Developer. This Hadoop Developer coaching can assist you to get a detailed plan concerning big data and Hadoop. A number of the topics enclosed are an introduction to the Hadoop ecosystem, understanding of HDFS and MapReduce as well as MapReduce abstraction. Learn to put in, implement numerous components of Hadoop like Pig, Hive Etc.

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Syllabus

Our syllabus for Hadoop Development.

  • 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.


  • Experts Panel

    Learn with the experts in the field.

    Faculty, Hadoop-Admin
    Experience: 3 Year(s).

    Arshad

    Arshad Is Working As Hadoop Consultant In An MNC Since Last 4 Years. In His Career, He Worked On Lots Of Projects And Have A Great Set Of Skills. Student Trained By Him Already Got Placed In An MNC.

    Faculty, Hadoop-Admin
    Experience: 5 Year(s).

    Prajyot

    Over 5+ Years Hadoop Trainer Is Highly Skilled And Diligent Hadoop Consultant With An Excellent Work Ethic And Client Satisfaction Record. He Is Currently Working In An MNC Company. He is very keen in this area.

    Faculty, Hadoop-Admin
    Experience: 8 Year(s).

    Pravin P

    Our Hadoop Trainer Is Certified. He Is A Sturdy Supervisor Of Enormous And Little-Skilled Code Engineering Groups Politely And Expertise. He Is Currently Working In An MNC And Has A Great Set Of Skills.


    Student Reviews

    See what student says about this course.



    Ashwini Kamble

    Big data is the future, every Java programmer should do this course and must be aware of big data.

    Javed Nadaf

    The training given during course was exceptional, thanks to Aspire Techsoft for bringing this course online also.

    Vinod Kale

    I recommended this online course to my friends as no one provide such great quality education at this affordable price.


    Schedule & Batches

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