Microtech Consultancy & Training Institute | Hadoop

Hadoop

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Hadoop

There is lots of Data that keeps flooding from varied social network sites, public information sites , Internet Archives etc .To manage such large amounts of information we've got Big Data. Hadoop is that the backbone for Big Data. Hadoop may be a set of programs and procedures used extensively after we find out about Big Data. It helps in distributed storage and process of information of huge Data of the Big Data. Understanding Hadoop may be a extremely valuable skill for anyone working with giant amounts of Data.It is a programming model that involves large scale process of information inside affordable time framework.

At Microtech Training, we offer a detailed understanding of the concepts of Hadoop and practical usage of the technology. The coaching starts with introduction of the scope of Hadoop and understanding the eventualities within which it will be applied. continuing more , the coaching focuses on learning the Pillars of Hadoop that is Hadoop Distributed file system and Mapreduce. The remaining a part of the training program consists of learning the various concept that build the Hadoop system like PIG,HBASE,SQOOP,NOSQL, HIVE, FLUME.

Course Objective

    What is Big Data

    What is Hadoop

    Why Hadoop and its use cases

    Different Componets of Hadoop

    Significance of HDFS in Hadoop

    Features of HDFS

    Name Node and its functionality

    Data Node and its functionality

    Job Tracker and its functionality

    Task Track and its functionality

    Secondary Name Node and its functionality.

    Introduction about Blocks

    Data Replication

    CLI (Command Line Interface) and Admin commands

    DataNode Recommendations

    NameNode Recommendations

    Hadoop Archives

    MapReduce

    MapReduce architecture

    Map Reduce Programming Model

    Different phases of Map Reduce Algorithm

    Different Data types in Map Reduce

    The Mapper

    The Reducer

    The Driver Code

    Creating Input and Output Formats in Map Reduce Jobs

    Text Input Format

    Key Value Input Format

    Introduction to Map Reduce Pipeline

    Combiner and Partioner

    YARN and Map Reducev2

    Introduction to Apache Pig

    Map Reduce Vs Apache Pig

    SQL Vs Apache Pig

    Different datatypes in Pig

    Local Mode

    Map Reduce

    Grunt Shell

    Script

    Transformations in Pig

    How to write a simple pig script

    UDFs in Pig

    Hive Introduction

    Difference between Pig and Hive

    Difference between Hive and RDBMS

    Hive Integration with Hadoop

    Hive Query Language(Hive QL)

    Internal and External Table

    Partition and Bucketing

    Tuning of Hive

    Authentication in Hive

    Authorization in Hive

    Speculative execution in Hive

    Hive UDF

    Introduction to Sqoop.

    MySQL client and Server Installation

    How to connect to Relational Database using Sqoop

    Different Sqoop Commands p>

    Import (MySQL data import to HDFS)

    Export

    Flume Introduction

    Different components of Flume

    Twitter data collection using Flume

    Introduction

    Requirements of Cassandra

    Cassandra Architecture

    Write Operation

    KeySpace and ColumnFamily

    Storing and Reading data in Columnfamily

    Datatypes in Cassandra

    CQL and CLI Utility

    CAP Theorem

    Difference between HBase and Cassandra

    Introduction to Splunk and Tableau