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Big Data
          &
Hadoop

Curriculum

Chapter 1: Understanding Big Data and Hadoop

  • Big Data

  • Limitations and Solutions of existing

  • Data Analytics Architecture

  • Hadoop

  • Hadoop Features

  • Hadoop Ecosystem

  • Hadoop 2.x core components

  • Hadoop Storage: HDFS

  • Hadoop Processing: MapReduce

  • Framework

  • Hadoop Different Distributions

Chapter 2:Hadoop Architecture and HDFS

  • Hadoop 2.x Cluster Architecture

  • Federation and High Availability

  • A Typical Production Hadoop Cluster

  • Hadoop Cluster Modes

  • Common Hadoop Shell Commands

  • Hadoop 2.x Configuration Files

  • Single node cluster and Multinode

  • cluster set up Hadoop Administration

Chapter 3: Hadoop MapReduce Framework

  • MapReduce Use Cases

  • Traditional way Vs MapReduce way

  • Why MapReduce

  • Hadoop 2.x MapReduce Architecture

  • Hadoop 2.x MapReduce Components

  • YARN MR Application Execution Flow

  • YARN Workflow

  • Anatomy of MapReduce Program

  • Demo on MapReduce

  • Input Splits

  • The relation between Input Splits and
    HDFS Blocks

  • MapReduce: Combiner & Partitioner

  • Demo on de-identifying Health Care

  • Data set

  • Demo on Weather Data set

Chapter 4: Advanced MapReduce

  • Counters

  • Distributed Cache

  • MR unit

  • Reduce Join

  • Custom Input Format

  • Sequence Input Format

  • XML file Parsing using MapReduce

Chapter 5: Pig

  • About Pig

  • MapReduce Vs Pig

  • Pig Use Cases

  • Programming Structure in Pig

  • Pig Running Modes

  • Pig components

  • Pig Execution

  • Pig Latin Program

  • Data Models in Pig

  • Pig Data Types

  • Shell and Utility Commands

  • Pig Latin: Relational Operators

  • File Loaders, Group Operator

  • COGROUP Operator

  • Joins and COGROUP

  • Union

  • Diagnostic Operators

  • Specialized joins in Pig

  • Built-In Functions ( Eval Function,

  • Load and Store Functions, Math
    function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution ( PIG macros and Pig Parameter substitution )

  • Pig Streaming

  • Testing Pig scripts with Punit

  • Aviation use case in PIG

  • Pig Demo on Healthcare Data set

Chapter 6: Hive

  • Hive Background

  • Hive Use Case

  • About Hive

  • Hive Vs Pig

  • Hive Architecture and Components

  • Metastore in Hive

  • Limitations of Hive

  • Comparison with Traditional Database

  • Hive Data Types and Data Models

  • Partitions and Buckets

  • Hive Tables(Managed Tables and External Tables)

  • Importing Data

  • Querying Data

  • Managing Output

  • Hive Script

  • Hive UDF

  • Retail use case in Hive

  • Hive Demo on Healthcare Data set

Chapter 7: Advanced Hive and HBase

  • Hive QL: Joining Tables

  • Dynamic Partitioning

  • Custom Map/Reduce Scripts

  • Hive Indexes and views Hive query optimizers

  • Hive: Thrift Server, User Defined Functions

  • HBase: Introduction to NoSQL

  • Databases and HBase

  • HBase v/s RDBMS

  • HBase Components

  • HBase Architecture

  • Run Modes & Configuration

  • HBase Cluster Deployment

Chapter 8: Advanced HBase

  • HBase Data Model

  • HBase Shell

  • HBase Client API

  • Data Loading Techniques

  • ZooKeeper Data Model

  • Zookeeper Service

  • Zookeeper

  • Demos on Bulk Loading

  • Getting and Inserting Data

  • Filters in HBase

Chapter 9:Processing Distributed Data with Apache Spark

  • What is Apache Spark

  • Spark Ecosystem

  • Spark Components

  • History of Spark and Spark

  • Versions/Releases

  • Spark a Polyglot

  • What is Scala?

  • Why Scala?

  • SparkContext

  • RDD

Chapter 10:Oozie and Hadoop Project

  • Flume and Sqoop Demo

  • Oozie

  • Oozie Components

  • Oozie Workflow

  • Scheduling with Oozie

  • Demo on Oozie Workflow

  • Oozie Co-ordinator

  • Oozie Commands

  • Oozie Web Console

  • Oozie for MapReduce

  • PIG

  • Hive, and Sqoop

  • Combine flow of MR

  • PIG

  • Hive in Oozie

  • Hadoop Project Demo

  • Hadoop Integration with Talend

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