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 Multi node 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
- 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
- MRunit
- 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
- 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
- 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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Course Features

Course Details

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

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 Multi node cluster set up Hadoop Administration

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

Relation between Input Splits and HDFS Blocks

MapReduce: Combiner & Partitioner

Demo on de-identifying Health Care Data set

Demo on Weather Data set

Counters

Distributed Cache

MRunit

Reduce Join

Custom Input Format

Sequence Input Format

Xml file Parsing using MapReduce

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

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

Testing Pig scripts with Punit

Aviation use case in PIG

Pig Demo on Healthcare Data set

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