Developing-Solutions-Using-Apache-Hadoop

Developing Solutions Using Apache Hadoop online training curriculum

Introduction

• What is Big Data?
• Introduction to Analytics and the need for big data analytics
• Hadoop Solutions - Big Picture
• Hadoop distributions
• Apache Hadoop
• Cloud era Hadoop
• Horton Works and Other Hadoop distributions
• Comparing Hadoop Vs. Traditional systems
• Data Retrieval - Radom Access Vs. Sequential Access

Hadoop: Basic Concepts

• What is Hadoop?
• The Hadoop Distributed File System
• Hadoop Map Reduce Works
• Anatomy of a Hadoop Cluster

Hadoop Daemons

• Master Daemons
• Slave Daemons

Master Daemons

• Name node
• Job Tracker
• Secondary name node

Slave Daemons

• Job tracker
• Task tracker

â–ºHDFS (Hadoop Distributed File System)

Blocks and Splits

• Input Splits
• HDFS Splits

â–º Data Replication

â–º Data high availability

â–º Data Integrity

â–º Cluster architecture and block placement

Accessing HDFS

• JAVA Approach
• CLI Approach

â–º Practices & Programming Performance Tuning

Developing Map Reduce Programs in Local Mode

• Running without HDFS and Map reduce

Developing Map Reduce Programs in Pseudo-distributed Mode

• Running all daemons in a single node

Developing Map Reduce Programs in Fully distributed mode

• Running daemons on dedicated nodes
• Map Reduce
• Map Reduce Overview
• Word Count Problem
• Word Count Flow and Solution
• Map Reduce Flow
• Algorithms for simple problems
• Algorithms for complex problems

Developing the Map Reduce Application

• Data Types
• File Formats
• Explain the Driver, Mapper and Reducer code
• Running locally
• Running on Cluster
• Hands on exercises

How Map-Reduce Works?

• Anatomy of Map Reduce Job runs
• Job Submission
• Job Initialization
• Task Assignment
• Job Completion
• Job Scheduling
• Job Failures
• Shuffle and sort
• Hands on Exercises

â–º Hadoop Ecosystem

Hive

• Hive concepts
• Hive architecture
• Hive meta-store
• Install and configure hive on cluster
• Create database, access it from java client
• Partitions
• Buckets
• Hive JDBC
• Joins in hive
• Inner joins
• Outer Joins
• Hive UDF
• Hive UDAF
• Hive UDTF
• Develop and run sample applications in Java to access hive
• Load New York Stock Exchange data into Hive and process it using Hive

PIG

• Pig basics
• Install and configure PIG on a cluster
• PIG Vs Map Reduce and SQL
• Pig Vs Hive
• Write sample Pig Latin scripts
• Modes of running PIG
• Local mode
• Map Reduce mode
• PIG UDFs

â–º PIG Macros

Hbase

• HBase and Zookeeper concepts
• HBase architecture
• Region server architecture
• File storage architecture
• HBase basics
• Column access
• Scans
• HBase use cases
• Install and configure HBase on a multi node cluster
• Create database, Develop and run sample applications
• Access data stored in HBase using clients like Java, Python and Pearl Map Reduce client to access the HBase data

Sqoop

• Install and configure Sqoop on cluster
• Connecting to RDBMS
• Installing MySql
• Import data from Oracle/MySql to hive
• Export data to Oracle/MySql
• Internal mechanism of import/export
• Import millions of records into HDFS from RDBMS using Sqoop

YARN and MR2

• YARN
• MR2 Demons (Resource Manager, Application Manager, App Master, Node Mgr)
• Execution of an MR2 Job
• Name Node High Availability
• Name Node federation

â–º Hadoop Administrative Tasks

Setup Hadoop cluster

• Install and configure Hadoop
• Make a fully distributed Hadoop cluster on a single laptop/desktop
• Monitoring the cluster
• Performance Tuning

Hadoop POC/real-life experience

Class Delivery

• Live Interactive classes with expert

Delivery Methodology

• We are using an experiential delivering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course