Course Description

Bigdata Hadoop Certification Training Course In Pune

Bigdata Hadoop Training and Certification in Pune

MODULE -1 INTRODUCTION TO HADOOP

• Hadoop- Demo
• What is Bigdata
• When data becomes Bigdata
• 3V’s of Bigdata
• Introduction to Hadoop Ecosystem
• Why Hadoop? If Existing Tools and Technologies are there in the market for decades?
• How Hadoop is getting two categories Projects- New projects on Hadoop
• Clients want POC and migration of Existing tools and Technologies on Hadoop
• Clients want POC and migration of Existing tools and Technologies on Hadoop Technology
• How Open Source tool (HADOOP) is capable to run jobs in lesser time which take longer time in other tools in the market.
• Hadoop Processing Framework (Map Reduce) / YARN
• Alternates of Map Reduce
• Why NoSQL is in more demand nowadays
• Distributed warehouse for DFS
• Most demanding tools which can run on the top of Hadoop Ecosystem for specific requirements in specific scenarios
• Data import/Export tools

MODULE 2 - HADOOP SETUP INSTALLATION AND PIG BASICS

• Hadoop installation
• Introduction to Hadoop FS and Processing Environment’s UIs
• How to read and write files
• Basic Unix commands for Hadoop
• Hadoop’s FS shell
• Hadoop’s releases
• Hadoop’s daemons

MODULE 3 - HIVE BASIC, HIVE ADVANCED

• Hive Introduction
• Hive Advanced
• Partitioning
• Bucketing
• External Tables
• Complex Use cases in Hive
• Hive Advanced Assignment
• Real-time scenarios of Hive

MODULE 4 - MAP REDUCE BASICS, POC (PROOF OF CONCEPT)

• How Map Reduce works as Processing Framework
• End to End execution flow of Map Reduce job
• Different tasks in Map Reduce job
• Why Reducer is optional while Mapper is mandatory?
• Introduction to Combiner
• Introduction to Partitioner
• Programming languages for Map Reduce
• Why Java is preferred for Map Reduce programming
• POC based on Pig, Hive, HDFS, MR

MODULE 5 - MAP-REDUCE ADVANCED, HBASE BASICS

• How to work on Map Reduce in real-time
• Map Reduce complex scenarios
• Drawbacks of Hadoop
• Why Hadoop can’t be used for real-time processing

MODULE- 6 ZOOKEEPER, SQOOP, QUICK REVISION OF PREVIOUS CLASSES

• Introduction to Zookeeper
• How Zookeeper helps in Hadoop Ecosystem
• How to load data from Relational storage in Hadoop
• Sqoop basics Sqoop practical implementation
• Quick revision of previous classes to fill the gap in understanding and correct understandings

MODULE- 7 FLUME, OOZIE, HADOOP RELEASES, INTRODUCTION TO YARN

• How to load data in Hadoop that is coming from the web server or other storage without fixed schema
• How to load unstructured and semi-structured data in Hadoop
• Introduction to Flume
• Hands-on on Flume
• How to load Twitter data in HDFS using Hadoop
• Introduction to Oozie
• What kind of jobs can be scheduled using Oozie
• How to schedule time-based jobs
• Hadoop releases
• From where to get Hadoop and other components to install
• Introduction to YARN
• Significance of YARN

MODULE- 8 INTRODUCTION TO HUE, DIFFERENT VENDORS IN THE MARKET, MAJOR PROJECT DISCUSSION

• Introduction to Hue
• How Hue is used in real-time
• Real-time Hadoop usage
• Real-time cluster introduction
• Hadoop Release 1 vs Hadoop Release 2 in real-time
• Hadoop real-time project
• Major POC based on the combination of several tools of Hadoop Ecosystem
• Datasets for practice purpose

MODULE- 9 SPARK AND PYTHON

• Introduction to Spark
• Introduction to Python
• Pyspark concepts
• Advantages of Spark over Hadoop
• Is Spark a replacement for Hadoop?
• How Spark is Faster than Hadoop
• Spark RDD
• Spark Transformation and Actions
• Spark SQL
• Datasets and Data Frames
• Real-time scenarios examples of Spark where we prefer Spark over Hadoop
• How Spark is capable to process complex data sets in lesser time
• In-Memory Processing Framework for Analytics

MODULE- 10 HADOOP IN CLOUD COMPUTING: AWS

• Introduction to Cloud Computing
• On-premises vs cloud setup
• Major cloud providers of Bigdata
• What is EMR
• HDFS vs S3
• Overview and working of AWS Glue jobs
• AWS Glue
• AWS Redshift
• AWS Athena