Hadoop Course in Chennai

Section 1: BIG DATA-HADOOP – An Introduction

• Basics of Hadoop Ecosystem
• A brief overview of other Big Data Systems
• Uses of Hadoop
• Integration of Hadoop into Exiting Software Products
• Understanding of the Hadoop Ecosystem
• Installation & Configuration of Hadoop
• Use Cases of Hadoop in HealthCare, Retail, Telecom

Section 3: Introduction to the algorithm MapReduce

• Theory of MapReduce
• The process of Data Flow (Map – Shuffle – Reduced)
• Difference between MapRed & MapReduce APIs
• Learning Programming: Mapper, Reducer, Combiner, Partitioner
• Understanding Writables
• Two different formats : Input Format &Output format
• Streaming API using python
• Inherent Failure Handling using Speculative Execution
• Getting to know the Magic of Shuffle Phase
• The different types of File Formats
• Learning the various Sequence Files

Section 5: Gaining knowledge in HIVE

• Learning the Architecture in detail
• Installation & Configuration
• Learning the differences between Hive & RDBMS
• Understanding Tables
• What is DDL?
• What is DML?
• What is UDF?
• Learning Partitioning in detail
• What is Bucketing?
• What are Hive functions?
• What are Date functions?
• What are String functions?
• Learning Cast function Meta Store

Section 7: Learning the SQOOP

• Architecture, Installation, Commands (Import, Hive-Import, EVal, Hbase Import, Import All Tables, Export)
• Connectors to Existing DBs and DW

Section 9: Handling OOZIE

• Understanding Architecture, Installation & Workflow
• Learning Coordinator
• Understanding Action (Map-Reduce, Hive, Pig, Sqoop)
• Introduction to Bundle
• Introduction to Mail Notifications

Section 11: Big Data Use cases – An Overview

• An introduction to Hadoop
• The HDFS architecture and usage
• Knowing MapReduce Architecture and real time exercises
• Learning the Hadoop Eco systems
• What is Sqoop? – MySQL DB Migration
• What is Hive? — Deep drive
• Definition of Pig – weblog parsing and ETL
• Understanding Oozie – Workflow scheduling
• Handling Flume – weblogs ingestion
• Learning No SQL
• Learning the HBase
• Basics of Apache Kafka
• What is Pentaho ETL Tool Integration? ‘Working with Hadoop Eco System.
• Introduction and working with RDD.
• Definition of Multinode Setup Guidance
• Learning the Hadoop’s latest version of the Pros and Cons discussion
• Introduction to Data Science.

Section 2: Understanding HDFS

• Basic Concepts in HDFS- explained in detail
• Architecture of HDFS
• Learning the Data Flow (File Read&File Write)
• Learning Fault Tolerance
• Understanding Shell Commands
• Data Flow Archives – explained in brief
• Coherency – Data Integrity
• The Role of Secondary NameNode

Section 4: Understanding HBASE

• Introduction to NoSQL
• The CAP Theorem
• Classification of NoSQL
• Difference between Hbase and RDBMS
• Learning about HBASE and HDFS
• Architecture (Read Path, Write Path, Compactions, Splits)
• Getting to know Installation & Configuration
• Role of Zookeeper
• HBase Shell and Introduction to Filters
• RowKeyDesign – What’s New in HBase Hands-On

Section 6: Understanding PIG

• Architecture of PIG
• Installation of PIG
• Hive vs Pig
• Learning the Pig Latin Syntax
• What are the different Data Types?
• The different Functions (Eval, Load/Store, String, Date,Time)
• What are Joins?
• The UDFs – Performance
• Troubleshooting
• Commonly Used Functions

Section 8: What is KAFKA?

• An introduction to Kafka
• An Introduction to Data streaming
• Understanding Producer – Consumer Topics
• What are Brokers?
• What are Partitions?
• How to stream Unix via Kafka

Section 10: Learning HADOOP 2.0 and Spark

• Limitations on Hadoop
• HDFS Federation
• High Availability in HDFS
• How to make HDFS Snapshots
• Other Improvements in HDFS2
• An Introduction to YARN/MR2
• What are the Limitations on MR1
• What is the Architecture of YARN
• How to use MapReduce Job Flow in YARN
• An Introduction to Stinger Initiative and Tez
• How to use BackWard Compatibility for Hadoop 1.X
• Learning the Spark Fundamentals
• RDD – Sample Scala Program – Spark Streaming

Section 12: Real-Time Projects

• How to get application web logs
• How to get user information from my sql via sqoop
• How to get the extracted data from Pig script
• Learning to create a Hive SQL Table for querying
• Learning how to create Reports from Hive QL

Hadoop Certificate in Chennai

By being certified for Bigdata Hadoop a person becomes skilful in deploying, using and manipulating Hadoop. A whole lot of multi-national companies like Cognizant, Standard Chartered, McDonald’s, IBM, Ericson, Sony, Cisco and Saint Gobain employ Bigdata in their organizations.

Cloudera offers various Hadoop Certifications like:
• Cloudera Certified Professional – CCP DS
• Cloudera Certified Administrator for Hadoop – CCAH &
• Cloudera Certified Hadoop Developer – CCDH
IBM also offers Certifications in:
• IBM Bigdata Architect Certification &
• IBM Bigdata Engineer Certification
Hortonworks offers two Hadoop Certifications for:
• Hortonworks Certified Apache Hadoop Developer – HCAHD
• Hortonworks Certified Apache Hadoop Administrator – HCAHA
We at BTree Systems provide for all such predominant and main certifications. Our faculties can train the students both theoretically and practically for the above said certifications and can guide them to acquire it.

Benefits of Hadoop

Apart from the ability to hold large amounts of data, Hadoop offers the following benefits:
Hadoop is flexible enough to process various kinds of data like email conversations, click stream data and Social media.
Hadoop can be used in a wide array of functions like fraud detection, data warehousing, market campaign analysis, log processing and recommendation systems.
Hadoop is very cost effective when it comes to storage solutions. Hadoop is designed to be a scale-out architecture that can be useful in storing a company’s old data for future use.

Hadoop Course Highlights

Hadoop Certification Career Opportunities

Hadoop Interview Questions

Training Classes in Chennai at BTree Systems

We at BTree Systems value your time. We conduct training classes with flexible batch timings in both weekdays and weekends.
BTree Systems provides group classes and online classes on request. The online classes are led by instructors so that you can clarify your doubts then and there. You can upgrade your skill set at your convenience and can save up your travel time. We know that you may want to complete the course fast because of time constraints. And some of you might be fast learners, so to satisfy your pace and needs BTree Systems provides fast track classes.
After the course completion you can carry with you:
1. Industry recognized Certificate
2. Course Materials
3. Completed Project
4. Exposure to the industry and
5. Placement assistance

Hadoop Training cost

At BTree Systems we provide quality training at affordable and reasonable costs as per the industry standards. Our aim is to offer the best instruction and coaching in a way that anybody can afford it.