Eminent IT Info distinguished itself as the leading Hadoop Training Institute in Bangalore. Our Hadoop Training Consultants or Trainers are highly qualified and Experienced to deliver high-quality Hadoop Classroom and Online Training across Bangalore.
Eminent IT Info is considered pioneer in the filed of IT/Non-IT Training in Bangalore. We are mainly focused on revolutionising learning by making it interesting and motivating. we provide range of career oriented courses for different segments like students, job seekers and corporate citizens.
Our team of certified experts have designed our Hadoop Training course content and syllabus for classroom and Online Training is based on current requirements from the industry. This enables them to be an Industry-Ready Professional, capable of handling majority of the real-world scenarios. Elegant IT Services also offer tailored made Hadoop Training courses for Corporates.
Module 1- Introduction to BigData
- What is BigData
- how did data become so big
- why BigData deserves your attention-
- use cases of big data
- Different option of analyzing big data.
- How can such a huge data are analyzed.
Module 2- Introduction To Hadoop
- What is Hadoop,
- History of Hadoop
- How Hadoop name was given
- Problems with Traditional Large-Scale Systems and Need for Hadoop
- Where Hadoop is being used
- Understanding distributed systems and Hadoop
- RDBMS and Hadoop
Module 3- Starting Hadoop
- Setup single node hadoop cluster
- Configuring Hadoop
- Understanding Hadoop Architecture
- Understanding Hadoop configuration files
- Hadoop Components- HDFS, Map Reduce
- Overview of Hadoop Processes
- Overview of Hadoop Distributed File System
- Name nodes
- Data nodes
- The Command-Line Interface
- The building blocks of Hadoop
- Setting up SSH for a Hadoop cluster
- Running Hadoop
- Web-based cluster UI-NameNode UI, MapReduce UI
- Hands-On Exercise: Using HDFS commands
Module 4- Understanding MapReduce
- How MapReduce Works
- Data flow in MapReduce
- Map operation
- Reduce operation
- MapReduce Program In JAVA using Eclipse
- Counting words with Hadoop—Running your first program
- Writing MapReduce Drivers, Mappers and Reducers in Java
- Real-world “MapReduce” problems
- Hands-On Exercise: Writing a MapReduce Program and Running a MapReduce Job
- Java WordCount Code Walkthrough
Module 5- Hadoop Ecosystem
- Hive
- Sqoop
- Pig
- HBase
- Flume
Module 6- Extended Subjects on Hive
- Installing Hive
- Introduction to Apache Hive
- Getting data into Hive
- Hive’s architecture
- Hive-HQL
- Query execution
- Programming Practices and projects in Hive
- Troubleshooting
- Hands-On Exercise: Hive Programming
Module 7- Extended Subjects on Sqoop
- Installing Sqoop
- Configure Sqoop
- Import RDBMS data to Hive using Sqoop
- Export from to Hive to RDBMS using Sqoop
- Hands-On Exercise: Import data from RDBMS to HDFS and Hive
- Hands-On Exercise: Export data from HDFS/Hive to RDBM
Module 8- Extended Subjects on Pig
- Introduction to Apache Pig
- Install Pig
- Pig architecture
- Pig Latin – Reading and writing data using Pig
- Hands-On Exercise: Programming with pig, Load data, execute data processing statements.
Module 9- Extended Subjects on
- What is HBase?
- Install HBase
- HBase Architecture
- HBase API
- Managing large data sets with HBase
Module 10- setup multi-node hadoop cluster
- Setup multi node hadoop cluster using CentOS dump.
Module 11- flume
Module 12- Advanced Map/reduce-
- Map Reduce API
- Combiner, partitioner
- Custom Data Types
- Input Formats
- Output Formats
- Common MapReduce Algorithms
- Sorting
- Searching
- Indexing
Module 13- advanced hadoop concept
- Authentication in hadoop,
- Administration best practices
- Hardware selection for master nodes (NameNode, Job Tracker, HBase Master)
- Hardware selection for slave nodes (Data Nodes, Task Trackers, and Region Servers)
- Cluster growth plan based on storage
Module 14- Summary
- Case studies
- Sample Applications
- References