HADOOP Training in Bangalore
Learn HADOOP Course from Expert Oracle Trainers who are Real-time Working Professionals.
Expert Trainers | Practical Training | Mock Interviews | Placement Assistance | Job Support
Best HADOOP Training in BTM Layout Bangalore
Based on Google and other third-party reviews, Softgen Infotech is recognized as one of the Best HADOOP Training in BTM Layout Bangalore. We have completed over 2000 HADOOP training sessions with a 100% placement rate, assisting college students. For the past 5 years, the team at Softgen Infotech has been dedicated to providing High-Quality Best HADOOP Training in BTM Layout Bangalore.
Softgen Infotech’s trainers are handpicked from the HADOOP industry, with a minimum of 5 years of expertise in implementing HADOOP technology. All HADOOP Trainers are real-world professionals who provide hands-on experience with practicals.
Softegen’s HADOOP Training in BTM Layout Bangalore is well-equipped with labs and excellent infrastructure to give you hands-on experience. We have successfully trained and placed the majority of our students in large MNC firms. Softgen provides accredited HADOOP training programmes with 100% placement assistance for our students.
Course materials for HADOOP are designed as per contemporary scenarios which helps students in understanding the HADOOP concept in detail. Our HADOOP Training Syllabus covers all topics connected to HADOOP Technology and provides students with a thorough understanding of real-world settings. Our HADOOP experts at Softgen Infotech’s HDOOP Training Institute in Bangalore have devised a unique method of effective coaching.
We offer normal training sessions (daytime classes), weekend training classes, and fast track training classes for HADOOP. For the HADOOP training institute in Bangalore , we also offer online training classes.
To schedule a free sample and learn more about the HADOOP Training Course, contact us today.
Enroll Today
Why Choose Softgen Infotech
Softgen Infotech is a leading Training Institute in Bangalore providing Quality Training for Multiple IT Courses with Placement Assistance. HADOOP Training Institute in Bangalore provides you in-depth knowledge on the subject.
Live & Interactive Sessions
Real Time Training
Practical Classes
Interview & Placement Assistance
Need Advice?
Worried or Confused whether this is the right course for you? Feel free to reach our Expert Consultant for all your Queries !
Course Material & Syllabus
Get all Course Content and Syllabus. Get Trained like a Professional. We Provide Course Material, Prepare for Interviews, Arrange Mock Interviews and 100 % Placement Assistance
Who Should Attend?
- The course is intended for programmers, architects, and project managers who have to process large amounts of data offline.
Benefits of Attendance:
- Upon completion of this course, students will be able to:
- Understand basic concepts of MapReduce applications developed using Hadoop
- Understand how Hadoop works and supports cloud computing and explore examples with Amazon Web Services and case studies
- Use Apache Hadoop and write MapReduce programs
Prerequisites:
- Students should have a basic familiarity with Linux administration and Java. Most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) is helpful to appreciate the more advanced data processing examples.
Course Outline:
What is Hadoop?
- Understanding distributed systems and Hadoop
- Comparing SQL databases and Hadoop
- Understanding MapReduce
- Counting words with Hadoop—running your first program, History of Hadoop.
Starting Hadoop
- The building blocks of Hadoop
- Setting up SSH for a Hadoop cluster
- Running Hadoop
- Web-based cluster UI
Components of Hadoop
- Working with files in HDFS
- Anatomy of a MapReduce program
- Reading and writing
Writing basic MapReduce programs
- Constructing the basic template of a MapReduce program
- Counting things
- Adapting for Hadoop’s API changes
- Streaming in Hadoop
- Improving performance with combiners
Advanced MapReduce
- Chaining MapReduce jobs
- Joining data from different sources
- Creating a Bloom filter
Programming Practices
- Developing MapReduce programs
- Monitoring and debugging on a production cluster
- Tuning for performance
Cookbook
- Passing job-specific parameters to your tasks
- Probing for task-specific information
- Partitioning into multiple output files
- Inputting from and outputting to a database
- Keeping all output in sorted order
Managing Hadoop
- Setting up parameter values for practical use
- Checking system’s health
- Setting permissions
- Managing quotas
- Enabling trash
- Removing DataNodes
- Adding DataNodes
- Managing NameNode and Secondary NameNode
- Recovering from a failed NameNode
- Designing network layout and rack awareness
- Scheduling jobs from multiple users
Running Hadoop in the cloud
- Introducing Amazon Web Services
- Setting up AWS
- Setting up Hadoop on EC2
- Running MapReduce programs on EC2
- Cleaning up and shutting down your EC2 instances
- Amazon Elastic MapReduce and other AWS services
Programming with Pig
- Installing Pig
- Running Pig
- Learning Pig Latin through Grunt
- Speaking Pig Latin
- Working with user-defined functions
- Working with scripts
- Seeing Pig in action—example of computing similar patents
Hadoop Related Technologies
- Hive
- Apache Accumulo
- Other Hadoop-related stuff
Case studies
- Converting 11 million image documents from the New York Times archive
- Mining data at China Mobile
- Recommending the best websites at StumbleUpon
- Building analytics for enterprise search—IBM’s Project ES2
HADOOP Training Course Duration & Batch Timings
| Duration : 30 Hours | Version : latest Version |
|---|---|
| Regular : 1 Hour per day | Fast Track : 2 - 3 Hours per day: 10 days |
| Weekdays : Monday - Friday | Weekend : Saturday and Sunday |
| Online Training : Available | Class Room Training : Available |
| Course Fee : Talk to our Customer Support | Mode of Payment : Talk to our Customer Support |
Frequently Asked Questions for HADOOP Training Course
Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.