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Learning Apache Storm For Big Data Processing

Learning Apache Storm For Big Data Processing


Using a free and open source, distributed real-time computation system was never this much fun!

Overview

Using a free and open source, distributed real-time computation system was never this much fun!

Apache Storm is a distributed real-time processing engine. Created by Nathanmarz for Backtype and later open sourced under Apache License 2, it's a scalable and a fault-tolerant engine used to process a massive number of unbounded streams. In this course you will see how simple yet efficient Apache Storm is when it comes to real-time processing.

In the course, you will learn about data processing types followed by Apache Storm and its features. You'll learn the core concepts of Apache Storm such as spouts, bolts, topology, and stream grouping, and set up Apache Storm in single-node and multi-node configurations. Also you'll explore how fault-tolerant Apache Storm is.

Taking this course will kick-start your experience with Apache Storm; you'll create a scalable, fault-tolerant, real-time processing application while setting a strong base for the fundamentals of the real-time processing paradigm and Apache Storm.

Course Information

This course targets data engineers, solution architects, Java developers, technical managers, and programming analysts working in a big data setup or anyone who is keen to learn the ins and outs of big data processing
The audience is expected to have a working knowledge of programming with Java. A basic knowledge of Apache Maven (and a working knowledge of Eclipse and Linux terminals) will help you understand its concepts a lot more easily

Core big data processing concepts
Core components of Apache Storm
Developing Apache Storm applications from scratch
Defining terms associated with Apache Storm
Setting up single- and multi-node clusters in Apache Storm
Integrating Apache Hadoop with Apache Storm
Performing transformation operations using tridents
Understanding Parallelism and using StreamGroupings for tuple interaction

This course targets data engineers, solution architects, Java developers, technical managers, and programming analysts working in a big data setup or anyone who is keen to learn the ins and outs of big data processing.

• Lifetime Access to Each Course
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Course Specifications

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Adult education is the non-credential activity of gaining skills and improved education. 

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Online education is electronically supported learning that relies on the Internet for teacher/student interaction. 

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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