Apache Storm Training | Learn Real Time Analytics about the wide variety of Streamed Data with Apache Storm

Apache Storm Course Description

Apache Storm is an open source distributed real-time computation system used with any programming language.

Storm Training is intended to make Storm easily deliverable, understandable, to guide and help learners up-skill themselves. Storm makes it easy to write and scale complex real-time computations on a cluster of computers, executing real-time processing what Hadoop does for batch processing. Storm guarantees that every message will be processed.

Pincorps Apache Storm course is designed to provide knowledge and skills for real time analytics of wide variety of streamed data. In our training, you learn the concepts of Storm like streams, spouts, bolts, and topologies, Developing and testing topologies using Storm’s local mode, Deploying topologies on Storm clusters, How Storm achieves fault-tolerance and guarantees data processing, Computing intense functions on the fly in parallel using Distributed RPC, Making real-time computations idempotent using transactional topologies.

Apache Storm Course Learning Outcomes

  • Master core concepts of Storm and Storm architecture 
  • Setup of multi-node Storm cluster
  • Process streaming data efficiently
  • Gain knowledge on spout and bolt
  • Grasp fundamental concepts like Tuple, Trident
  • Learn development of real-time Storm applications
  • Work on various business problems related to Storm
  • Develop real time live Storm Project

Apache Storm Training - Suggested Audience

Apache Storm tutorial is aimed at professionals who are looking to make their career in real time Computation system “ Apache Storm” should go for this course. Suggested attendees based on our past programs are:
  • Software Developers
  • ETL Developers
  • Project Managers
  • Data Analysts
  • Big Data professionals
  • BI Professionals

Apache Storm Training Duration
  • Open-House F2F (Public): 1/2/3 days
  • In-House F2F (Private): 2/3 days, for commercials please send us an email with group size to hello@pincorps.com

Apache Storm Training Prerequisites

  • Knowledge of core java will be helpful.
  • Prior Hadoop knowledge will be added advantage but it is not mandatory to learn Apache Storm.

Apache Storm course syllabus includes:

Module 1 - About Apache Storm
  • Introduction and need for Big Data
  • Basics Introduction to Hadoop and its limitations
  • Conventional technologies for real time processing
  • Need for distributed real-time processing engine
  • What is the need of Storm
  • What is Apache Storm
  • Apache storm features and terminologies
  • Internals of Storm architecture
  • Create topologies in Storm
  • Storm data and execution flow
  • Grouping multiple stream together
  • Work on Tuple, Bolt and Spout
  • Bolt normalization

Module 2 - Installation and Configuration of Apache Storm
  • Setup and configuration of environment
  • Deploy Apache storm
  • Testing and troubleshooting
  • Best practices of deployment

Module 3 - Advanced Concepts of Storm
  • Develop applications to process streams of data
  • Grouping of Bolt and Spout
  • Reliable stream processing
  • Connection with different data sources
  • Collecting data from Apache Kafka and process it
  • Life cycle of bolt and best practices

Module 4 - Play with Trident
  • What and why of Trident
  • Trident Spouts and best practices
  • Components of trident spout
  • Work with trident interfaces
  • Play with Trident filtering and aggregation

Module 5 - Dive into Storm Programming
  • Develop complex applications for real-time processing
  • Best practices of stream data processing
  • Deploy application on multi-node cluster
  • Best practices for different deployments

Module 6 - Real Life Project
  • Live real life project based on industry use-case
Keny White

Professor

Keny White is Professor of the Department of Computer Science at Boston University, where he has been since 2004. He also currently serves as Chief Scientist of Guavus, Inc. During 2003-2004 he was a Visiting Associate Professor at the Laboratoire d'Infomatique de Paris VI (LIP6). He received a B.S. from Cornell University in 1992, and an M.S. from the State University of New York at Buffalo.

Bachelor

After working as a software developer and contractor for over 8 years for a whole bunch of companies including ABX, Proit, SACC and AT&T in the US, He decided to work full-time as a private software trainer. He received his Ph.D. in Computer Science from the University of Rochester in 2001. "What I teach varies from beginner to advanced and from what I have seen, anybody can learn and grow from my courses".

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