This self-paced online course is designed to take you through a powerful, distributed, real-time computation system “Apache Storm” for processing fast and large streams of data.

Faculty : Real Time Expert  |  Duration : 25hrs   |   Material : Yes   | Price : Rs.15,000/-

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Itabhyas online training is the Best Storm Online Training in USA, UK, Australia, Canada and India.

Apache Storm, in simple terms, is a distributed framework for real time processing of Big Data like Apache Hadoop is a distributed framework for batch processing. Apache Storm works on task parallelism principle where in the same code is executed on multiple nodes with different input data.

Apache Storm does not have any state managing capabilities. It instead utilizes Apache ZooKeeper to manage its cluster state such as message acknowledgements, processing status etc. This enables Storm to start right from where it left even after the restart.

Since Storm’s master node (called Nimbus) is a Thrift service, one can create and submit processing logic graph (called topology) in any programming language. Moreover, It is scalable, fault-tolerant and guarantees that input data will be processed.

 Strom Online Training batches will start every week. Make a call on +91-9030403937 or send a mail to info@itabhyas.com 

Who should do this Course ?

 This course is designed for professionals aspiring to make a career in Real Time Big Data Analytics using Apache Storm and the Hadoop Framework. Software Professionals, Data Scientists, ETL developers and Project Managers are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Apache Storm Architecture can also opt for this course.

  • Topics – Topics covered:
    • What is Big data?
    • Big Data Analytics: Batch Vs Real Time
    • Hadoop for Batch Analytics
    • Shortcomings of Hadoop
    • Storm for Real Time Analytics
    • What is Storm?
    • Use Cases of Storm
    • Components of Storm
    • Properties of Storm
    • Storm Vs Hadoop
    1. Storm Technology Stack and Groupings

    Learning Objectives – In this module you’ll learn Storm Installation, different run modes of Storm, creating a simple Storm program and different topologies available in Storm.

    Topics – Topics covered:

    • Storm Installation
    • Storm Running Modes
    • Creating First Storm Topology
    • Topologies in Storm
    1.  Spouts and Bolts

    Learning Objectives – In this module you’ll learn about Spouts and Bolts, two basic building blocks of any Storm topology.

    Topics – Topics covered:

    • Reliable Vs Unreliable Messages
    • Getting Data
    • Bolt Lifecycle
    • Bolt Structure
    • Reliable Vs Unreliable Bolts
    1. Trident Topologies

    In this module you’ll learn about Trident

    Learning Objectives – Topologies, a new feature included in Storm to handle failures.

    Topics – Topics covered:

    • Design
    • Trident in Storm
    • Spout
    • RQ Class
    • Co-ordinator
    • Emitter
    • Bolt
    • Committer Bolts
    • Partitioned Transactional Spouts
    1. Real Life Storm Project

    Learning Objectives – In this module we’ll discuss first real life project, its set up, code and execution.

  • who is a trainer ?

IT Abhyas trainers are working professionals from the Industry and have 10 yrs of relevant experience.

  • Will i ask for Demo session?

yes , we r conducting the demo sessions when u need.

  • How i will practice ?

We will provide a software to do the practice.In case you come across any doubt, we have a 24*7 support team they will assist you.

  • If I miss the session ?

Any situation you are not attend the session we will provide the Recorded session.

  • What about the course Material?

We are ready to provide the course material.

  • will i get the videos of course?

yes , you get the videos after completion of daily session.that access for life time.

  • Will i enroll now take a sessions after?

yes you will join u take a sessions later.

  • If i have any queries ?

you will send a mail or give a call to support team.