Apache Spark Training

Anyone can start Apache Spark Training because there are no prior requirements necessary. We provide a 30-hour Apache Spark taught by instructors with more than 10 years of real-time experience. The course includes real-world assignments and the faculty will direct you toward setting a work environment to practice assignments.

Assistance in CV preparation, interview questions answers, and materials are part of the training program. We do advise taking a one-hour session every day, From Monday through Friday, but one can also look into the weekend, fast-track, one-on-one, or customized programs.

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Spark Developer Career

✔️Spark Pre-requisites

Basic Computer Knowledge.

✔️Jobs On Spark

Top IT MNC such as Capgemini, Cognizant, IBM, Infosys, Accenture, etc.,

✔️Spark Developer Salary

The average salary for a Spark Developer with 4 years experience in India is ₹40,00,000.

✍️ Detailed Course Curriculum

Our Technical expert will help you with real time issues. He also guide you in certification preparation and career mentoring if required.

Spark Course FAQ's

01. can you help me in CV preparation?
Yes, We can help you preparing your resume.

02. will you help in interview preparation?
We can provide you interview question answers. The course covered many real-time examples. These examples might help you.

03. Is this course sufficient to get a job?
Our training covered as many real-time examples as we can. This course may equivalent to 2 to 3 years of work experience. You have to work hard if you are aimed at 4+ years of experience.

04. What’s the certification process?
Please come with an exam code. We’ll guide you further. We’ll guide you on how to get certified. Don’t worry, we’ll help you in certification process.

05. Can you provide Work Support?
We can provide job support for an additional fee. Contact the support team for fee details. You can choose either the hourly rate or monthly fee.

01. Introduction to Spark and Hadoop platform

  • What is Hadoop platform
  • Why Hadoop platform
  • What is Spark
  • Why spark
  • Evolution of Spark

02. Introduction to Scala

  • Functional Programing Vs Object Orient Programing
  • Scalable language
  • Scala Overview

03. SPARK Environment

  • Configuring Apache Spark

04. SCALA Environment

  • JAVA Setup
  • SCALA Editor
  • Interpreter
  • compiler

05. Deep Dive into Scala

  • Benefits of Scala
  • Language Offerings
  • Type inferencing
  • Variables
  • Functions
  • LOOPS
  • Control Structures
  • Vals
  • Arrays
  • Lists
  • Tuples
  • Sets
  • Maps
  • Traits and Mixins
  • Classes and
  • Objects
  • First class functions
  • Clousers
  • Inheritance
  • Sub classes
  • Case Classes
  • Modules
  • Pattern Matching
  • Exception Handling
  • FILE Operations

06. Deep Dive into Spark

  • Spark Shell
  • Parallel Programming
  • context
  • RDD
  • Transformations
  • Programming with RDD
  • Actions
  • Broadcast Variables
  • Accumulators

07. Spark Eco-System

  • Spark Streaming
  • MLlib
  • Graphx
  • Spark SQL

08. Submitting Spark jobs on Hadoop cluster

09. Projects and Use Cases

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