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Apache Spark

This web-based training course on Apache Spark functionality, administration and development, is available online to all individuals, institutions, corporates and enterprises in India (New Delhi NCR, Bangalore, Chennai, Kolkatta), US, UK, Canada, Australia, Singapore, United Arab Emirates (UAE), China and South Africa. No matter where you are located, you can enroll for any training with us - because all our training sessions are delivered online by live instructors using interactive, intensive learning methods.

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Course Details

Apache Spark is an open-source in-memory data processing engine that provides an interface for programming complete clusters with implied fault tolerance and data parallelism. The entire data processing engine is developed around speed, accuracy, ease of access and refined analytics. Mainly used for large scale data processing, Apache Spark has become the largest open source tool for Big Data. The Apache Spark Certification Course online will teach students about the functional concepts of the data processing engine. The course is for professionals who want to acquaint themselves with the basic and advanced concepts and practices of Apache Spark.

Getting Started with Apache Spark

  • Overview of Spark and What Purpose it Serves?
  • Spark Unified Stack core Components
  • What is Resilient Distributed Dataset (RDD)
  • Spark standalone Download and Installation
  • Introduction to Scala and Python
  • Spark's Scala and Python shell: Launch and Use

Module 2-Resilient Distributed Dataset and DataFrames

  • Getting familiar with creating parallelized collections and external datasets
  • Working with Resilient Distributed Dataset (RDD) operations
  • Using shared variables and key-value pairs

Module 3-Programming of Spark Application

  • A Brief Overview of purpose and use of the SparkContext
  • Initializing Spark with the different programming languages
  • Running and Demonstrating a few Spark examples
  • Passing functions to Spark
  • Developing and running a Spark standalone application
  • Submitting applications to the cluster

Module 4 - Introduction to Spark libraries

  • Getting familiar with various Spark libraries and their uses

Module 5 Spark configuration, monitoring and tuning

  • Spark cluster and its Components
  • Configuring Spark to transform the Spark properties, environmental variables, or logging properties
  • Using Web UIs, metrics, and external instrumentation to monitor Spark
  • Studying and Evaluating performance tuning considerations

Live Instructor-led & Interactive Online Sessions

Regular Course

Duration : 40 Hours

Capsule Course

Duration : 4-8 Hours

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Training Options


Weekdays- Cloud Based Training

Mon - Fri 07:00 AM - 09:00 AM(Mon, Wed, Fri)

Weekdays Online Lab

Mon - Fri 07:00 AM - 09:00 AM(Tue, Thur)


Weekend- Cloud Based Training

Sat-Sun 09:00 AM - 11:00 AM (IST)

Weekend Online Lab

Sat-Sun 11:00 AM - 01:00 PM

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