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Course Overview

This Apache Spark certification training will enable learners to understand how Spark executes in-memory data processing and runs much faster than Hadoop MapReduce. Learners will master Scala programming and will get trained on different APIs which Spark offers such as Spark Streaming, Spark SQL, Spark RDD, Spark MLlib and Spark GraphX. This course is an integral part of the Big Data developer’s learning path.

In this era of ever-growing data, the need for analyzing it for meaningful business insights is paramount. There are different big data processing alternatives like Hadoop, Spark, Storm and many more. Spark, however, is unique in providing batch as well as streaming capabilities, thus making it a preferred choice for lightning fast big data analysis platforms.

Who Should Attend?

Data scientists, data analytics, developers, solution architects can go for Apache Spark certification training course or anyone who is interested and willing to learn new tech stack.

Course Outline

Module 1: Introduction to Spark – Getting started

  • What is Spark and what is its purpose?
  • Components of the Spark unified stack
  • Resilient Distributed Dataset (RDD)
  • Scala and Python overview
  • Launching and using Spark’s Scala and Python shell

Module 2: Resilient Distributed Dataset and DataFrames

  • Understand how to create parallelized collections and external datasets
  • Work with Resilient Distributed Dataset (RDD) operations
  • Utilize shared variables and key-value pairs

Module 3: Spark application programming

  • Understand the purpose and usage of the SparkContext
  • Initialize Spark with the various programming languages
  • Describe and run some Spark examples
  • Pass functions to Spark
  • Create and run a Spark standalone application
  • Submit applications to the cluster

Module 4: Introduction to Spark libraries

  • Understand and use the various Spark libraries
  • SPARK Core and its programming
  • Spark SQL and its implementation
  • Spark Machine learning

Module 5: Spark Top End Components

  • Machine Learning algorithms
  • Various examples
  • Spark Streaming

Module 6: Spark configuration, monitoring and tuning

  • Understand the components of the Spark cluster
  • Configure Spark to modify the Spark properties, environmental variables, or logging properties
  • Monitor Spark using the web UIs, metrics, and external instrumentation
  • Understand performance tuning considerations

Course Objectives

This Apache Spark certification course training will cover these objectives

  • Understand Scala and its implementation
  • Install Spark and implement Spark operations on Spark Shell
  • Understand the role of Spark RDD
  • Implement Spark applications on YARN (Hadoop)
  • Learn Spark Streaming API
  • Implement machine learning algorithms in Spark MLlib API
  • Analyze Hive and Spark SQL architecture
  • Implement Broadcast variable and Accumulators for performance tuning
  • Project

General Notes

  • All our courses can be facilitated as Customized In-House Training course.
  • Course duration is flexible and the contents can be modified to fit any number of days.
  • As for Open Enrolment Courses, we offer our clients the flexibility to chose the location, date, and time and our team of experts who are spread around the globe will assist in facilitating the course.
  • The course fee includes facilitation, training materials, 2 coffee breaks, buffet lunch and a Certificate of successful completion of Training.
  • FREE Consultation and Coaching provided during and after the course.

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