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Apache Spark Apache Spark Fundamentals
Apache Spark Fundamentals
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Apache Spark Fundamentals

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Apache Spark Apache Spark Fundamentals
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Apache Spark Fundamentals Elearning

Order this unique Elearning Apache Spark Fundamentals course online, 1 year 24/7 access to rich interactive videos, voice, progress monitoring through reports tests.

Content

Apache Spark Fundamentals

Programming and Deploying Apache Spark Applications

  • start the course
  • describe Apache Spark and the main components of a Spark application
  • download and install Apache Spark on Windows 8.1 Pro N
  • download and install Apache Spark on Mac OS X Yosemite
  • download and install Java Development Kit or JDK 8 and build Apache Spark using Simple Build Tool or SBT on Mac OS X Yosemite
  • use the Spark shell for analyzing data interactively
  • link an application to Spark
  • create a SparkContext to initialize Apache Spark
  • introduce Resilient Distributed Datasets or RDDs and create a parallelized collection to generate an RDD
  • load external datasets to create Resilient Distributed Datasets or RDDs
  • distinguish transformations and actions, describe some of the transformations supported by Spark, and use transformations
  • describe some of the actions supported by Spark and use the actions
  • use anonymous function syntax and use static methods in a global singleton to pass functions to Spark
  • work with key-value pairs
  • persist Spark RDDs
  • use broadcast variables in a Spark operation
  • use accumulators in Spark operations
  • use different formats for loading and saving Spark data
  • use basic Spark SQL for data queries in a Spark application
  • use basic Spark GraphX to work with graphs in a Spark application
  • describe how Spark applications run in a cluster
  • deploy a Spark application to a cluster
  • unit test a Spark application
  • describe how to monitor a Spark application or cluster with Web UIs
  • describe options for scheduling resources across applications in a Spark cluster
  • describe how to enable a fair scheduler for fair sharing within an application in a Spark cluster
  • configure fair scheduler pool properties for a Spark context within a cluster
  • practice programming and deploying a Spark application to a cluster
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General properties
Availabilty: 5 hours
Language: English
Certificate of participation: Yes
Online access: 90 days
Progress monitoring: Yes
Award Winning E-learning: Yes
Suitable for mobile: Yes
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