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Essential Beginners Apache Spark For You 2024

Learn Apache Spark right from your home. Train with the best and work for the best

  • 13
  • 150 Hrs
  • 38
  • (4.1)

Before diving into Apache Spark, it's beneficial to understand some foundational technologies. One of the first areas to familiarise yourself with is data store interaction, given that Spark can leverage a multitude of different data stores.

Additionally, a basic understanding of Hadoop is beneficial, as this popular distributed data infrastructure often complements Spark in executing big data tasks. Alongside this, having a grasp on SQL enables you to interact with and retrieve data from databases efficiently, should you plan to use these as a data source within Spark.

A basic familiarity with distributed database systems, such as Hbase or Cassandra, can be advantageous as well. Lastly, to effectively interact with Spark, proficiency in a programming language that Spark recognises- like Python, Java, R, or Scala programming languages- is essential. With these skills under your belt, you'll be well-equipped to make the most of what Apache Spark has to offer.

What Will You Learn?

This tutorial offers a swift yet comprehensive learning experience, ensuring mastery through efficient instruction and practical examples.

  • module 1: SPARK FUNDAMENTALS
  • module 2:STARTING WITH SPARK
  • module 3:DELVING INTO RDDS
  • module 4:DATA AGGREGATION USING PAIR RDDS
  • module 5:CRAFTING AND LAUNCHING SPARK APPLICATIONS
  • module 6:MASTERY IN PARALLEL PROCESSING
  • module 7:PERSISTENCE IN SPARK RDD
  • module 8:INTRODUCTION TO SPARK'S MLlib
  • module 9:APACHE FLUME AND APACHE KAFKA SYNERGY
  • module 10:REAL-TIME DATA WITH SPARK STREAMING
  • module 11:ENHANCING SPARK'S EFFICIENCY
  • module 12:ENGAGING WITH SPARK SQL AND DATA FRAMES
  • module 13:SPARK'S SCHEDULING AND PARTITION TECHNIQUES

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