Apache Spark 2.4 for Big Data Applications

[mitsumi]

Apache Spark 2.4 for Big Data Applications
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | 1.75 GB
Duration: 3 hours | Genre: eLearning | Language: English

Learn Apache Spark's key concepts using real-world examples

What you'll learn

    How to create RDD's, Dataframes and Datasets
    How to properly use Map, Reduce & Filter
    How to Partition RDD's in Distributed Systems
    Caching Datasets in Memory to Reduce computations
    How to tune Spark Programs
    How to run Iterative Algorithms on a cluster
    Difference between GroupByKey and ReduceByKey

Requirements

    Familiar with Ubuntu
    Familiar with Scala

Description

Learn Apache Spark's key concepts using real-world examples. This course goes over everything you need to know to get started using Spark. We start with resilient distributed data-sets and the main transformations and actions that can be performed on them. Then we move on to Advanced Spark concepts such as Partitioning and Persistence. Finally the course ends with Spark's SQL API which includes two data abstractions called Dataframes and Datasets which sit on top of Spark RDD's. They allow for new levels of optimization and SQL querying capabilities.

Who this course is for:

    Beginner scala developers curious about data science
   

               

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