Tutorialspoint

Apache Spark with Scala useful for Databricks Certification

Apache Spark with Scala Crash Course useful for Databricks Certification Unofficial for beginners

  Bigdata Engineer

   IT & Software, IT Certification, IT Certification Other

Language - English Published on 12/2020

  • Introduction
    02:39
    Preview
  • Download Resources
  • Introduction to Spark
    07:21
  • (Old) Free Account creation in Databricks
    01:51
  • (New) Free Account Creation in Databricks
    01:50
  • Provisioning a Spark Cluster
    02:14
  • Basics about notebooks
    07:29
    Preview
  • Why we should learn Apache Spark?
    03:08
    Preview
  • Spark Architecture Components
    07:10
  • Driver
    02:38
  • Partitions
    01:26
  • Executors
    02:48
  • Spark Jobs
    02:10
  • Spark Stages
    00:57
  • Spark Tasks
    00:48
  • Practical Demonstration of Jobs, Tasks and Stages
    03:14
  • Spark RDD (Create and Display Practical)
    18:21
  • Spark Dataframe (Create and Display Practical)
    12:06
    Preview
  • Anonymus Functions in Scala
    04:38
  • Extra (Optional on Spark DataFrame)
    04:47
  • Extra (Optional on Spark DataFrame) in Details
    12:46
  • Spark Datasets (Create and Display Practical)
    17:01
  • Caching
    02:27
  • Notes on reading files with Spark
    04:16
  • Data Source CSV File
    08:53
    Preview
  • Data Source JSON File
    06:21
  • Data Source LIBSVM File
    03:52
  • Data Source Image File
    04:44
    Preview
  • Data Source Arvo File
    02:22
  • Data Source Parquet File
    02:50
  • Untyped Dataset Operations (aka DataFrame Operations)
    03:52
  • Running SQL Queries Programmatically
    02:55
  • Global Temporary View
    03:04
  • Creating Datasets
    03:42
  • Scalar Functions (Built-in Scalar Functions) Part 1
    08:34
  • Scalar Functions (Built-in Scalar Functions) Part 2
    14:12
  • Scalar Functions (Built-in Scalar Functions) Part 3
    14:32
  • User Defined Scalar Functions
    07:15

Description

Apache Spark with Scala useful for Databricks Certification(Unofficial)

Apache Spark with Scala its a Crash Course for Databricks Certification Enthusiast (Unofficial) for beginners 

“Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon, eBay, NASA, Yahoo, and many more. All are using Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Operating system right at home.

So, What are we going to cover in this course then?

Learn and master the art of framing data analysis problems as Spark problems through over 30+ hands-on examples, and then execute them up to run on Databricks cloud computing services (Free Service) in this course. Well, the course is covering topics which are included for certification:  

1) Spark Architecture Components 

  • Driver, 

  • Core/Slots/Threads, 

  • Executor 

  • Partitions

2) Spark Execution 

  • Jobs 

  • Tasks 

  • Stages 

3) Spark Concepts 

  • Caching, 

  • DataFrame Transformations vs. Actions, Shuffling 

  • Partitioning, Wide vs. Narrow Transformations   

4) DataFrames API 

  • DataFrameReader 

  • DataFrameWriter 

  • DataFrame [Dataset]

5) Row & Column (DataFrame)

6) Spark SQL Functions 

In order to get started with the course And to do that you're going to have to set up your environment.

So, the first thing you're going to need is a web browser that can be (Google Chrome or Firefox, or Safari, or Microsoft Edge (Latest version)) on Windows, Linux, and macOS desktop 

This is completely Hands-on Learning with the Databricks environment.

What Will I Get ?

  • Apache Spark ( Spark Core, Spark SQL, Spark RDD and Spark DataFrame)
  • Databricks Certification syllabus included in the Course
  • An overview of the architecture of Apache Spark.
  • Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.
  • Develop Apache Spark 3.0 applications using RDD transformations and actions and Spark SQL.
  • Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding about Spark SQL.

Requirements

  • Some programming experience is required and Scala fundamental knowledge is also required , but you need to know the fundamentals of programming in order to pick it up.
  • You will need a desktop PC and an Internet connection.
  • Any flavor of Operating System is fine.

    Feedbacks (0)

  • No Feedbacks Posted Yet..!

We make use of cookies to improve our user experience. By using this website, you agree with our Cookies Policy.