Apache Spark 2 and 3 using Scala (Formerly CCA 175) by Durga Viswanatha Raju Gadiraju

Udemy course Apache Spark 2 and 3 using Scala (Formerly CCA 175) by Durga Viswanatha Raju Gadiraju

Apache Spark 2 and 3 using Scala (Formerly CCA 175) is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the IT Certifications category. Therefore, if you are looking to improve your IT Certifications skills we recommend that you download Apache Spark 2 and 3 using Scala (Formerly CCA 175) udemy course.

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Course data:

  • Author: Durga Viswanatha Raju Gadiraju
  • Course rating: 4.4
  • Category: IT Certifications
  • Modality: Online
  • Status: Available
  • Idiom: English

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Abouth Durga Viswanatha Raju Gadiraju

13+ years of experience in executing complex projects using vast array of technologies including Big Data and Cloud.

Apache Spark 2 and 3 using Scala (Formerly CCA 175)

What the udemy Apache Spark 2 and 3 using Scala (Formerly CCA 175) course teaches?

What you’ll learn Entire curriculum of CCA Spark and Hadoop Developer HDFS Commands Scala Fundamentals Core Spark – Transformations and Actions Spark SQL and Data Frames

Data Engineering using Apache Spark 2 or 3 using Scala as Programming Language

More information about the course Apache Spark 2 and 3 using Scala (Formerly CCA 175)

As part of this course, you will learn all the key skills to build Data Engineering Pipelines using Spark SQL and Data Frame APIs using Scala as Programming language. This course used to be CCA 175 Spark and Hadoop Developer course for the preparation of Certification Exam. As of 10/31/2021, the exam is sunset and we have renamed it to Apache Spark 2 and 3 using Scala 3 as it covers industry relevant topics beyond the scope of certification. About Data Engineering Data Engineering is nothing but processing the data depending upon our downstream needs. We need to build different pipelines such as Batch Pipelines, Streaming Pipelines, etc as part of Data Engineering. All roles related to Data Processing are consolidated under Data Engineering. Conventionally, they are known as ETL Development, Data Warehouse Development, etc. Course Details Here is the high level outline of the topics related to this course. Quick recap of Scala Data Engineering using Spark SQL Let us, deep-dive into Spark SQL to understand how it can be used to build Data Engineering Pipelines. Spark with SQL will provide us the ability to leverage distributed computing capabilities of Spark coupled with easy-to-use developer-friendly SQL-style syntax. Getting Started with Spark SQL Basic Transformations Managing Tables – Basic DDL and DML Managing Tables – DML and Partitioning Overview of Spark SQL Functions Windowing Functions Data Engineering using Spark Data Frame APIs Spark Data Frame APIs are an alternative way of building Data Engineering applications at scale leveraging distributed computing capabilities of Spark. Data Engineers from application development backgrounds might prefer Data Frame APIs over Spark SQL to build Data Engineering applications. Data Processing Overview Processing Column Data Basic Transformations – Filtering, Aggregations, and Sorting Joining Data Sets Windowing Functions – Aggregations, Ranking, and Analytic Functions Spark Metastore Databases and Tables Please note that the syllabus is recently changed and now the exam is primarily focused on Spark Data Frames and/or Spark SQL. All the demos are given on our state of the art Big Data cluster. You can avail one-month complimentary lab access by reaching out to support@itversity.com with Udemy receipt.

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