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

Apache Spark 2 and 3 using Scala (Formerly CCA 175) | Udemy
English | Size: 9.48 GB
Genre: eLearning

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

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 TablesPlease 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 [email protected] with Udemy receipt.

Who this course is for:
Any IT aspirant/professional willing to learn Big Data and give CCA 175 certification

If any links die or problem unrar, send request to
forms.gle/e557HbjJ5vatekDV9

Leave a Comment Cancel reply