Spark Scala Coding Framework, Testing, Structured Streaming

Spark Scala Framework, Hive, IntelliJ, Maven, Logging, Exception Handling, log4j, ScalaTest, JUnit, Structured Streaming

What you'll learn

Spark Scala industry standard coding practices - Logging, Exception Handling, Reading from Configuration File
Unit Testing Spark Scala using JUnit , ScalaTest, FlatSpec & Assertion
Building a data pipeline using Hive, Spark and PostgreSQL
Spark Scala development with Intellij, Maven
Cloudera QuickStart VM setup on GCP


Requirements

Basic Big Data, Spark knowledge required

Description

This course will bridge the gap between your academic and real world knowledge and prepare you for an entry level Big Data Spark Scala developer role. You will learn the following

Spark Scala coding best practices

Logging - log4j, slf4

Exception Handling

Configuration using Typesafe config

Doing development work using IntelliJ, Maven

Using your local environment as a Hadoop Hive environment

Reading and writing to a Postgres database using Spark

Unit Testing Spark Scala using JUnit , ScalaTest, FlatSpec & Assertion

Building a data pipeline using Hadoop , Spark and Postgres

Bonus - Setting up Cloudera QuickStart VM on Google Cloud Platform (GCP)

Structured Streaming


Prerequisites :

Basic programming skills

Basic database knowledge

Big Data and Spark entry level knowledge


Who this course is for:

Students looking at moving from Big Data Spark academic background to a real world developer role