Spark Scala coding framework, testing, Structured streaming

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

Ratings: 4.08 / 5.00




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



What You Will 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

Who Should Attend!

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