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 programming skills
Basic database skills
Hadoop entry level knowledge
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 followingSpark Scala coding best practicesLogging - log4j, slf4Exception HandlingConfiguration using Typesafe configDoing development work using IntelliJ, MavenUsing your local environment as a Hadoop Hive environmentReading and writing to a Postgres database using SparkUnit Testing Spark Scala using JUnit , ScalaTest, FlatSpec & AssertionBuilding a data pipeline using Hadoop , Spark and PostgresBonus - Setting up Cloudera QuickStart VM on Google Cloud Platform (GCP)Structured StreamingPrerequisites :Basic programming skillsBasic database knowledgeBig 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


Homepage

https://www.udemy.com/course/spark-scala-coding-best-practices-data-pipeline/

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