Introduction to Apache Spark is designed to introduce you to one of the most important Big Data technologies on the market, Apache Spark. You will start by learning about some of the basic concepts behind Spark, including the Resilient Distributed Datasets which tie everything together. From there, you will learn how to work with datasets in Spark using a functional programming approach as well as SQL. Finally, you will learn how to use the Eclipse IDE to write programs to work with data, learning a common technique for deploying code for Apache Spark jobs.
Training Content Manager
Mitchell Pearson has been with Pragmatic Works for 8 years as a Data Platform Consultant and the Training Content manager. Mitchell has authored books on SQL Server, Power BI and the Power Platform. Data Platform experience includes designing and implementing enterprise level Business Intelligence solutions with the Microsoft SQL Server stack (T-SQL, SSIS, SSAS, SSRS), the Power Platform and Microsoft Azure.
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Spark does not publish minimum requirements for single-node machines like VMs or laptops, but at least 8 GB of RAM is recommended. Spark can run on any edition of Windows, Linux, or Mac OS which supports Oracle Java 1.8.
The target audience of this course is an application or database developer interested in learning about Big Data technologies. No knowledge of Spark or Hadoop is assumed. Knowledge of development languages like Java, C#, or Python are helpful but not required.
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