The exam assesses an understanding of the basics of the Spark architecture and the ability to apply the Spark DataFrame API to complete individual data manipulation tasks.

The purpose of this exam course is to measure your knowledge and identify where to revisit some Spark topics in order to make sure whether you are ready for the exam

The exams are covers the following topics

• Basic Spark architecture,

• Adaptive Query Execution

• Data manipulation tasks;

  • selecting, renaming and manipulating columns

  • filtering, dropping, sorting, and aggregating rows

  • joining, reading, writing and partitioning DataFrames

  • working with UDFs and Spark SQL functions

Every exam answer is going to be linked to official Spark documentation, so you can easily refresh your knowledge.

Exam Details

During the exam, candidates will be provided with a PDF version of the Apache Spark documentation for the language in which they are taking the exam and a digital notepad for taking notes and writing example code

Description

The Databricks Certified Associate Developer for Apache Spark certification exam assesses the understanding of the Spark DataFrame API and the ability to apply the Spark DataFrame API to complete basic data manipulation tasks within a Spark session. These tasks include selecting, renaming and manipulating columns; filtering, dropping, sorting, and aggregating rows; handling missing data; combining, reading, writing and partitioning DataFrames with schemas; and working with UDFs and Spark SQL functions. In addition, the exam will assess the basics of the Spark architecture like execution/deployment modes, the execution hierarchy, fault tolerance, garbage collection, and broadcasting.