The Databricks Spark 3 certification is officially known as the Databricks Certified Associate Developer for Apache Spark 3.0. It is designed to validate your understanding of the Spark architecture and your ability to apply the Spark DataFrame API to complete various data manipulation tasks.

Key topics covered in the certification exam include:

• Understanding the basics of the Spark architecture, including Adaptive Query Execution
• Applying the Spark DataFrame API to complete individual data manipulation tasks such as:
  • Selecting, renaming, and manipulating columns
  • Filtering, dropping, sorting, and aggregating rows
  • Joining, reading, writing, and partitioning DataFrames
  • Working with UDFs and Spark SQL functions

To prepare for the exam, you can utilize the following resources:

• Databricks Certified Associate Developer for Apache Spark 3.0 Exam Preparation Guide: This guide provides an overview of the exam topics and links to relevant documentation and training materials.
• Databricks Academy courses: Databricks offers various courses on Apache Spark, including a dedicated course for preparing for the certification exam.
• Online articles and blogs: Numerous articles and blog posts offer tips and strategies for passing the certification exam. For example, you can refer to “How to Crack Databricks Certified Associate Developer for Apache Spark 3.0 Exam” on Medium.

By passing the Databricks Certified Associate Developer for Apache Spark 3.0 exam, you will demonstrate your expertise in Apache Spark and your ability to work with big data effectively.