Databricks Certified Associate Developer - Practice Test

This course brings you Three (180 questions) high-quality practice tests in PySpark

Each practice set will help you test yourself and improve your knowledge for Databricks Certified Associate Developer for the Apache Spark 3.0 exam.

About the Certification

The Databricks Certified Associate Developer for Apache Spark 3.0 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.

Exam Details

The exam details are as follows:

The exam consists of 60 multiple-choice questions. Candidates will have 120 minutes to complete the exam.

The minimum passing score for the exam is 70 percent. This translates to answer a minimum of 42 of the 60 questions correctly.

You will be testing your knowledge on the following topics:

Spark Architecture: Conceptual and Applied understanding (~28%):

• Spark Use Cases

• Spark Architecture

• Spark Configurations

• Spark Query Planning

• Adaptive Query Execution

• Garbage Collection

• Query Performance

• Scheduling

Spark DataFrame API Applications (~72%):

• Concepts of Transformations and Actions

• Selecting and Manipulating Columns

• Adding, Removing, and Renaming Columns

• Working with Date and Time

• Data Type Conversions and Casting

• Filtering, Dropping, and Sorting Rows

• Aggregation Joins and Broadcast

• Partitioning and Coalseing

• Reading, Writing Data Files

• CSV and Parquet Options

• Working with NULLs and Literals

• Combining Data Frames

• Data Sampling and Splits

• Data Frame Schema and Catalog

• Collecting data at Driver

• Catching and Persistence

• Syntax Problems Code

• Tracing and Output Determinations

• Working with UDF

• Spark SQL, Database, Tables, and Views

• Spark SQL Functions

• Text File Options

Note: These are not exam dumps. The practice test assesses your Apache Spark 3.0 knowledge and exam preparedness.

It may also help you improve your Apache Spark 3.0 knowledge.