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Databricks Certified Associate Developer for Apache Spark 3.0 FAQs

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Databricks Certified Associate Developer for Apache Spark 3.0 FAQs

Get all your queries cleared with the latest Databricks Certified Associate Developer for Apache Spark 3.0 FAQs.

1. What is Databricks Certified Associate Developer for Apache Spark 3.0?

Databricks Academy offers certification for Databricks Certified Associate Developer for Apache Spark 3.0. The Databricks Certified Associate Developer for Apache Spark 3.0 exam tests your knowledge of the Spark architecture and your ability to use the Spark DataFrame API to execute particular data manipulation tasks. Furthermore, this certification exam assesses your knowledge of the Spark DataFrame API as well as your ability to use it to perform fundamental data manipulation activities within a Spark session. The following are some examples of these tasks:

  • Selecting, renaming, and manipulating columns
  • Filtering, dropping, sorting, and aggregating rows
  • Handling missing data
  • Combining, reading, writing, and partitioning DataFrames with schemas
  • 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.

2. How many questions are asked in the exam?

The number of questions asked in the exam is 60.

3. What is the time duration?

The time duration of the exam is 2 hours.

4. What is the examination fee?

The total amount to register for the exam is 200 USD per attempt.

5. What is the passing score?

The passing score is 70% and above (42 of the 60 questions).

6. What is the preferred language for the exam?

This exam is only available in the Python or Scala language.

7. What is the exam format?

The exam comes in Multiple Choice Questions.

8. Where to schedule my exam?

  • Create an account (or login) at https://academy.databricks.com.
  • Click on the Certifications tab to see all available certificate exams
  • For the exam, you want to take, click the Register button.
  • To arrange an exam with our partner proctoring service, follow the on-screen steps.

9. What are the prerequisites for the exam?

  • You should have a basic understanding of the Spark architecture, including Adaptive Query Execution
  • You must be able to apply the Spark DataFrame API to complete individual data manipulation task, including: 
    • selecting, renaming, and manipulating columns
    • filtering, dropping, sorting, and aggregating rows
    • joining, reading, writing and partitioning DataFrames
    • working with UDFs and Spark SQL functions

10. How can I reschedule/retake my exam?

  • Simply log in to your Webassessor account and reschedule if you need to reschedule your exam and it is more than 24 hours out from the start time. Please call Kryterion if you need to reschedule your exam within 24 hours of the commencement time.
  • You have unlimited opportunities to re-register and retake the exam. Each try is priced at $200. For this exam, Databricks will not provide free retake vouchers.

11. What are the learning outcomes of this exam?

  • The architecture of an Apache Spark Application
  • Learn to run Apache Spark on a cluster of computer
  • Learn the Execution Hierarchy of Apache Spark
  • Create DataFrame from files and Scala Collections
  • Spark DataFrame API and SQL functions
  • Different techniques to select the columns of a DataFrame
  • Define the schema of a DataFrame and set the data types of the columns
  • Apply various methods to manipulate the columns of a DataFrame
  • Filter your DataFrame based on specifics rules
  • Sort data in a specific order
  • Sort rows of a DataFrame in a specific order
  • Arrange the rows of DataFrame as groups
  • Handle NULL Values in a DataFrame
  • Use JOIN or UNION to combine two data sets
  • Save the result of complex data transformations to an external storage system
  • Different deployment modes of an Apache Spark Application
  • Working with UDFs and Spark SQL functions
  • Use Databricks Community Edition to write Apache Spark Code

12. What is the course outline?

  • To begin with, Spark Architecture: Conceptual understanding (~17%)
  • Then, Spark Architecture: Applied understanding (~11%)
  • Lastly, Spark DataFrame API Applications (~72%)

13. Give some study resources for this certification?

1. Apache Spark™ Programming with Databricks:

This course explores the fundamentals of Spark Programming with Databricks using a case study-based approach, including Spark architecture, the DataFrame API, query optimization, Structured Streaming, and Delta. This is a two-day workshop. The following are the course objectives:

  • Define the major components of Spark architecture and execution hierarchy
  • Describe how DataFrames are built, transformed, and evaluated in Spark
  • Apply the DataFrame API to explore, preprocess, join, and ingest data in Spark
  • Apply the Structured Streaming API to perform analytics on streaming data
  • Navigate the Spark UI and describe how the catalyst optimizer, partitioning, and caching affect Spark’s execution performance
2. Quick Reference: Spark Architecture:

Apache SparkTM is a unified analytics engine for large-scale data processing that is noted for its speed, ease of use, and ability to access a variety of data sources, as well as APIs designed to enable a variety of use-cases. The purpose of this course is to provide you an understanding of Spark’s internal architecture. This course’s learning objectives are as follows:

  • Describe basic Spark architecture and define terminology such as “driver” and “executor”.
  • Explain how parallelization allows Spark to improve speed and scalability of an application.
  • Describe lazy evaluation and how it relates to pipelining.
  • Identify high-level events for each stage in the Optimization process.
3. Learning Spark:

This book demonstrates how to use machine learning algorithms and perform simple and advanced data analytics. You’ll be able to do the following with the help of step-by-step walkthroughs, code snippets, and notebooks:

  • Learn Python, SQL, Scala, or Java high-level Structured APIs
  • Understand Spark operations and SQL Engine
  • Inspect, tune, and debug Spark operations with Spark configurations and Spark UI
  • Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka
  • Perform analytics on batch and streaming data using Structured Streaming
  • Build reliable data pipelines with open source Delta Lake and Spark
  • Develop machine learning pipelines with MLlib and productionize models using MLflow

4. Self Paced learning:

The courses included in this learning bundle are listed in alphabetical order.

14. What happens if I don’t pass the exam the first time?

You are welcome to re-register and retake the exam as many times as you would like. Each attempt costs $200. Databricks will not issue free retake vouchers for this exam.

15. How much does it cost to take Databricks certification exams?

$200 US. There are no free retakes.

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