Free Certified Associate Developer for Apache Spark Exam Questions and Answers
Certified Associate Developer for Apache Spark is part of the Databricks certification programme. Three things hold across every Databricks exam: it costs $200, it is delivered by Kryterion either online-proctored or at a test centre, and it is valid for two years, after which you retake the current version in full — there is no continuing-education route and no free retake voucher, and you must wait 14 days between attempts. Associate papers run 45 to 48 scored questions in 90 minutes with six months' hands-on experience recommended but nothing required. Databricks deliberately publishes no pass mark for any of its exams.
The first 10 questions on this page are free to read, answers included — no account and no card. A plan opens the rest of the bank, the full timed practice test and your weak-topic reporting.
Last updated: September 11, 2026
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- 130 mins · 70%
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Recommended: Switch to Test Mode to start a practice test that simulates the real exam experience.
Question #1
What is the primary purpose of Apache Spark in data processing?
Please select an optionIncorrectCorrect answer: D
Apache Spark is designed for batch processing, allowing for the processing of large datasets in parallel across a cluster.
Was this answer correct?Question #2
If you need to transform a DataFrame in Spark, which operation would you use?
Please select an optionIncorrectCorrect answer: D
The filter() operation allows you to filter rows in a DataFrame based on a specified condition.
Was this answer correct?Question #3
When optimizing a Spark job, which of the following techniques can improve performance?
Please select an optionIncorrectCorrect answer: A
Increasing the number of shuffle partitions can help distribute the workload more evenly and reduce the overall processing time for large datasets.
Was this answer correct?Question #4
In Spark SQL, which command is used to create a temporary view that can be queried using SQL?
Please select an optionIncorrectCorrect answer: A
The createOrReplaceTempView() function allows you to create a temporary view which can be queried using SQL syntax.
Was this answer correct?Question #5
What is an advantage of using DataFrames over RDDs in Spark?
Please select an optionIncorrectCorrect answer: D
DataFrames provide a higher-level API with optimizations that can make data manipulation more efficient compared to RDDs, which require more verbose coding.
Was this answer correct?Question #6
When using Spark Streaming, what is the purpose of the micro-batch processing model?
Please select an optionIncorrectCorrect answer: A
The micro-batch processing model allows data to be processed in small batches, balancing the need for real-time processing with system resource management.
Was this answer correct?Question #7
In which scenario should you prefer using a DataFrame over an RDD?
Please select an optionIncorrectCorrect answer: C
DataFrames are optimized for structured data, providing various built-in functions for data manipulation and analysis, making them preferable over RDDs in such cases.
Was this answer correct?Question #8
If a Spark job fails, what is the first thing you should check?
Please select an optionIncorrectCorrect answer: B
Checking the driver memory settings is crucial as memory-related issues are common causes of job failures in Spark.
Was this answer correct?Question #9
What does the term "lazy evaluation" mean in the context of Apache Spark?
Please select an optionIncorrectCorrect answer: B
Lazy evaluation means that Spark does not execute transformations until an action is called, allowing for optimizations and reduced computation until necessary.
Was this answer correct?Question #10
What is the main purpose of the Catalyst optimizer in Spark SQL?
Please select an optionIncorrectCorrect answer: B
The Catalyst optimizer is responsible for optimizing the execution plans of SQL queries, improving performance and efficiency in data processing.
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FAQ
Learn More: https://www.databricks.com/learn/training/certification
- Q1: What is the Certified Associate Developer for Apache Spark exam?
- A: Certified Associate Developer for Apache Spark is a Databricks certification exam. Judging by the questions in our bank, it concentrates on spark, dataframe, apache, dataframes and streaming.
- Q2: What topics does the Certified Associate Developer for Apache Spark exam cover?
- A: Questions in our Certified Associate Developer for Apache Spark bank cluster around spark, dataframe, apache, dataframes, streaming, join, operation and processing. Working through the full set is the quickest way to find which of these you are weakest on.
- Q3: How should I prepare for Certified Associate Developer for Apache Spark?
- A: Work through the Certified Associate Developer for Apache Spark practice questions here, checking your answer on each one, then sit the practice test to rehearse the exam under timed conditions before the real thing.
- Q4: Are these real Certified Associate Developer for Apache Spark exam questions?
- A: They are drawn from officially released past questions and from community members who have sat Certified Associate Developer for Apache Spark. Answers are verified and updated weekly.
- Q5: Where do I register for the Certified Associate Developer for Apache Spark exam?
- A: Register through Databricks directly at https://www.databricks.com/learn/training/certification. Exampractice is not affiliated with Databricks and does not administer the exam.
- Q6: Is there a free Certified Associate Developer for Apache Spark sample?
- A: Yes. Every Certified Associate Developer for Apache Spark page shows a free sample of real questions. Upgrading opens the full bank and the practice test.
- Q7: What are Databricks Certification Exams?
- A: Databricks Certification Exams validate your expertise in using Databricks’ unified data analytics platform. These certifications demonstrate your proficiency in data engineering, data analysis, and machine learning, utilizing Databricks tools and the Apache Spark framework.
- Q8: Why should I pursue Databricks Certification?
- A: Databricks Certification enhances your professional credibility, showcasing your skills and knowledge in big data analytics and machine learning. This can lead to better job opportunities, higher salaries, and career advancement in data science, data engineering, and IT industries.
- Q9: What are the benefits of Databricks Certification?
- A: Benefits include recognition as a certified data professional, improved job performance, access to exclusive resources, continuing education opportunities, and staying current with the latest data analytics technologies and best practices.
- Q10: Who should take Databricks Certification Exams?
- A: Data engineers, data scientists, data analysts, machine learning practitioners, and anyone involved in processing and analyzing large datasets should consider these certifications to validate their expertise and advance their careers.
- Q11: What types of Databricks Certification Exams are available?
- A: Databricks offers various certification paths, including:
- Q12: How do I prepare for Databricks Certification Exams?
- A: Preparation can include official Databricks training courses, study guides, practice exams, online tutorials, and hands-on experience with Databricks tools and the Apache Spark framework.
- Q13: Where can I take Databricks Certification Exams?
- A: Databricks Certification Exams can be taken online, providing flexibility to fit your schedule and location.
- Q14: How do Databricks Certifications impact my career?
- A: Databricks Certifications significantly boost your career by demonstrating your expertise to employers, making you a more competitive candidate for advanced roles and promotions in data science, data engineering, and IT.
- Q15: Are there any prerequisites for Databricks Certification Exams?
- A: Some exams may have prerequisites, such as foundational knowledge or prior experience with Databricks and Apache Spark. Check the specific requirements for each certification path on the Databricks website.
- Q16: How often do I need to recertify for Databricks Certifications?
- A: Databricks Certifications typically require recertification every two years to ensure that certified professionals stay updated with the latest data analytics technologies and industry practices.