Databricks Certified Developer for Spark 3.0 Practice Exams

SAMPLE QUESTION

Curious about what a high-quality question looks like? Here is an example from the DataFrame API section of the practice exams!

Question:

Which of the following code blocks returns approximately 1000 rows, some of them potentially being duplicates, from the 2000-row DataFrame transactionsDf that only has unique rows?

1. transactionsDf.take(1000).distinct()

2. transactionsDf.sample(False, 0.5)

3. transactionsDf.take(1000)

4. transactionsDf.sample(True, 0.5)

5. transactionsDf.sample(True, 0.5, force=True)

Correct Answer:

4. transactionsDf.sample(True, 0.5)

Explanation:

To solve this question, you need to know that “DataFrame.sample()” is not guaranteed to return the exact fraction of the number of rows specified as an argument. Furthermore, since duplicates may be returned, you should understand that the operator’s “withReplacement” argument should be set to “True”. A “force=” argument for the operator does not exist.

While the “take” argument returns an exact number of rows, it will just take the first specified number of rows (“1000” in this question) from the DataFrame. Since the DataFrame does not include duplicate rows, there is no potential of any of those returned rows being duplicates when using “take()”, so the correct answer cannot involve “take()”.

More info: [Link to the Spark documentation for DataFrame.sample(), available in the practice exams once purchased]

COURSE CONTENT

The practice exams cover the following topics:

Spark Architecture: Conceptual understanding (ca. 17 %): Spark driver, execution hierarchy, DAGs, execution modes, deployment modes, memory management, cluster configurations, fault tolerance, partitioning, narrow vs. wide transformations, executors, Python vs. Scala, Spark vs. Hadoop

Spark Architecture: Applied understanding (ca. 11%): Memory management, configurations, lazy evaluation, action vs. transformation, shuffles, broadcasting, fault tolerance, accumulators, adaptive query execution, Spark UI, partitioning

Spark DataFrame API Applications (ca. 72%): Selecting/dropping columns, renaming columns, aggregating rows, filtering DataFrames, different types of joins, partitioning/coalescing, reading and writing DataFrames in different formats, string functions, math functions, UDFs, Spark configurations, caching, collect/take

All questions are original, high-quality questions, not anything like Databricks Spark certification dumps.

These practice exams are specifically for the Python version of the exam. If you have been preparing to the take exam in Scala, only the 51 included Spark Architecture questions will apply to you, as the DataFrame API Applications questions focus on Python syntax exclusively.

LET’S GET YOU CERTIFIED!

Ready to pass your Databricks Certified Associate Developer for Apache Spark 3.0 exam? Click “Buy now” and immediately get started with these benefits:

• Get 3 practice exams with 180 high-quality questions in total, mimicking the original exam
• Take the exams as many times as you would like
• Get support from the instructor if you have questions
• Dive in deeper with the detailed explanations and links to additional resources for most questions
• Access the exams anywhere, anytime on your desktop, tablet, or mobile device through the Udemy app
• 30-days money back guarantee if you are not satisfied

I am excited to have you as a student and to see you pass the exam, taking your next career step as a Databricks Certified Associate Developer for Apache Spark 3.0!

Disclaimer: Neither this course nor the certification are endorsed by the Apache Software Foundation. The “Spark”, “Apache Spark” and the Spark logo are trademarks of the Apache Software Foundation. This course is not sponsored by or affiliated with Databricks.