Databricks Certified Developer for Spark 3.0 Practice Exams
If you have been looking for a comprehensive set of realistic, high-quality questions to practice for the Databricks Certified Developer for Apache Spark 3.0 exam in Python, look no further!
These up-to-date practice exams provide you with the knowledge and confidence you need to pass the exam with excellence. All 180 questions have been written from scratch, based on the actual distribution of topics and tone in the real exam. The questions cover all themes being tested for in the exam, including specifics to Python and Apache Spark 3.0.
Most questions come with detailed explanations, giving you a chance to learn from your mistakes and have links to the Spark documentation and expert web content, helping you to understand how Spark works even better.
These practice exams come with valuable exam tips & tricks and code snippets that you can execute for free on the Databricks Community Edition. These supplemental materials will help you understand the many tricky details of the exam and the Spark syntax, giving you the knowledge and confidence you need to be a top performer in the real exam!
Curious about what a high-quality question looks like? Here is an example from the DataFrame API section of the practice exams!
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?
2. transactionsDf.sample(False, 0.5)
4. transactionsDf.sample(True, 0.5)
5. transactionsDf.sample(True, 0.5, force=True)
4. transactionsDf.sample(True, 0.5)
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]
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.
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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
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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.
Who this course is for:
- For those who are about to take the Databricks Certified Associate Developer for Apache Spark 3.0 exam in Python
- For all IT and data professionals who want to brush up their Spark knowledge for a job interview
- For all learners who want to level up their career with an official Databricks certification
Florian is a Databricks Certified Associate Developer. His mission is to make you succeed in your Apache Spark learning journey.
Florian fell in love with Python at an MIT-founded startup and has been bringing new data science methods to the renewable energy industry, teaching many of his coworkers the principles and practicalities of great code.