Chapter 7 of 7 · Databricks Associate Developer for Apache Spark
Using Pandas API on Spark
When to use each, how they scale and what they cost.
- 1topics
- 4 minfast track
- 5%of the exam
Topics in this chapter
Take them in order, or jump to the one you need.
About this chapter
What this chapter covers
Using Pandas API on Spark is 5% of the Databricks Associate Developer for Apache Spark exam. It covers why you would run pandas style code on Spark and how to write a pandas UDF.
The chapter has one topic page. It explains the advantages of the pandas API on Spark, the difference from plain pandas, and how to create and call a pandas UDF with Python type hints.
Questions are single-answer multiple choice. Many show a short PySpark snippet in the stem or the options and ask what it returns, which UDF type fits a requirement, or which call meets a need. There are no exhibits.
How the topics fit together
The pandas API on Spark lets pandas users work on distributed data. A pandas UDF lets you run pandas code on batches of a Spark DataFrame inside a normal PySpark query.
- Advantage questions ask what you gain over single machine pandas.
- UDF questions ask which UDF form fits a row, batch or group requirement and how it is declared.
The word "vectorized" in an answer choice points to a pandas UDF. A plain Python UDF processes one row at a time.
How to use these pages
Each topic page has the same shape, so you can skim for what you need.
- What it is: the idea in plain words.
- How it works: the mechanism, with tables and examples.
- What to remember for the exam: the facts to memorize and how questions are phrased.
- Common mistakes: the classic traps.
- Check yourself: three questions to test your understanding.
Ready for more practice?
The full Databricks Associate Developer for Apache Spark question bank has 600 questions, with timed practice exams and an explanation for every answer.
This study guide is independent and is not affiliated with, endorsed by, or sponsored by Databricks. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.