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Exam Code: Associate-Developer-Apache-Spark-3.5
Exam Name: Databricks Certified Associate Developer for Apache Spark 3.5 - Python
Q & A: 135 Questions and Answers
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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:

Section	Weight	Objectives
Developing Apache Spark DataFrame API Applications	30%	- Handling missing values and data quality - Joining and combining datasets - Reading and writing data in various formats - Filtering, sorting, and aggregating data - Partitioning and bucketing data - Creating DataFrames and defining schemas - User-defined functions (UDFs) - Selecting, renaming, and modifying columns
Troubleshooting and Tuning Apache Spark DataFrame API Applications	10%	- Managing memory and resource usage - Optimizing transformations and actions - Identifying performance bottlenecks - Debugging and logging
Using Spark SQL	20%	- Using catalog and metadata APIs - Working with functions and expressions - Integrating Spark SQL with DataFrames - Running SQL queries
Apache Spark Architecture and Components	20%	- Shuffling, actions, and broadcasting - Fault tolerance and garbage collection - Execution hierarchy and lazy evaluation - Execution and deployment modes - Spark architecture overview
Using Pandas API on Apache Spark	5%	- Key differences and limitations - Overview of Pandas API on Spark - Converting between Pandas and Spark structures
Structured Streaming	10%	- Defining streaming queries - Streaming concepts and architecture - Fault tolerance and state management - Output modes and triggers
Using Spark Connect to Deploy Applications	5%	- Spark Connect architecture - Running applications via Spark Connect - Connecting to remote Spark clusters

Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:

Question #1

A data engineer is asked to build an ingestion pipeline for a set of Parquet files delivered by an upstream team on a nightly basis. The data is stored in a directory structure with a base path of "/path/events/data". The upstream team drops daily data into the underlying subdirectories following the convention year/month/day.
A few examples of the directory structure are:

Which of the following code snippets will read all the data within the directory structure?