Exam Name: Databricks Certified Associate Developer for Apache Spark 3.5 - Python
Certification Provider: Databricks
Corresponding Certification: Databricks Certification
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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Apache Spark Fundamentals | - Spark architecture and execution model - RDD vs DataFrame vs Dataset concepts |
| Topic 2: Spark SQL | - Window functions and aggregations - SQL queries on DataFrames and tables |
| Topic 3: DataFrame API with PySpark | - Built-in functions and expressions - DataFrame creation and schema management - Transformations and actions |
| Topic 4: Data Ingestion and Storage | - Reading and writing data (Parquet, JSON, CSV) - Delta Lake basics |
| Topic 5: Structured Streaming Basics | - Windowed aggregations in streaming - Streaming DataFrames |
| Topic 6: Data Processing and Performance | - Optimization techniques - Joins and data partitioning - Caching and persistence strategies |
Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:
36 of 55.
What is the main advantage of partitioning the data when persisting tables?
- A. It ensures that data is loaded into memory all at once for faster query execution.
- B. It automatically cleans up unused partitions to optimize storage.
- C. It optimizes by reading only the relevant subset of data from fewer partitions.
- D. It compresses the data to save disk space.
Correct Answer: C 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
What is the relationship between jobs, stages, and tasks during execution in Apache Spark?
Options:
- A. A job contains multiple tasks, and each task contains multiple stages.
- B. A job contains multiple stages, and each stage contains multiple tasks.
- C. A stage contains multiple jobs, and each job contains multiple tasks.
- D. A stage contains multiple tasks, and each task contains multiple jobs.
Correct Answer: B 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
Which feature of Spark Connect is considered when designing an application to enable remote interaction with the Spark cluster?
- A. It provides a way to run Spark applications remotely in any programming language
- B. It is primarily used for data ingestion into Spark from external sources
- C. It can be used to interact with any remote cluster using the REST API
- D. It allows for remote execution of Spark jobs
Correct Answer: D 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
A developer notices that all the post-shuffle partitions in a dataset are smaller than the value set for spark.sql.adaptive.maxShuffledHashJoinLocalMapThreshold.
Which type of join will Adaptive Query Execution (AQE) choose in this case?
- A. A shuffled hash join
- B. A sort-merge join
- C. A broadcast nested loop join
- D. A Cartesian join
Correct Answer: A 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
A data engineer is working on the DataFrame:
(Referring to the table image: it has columns Id, Name, count, and timestamp.) Which code fragment should the engineer use to extract the unique values in the Name column into an alphabetically ordered list?
- A. df.select("Name").orderBy(df["Name"].asc())
- B. df.select("Name").distinct().orderBy(df["Name"])
- C. df.select("Name").distinct().orderBy(df["Name"].desc())
- D. df.select("Name").distinct()
Correct Answer: B 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
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