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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Spark SQL | - Window functions and aggregations - SQL queries on DataFrames and tables |
| Apache Spark Fundamentals | - Spark architecture and execution model - RDD vs DataFrame vs Dataset concepts |
| Structured Streaming Basics | - Streaming DataFrames - Windowed aggregations in streaming |
| DataFrame API with PySpark | - Transformations and actions - Built-in functions and expressions - DataFrame creation and schema management |
| Data Ingestion and Storage | - Delta Lake basics - Reading and writing data (Parquet, JSON, CSV) |
| Data Processing and Performance | - Joins and data partitioning - Caching and persistence strategies - Optimization techniques |
Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:
24 of 55.
Which code should be used to display the schema of the Parquet file stored in the location events.parquet?
- A. spark.sql("SELECT * FROM events.parquet").show()
- B. spark.sql("SELECT schema FROM events.parquet").show()
- C. spark.read.parquet("events.parquet").printSchema()
- D. spark.read.format("parquet").load("events.parquet").show()
Correct Answer: C 🗳️
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7 of 55.
A developer has been asked to debug an issue with a Spark application. The developer identified that the data being loaded from a CSV file is being read incorrectly into a DataFrame.
The CSV file has been read using the following Spark SQL statement:
CREATE TABLE locations
USING csv
OPTIONS (path '/data/locations.csv')
The first lines of the command SELECT * FROM locations look like this:
| city | lat | long |
| ALTI Sydney | -33... | ... |
Which parameter can the developer add to the OPTIONS clause in the CREATE TABLE statement to read the CSV data correctly again?
- A. 'sep' '|'
- B. 'header' 'false'
- C. 'sep' ','
- D. 'header' 'true'
Correct Answer: D 🗳️
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A data analyst wants to add a column date derived from a timestamp column.
Options:
- A. dates_df.withColumn("date", f.from_unixtime("timestamp")).show()
- B. dates_df.withColumn("date", f.date_format("timestamp", "yyyy-MM-dd")).show()
- C. dates_df.withColumn("date", f.to_date("timestamp")).show()
- D. dates_df.withColumn("date", f.unix_timestamp("timestamp")).show()
Correct Answer: C 🗳️
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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 tasks, and each task contains multiple jobs.
- D. A stage contains multiple jobs, and each job contains multiple tasks.
Correct Answer: B 🗳️
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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").distinct()
- B. df.select("Name").orderBy(df["Name"].asc())
- C. df.select("Name").distinct().orderBy(df["Name"].desc())
- D. df.select("Name").distinct().orderBy(df["Name"])
Correct Answer: D 🗳️
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