- Exam Code: Associate-Developer-Apache-Spark-3.5
- 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: DataFrame API with PySpark | - DataFrame creation and schema management - Transformations and actions - Built-in functions and expressions |
| Topic 2: Data Processing and Performance | - Optimization techniques - Caching and persistence strategies - Joins and data partitioning |
| Topic 3: Data Ingestion and Storage | - Delta Lake basics - Reading and writing data (Parquet, JSON, CSV) |
| Topic 4: Spark SQL | - Window functions and aggregations - SQL queries on DataFrames and tables |
| Topic 5: Structured Streaming Basics | - Streaming DataFrames - Windowed aggregations in streaming |
| Topic 6: Apache Spark Fundamentals | - RDD vs DataFrame vs Dataset concepts - Spark architecture and execution model |
Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:
1 of 55. A data scientist wants to ingest a directory full of plain text files so that each record in the output DataFrame contains the entire contents of a single file and the full path of the file the text was read from.
The first attempt does read the text files, but each record contains a single line. This code is shown below:
txt_path = "/datasets/raw_txt/*"
df = spark.read.text(txt_path) # one row per line by default
df = df.withColumn("file_path", input_file_name()) # add full path
Which code change can be implemented in a DataFrame that meets the data scientist's requirements?
- A. Add the option lineSep=", " to the text() function.
- B. Add the option wholetext=False to the text() function.
- C. Add the option wholetext to the text() function.
- D. Add the option lineSep to the text() function.
Correct Answer: C 🗳️
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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.date_format("timestamp", "yyyy-MM-dd")).show()
- B. dates_df.withColumn("date", f.unix_timestamp("timestamp")).show()
- C. dates_df.withColumn("date", f.from_unixtime("timestamp")).show()
- D. dates_df.withColumn("date", f.to_date("timestamp")).show()
Correct Answer: D 🗳️
Explanation: Only visible for ExamBoosts members. You can sign-up / login (it's free).
A data engineer wants to process a streaming DataFrame that receives sensor readings every second with columns sensor_id, temperature, and timestamp. The engineer needs to calculate the average temperature for each sensor over the last 5 minutes while the data is streaming.
Which code implementation achieves the requirement?
Options from the images provided:
- A.
- B.
- C.
- D.
Correct Answer: B 🗳️
Explanation: Only visible for ExamBoosts members. You can sign-up / login (it's free).
17 of 55.
A data engineer has noticed that upgrading the Spark version in their applications from Spark 3.0 to Spark 3.5 has improved the runtime of some scheduled Spark applications.
Looking further, the data engineer realizes that Adaptive Query Execution (AQE) is now enabled.
Which operation should AQE be implementing to automatically improve the Spark application performance?
- A. Optimizing the layout of Delta files on disk
- B. Collecting persistent table statistics and storing them in the metastore for future use
- C. Dynamically switching join strategies
- D. Improving the performance of single-stage Spark jobs
Correct Answer: C 🗳️
Explanation: Only visible for ExamBoosts members. You can sign-up / login (it's free).
38 of 55.
A data engineer is working with Spark SQL and has a large JSON file stored at /data/input.json.
The file contains records with varying schemas, and the engineer wants to create an external table in Spark SQL that:
Reads directly from /data/input.json.
Infers the schema automatically.
Merges differing schemas.
Which code snippet should the engineer use?
- A. CREATE EXTERNAL TABLE users
USING json
OPTIONS (path '/data/input.json', mergeAll 'true'); - B. CREATE TABLE users
USING json
OPTIONS (path '/data/input.json'); - C. CREATE EXTERNAL TABLE users
USING json
OPTIONS (path '/data/input.json', inferSchema 'true'); - D. CREATE EXTERNAL TABLE users
USING json
OPTIONS (path '/data/input.json', mergeSchema 'true');
Correct Answer: D 🗳️
Explanation: Only visible for ExamBoosts members. You can sign-up / login (it's free).
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