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Databricks Associate-Developer-Apache-Spark-3.5 real answers - Databricks Certified Associate Developer for Apache Spark 3.5 - Python

Associate-Developer-Apache-Spark-3.5
  • Exam Code: Associate-Developer-Apache-Spark-3.5
  • Exam Name: Databricks Certified Associate Developer for Apache Spark 3.5 - Python
  • Updated: Jun 02, 2026
  • Q & A: 135 Questions and Answers
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Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:

1. 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 broadcast nested loop join
B) A shuffled hash join
C) A sort-merge join
D) A Cartesian join


2. A data scientist is working on a large dataset in Apache Spark using PySpark. The data scientist has a DataFrame df with columns user_id, product_id, and purchase_amount and needs to perform some operations on this data efficiently.
Which sequence of operations results in transformations that require a shuffle followed by transformations that do not?

A) df.groupBy("user_id").agg(sum("purchase_amount").alias("total_purchase")).repartition(10)
B) df.withColumn("purchase_date", current_date()).where("total_purchase > 50")
C) df.filter(df.purchase_amount > 100).groupBy("user_id").sum("purchase_amount")
D) df.withColumn("discount", df.purchase_amount * 0.1).select("discount")


3. A data engineer noticed improved performance after upgrading from Spark 3.0 to Spark 3.5. The engineer found that Adaptive Query Execution (AQE) was enabled.
Which operation is AQE implementing to improve performance?

A) Improving the performance of single-stage Spark jobs
B) Dynamically switching join strategies
C) Optimizing the layout of Delta files on disk
D) Collecting persistent table statistics and storing them in the metastore for future use


4. A data scientist is working on a project that requires processing large amounts of structured data, performing SQL queries, and applying machine learning algorithms. The data scientist is considering using Apache Spark for this task.
Which combination of Apache Spark modules should the data scientist use in this scenario?
Options:

A) Spark DataFrames, Spark SQL, and MLlib
B) Spark Streaming, GraphX, and Pandas API on Spark
C) Spark SQL, Pandas API on Spark, and Structured Streaming
D) Spark DataFrames, Structured Streaming, and GraphX


5. A data engineer wants to write a Spark job that creates a new managed table. If the table already exists, the job should fail and not modify anything.
Which save mode and method should be used?

A) saveAsTable with mode ErrorIfExists
B) save with mode ErrorIfExists
C) saveAsTable with mode Overwrite
D) save with mode Ignore


Solutions:

Question # 1
Answer: B
Question # 2
Answer: A
Question # 3
Answer: B
Question # 4
Answer: A
Question # 5
Answer: A

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