Associate-Developer-Apache-Spark-3.5試験無料問題集（135題）「Databricks Certified Associate Developer for Apache Spark 3.5

出題：1

Given:
python
CopyEdit
spark.sparkContext.setLogLevel("<LOG_LEVEL>")
Which set contains the suitable configuration settings for Spark driver LOG_LEVELs?

A. FATAL, NONE, INFO, DEBUG

B. ERROR, WARN, TRACE, OFF

C. ALL, DEBUG, FAIL, INFO

D. WARN, NONE, ERROR, FATAL

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

A Spark engineer must select an appropriate deployment mode for the Spark jobs.
What is the benefit of using cluster mode in Apache Spark™?

A. In cluster mode, resources are allocated from a resource manager on the cluster, enabling better performance and scalability for large jobs

B. In cluster mode, the driver runs on the client machine, which can limit the application's ability to handle large datasets efficiently.

C. In cluster mode, the driver program runs on one of the worker nodes, allowing the application to fully utilize the distributed resources of the cluster.

D. In cluster mode, the driver is responsible for executing all tasks locally without distributing them across the worker nodes.

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

5 of 55.
What is the relationship between jobs, stages, and tasks during execution in Apache Spark?

A. A job contains multiple stages, and each stage contains multiple tasks.

B. A stage contains multiple jobs, and each job contains multiple tasks.

C. A stage contains multiple tasks, and each task contains multiple jobs.

D. A job contains multiple tasks, and each task contains multiple stages.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

A developer wants to test Spark Connect with an existing Spark application.
What are the two alternative ways the developer can start a local Spark Connect server without changing their existing application code? (Choose 2 answers)

A. Ensure the Spark property spark.connect.grpc.binding.port is set to 15002 in the application code

B. Add .remote("sc://localhost") to their SparkSession.builder calls in their Spark code

C. Execute their pyspark shell with the option --remote "sc://localhost"

D. Execute their pyspark shell with the option --remote "https://localhost"

E. Set the environment variable SPARK_REMOTE="sc://localhost" before starting the pyspark shell

正解：C,E 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

30 of 55.
A data engineer is working on a num_df DataFrame and has a Python UDF defined as:
def cube_func(val):
return val * val * val
Which code fragment registers and uses this UDF as a Spark SQL function to work with the DataFrame num_df?

A. spark.createDataFrame(cube_func("num")).show()

B. spark.udf.register("cube_func", cube_func)
num_df.selectExpr("cube_func(num)").show()

C. num_df.register("cube_func").select("num").show()

D. num_df.select(cube_func("num")).show()

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：6

35 of 55.
A data engineer is building a Structured Streaming pipeline and wants it to recover from failures or intentional shutdowns by continuing where it left off.
How can this be achieved?

A. By configuring the option recoveryLocation during writeStream.

B. By configuring the option recoveryLocation during SparkSession initialization.

C. By configuring the option checkpointLocation during readStream.

D. By configuring the option checkpointLocation during writeStream.

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：7

32 of 55.
A developer is creating a Spark application that performs multiple DataFrame transformations and actions. The developer wants to maintain optimal performance by properly managing the SparkSession.
How should the developer handle the SparkSession throughout the application?

A. Avoid using a SparkSession and rely on SparkContext only.

B. Stop and restart the SparkSession after each action.

C. Use a single SparkSession instance for the entire application.

D. Create a new SparkSession instance before each transformation.

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

Associate-Developer-Apache-Spark-3.5試験無料問題集「Databricks Certified Associate Developer for Apache Spark 3.5 - Python 認定」