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最新的 Databricks Certification Associate-Developer-Apache-Spark-3.5 免費考試真題:

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

2. 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) Stop and restart the SparkSession after each action.
B) Avoid using a SparkSession and rely on SparkContext only.
C) Create a new SparkSession instance before each transformation.
D) Use a single SparkSession instance for the entire application.

3. 20 of 55.
What is the difference between df.cache() and df.persist() in Spark DataFrame?

A) Both cache() and persist() can be used to set the default storage level (MEMORY_AND_DISK_DESER).
B) persist() - Persists the DataFrame with the default storage level (MEMORY_AND_DISK_DESER), and cache() - Can be used to set different storage levels.
C) Both functions perform the same operation. The persist() function provides improved performance as its default storage level is DISK_ONLY.
D) cache() - Persists the DataFrame with the default storage level (MEMORY_AND_DISK_DESER), and persist() - Can be used to set different storage levels to persist the contents of the DataFrame.

4. An application architect has been investigating Spark Connect as a way to modernize existing Spark applications running in their organization.
Which requirement blocks the adoption of Spark Connect in this organization?

A) Complete Spark API support: the ability to migrate all existing code to Spark Connect without modification, including the RDD APIs
B) Debuggability: the ability to perform interactive debugging directly from the application code
C) Stability: isolation of application code and dependencies from each other and the Spark driver
D) Upgradability: the ability to upgrade the Spark applications independently from the Spark driver itself

5. Given this view definition:
df.createOrReplaceTempView("users_vw")
Which approach can be used to query the users_vw view after the session is terminated?
Options:

A) Query the users_vw using Spark
B) Persist the users_vw data as a table
C) Save the users_vw definition and query using Spark
D) Recreate the users_vw and query the data using Spark

問題與答案：