最新のAssociate-Developer-Apache-Spark問題集で試験を準備する

Databricks Associate-Developer-Apache-Spark 試験概要:

Databricks Associate-Developer-Apache-Spark 試験シラバストピック:

Databricks Certified Associate Developer for Apache Spark 3.0 認定 Associate-Developer-Apache-Spark 試験問題：

問題 #1

Which of the following code blocks returns all unique values of column storeId in DataFrame transactionsDf?

A. transactionsDf.distinct("storeId")
B. transactionsDf.filter("storeId").distinct()
C. transactionsDf["storeId"].distinct()
D. transactionsDf.select("storeId").distinct()
(Correct)
E. transactionsDf.select(col("storeId").distinct())

問題 #2

Which of the following is not a feature of Adaptive Query Execution?

A. Replace a sort merge join with a broadcast join, where appropriate.
B. Coalesce partitions to accelerate data processing.
C. Collect runtime statistics during query execution.
D. Split skewed partitions into smaller partitions to avoid differences in partition processing time.
E. Reroute a query in case of an executor failure.

問題 #3

Which of the following code blocks reads in the JSON file stored at filePath as a DataFrame?

A. spark.read.path(filePath)
B. spark.read.path(filePath, source="json")
C. spark.read.json(filePath)
D. spark.read().json(filePath)
E. spark.read().path(filePath)

問題 #4

The code block displayed below contains an error. The code block should produce a DataFrame with color as the only column and three rows with color values of red, blue, and green, respectively.
Find the error.
Code block:
1.spark.createDataFrame([("red",), ("blue",), ("green",)], "color")
Instead of calling spark.createDataFrame, just DataFrame should be called.

A. The commas in the tuples with the colors should be eliminated.
B. The colors red, blue, and green should be expressed as a simple Python list, and not a list of tuples.
C. The "color" expression needs to be wrapped in brackets, so it reads ["color"].
D. Instead of color, a data type should be specified.

問題 #5

Which of the following code blocks generally causes a great amount of network traffic?

A. DataFrame.collect()
B. DataFrame.coalesce()
C. DataFrame.count()
D. DataFrame.rdd.map()
E. DataFrame.select()

解説：