Associate-Developer-Apache-Spark 試験問題を無料オンラインアクセス

Which of the following code blocks performs an inner join between DataFrame itemsDf and DataFrame transactionsDf, using columns itemId and transactionId as join keys, respectively?

• A.itemsDf.join(transactionsDf, "inner", itemsDf.itemId == transactionsDf.transactionId)
• B.itemsDf.join(transactionsDf, col(itemsDf.itemId) == col(transactionsDf.transactionId))
• C.itemsDf.join(transactionsDf, "itemsDf.itemId == transactionsDf.transactionId", "inner")
• D.itemsDf.join(transactionsDf, itemId == transactionId)
• E.itemsDf.join(transactionsDf, itemsDf.itemId == transactionsDf.transactionId, "inner")

The code block displayed below contains an error. The code block should return DataFrame transactionsDf, but with the column storeId renamed to storeNumber. Find the error.
Code block:
transactionsDf.withColumn("storeNumber", "storeId")

• A.Instead of withColumn, the withColumnRenamed method should be used and argument "storeId" should be the first and argument "storeNumber" should be the second argument to that method.
• B.The withColumn operator should be replaced with the copyDataFrame operator.
• C.Instead of withColumn, the withColumnRenamed method should be used.
• D.Argument "storeId" should be the first and argument "storeNumber" should be the second argument to the withColumn method.
• E.Arguments "storeNumber" and "storeId" each need to be wrapped in a col() operator.

The code block shown below should return a one-column DataFrame where the column storeId is converted to string type. Choose the answer that correctly fills the blanks in the code block to accomplish this.
transactionsDf.__1__(__2__.__3__(__4__))

• A.1. select
  2. storeId
  3. cast
  4. StringType()
• B.1. cast
  2. "storeId"
  3. as
  4. StringType()
• C.1. select
  2. col("storeId")
  3. as
  4. StringType
• D.1. select
  2. col("storeId")
  3. cast
  4. StringType()
• E.1. select
  2. col("storeId")
  3. cast
  4. StringType

Which of the following code blocks returns a DataFrame showing the mean value of column "value" of DataFrame transactionsDf, grouped by its column storeId?

• A.transactionsDf.groupBy("storeId").agg(average("value"))
• B.transactionsDf.groupBy("storeId").agg(avg("value"))
• C.transactionsDf.groupBy("storeId").avg(col("value"))
• D.transactionsDf.groupBy(col(storeId).avg())
• E.transactionsDf.groupBy("value").average()

The code block displayed below contains an error. The code block should return all rows of DataFrame transactionsDf, but including only columns storeId and predError. Find the error.
Code block:
spark.collect(transactionsDf.select("storeId", "predError"))

• A.Instead of collect, collectAsRows needs to be called.
• B.Columns storeId and predError need to be represented as a Python list, so they need to be wrapped in brackets ([]).
• C.The collect method is not a method of the SparkSession object.
• D.Instead of select, DataFrame transactionsDf needs to be filtered using the filter operator.
• E.The take method should be used instead of the collect method.