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

1. Which of the following statements about garbage collection in Spark is incorrect?

A) Serialized caching is a strategy to increase the performance of garbage collection.
B) Optimizing garbage collection performance in Spark may limit caching ability.
C) Manually persisting RDDs in Spark prevents them from being garbage collected.
D) In Spark, using the G1 garbage collector is an alternative to using the default Parallel garbage collector.
E) Garbage collection information can be accessed in the Spark UI's stage detail view.

2. Which of the following code blocks adds a column predErrorSqrt to DataFrame transactionsDf that is the square root of column predError?

A) transactionsDf.withColumn("predErrorSqrt", col("predError").sqrt())
B) transactionsDf.withColumn("predErrorSqrt", sqrt(predError))
C) transactionsDf.select(sqrt("predError"))
D) transactionsDf.select(sqrt(predError))
E) transactionsDf.withColumn("predErrorSqrt", sqrt(col("predError")))

3. Which of the following code blocks applies the boolean-returning Python function evaluateTestSuccess to column storeId of DataFrame transactionsDf as a user-defined function?

A) 1.from pyspark.sql import types as T
2.evaluateTestSuccessUDF = udf(evaluateTestSuccess, T.BooleanType())
3.transactionsDf.withColumn("result", evaluateTestSuccess(col("storeId")))
B) 1.from pyspark.sql import types as T
2.evaluateTestSuccessUDF = udf(evaluateTestSuccess, T.IntegerType())
3.transactionsDf.withColumn("result", evaluateTestSuccess(col("storeId")))
C) 1.evaluateTestSuccessUDF = udf(evaluateTestSuccess)
2.transactionsDf.withColumn("result", evaluateTestSuccessUDF(col("storeId")))
D) 1.from pyspark.sql import types as T
2.evaluateTestSuccessUDF = udf(evaluateTestSuccess, T.BooleanType())
3.transactionsDf.withColumn("result", evaluateTestSuccessUDF(col("storeId")))
E) 1.evaluateTestSuccessUDF = udf(evaluateTestSuccess)
2.transactionsDf.withColumn("result", evaluateTestSuccessUDF(storeId))

4. The code block displayed below contains an error. The code block should merge the rows of DataFrames transactionsDfMonday and transactionsDfTuesday into a new DataFrame, matching column names and inserting null values where column names do not appear in both DataFrames. Find the error.
Sample of DataFrame transactionsDfMonday:
1.+-------------+---------+-----+-------+---------+----+
2.|transactionId|predError|value|storeId|productId| f|
3.+-------------+---------+-----+-------+---------+----+
4.| 5| null| null| null| 2|null|
5.| 6| 3| 2| 25| 2|null|
6.+-------------+---------+-----+-------+---------+----+
Sample of DataFrame transactionsDfTuesday:
1.+-------+-------------+---------+-----+
2.|storeId|transactionId|productId|value|
3.+-------+-------------+---------+-----+
4.| 25| 1| 1| 4|
5.| 2| 2| 2| 7|
6.| 3| 4| 2| null|
7.| null| 5| 2| null|
8.+-------+-------------+---------+-----+
Code block:
sc.union([transactionsDfMonday, transactionsDfTuesday])

A) Instead of the Spark context, transactionDfMonday should be called with the join method instead of the union method, making sure to use its default arguments.
B) Instead of the Spark context, transactionDfMonday should be called with the union method.
C) The DataFrames' RDDs need to be passed into the sc.union method instead of the DataFrame variable names.
D) Instead of the Spark context, transactionDfMonday should be called with the unionByName method instead of the union method, making sure to not use its default arguments.
E) Instead of union, the concat method should be used, making sure to not use its default arguments.

5. Which of the following describes the conversion of a computational query into an execution plan in Spark?

A) The executed physical plan depends on a cost optimization from a previous stage.
B) Spark uses the catalog to resolve the optimized logical plan.
C) Depending on whether DataFrame API or SQL API are used, the physical plan may differ.
D) The catalog assigns specific resources to the physical plan.
E) The catalog assigns specific resources to the optimized memory plan.

問題與答案：