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Databricks Certified Associate Developer for Apache Spark 3.0 Exam

Last Update Jul 19, 2024
Total Questions : 180

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Databricks Certified Associate Developer for Apache Spark 3.0 Exam Questions and Answers

Questions 1

Which of the following is a problem with using accumulators?

Options:

A.

Only unnamed accumulators can be inspected in the Spark UI.

B.

Only numeric values can be used in accumulators.

C.

Accumulator values can only be read by the driver, but not by executors.

D.

Accumulators do not obey lazy evaluation.

E.

Accumulators are difficult to use for debugging because they will only be updated once, independent if a task has to be re-run due to hardware failure.

Questions 2

The code block displayed below contains an error. The code block should display the schema of DataFrame transactionsDf. Find the error.

Code block:

transactionsDf.rdd.printSchema

Options:

A.

There is no way to print a schema directly in Spark, since the schema can be printed easily through using print(transactionsDf.columns), so that should be used instead.

B.

The code block should be wrapped into a print() operation.

C.

printSchema is only accessible through the spark session, so the code block should be rewritten as spark.printSchema(transactionsDf).

D.

printSchema is a method and should be written as printSchema(). It is also not callable through transactionsDf.rdd, but should be called directly from transactionsDf.

(Correct)

E.

printSchema is a not a method of transactionsDf.rdd. Instead, the schema should be printed via transactionsDf.print_schema().

Questions 3

Which of the following code blocks stores DataFrame itemsDf in executor memory and, if insufficient memory is available, serializes it and saves it to disk?

Options:

A.

itemsDf.persist(StorageLevel.MEMORY_ONLY)

B.

itemsDf.cache(StorageLevel.MEMORY_AND_DISK)

C.

itemsDf.store()

D.

itemsDf.cache()

E.

itemsDf.write.option('destination', 'memory').save()

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