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

1. The code block shown below should write DataFrame transactionsDf as a parquet file to path storeDir, using brotli compression and replacing any previously existing file. Choose the answer that correctly fills the blanks in the code block to accomplish this.
transactionsDf.__1__.format("parquet").__2__(__3__).option(__4__, "brotli").__5__(storeDir)

A) 1. store
2. with
3. "replacement"
4. "compression"
5. path
B) 1. write
2. mode
3. "overwrite"
4. "compression"
5. save
(Correct)
C) 1. save
2. mode
3. "replace"
4. "compression"
5. path
D) 1. write
2. mode
3. "overwrite"
4. compression
5. parquet
E) 1. save
2. mode
3. "ignore"
4. "compression"
5. path

2. Which of the following describes a valid concern about partitioning?

A) A shuffle operation returns 200 partitions if not explicitly set.
B) Short partition processing times are indicative of low skew.
C) Decreasing the number of partitions reduces the overall runtime of narrow transformations if there are more executors available than partitions.
D) No data is exchanged between executors when coalesce() is run.
E) The coalesce() method should be used to increase the number of partitions.

3. Which of the following statements about executors is correct, assuming that one can consider each of the JVMs working as executors as a pool of task execution slots?

A) There must be more slots than tasks.
B) Slot is another name for executor.
C) There must be less executors than tasks.
D) An executor runs on a single core.
E) Tasks run in parallel via slots.

4. The code block shown below should return a DataFrame with two columns, itemId and col. In this DataFrame, for each element in column attributes of DataFrame itemDf there should be a separate row in which the column itemId contains the associated itemId from DataFrame itemsDf. The new DataFrame should only contain rows for rows in DataFrame itemsDf in which the column attributes contains the element cozy.
A sample of DataFrame itemsDf is below.
Code block:
itemsDf.__1__(__2__).__3__(__4__, __5__(__6__))

A) 1. where
2. "array_contains(attributes, 'cozy')"
3. select
4. itemId
5. explode
6. attributes
B) 1. filter
2. "array_contains(attributes, cozy)"
3. select
4. "itemId"
5. explode
6. "attributes"
C) 1. filter
2. "array_contains(attributes, 'cozy')"
3. select
4. "itemId"
5. explode
6. "attributes"
D) 1. filter
2. array_contains("cozy")
3. select
4. "itemId"
5. explode
6. "attributes"
E) 1. filter
2. "array_contains(attributes, 'cozy')"
3. select
4. "itemId"
5. map
6. "attributes"

5. Which of the following describes characteristics of the Spark UI?

A) Some of the tabs in the Spark UI are named Jobs, Stages, Storage, DAGs, Executors, and SQL.
B) The Scheduler tab shows how jobs that are run in parallel by multiple users are distributed across the cluster.
C) Via the Spark UI, workloads can be manually distributed across executors.
D) There is a place in the Spark UI that shows the property spark.executor.memory.
E) Via the Spark UI, stage execution speed can be modified.

問題與答案：