Free Online Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Practice Test

Prepare Your Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Questions with Free online Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Practice Test. Get Brilliant Databricks Certified Associate Developer for Apache Spark 3.0 Exam Results with Valid Databricks Certified Associate Developer for Apache Spark 3.0 Exam Dumps.

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Total 420 Questions | Updated On: Apr 25, 2024

Question 1

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. filter

2. array_contains("cozy")

3. select

4. "itemId"

5. explode

6. "attributes"

B :

1. where

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. map

6. "attributes"

D :

1. filter

2. "array_contains(attributes, cozy)"

3. select

4. "itemId"

5. explode

6. "attributes"

E :

1. filter

2. "array_contains(attributes, 'cozy')"

3. select

4. "itemId"

5. explode

6. "attributes"

Answer: A

Question 2

Which of the following code blocks reads in parquet file /FileStore/imports.parquet as a DataFrame?

A : spark.mode("parquet").read("/FileStore/imports.parquet")

B : spark.read.path("/FileStore/imports.parquet", source="parquet")

C : spark.read().parquet("/FileStore/imports.parquet")

D : spark.read.parquet("/FileStore/imports.parquet")

E : spark.read().format('parquet').open("/FileStore/imports.parquet")

Answer: D

Question 3

You have a need to transform a column named ‘date’ to a timestamp format. Assume that the column ‘date’ is timestamp compatible. You have written the code block

down below, but it contains an error. Identify and fix it.

df.select(to_timestamp("yyyy-dd-MM", col("date"))).show()

A :

to_timestamp() is not a valid operation. Proper function is toTimestamp()

1. df.select(toTimestamp(col("date"), "yyyy-dd-MM"))

B :

to_timestamp() is not a valid operation. Proper function is toTimestamp()

1. df.select(toTimestamp("yyyy-dd-MM", col("date")))

C :

No need for the quotes.

df.select(to_timestamp(yyyy-dd-MM, col(date)))

D :

First parameter should be column and then it should be followed by the desired format.

df.select(to_timestamp(col("date"), "yyyy-dd-MM"))

Answer: D

Question 4

Which of the following is true for driver ?

A : Is a chunk of data that sit on a single machine in a cluster.

B : Responsible for executing work that will be completed in parallel.

C : Responsible for assigning work that will be completed in parallel.

D : Reports the state of some computation back to a central system.

E : Responsible for allocating resources for worker nodes.

Answer: C

Question 5

Which of the following 3 DataFrame operations are classified as a wide transformation ? Choose 3 answers:

A : orderBy()

B : drop()

C : repartition()

D : distinct()

E : filter()

F : cache()

Answer: A,C,D

Page: 1 / 84

Total 420 Questions | Updated On: Apr 25, 2024