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Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0
Exam Name:
Databricks Certified Associate Developer for Apache Spark 3.0 Exam
Certification:
Vendor:
Questions:
180
Last Updated:
May 15, 2025
Exam Status:
Stable
Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0

Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0: Databricks Certification Exam 2025 Study Guide Pdf and Test Engine

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

Question 1

The code block displayed below contains an error. The code block below is intended to add a column itemNameElements to DataFrame itemsDf that includes an array of all words in column

itemName. Find the error.

Sample of DataFrame itemsDf:

1.+------+----------------------------------+-------------------+

2.|itemId|itemName |supplier |

3.+------+----------------------------------+-------------------+

4.|1 |Thick Coat for Walking in the Snow|Sports Company Inc.|

5.|2 |Elegant Outdoors Summer Dress |YetiX |

6.|3 |Outdoors Backpack |Sports Company Inc.|

7.+------+----------------------------------+-------------------+

Code block:

itemsDf.withColumnRenamed("itemNameElements", split("itemName"))

itemsDf.withColumnRenamed("itemNameElements", split("itemName"))

Options:

A.

All column names need to be wrapped in the col() operator.

B.

Operator withColumnRenamed needs to be replaced with operator withColumn and a second argument "," needs to be passed to the split method.

C.

Operator withColumnRenamed needs to be replaced with operator withColumn and the split method needs to be replaced by the splitString method.

D.

Operator withColumnRenamed needs to be replaced with operator withColumn and a second argument " " needs to be passed to the split method.

E.

The expressions "itemNameElements" and split("itemName") need to be swapped.

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Question 2

Which of the following code blocks returns a DataFrame where columns predError and productId are removed from DataFrame transactionsDf?

Sample of DataFrame transactionsDf:

1.+-------------+---------+-----+-------+---------+----+

2.|transactionId|predError|value|storeId|productId|f |

3.+-------------+---------+-----+-------+---------+----+

4.|1 |3 |4 |25 |1 |null|

5.|2 |6 |7 |2 |2 |null|

6.|3 |3 |null |25 |3 |null|

7.+-------------+---------+-----+-------+---------+----+

Options:

A.

transactionsDf.withColumnRemoved("predError", "productId")

B.

transactionsDf.drop(["predError", "productId", "associateId"])

C.

transactionsDf.drop("predError", "productId", "associateId")

D.

transactionsDf.dropColumns("predError", "productId", "associateId")

E.

transactionsDf.drop(col("predError", "productId"))

Question 3

The code block shown below should show information about the data type that column storeId of DataFrame transactionsDf contains. Choose the answer that correctly fills the blanks in the code

block to accomplish this.

Code block:

transactionsDf.__1__(__2__).__3__

Options:

A.

1. select

2. "storeId"

3. print_schema()

B.

1. limit

2. 1

3. columns

C.

1. select

2. "storeId"

3. printSchema()

D.

1. limit

2. "storeId"

3. printSchema()

E.

1. select

2. storeId

3. dtypes