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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:
Apr 27, 2025
Exam Status:
Stable
Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0

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

Question 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)

Options:

A.

1. save

2. mode

3. "ignore"

4. "compression"

5. path

B.

1. store

2. with

3. "replacement"

4. "compression"

5. path

C.

1. write

2. mode

3. "overwrite"

4. "compression"

5. save

(Correct)

D.

1. save

2. mode

3. "replace"

4. "compression"

5. path

E.

1. write

2. mode

3. "overwrite"

4. compression

5. parquet

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Question 2

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

Options:

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")

Question 3

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"))