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Databricks Updated Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Questions and Answers by zaviyar

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Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Overview :

Exam Name: Databricks Certified Associate Developer for Apache Spark 3.0 Exam
Exam Code: Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Dumps
Vendor: Databricks Certification: Databricks Certification
Questions: 180 Q&A's Shared By: zaviyar
Question 20

Which of the following code blocks uses a schema fileSchema to read a parquet file at location filePath into a DataFrame?

Options:

A.

spark.read.schema(fileSchema).format("parquet").load(filePath)

B.

spark.read.schema("fileSchema").format("parquet").load(filePath)

C.

spark.read().schema(fileSchema).parquet(filePath)

D.

spark.read().schema(fileSchema).format(parquet).load(filePath)

E.

spark.read.schema(fileSchema).open(filePath)

Discussion
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Question 21

The code block shown below should add a column itemNameBetweenSeparators to DataFrame itemsDf. The column should contain arrays of maximum 4 strings. The arrays should be composed of

the values in column itemsDf which are separated at - or whitespace characters. Choose the answer that correctly fills the blanks in the code block to accomplish this.

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.__1__(__2__, __3__(__4__, "[\s\-]", __5__))

Options:

A.

1. withColumn

2. "itemNameBetweenSeparators"

3. split

4. "itemName"

5. 4

(Correct)

B.

1. withColumnRenamed

2. "itemNameBetweenSeparators"

3. split

4. "itemName"

5. 4

C.

1. withColumnRenamed

2. "itemName"

3. split

4. "itemNameBetweenSeparators"

5. 4

D.

1. withColumn

2. "itemNameBetweenSeparators"

3. split

4. "itemName"

5. 5

E.

1. withColumn

2. itemNameBetweenSeparators

3. str_split

4. "itemName"

5. 5

Discussion
Question 22

In which order should the code blocks shown below be run in order to create a DataFrame that shows the mean of column predError of DataFrame transactionsDf per column storeId and productId,

where productId should be either 2 or 3 and the returned DataFrame should be sorted in ascending order by column storeId, leaving out any nulls in that column?

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.| 4| null| null| 3| 2|null|

8.| 5| null| null| null| 2|null|

9.| 6| 3| 2| 25| 2|null|

10.+-------------+---------+-----+-------+---------+----+

1. .mean("predError")

2. .groupBy("storeId")

3. .orderBy("storeId")

4. transactionsDf.filter(transactionsDf.storeId.isNotNull())

5. .pivot("productId", [2, 3])

Options:

A.

4, 5, 2, 3, 1

B.

4, 2, 1

C.

4, 1, 5, 2, 3

D.

4, 2, 5, 1, 3

E.

4, 3, 2, 5, 1

Discussion
Question 23

The code block displayed below contains an error. The code block is intended to return all columns of DataFrame transactionsDf except for columns predError, productId, and value. Find the error.

Excerpt of DataFrame transactionsDf:

transactionsDf.select(~col("predError"), ~col("productId"), ~col("value"))

Options:

A.

The select operator should be replaced by the drop operator and the arguments to the drop operator should be column names predError, productId and value wrapped in the col operator so they

should be expressed like drop(col(predError), col(productId), col(value)).

B.

The select operator should be replaced with the deselect operator.

C.

The column names in the select operator should not be strings and wrapped in the col operator, so they should be expressed like select(~col(predError), ~col(productId), ~col(value)).

D.

The select operator should be replaced by the drop operator.

E.

The select operator should be replaced by the drop operator and the arguments to the drop operator should be column names predError, productId and value as strings.

(Correct)

Discussion
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