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Databricks Certification Databricks Certified Associate Developer for Apache Spark 3.0 Exam

Databricks Certified Associate Developer for Apache Spark 3.0 Exam

Last Update Apr 23, 2025
Total Questions : 180

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Questions 2

Which of the following code blocks returns a copy of DataFrame transactionsDf that only includes columns transactionId, storeId, productId and f?

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.drop(col("value"), col("predError"))

B.  

transactionsDf.drop("predError", "value")

C.  

transactionsDf.drop(value, predError)

D.  

transactionsDf.drop(["predError", "value"])

E.  

transactionsDf.drop([col("predError"), col("value")])

Discussion 0
Questions 3

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 0
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Questions 4

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 0
Questions 5

Which of the following code blocks selects all rows from DataFrame transactionsDf in which column productId is zero or smaller or equal to 3?

Options:

A.  

transactionsDf.filter(productId==3 or productId<1)

B.  

transactionsDf.filter((col("productId")==3) or (col("productId")<1))

C.  

transactionsDf.filter(col("productId")==3 | col("productId")<1)

D.  

transactionsDf.where("productId"=3).or("productId"<1))

E.  

transactionsDf.filter((col("productId")==3) | (col("productId")<1))

Discussion 0

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