Free Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Questions

Become Databricks Certified with updated Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam questions and correct answers

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Total 420 Questions | Updated On: Feb 05, 2025

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Question 1

The code block shown below should return a column that indicates through boolean variables whether rows in DataFrame transactionsDf have values greater or equal to 20 and smaller or equal to 30 in column storeId and have the value 2 in column productId. Choose the answer that correctly fills the

blanks in the code block to accomplish this.

transactionsDf.__1__((__2__.__3__) __4__ (__5__))

A : 1. select 2. col("storeId") 3. between(20, 30) 4. and 5. col("productId")==2

B : 1. where2. col("storeId")3. geq(20).leq(30)4. &5. col("productId")==2

C : 1. select2. "storeId"3. between(20, 30)4. &&5. col("productId")==2

D : 1. select2. col("storeId")3. between(20, 30)4. &&5. col("productId")=2

E : 1. select2. col("storeId")3. between(20, 30)4. &5. col("productId")==2

Answer: D

Question 2

If we want to create a constant integer 1 as a new column ‘new_column’ in a dataframe df, which code block we should select ?

A : .withColumn(“new_column”, 1)

B : .withColumn(new_column, lit(1))

C : .withColumn”'new_column”, lit(“1”))

D : .withColumnRenamed('new_column', lit(1))

E : .withColumn(“new_column”, lit(1))

Answer: A

Question 3

Given the code block down below, a database test containing nulls, identify the error

1. def my_udf(s):

2. If s is not null:

3. return len(s)

5. spark.udf.register("strlen", my_udf)

6. spark.sql("select s from test where s is not null and strlen(s) > 1")

A : ere are no problems in this query.

B : need to use function ‘query’ instead of ‘sql’ to query table test.

C : need to create the function first and then pass it to udf.register

D : is WHERE clause does not guarantee the strlen UDF to be invoked after filtering out nulls. So we will have null pointer

Answer: A

Question 4

How to make sure that dataframe df has 12 partitions given that df has 4 partitions ?

A : .repartition(12)

B : .setPartitition(12)

C : .repartition()

D : .setPartitition()

Answer: A

Question 5

When joining two dataframes, if there is a need to evaluate the keys in both of the DataFrames or tables and include all rows from the right DataFrame as well as any rows

in the left DataFrame that have a match in the righ DataFrame also If there is no equivalent row in the left DataFrame, we want to instert null: which join type we should

select ? df1.join(person, joinExpression, joinType)

A : joinType = “right_outer”

B : inType = “rightSemi”

C : joinType = “rightAnti”

D : joinType = “rightOuter”

Answer: A

Page: 1 / 84

Total 420 Questions | Updated On: Feb 05, 2025

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