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

Question 1

Ifspark is running in client mode, which of the following statement about is correct ?

A

Spark driver is attributed to the machine that has the most resources

B

Spark driver is randomly attributed to a machine in the cluster

C

The entire spark application is run on a single machine

D

Spark driver remainse on the client machine that submitted the application.

Correct Answer: D

Explanation:

Client mode is nearly the same as cluster mode except that the Spark driver remains on the client machine that submitted the application.

Question 2

Which of the following code blocks reads from a csv file where values are separated with ‘;’ ?

A

spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)

B

spark.load.format("csv").option("header", ''true").option(“inferSchema”, “true”).read(file)

C

spark.read.format("csv").option("header", ''true").option(“inferSchema”, “true”).load(file)

D

spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “true”).toDf(file)

Correct Answer: A

Explanation:

Correct syntax is;
spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)
Get familiar with the syntax of reading and writing from/to files. You will be tested on this in your exam.

Question 3

Which of the following code blocks returns a DataFrame with a new column aSquared and all previously existing columns from DataFrame df given that df has a column named a ?

A

df.withColumn(“aSquared”, col(a) * col(a))

B

df.withColumn(col(“a”) * col(“a”), “aSquared”)

C

df.withColumn(aSquared, col(a) * col(a))

D

df.withColumn(aSquared, col(“a”) * col(“a”))

E

df.withColumn(aSquared, col(“a”) * col(“a”))

Correct Answer: E

Explanation:

You will have such questions in the exam, be careful while reading the responses.

Question 4

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

.df.withColumn(new_column, lit(1))
https://www.dumpsgeek.com/Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0-pdf-du mps.html

B

df.withColumn(”new_column”, lit(“1”))

C

df.withColumnRenamed('new_column', lit(1))

D

df.withColumn(“new_column”, 1)

E

df.withColumn(“new_column”, lit(1))

Correct Answer: E

Explanation:

The second argument for DataFrame.withColumn should be a Column so you have to use a literal to add constant value 1:

Question 5

Which of the following code blocks returns a DataFrame with two new columns ‘a’ and ‘b’ from the existing column ‘aSquared’ where the values of ‘a’ and ‘b’ is half of the column ‘aSquared’ ?

A

df.withColumn(“aSquared” /2 , col(a) ).withColumn(“aSquared” /2 , col(b) )

B

df.withColumn(aSquared/2 , col(a) ).withColumn(aSquared /2 , col(b) )

C

df.withColumn(aSquared, col(a) * col(a))

D

df.withColumn(“aSquared” /2 , col(“a”) ).withColumn(“aSquared” /2 , col(“b”) )

E

df.withColumn(“a”, col(“aSquared”)/2).withColumn(“b”, col(“aSquared”)/2)

Correct Answer: E

Explanation:

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

Ifspark is running in client mode, which of the following statement about is correct ?

Spark driver is attributed to the machine that has the most resources

Spark driver is randomly attributed to a machine in the cluster

The entire spark application is run on a single machine

Spark driver remainse on the client machine that submitted the application.

Correct Answer: D

Client mode is nearly the same as cluster mode except that the Spark driver remains on the client machine that submitted the application.

Which of the following code blocks reads from a csv file where values are separated with ‘;’ ?

spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)

spark.load.format("csv").option("header", ''true").option(“inferSchema”, “true”).read(file)

spark.read.format("csv").option("header", ''true").option(“inferSchema”, “true”).load(file)

spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “true”).toDf(file)

Correct Answer: A

Correct syntax is;
spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)
Get familiar with the syntax of reading and writing from/to files. You will be tested on this in your exam.

Which of the following code blocks returns a DataFrame with a new column aSquared and all previously existing columns from DataFrame df given that df has a column named a ?

df.withColumn(“aSquared”, col(a) * col(a))

df.withColumn(col(“a”) * col(“a”), “aSquared”)

df.withColumn(aSquared, col(a) * col(a))

df.withColumn(aSquared, col(“a”) * col(“a”))

df.withColumn(aSquared, col(“a”) * col(“a”))

Correct Answer: E

You will have such questions in the exam, be careful while reading the responses.

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 ?

.df.withColumn(new_column, lit(1))
https://www.dumpsgeek.com/Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0-pdf-du mps.html

df.withColumn(”new_column”, lit(“1”))

df.withColumnRenamed('new_column', lit(1))

df.withColumn(“new_column”, 1)

df.withColumn(“new_column”, lit(1))

Correct Answer: E

The second argument for DataFrame.withColumn should be a Column so you have to use a literal to add constant value 1:

Which of the following code blocks returns a DataFrame with two new columns ‘a’ and ‘b’ from the existing column ‘aSquared’ where the values of ‘a’ and ‘b’ is half of the column ‘aSquared’ ?

df.withColumn(“aSquared” /2 , col(a) ).withColumn(“aSquared” /2 , col(b) )

df.withColumn(aSquared/2 , col(a) ).withColumn(aSquared /2 , col(b) )

df.withColumn(aSquared, col(a) * col(a))

df.withColumn(“aSquared” /2 , col(“a”) ).withColumn(“aSquared” /2 , col(“b”) )

df.withColumn(“a”, col(“aSquared”)/2).withColumn(“b”, col(“aSquared”)/2)

Correct Answer: E

Familiarize yourself with the syntax of withColumn and withColumnRenamed.

Demo Practice Mode

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

Ifspark is running in client mode, which of the following statement about is correct ?

Spark driver is attributed to the machine that has the most resources

Spark driver is randomly attributed to a machine in the cluster

The entire spark application is run on a single machine

Spark driver remainse on the client machine that submitted the application.

Correct Answer: D

Client mode is nearly the same as cluster mode except that the Spark driver remains on the client machine that submitted the application.

Which of the following code blocks reads from a csv file where values are separated with ‘;’ ?

spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)

spark.load.format("csv").option("header", ''true").option(“inferSchema”, “true”).read(file)

spark.read.format("csv").option("header", ''true").option(“inferSchema”, “true”).load(file)

spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “true”).toDf(file)

Correct Answer: A

Correct syntax is;spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file) Get familiar with the syntax of reading and writing from/to files. You will be tested on this in your exam.

Which of the following code blocks returns a DataFrame with a new column aSquared and all previously existing columns from DataFrame df given that df has a column named a ?

df.withColumn(“aSquared”, col(a) * col(a))

df.withColumn(col(“a”) * col(“a”), “aSquared”)

df.withColumn(aSquared, col(a) * col(a))

df.withColumn(aSquared, col(“a”) * col(“a”))

df.withColumn(aSquared, col(“a”) * col(“a”))

Correct Answer: E

You will have such questions in the exam, be careful while reading the responses.

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 ?

.df.withColumn(new_column, lit(1)) https://www.dumpsgeek.com/Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0-pdf-du mps.html

df.withColumn(”new_column”, lit(“1”))

df.withColumnRenamed('new_column', lit(1))

df.withColumn(“new_column”, 1)

df.withColumn(“new_column”, lit(1))

Correct Answer: E

The second argument for DataFrame.withColumn should be a Column so you have to use a literal to add constant value 1:

Which of the following code blocks returns a DataFrame with two new columns ‘a’ and ‘b’ from the existing column ‘aSquared’ where the values of ‘a’ and ‘b’ is half of the column ‘aSquared’ ?

df.withColumn(“aSquared” /2 , col(a) ).withColumn(“aSquared” /2 , col(b) )

df.withColumn(aSquared/2 , col(a) ).withColumn(aSquared /2 , col(b) )

df.withColumn(aSquared, col(a) * col(a))

df.withColumn(“aSquared” /2 , col(“a”) ).withColumn(“aSquared” /2 , col(“b”) )

df.withColumn(“a”, col(“aSquared”)/2).withColumn(“b”, col(“aSquared”)/2)

Correct Answer: E

Familiarize yourself with the syntax of withColumn and withColumnRenamed.

Demo Practice Mode

Correct syntax is;
spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)
Get familiar with the syntax of reading and writing from/to files. You will be tested on this in your exam.

.df.withColumn(new_column, lit(1))
https://www.dumpsgeek.com/Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0-pdf-du mps.html