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

Explanation

Correct code block:

transactionsDf.select((col("storeId").between(20, 30)) & (col("productId")==2))

Although this QUESTION NO: may make you think that it asks for a filter or where statement, it does not. It asks explicity to return a column with booleans – this should point you to the select

statement.

Another trick here is the rarely used between() method. It exists and resolves to ((storeId >= 20) AND (storeId <= 30)) in SQL. geq() and leq() do not exist.

Another riddle here is how to chain the two conditions. The only valid answer here is &. Operators like && or and are not valid. Other boolean operators that would be valid in Spark are | and.

Static notebook | Dynamic notebook: See test 1, QUESTION NO: 42 (Databricks import instructions)

Explanation

Correct code block:

transactionsDf.filter(col('predError').isin([3, 6])).count()

The isin method is the correct one to use here – the in method does not exist for the Column object.

More info: pyspark.sql.Column.isin — PySpark 3.1.2 documentation

While only one of these code blocks works, the DataFrame API is pretty flexible when it comes to accepting columns into the pow() method. The following code blocks would also work:

transactionsDf.withColumn("predErrorSquared", pow("predError", 2))

transactionsDf.withColumn("predErrorSquared", pow("predError", lit(2)))

Static notebook | Dynamic notebook: See test 1, QUESTION NO: 26 (Databricks import instructions) ,