Question 1

You had AUTO LOADER to process millions of files a day and noticed slowness in load process, so you scaled up the Databricks cluster but realized the performance of the Auto loader is still not improving, what is the best way to resolve this.

Options :

A : AUTO LOADER is not suitable to process millions of files a day

B : Setup a second AUTO LOADER process to process the data

C : Increase the maxFilesPerTrigger option to a sufficiently high number

D :

Copy the data from cloud storage to local disk on the cluster for faster access

E : Merge files to one large file

Answer: C

Question 2

Which of the following must be specified when creating a new Delta Live Tables pipeline?

Options :

A : A key-value pair configuration

B : The preferred DBU/hour cost

C : A path to cloud storage location for the written data

D : A location of a target database for the written data

E : At least one notebook library to be executed

Answer: E

Question 3

A data engineer and data analyst are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.

Which of the following changes will need to be made to the pipeline when migrating to Delta Live Tables?

Options :

A : None of these changes will need to be made

B : The pipeline will need to stop using the medallion-based multi-hop architecture

C : The pipeline will need to be written entirely in SQL

D : The pipeline will need to use a batch source in place of a streaming source

E : The pipeline will need to be written entirely in Python

Answer: B

Question 4

Which of the following SQL statement can be used to query a table by eliminating duplicate rows from the query results?

Options :

A : SELECT DISTINCT * FROM table_name

B : SELECT DISTINCT * FROM table_name HAVING COUNT(*) > 1

C : SELECT DISTINCT_ROWS (*) FROM table_name

D : SELECT * FROM table_name GROUP BY * HAVING COUNT(*) < 1

E : SELECT * FROM table_name GROUP BY * HAVING COUNT(*) > 1

Answer: A

Question 5

A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.

Which command could the data engineering team use to access sales in PySpark?

Options :

A : SELECT * FROM sales

B : spark.table("sales")

C : spark.sql("sales")

D : spark.delta.table("sales")

Answer: B

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