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Databricks Databricks-Certified-Data-Engineer-Associate - Databricks Certified Data Engineer Associate Exam

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Total 153 questions

A data engineer has written a function in a Databricks Notebook to calculate the population of bacteria in a given medium.

Analysts use this function in the notebook and sometimes provide input arguments of the wrong data type, which can cause errors during execution.

Which Databricks feature will help the data engineer quickly identify if an incorrect data type has been provided as input?

A.

The Data Engineer should add print statements to find out what the variable is.

B.

The Databricks debugger enables breakpoints that will raise an error if the wrong data type is submitted

C.

The Spark User interface has a debug tab that contains the variables that are used in this session.

D.

The Databricks debugger enables the use of a variable explorer to see at a glance the value of the variables.

A data engineer needs to create a table in Databricks using data from a CSV file at location /path/to/csv.

They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

A.

None of these lines of code are needed to successfully complete the task

B.

USING CSV

C.

FROM CSV

D.

USING DELTA

E.

FROM "path/to/csv"

A data engineer needs access to a table new_uable, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is.

Which approach can be used to identify the owner of new_table?

A.

There is no way to identify the owner of the table

B.

Review the Owner field in the table's page in the cloud storage solution

C.

Review the Permissions tab in the table's page in Data Explorer

D.

Review the Owner field in the table’s page in Data Explorer

A data engineer is inspecting an ETL pipeline based on a Pyspark job that consistently encounters performance bottlenecks. Based on developer feedback, the data engineer assumes the job is low on compute resources. To pinpoint the issue, the data engineer observes the Spark Ul and finds out the job has a high CPU time vs Task time.

Which course of action should the data engineer take?

A.

High CPU time vs Task time means an under-utilized cluster. The data engineer may need to repartition data to spread the jobs more evenly throughout the cluster.

B.

High CPU time vs Task time means efficient use of cluster and no change needed

C.

High CPU time vs Task time means over-utilized memory and the need to increase parallelism

D.

High CPU time vs Task time means a CPU over-utilized job. The data engineer may need to consider executor and core tuning or resizing the cluster

A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.

Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

A.

They can turn on the Auto Stop feature for the SQL endpoint.

B.

They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.

C.

They can reduce the cluster size of the SQL endpoint.

D.

They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.

E.

They can set up the dashboard's SQL endpoint to be serverless.