Question 1

A data engineer has a streaming job that updates a Delta table named ‘user_activities’ by the results of a join between a streaming Delta table ‘activity_logs’ and a static Delta table ‘users’.

They noticed that adding new users into the ‘users’ table does not automatically trigger updates to the ‘user_activities’ table, even when there were activities for those users in the ‘activity_logs’ table.

Which of the following likely explains this issue ?

Options :

A : The users table must be refreshed with REFRESH TABLE command for each microbatch of this join

B : This stream-static join is not stateful by default unless they set the spark configuration delta.statefulStreamStaticJoin to true.

C : The streaming portion of this stream-static join drives the join process. Only new data appearing on the streaming side of the join will trigger the processing.

D : The static portion of the stream-static join drives this join process only in batch mode.

E : In Delta Lake, static tables can not be joined with streaming tables.

Answer: C

Question 2

The data engineering team is looking for a simple solution to share part of a large Delta Lake table with the data science team. Only department-specific columns in the table need to be shared, but with different names. In addition, there is some sensitive data that must be filtered out before sharing.

Which of the following objects can be created to meet the specified requirements ?

Options :

A : A new Delta Table created using DEEP CLONE from the existing table

B : A new Delta Table created using SHALLOW CLONE from the existing table

C : A new Delta Table created using CTAS statement on the existing table

D : A stored view on the existing table

E : An ad-hoc query on the existing table

Answer: D

Question 3

The data governance team is reviewing code used for deleting records for compliance with GDPR. The following logic has been implemented to propagate delete requests from the user_lookup table to the user_aggregates table.

Assuming that user_id is a unique identifying key and that all users that have requested deletion have been removed from the user_lookup table, which statement describes whether successfully executing the above logic guarantees that the records to be deleted from the user_aggregates table are no longer accessible and why?

Options :

A : No; the Delta Lake DELETE command only provides ACID guarantees when combined with the MERGE INTO command.

B : No; files containing deleted records may still be accessible with time travel until a VACUUM command is used to remove invalidated data files.

C : Yes; the change data feed uses foreign keys to ensure delete consistency throughout the Lakehouse.

D : Yes; Delta Lake ACID guarantees provide assurance that the DELETE command succeeded fully and permanently purged these records.

E : No; the change data feed only tracks inserts and updates, not deleted records.

Answer: B

Question 4

You are testing a collection of mathematical functions, one of which calculates the area under a curve as described by another function. assert(myIntegrate(lambda x: x*x, 0, 3) [0] == 9) Which kind of test would the above line exemplify?

Options :

A : Unit

B : Manual

C : Functional

D : Integration

E : End-to-end

Answer: A

Question 5

A data engineering team has a time-consuming data ingestion job with three data sources. Each notebook takes about one hour to load new data. One day, the job fails because a notebook update introduced a new required configuration parameter. The team must quickly fix the issue and load the latest data from the failing source. Which action should the team take?

Options :

A : Repair the run with the new parameter, and update the task by adding the missing task parameter.

B : Update the task by adding the missing task parameter, and manually run the job.

C : Repair the run with the new parameter.

D : Share the analysis with the failing notebook owner so that they can fix it quickly.

Answer: A

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