Databricks Exam Databricks-Certified-Professional-Data-Engineer Topic 1 Question 22 Discussion

Actual exam question for Databricks's Databricks-Certified-Professional-Data-Engineer exam

Question #: 22
Topic #: 1

[All Databricks-Certified-Professional-Data-Engineer Questions]

A user wants to use DLT expectations to validate that a derived table report contains all records from the source, included in the table validation_copy.

The user attempts and fails to accomplish this by adding an expectation to the report table definition.

Which approach would allow using DLT expectations to validate all expected records are present in this table?

ADefine a SQL UDF that performs a left outer join on two tables, and check if this returns null values for report key values in a DLT expectation for the report table.

BDefine a function that performs a left outer join on validation_copy and report and report, and check against the result in a DLT expectation for the report table

CDefine a temporary table that perform a left outer join on validation_copy and report, and define an expectation that no report key values are null

DDefine a view that performs a left outer join on validation_copy and report, and reference this view in DLT expectations for the report table

Show Suggested Answer

Suggested Answer: D

To validate that all records from the source are included in the derived table, creating a view that performs a left outer join between the validation_copy table and the report table is effective. The view can highlight any discrepancies, such as null values in the report table's key columns, indicating missing records. This view can then be referenced in DLT (Delta Live Tables) expectations for the report table to ensure data integrity. This approach allows for a comprehensive comparison between the source and the derived table.

Databricks Documentation on Delta Live Tables and Expectations: Delta Live Tables Expectations

by Sheridan at Sep 19, 2024, 12:52 AM

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Essie

6 months ago

Ah, the joys of data validation. It's like trying to herd cats - except the cats are your source data and the herder is a SQL query. Good luck with that!

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Matilda

5 months ago

D) Define a view that performs a left outer join on validation_copy and report, and reference this view in DLT expectations for the report table

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Flo

5 months ago

C) Define a temporary table that perform a left outer join on validation_copy and report, and define an expectation that no report key values are null

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Wynell

5 months ago

B) Define a function that performs a left outer join on validation_copy and report and report, and check against the result in a DLT expectation for the report table

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Gabriele

5 months ago

A) Define a SQL UDF that performs a left outer join on two tables, and check if this returns null values for report key values in a DLT expectation for the report table.

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Lajuana

6 months ago

Option C sounds good to me. Temporary tables are a nice way to encapsulate the join logic without cluttering up the main report definition.

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France

6 months ago

I hope the exam proctors don't catch me looking up the answer key on my smartwatch. That would be a total DLT (disaster).

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Ruby

6 months ago

Option B seems the most straightforward approach. Directly joining the tables and checking the results in the DLT expectation is the clearest way to validate the records are present.

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Tricia

5 months ago

Let's go with option B then.

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Jules

5 months ago

That's true, it's the most straightforward approach.

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Cecily

5 months ago

I agree, directly joining the tables makes it clear.

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Dalene

5 months ago

I think option B is the best choice.

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Carri

6 months ago

I'm gonna have to go with option A. Who doesn't love a good SQL UDF? It's like the duct tape of data validation - it may not be pretty, but it gets the job done.

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Jacki

5 months ago

Definitely, option A seems like the most reliable choice for using DLT expectations.

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Josefa

5 months ago

I agree, SQL UDFs can be a lifesaver when it comes to data validation.

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Julio

6 months ago

Option A sounds like the way to go. SQL UDFs are always handy for these situations.

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Herminia

6 months ago

Haha, I bet the user's first attempt involved just staring at the report table and willing the records to appear. Option B is where it's at!

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Anna

5 months ago

User 3: Yeah, defining a function that performs a left outer join on validation_copy and report seems like the right approach.

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Rolande

6 months ago

Option B is where it's at!

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Linsey

6 months ago

Haha, I bet the user's first attempt involved just staring at the report table and willing the records to appear.

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Temeka

7 months ago

I like the idea of using a temporary table in option C, but defining a view feels more robust and maintainable in the long run.

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Jacquline

7 months ago

Hmm, that's a good point. Option D) does sound simpler. I might reconsider my choice now.

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Mitzie

7 months ago

I disagree, I believe option D) is the way to go. Defining a view that performs a left outer join and referencing it in DLT expectations seems more straightforward.

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Jacquline

7 months ago

I think option A) is the best approach because it involves using a SQL UDF to perform a left outer join and check for null values in the DLT expectation.

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Paz

7 months ago

Option D seems like the way to go. Defining a view to perform the left outer join and then referencing that in the DLT expectations is a clean and efficient approach.

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Eva

6 months ago

I think I'll give that a try, thanks for the suggestion!

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Yuette

6 months ago

Definitely, it's a smart way to ensure all expected records are present in the table without complicating the report table definition.

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Tammy

6 months ago

I agree, using a view would simplify the process and make it easier to manage the validation of records.

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Luann

6 months ago

Option D seems like the way to go. Defining a view to perform the left outer join and then referencing that in the DLT expectations is a clean and efficient approach.

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