You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline that writes numerical data to a table named Table1 by using a data quality validation rule named rule1.
You need to modify rule1 to meet the following requirements:
- Ensure that amount is always greater than 0.
- Prevent an update to Table1 from being committed when data that
violates rule1 is detected.
Which statement should you execute?

• A.@dlt.expect_or_fail("rule1", "amount > 0")
• B.@dlt.expect("rule1", "amount > 0")
• C.@dlt.expect_all_or_drop({"rule1": "amount > 0"})
• D.@dlt.expect_or_drop("rule1", "amount > 0")

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Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline that writes records to a Delta table named Table1 by using a data quality rule named rule1.
You need to meet the following requirements:
- Records that violate rule1 must NOT be written to Table1, but the
pipeline must continue processing valid records.
- Data engineers must be able to review expectation metrics by using
minimal development effort.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

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Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named Catalog1. Catalog1 contains a schema named Schema1 and a table named Table1.
You need to ensure that access to the data in Table1 is controlled by using attribute-based access control (ABAC).
What should you apply to Table1, and how should you control access for users? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

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You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a complex job named Job1 that contains eight tasks. Job1 takes multiple hours to complete.
During the last job run, the final task fails due to a transient issue.
You need to retry the last task without rerunning tasks that have already completed.
What should you do?

• A.Repair the current job run.
• B.Update the job parameters.
• C.Restart Job1.
• D.Disable and reenable the job schedule.

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What is the best way to reduce Databricks compute cost for intermittent workloads?

• A.Use all-purpose clusters
• B.Enable autoscaling and auto-termination
• C.Increase cluster size
• D.Use single-node clusters only

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