Free Access Databricks.Databricks-Certified-Professional-Data-Engineer.v2025-10-30.q132 Practice Test (Page 4)

Question 11

A dataset has been defined using Delta Live Tables and includes an expectations clause:
1. CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01')
What is the expected behaviour when a batch of data containing data that violates these constraints is
processed?

A.Records that violate the expectation are added to the target dataset and recorded as invalid in the event log

B.Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log

C.Records that violate the expectation are added to the target dataset and flagged as in-valid in a field added to the target dataset

D.Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table

E.Records that violate the expectation cause the job to fail

Question 12

An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the fieldpk_id.
For auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour.
Which solution meets these requirements?

A.Create a separate history table for each pk_id resolve the current state of the table by running a union all filtering the history tables for the most recent state.

B.Use merge into to insert, update, or delete the most recent entry for each pk_id into a bronze table, then propagate all changes throughout the system.

C.Iterate through an ordered set of changes to the table, applying each in turn; rely on Delta Lake's versioning ability to create an audit log.

D.Use Delta Lake's change data feed to automatically process CDC data from an external system, propagating all changes to all dependent tables in the Lakehouse.

E.Ingest all log information into a bronze table; use merge into to insert, update, or delete the most recent entry for each pk_id into a silver table to recreate the current table state.

Question 13

An upstream source writes Parquet data as hourly batches to directories named with the current date. A nightly batch job runs the following code to ingest all data from the previous day as indicated by thedatevariable:

Assume that the fieldscustomer_idandorder_idserve as a composite key to uniquely identify each order.
If the upstream system is known to occasionally produce duplicate entries for a single order hours apart, which statement is correct?

A.Each write to the orders table willonly contain unique records, and only those records without duplicates in the target table will be written.

B.Each write to the orders table willonly contain unique records, but newly written records may have duplicates already present in the target table.

C.Each write to the orders table will only contain unique records; if existing records with the same key are present in the target table, these records will be overwritten.

D.Each write to the orders table will only contain unique records; if existing records with the same key are present in the target table, the operation will tail.

E.Each write to the orders table willrun deduplication over the union of new and existing records, ensuringno duplicate records are present.

Question 14

A junior data engineer is migrating a workload from a relational database system to the Databricks Lakehouse.
The source system uses a star schema, leveraging foreign key constrains and multi-table inserts to validate records on write.
Which consideration will impact the decisions made by the engineer while migrating this workload?

A.All Delta Lake transactions are ACID compliance against a single table, and Databricks does not enforce foreign key constraints.

B.Databricks only allows foreign key constraints on hashed identifiers, which avoid collisions in highly-parallel writes.

C.Foreign keys must reference a primary key field; multi-table inserts must leverage Delta Lake's upsert functionality.

D.Committing to multiple tables simultaneously requires taking out multiple table locks and can lead to a state of deadlock.

Question 15

Assuming that the Databricks CLI has been installed and configured correctly, which Databricks CLI command can be used to upload a custom Python Wheel to object storage mounted with the DBFS for use with a production job?

A.configure

B.fs

C.jobs

D.libraries

E.workspace

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Question 11

Question 12

Question 13

Question 14

Question 15

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