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Databricks Certified Data Engineer Professional Exam

Last Update May 23, 2024
Total Questions : 120

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Last Update May 23, 2024
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Databricks Certified Data Engineer Professional Exam Questions and Answers

Questions 1

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 the date variable:

Databricks-Certified-Professional-Data-Engineer Question 1

Assume that the fields customer_id and order_id serve 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?

Options:

A.

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

B.

Each write to the orders table will only 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 will run deduplication over the union of new and existing records, ensuring no duplicate records are present.

Questions 2

What statement is true regarding the retention of job run history?

Options:

A.

It is retained until you export or delete job run logs

B.

It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3

C.

t is retained for 60 days, during which you can export notebook run results to HTML

D.

It is retained for 60 days, after which logs are archived

E.

It is retained for 90 days or until the run-id is re-used through custom run configuration

Questions 3

A data architect has heard about lake's built-in versioning and time travel capabilities. For auditing purposes they have a requirement to maintain a full of all valid street addresses as they appear in the customers table.

The architect is interested in implementing a Type 1 table, overwriting existing records with new values and relying on Delta Lake time travel to support long-term auditing. A data engineer on the project feels that a Type 2 table will provide better performance and scalability.

Which piece of information is critical to this decision?

Options:

A.

Delta Lake time travel does not scale well in cost or latency to provide a long-term versioning solution.

B.

Delta Lake time travel cannot be used to query previous versions of these tables because Type 1 changes modify data files in place.

C.

Shallow clones can be combined with Type 1 tables to accelerate historic queries for long-term versioning.

D.

Data corruption can occur if a query fails in a partially completed state because Type 2 tables requires

Setting multiple fields in a single update.

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