Question 1

A nightly batch job is configured to ingest all data files from a cloud object storage container where records are stored in a nested directory structure YYYY/MM/DD. The data for each date represents all records that were processed by the source system on that date, noting that some records may be delayed as they await moderator approval. Each entry represents a user review of a product and has the following schema:

user_id STRING, review_id BIGINT, product_id BIGINT, review_timestamp TIMESTAMP, review_text STRING

The ingestion job is configured to append all data for the previous date to a target table reviews_raw with an identical schema to the source system. The next step in the pipeline is a batch write to propagate all new records inserted into reviews_raw to a table where data is fully deduplicated, validated, and enriched.

Which solution minimizes the compute costs to propagate this batch of data?

Options :

A : Perform a batch read on the reviews_raw table and perform an insert-only merge using the natural composite key user_id, review_id, product_id, review_timestamp.

B : Configure a Structured Streaming read against the reviews_raw table using the trigger once execution mode to process new records as a batch job.

C : Use Delta Lake version history to get the difference between the latest version of reviews_raw and one version prior, then write these records to the next table.

D : Filter all records in the reviews_raw table based on the review_timestamp; batch append those records produced in the last 48 hours.

E : Reprocess all records in reviews_raw and overwrite the next table in the pipeline.

Answer: A

Question 2

A junior data engineer seeks to leverage Delta Lake's Change Data Feed functionality to create a Type 1 table representing all of the values that have ever been valid for all rows in a bronze table created with the property delta.enableChangeDataFeed = true. They plan to execute the following code as a daily job:

Databricks-Certified-Professional-Data-Engineer-page61-image24

Which statement describes the execution and results of running the above query multiple times?

Options :

A :

Each time the job is executed, newly updated records will be merged into the target table, overwriting previous values with the same primary keys.

B :

Each time the job is executed, the entire available history of inserted or updated records will be appended to the target table, resulting in many duplicate entries.

C :

Each time the job is executed, the target table will be overwritten using the entire history of inserted or updated records, giving the desired result.

D :

Each time the job is executed, the differences between the original and current versions are calculated; this may result in duplicate entries for some records.

E :

Each time the job is executed, only those records that have been inserted or updated since the last execution will be appended to the target table, giving the desired result.

Answer: B

Question 3

Which of the following describes Cron syntax in Databricks Jobs ?

Options :

A : It’s an expression to represent the maximum concurrent runs of a job

B : It’s an expression to represent the retry policy of a job

C : It’s an expression to describe the email notification events (start, success, failure)

D : It’s an expression to represent the run timeout of a job

E : It’s an expression to represent complex job schedule that can be defined programmatically

Answer: E

Question 4

Given the following code block in a notebook

db_password = dbutils.secrets.get(scope="dev", key="database_password")

print (db_password)

Which statement describes what will happen when the above code is executed?

Options :

A : An interactive input box will appear in the notebook

B : The string "REDACTED" will be printed.

C : The error message “Secrets can not be printed” will be shown

D : The string value of the password will be printed in plain text.

E : If the user has “Can Read” permission, the string value of the password will be printed in plain text. Otherwise, the string "REDACTED" will be printed

Answer: B

Question 5

Which statement describes Delta Lake optimized writes?

Options :

A : Before a Jobs cluster terminates, OPTIMIZE is executed on all tables modified during the most recent job.

B : An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an OPTIMIZE job is executed toward a default of 1 GB.

C : Data is queued in a messaging bus instead of committing data directly to memory; all data is committed from the messaging bus in one batch once the job is complete.

D : Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.

E : A shuffle occurs prior to writing to try to group similar data together resulting in fewer files instead of each executor writing multiple files based on directory partitions.

Answer: E

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