Databricks Certified-Data-Engineer-Professional Exam : Databricks Certified Data Engineer Professional

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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer is designing a secure data sharing strategy for their organization. The company needs to share sensitive customer analytics data with two different partners. Partner A uses Databricks with Unity Catalog enabled, while Partner B uses Apache Spark on AWS without Databricks. How should the company implement secure data sharing for these scenarios?

A) For Partner A, implement Databricks-to-Databricks sharing (D2D) with Unit Catalog integration and no-token exchange system. For Partner B, use open sharing protocol (D2O) with either bearer tokens or OIDC federation for authentication, ensuring both approaches maintain robust security and governance.
B) Both partners should use the same Delta Sharing approach since security requirements are identical. You should create bearer tokens for both partners and use the open sharing protocol (D2O) for maximum compatibility.
C) Open sharing protocol (D2O) should be used for both partners because it provides better security than D2D sharing. The bearer token approach is always more secure than Unity Catalog's native authentication.
D) Databricks-to-Databricks sharing (D2D) can only be used within the same cloud provider, so you must use open sharing (D2O) for any cross-cloud scenarios. Unit Catalog governance is not available when sharing with external platforms.

2. Where in the Spark UI can one diagnose a performance problem induced by not leveraging predicate push-down?

A) In the Delta Lake transaction log. by noting the column statistics
B) In the Stage's Detail screen, in the Completed Stages table, by noting the size of data read from the Input column
C) In the Query Detail screen, by interpreting the Physical Plan
D) In the Storage Detail screen, by noting which RDDs are not stored on disk
E) In the Executor's log file, by gripping for "predicate push-down"

3. All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion.
However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?

A) Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.
B) Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
C) Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
D) All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.
E) Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.

4. Which configuration parameter directly affects the size of a spark-partition upon ingestion of data into Spark?

A) spark.sql.adaptive.coalescePartitions.minPartitionNum
B) spark.sql.files.maxPartitionBytes
C) spark.sql.adaptive.advisoryPartitionSizeInBytes
D) spark.sql.autoBroadcastJoinThreshold
E) spark.sql.files.openCostInBytes

5. A data architect has designed a system in which two Structured Streaming jobs will concurrently write to a single bronze Delta table. Each job is subscribing to a different topic from an Apache Kafka source, but they will write data with the same schema. To keep the directory structure simple, a data engineer has decided to nest a checkpoint directory to be shared by both streams.
The proposed directory structure is displayed below:

Which statement describes whether this checkpoint directory structure is valid for the given scenario and why?

A) Yes; both of the streams can share a single checkpoint directory.
B) No; only one stream can write to a Delta Lake table.
C) No; each of the streams needs to have its own checkpoint directory.
D) Yes; Delta Lake supports infinite concurrent writers.
E) No; Delta Lake manages streaming checkpoints in the transaction log.

Solutions: