Expert Answers to Databricks Exam Databricks-Certified-Professional-Data-Engineer Questions

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Databricks Certification Databricks Certified Data Engineer Professional Exam

Databricks Certified Data Engineer Professional Exam

Last Update Oct 26, 2024
Total Questions : 120

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Questions 2

A junior data engineer is working to implement logic for a Lakehouse table named silver_device_recordings. The source data contains 100 unique fields in a highly nested JSON structure.

The silver_device_recordings table will be used downstream to power several production monitoring dashboards and a production model. At present, 45 of the 100 fields are being used in at least one of these applications.

The data engineer is trying to determine the best approach for dealing with schema declaration given the highly-nested structure of the data and the numerous fields.

Which of the following accurately presents information about Delta Lake and Databricks that may impact their decision-making process?

Options:

The Tungsten encoding used by Databricks is optimized for storing string data; newly-added native support for querying JSON strings means that string types are always most efficient.

Because Delta Lake uses Parquet for data storage, data types can be easily evolved by just modifying file footer information in place.

Human labor in writing code is the largest cost associated with data engineering workloads; as such, automating table declaration logic should be a priority in all migration workloads.

Because Databricks will infer schema using types that allow all observed data to be processed, setting types manually provides greater assurance of data quality enforcement.

Schema inference and evolution on .Databricks ensure that inferred types will always accurately match the data types used by downstream systems.

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Questions 3

A Spark job is taking longer than expected. Using the Spark UI, a data engineer notes that the Min, Median, and Max Durations for tasks in a particular stage show the minimum and median time to complete a task as roughly the same, but the max duration for a task to be roughly 100 times as long as the minimum.

Which situation is causing increased duration of the overall job?

Options:

Task queueing resulting from improper thread pool assignment.

Spill resulting from attached volume storage being too small.

Network latency due to some cluster nodes being in different regions from the source data

Skew caused by more data being assigned to a subset of spark-partitions.

Credential validation errors while pulling data from an external system.

Discussion 0

Questions 4

A data engineer wants to join a stream of advertisement impressions (when an ad was shown) with another stream of user clicks on advertisements to correlate when impression led to monitizable clicks.

Questions 4

Which solution would improve the performance?

Questions 4

Options:

Option A

Option B

Option C

Option D

Discussion 0

Questions 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?

Options:

No; Delta Lake manages streaming checkpoints in the transaction log.

Yes; both of the streams can share a single checkpoint directory.

No; only one stream can write to a Delta Lake table.

Yes; Delta Lake supports infinite concurrent writers.

No; each of the streams needs to have its own checkpoint directory.

Discussion 0

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