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

Databricks Certified Data Engineer Professional Sample Questions:

Question 1

A data engineer and a platform engineer are working together to automate their system tasks. A script needs to be executed outside of Databricks only if a particular daily Databricks job finishes successfully for the day. Databricks CLI command was used to check the last execution of the job. What are the required command options for that task?

A. databricks jobs list-runs --job-id JOB_ID --start-time-to TODAY_MIDNIGHT_EPOCH_MS --active- only
B. databricks jobs list-runs --job-id JOB_ID --start-time-from TODAY_MIDNIGHT_EPOCH_MS -- completed-only
C. databricks jobs list-runs --job-id JOB_ID --start-time-from TODAY_MIDNIGHT_EPOCH_MS -- active-only
D. databricks jobs list-runs --job-id JOB_ID --start-time-to TODAY_MIDNIGHT_EPOCH_MS -- completed-only

Question 2

A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:
SELECT COUNT (*) FROM table
Which of the following describes how results are generated each time the dashboard is updated?

A. The total count of records is calculated from the Hive metastore
B. The total count of records is calculated from the Delta transaction logs
C. The total count of rows will be returned from cached results unless REFRESH is run
D. The total count of rows is calculated by scanning all data files
E. The total count of records is calculated from the parquet file metadata

Question 3

The data science team has requested assistance in accelerating queries on free form text from user reviews. The data is currently stored in Parquet with the below schema:
item_id INT, user_id INT, review_id INT, rating FLOAT, review STRING
The review column contains the full text of the review left by the user. Specifically, the data science team is looking to identify if any of 30 key words exist in this field.
A junior data engineer suggests converting this data to Delta Lake will improve query performance.
Which response to the junior data engineer's suggestion is correct?

A. ZORDER ON review will need to be run to see performance gains.
B. Text data cannot be stored with Delta Lake.
C. Delta Lake statistics are not optimized for free text fields with high cardinality.
D. Delta Lake statistics are only collected on the first 4 columns in a table.
E. The Delta log creates a term matrix for free text fields to support selective filtering.

Question 4

How are the operational aspects of Lakeflow Declarative Pipelines different from Spark Structured Streaming?

A. Lakeflow Declarative Pipelines manage the orchestration of multi-stage pipelines automatically, while Structured Streaming requires external orchestration for complex dependencies.
B. Structured Streaming can process continuous data streams, while Lakeflow Declarative Pipelines cannot.
C. Lakeflow Declarative Pipelines automatically handle schema evolution, while Structured Streaming always requires manual schema management.
D. Lakeflow Declarative Pipelines can write to Delta Lake format, while Structured Streaming cannot.

Question 5

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?

A. Skew caused by more data being assigned to a subset of spark-partitions.
B. Spill resulting from attached volume storage being too small.
C. Task queueing resulting from improper thread pool assignment.
D. Network latency due to some cluster nodes being in different regions from the source data
E. Credential validation errors while pulling data from an external system.

Solutions: