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

Databricks Certified Data Engineer Professional Sample Questions:

Question 1

When evaluating the Ganglia Metrics for a given cluster with 3 executor nodes, which indicator would signal proper utilization of the VM's resources?

A. Network I/O never spikes
B. Bytes Received never exceeds 80 million bytes per second
C. Total Disk Space remains constant
D. The five Minute Load Average remains consistent/flat
E. CPU Utilization is around 75%

Question 2

A data engineer is configuring a pipeline that will potentially see late-arriving, duplicate records.
In addition to de-duplicating records within the batch, which of the following approaches allows the data engineer to deduplicate data against previously processed records as it is inserted into a Delta table?

A. Set the configuration delta.deduplicate = true.
B. Perform an insert-only merge with a matching condition on a unique key.
C. Rely on Delta Lake schema enforcement to prevent duplicate records.
D. VACUUM the Delta table after each batch completes.
E. Perform a full outer join on a unique key and overwrite existing data.

Question 3

A data engineer is developing a Lakeflow Declarative Pipeline (LDP) using a Databricks notebook directly connected to their pipeline. After adding new table definitions and transformation logic in their notebook, they want to check for any syntax errors in the pipeline code without actually processing data or running the pipeline. How should the data engineer perform this syntax check?

A. Disconnect the notebook from the pipeline and reconnect it to a compute cluster to access code validation features.
B. Open the web terminal from the notebook and run a shell command to validate the pipeline code.
C. Use the "Validate" option in the notebook to check for syntax errors.
D. Switch to a workspace file instead of a notebook to access validation and diagnostics tools.

Question 4

A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?

A. Executor's log file
B. Driver's log file
C. Workspace audit logs
D. Ganglia
E. Cluster Event Log

Question 5

A data engineer is implementing liquid clustering on a Delta Lale table and needs to understand how it affects data management operations. The table will be updated frequently with new data.
The table is an external table and not managed by Unity Catalog. How does liquid clustering in Delta Lake handle new data that is inserted after the initial table creation?

A. New data is written to a staging area and clustered during scheduled maintenance.
B. New data is automatically clustered during write operations.
C. New data remains unclustered until the next OPTIMIZE operation.
D. New data is rejected if it doesn't match the clustering pattern.

Solutions: