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

Databricks Certified Data Engineer Professional Sample Questions:

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

2. A data engineer needs to design an efficient pipeline that automatically processes new CSV files as they arrive in S3 storage. Which Databricks feature should the data engineer use to meet these requirements?

A) Streaming from cloud storage using standard Spark readStream with format ("csv") and format ("json")
B) Traditional batch processing with scheduled Databricks Jobs
C) Auto Loader with schema inference and evolution enabled
D) COPY INTO SQL command with parameters to track processed files

3. Which method can be used to determine the total wall-clock time it took to execute a query?

A) In the Spark UI, take the sum of all task durations that ran across all stages for all jobs associated with that query.
B) Open the Query Profiler associated with that query and use the Aggregated task time metric.
C) Open the Query Profiler associated with that query and use the Total wall-clock duration metric.
D) In the Spark UI, take the job duration of the longest-running job associated with that query.

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

5. A data engineer is masking a column containing email addresses. The goal is to produce output strings of identical length for all rows, while generating different outputs for different email values.
Which SQL function should be used to achieve this?

A) hash(email)
B) sha2(email, 0)
C) mask(email, '?')
D) sha1(email)

Solutions: