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

Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer wants to automate job monitoring and recovery in Databricks using the Jobs API.
They need to list all jobs, identify a failed job, and rerun it. Which sequence of API actions should the data engineer perform?

A) Use the jobs/cancel endpoint to remove failed jobs, then recreate them with jobs/create and run the new ones.
B) Use the jobs/list endpoint to list jobs, then use the jobs/create endpoint to create a new job, and run the new job using jobs/run-now.
C) Use the jobs/get endpoint to retrieve job details, then use jobs/update to rerun failed jobs.
D) Use the jobs/list endpoint to list jobs, check job run statuses with jobs/runs/list, and rerun a failed job using jobs/run-now.

2. When monitoring a complex workload, being able to see the query plan is critical to understanding what the workload is doing. Where can the visualization of the query plan be found?

A) In the Query Profiler, under Query Source
B) In the Query Profiler, under the Stages tab
C) In the Spart UI, under the Jobs tab
D) In the Spark UI, under the SQL/DataFrame tab

3. 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.

Which solution would improve the performance?

A)

B)

C)

D)

4. A data engineer is using Structured Streaming to read in transaction data from a bronze Delta table. It was discovered that the data has quality issues where sometimes the transaction value is negative, and when that occurs, the rows need to be routed to a separate quarantine table. They have low latency requirements for the good data since it is used by downstream systems, but the bad data will only be analyzed periodically and has no production dependencies. The quarantine job needs to be implemented so that it cannot affect the production processes that depend on the good data, and the cost of the job needs to be minimized. How should the quarantine process be implemented in order to satisfy these requirements?

A) The existing streaming job for the good data should be updated to incorporate the quarantining of the bad data. Inside a foreachBatch function, the dataframe should be filtered so that records with a transaction value greater than or equal to 0 are written to the good data table and records with a transaction value less than 0 are written to a quarantine table. Try/Catch can be added around the writes in the foreachBatch function so that the stream can't fail.
B) The streaming job for the good data needs to be modified to filter out records with a transaction value less than 0 before writing, and should not share compute with other processes. The streaming job for the quarantine data needs to filter out records with a transaction value greater than or equal to 0 before writing, and should be implemented on a separate small cluster and only run once a day to minimize cost.
C) The existing streaming job for the good data should be updated to incorporate the quarantining of the bad data. A new boolean column called "quarantine" should be added to the dataframe, and its value should be set to true if the transaction value is less than 0 and false if the transaction value is greater than or equal to 0. Processing and storing all the data together will save costs.
D) The streaming job for the good data needs to be modified to filter out records with a transaction value less than 0 before writing. The streaming job for the quarantine data needs to filter out records with a transaction value greater than or equal to 0 before writing. Both should run as separate streams on the same cluster to minimize cost.

5. A junior data engineer seeks to leverage Delta Lake's Change Data Feed functionality to create a Type 1 table representing all of the values that have ever been valid for all rows in a bronze table created with the property delta.enableChangeDataFeed = true. They plan to execute the following code as a daily job:

Which statement describes the execution and results of running the above query multiple times?

A) Each time the job is executed, the target table will be overwritten using the entire history of inserted or updated records, giving the desired result.
B) Each time the job is executed, the differences between the original and current versions are calculated; this may result in duplicate entries for some records.
C) Each time the job is executed, only those records that have been inserted or updated since the last execution will be appended to the target table giving the desired result.
D) Each time the job is executed, newly updated records will be merged into the target table, overwriting previous values with the same primary keys.
E) Each time the job is executed, the entire available history of inserted or updated records will be appended to the target table, resulting in many duplicate entries.

Solutions: