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Exam Databricks-Certified-Professional-Data-Engineer Quick Prep - New Databricks-Certified-Professional-Data-Engineer Test Review
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Databricks Certified Professional Data Engineer Exam Sample Questions (Q103-Q108):
NEW QUESTION # 103
Review the following error traceback:
Which statement describes the error being raised?
- A. There is no column in the table named heartrateheartrateheartrate
- B. There is a type error because a DataFrame object cannot be multiplied.
- C. There is a type error because a column object cannot be multiplied.
- D. The code executed was PvSoark but was executed in a Scala notebook.
- E. There is a syntax error because the heartrate column is not correctly identified as a column.
Answer: E
Explanation:
The error being raised is an AnalysisException, which is a type of exception that occurs when Spark SQL cannot analyze or execute a query due to some logical or semantic error1. In this case, the error message indicates that the query cannot resolve the column name 'heartrateheartrateheartrate' given the input columns
'heartrate' and 'age'. This means that there is no column in the table named 'heartrateheartrateheartrate', and the query is invalid. A possible cause of this error is a typo or a copy-paste mistake in the query. To fix this error, the query should use a valid column name that exists in the table, such as
'heartrate'. References: AnalysisException
NEW QUESTION # 104
You have written a notebook to generate a summary data set for reporting, Notebook was scheduled using the job cluster, but you realized it takes an average of 8 minutes to start the cluster, what feature can be used to start the cluster in a timely fashion?
- A. Use the Databricks cluster pools feature to reduce the startup time
- B. Use Databricks Premium edition instead of Databricks standard edition
- C. Setup an additional job to run ahead of the actual job so the cluster is running second job starts
- D. Disable auto termination so the cluster is always running
- E. Pin the cluster in the cluster UI page so it is always available to the jobs
Answer: A
Explanation:
Explanation
Cluster pools allow us to reserve VM's ahead of time, when a new job cluster is created VM are grabbed from the pool. Note: when the VM's are waiting to be used by the cluster only cost incurred is Azure. Databricks run time cost is only billed once VM is allocated to a cluster.
Here is a demo of how to setup and follow some best practices,
https://www.youtube.com/watch?v=FVtITxOabxg&ab_channel=DatabricksAcademy
NEW QUESTION # 105
Which statement describes integration testing?
- A. Validates interactions between subsystems of your application
- B. Validates behavior of individual elements of your application
- C. Validates an application use case
- D. Requires manual intervention
- E. Requires an automated testing framework
Answer: A
Explanation:
This is the correct answer because it describes integration testing. Integration testing is a type of testing that validates interactions between subsystems of your application, such as modules, components, or services. Integration testing ensures that the subsystems work together as expected and produce the correct outputs or results. Integration testing can be done at different levels of granularity, such as component integration testing, system integration testing, or end-to-end testing. Integration testing can help detect errors or bugs that may not be found by unit testing, which only validates behavior of individual elements of your application. Verified Reference: [Databricks Certified Data Engineer Professional], under "Testing" section; Databricks Documentation, under "Integration testing" section.
NEW QUESTION # 106
A notebook accepts an input parameter that is assigned to a python variable called department and this is an optional parameter to the notebook, you are looking to control the flow of the code using this parameter. you have to check department variable is present then execute the code and if no department value is passed then skip the code execution. How do you achieve this using python?
- A. 1.if (department is not None)
2. #Execute code
3.else
4. pass - B. 1.if department is not None:
2. #Execute code
3.end:
4. pass - C. 1.if department is not None:
2. #Execute code
3.else:
4. pass
(Correct) - D. 1.if department is not None:
2. #Execute code
3.then:
4. pass - E. 1.if department is None:
2. #Execute code
3.else:
4. pass
Answer: C
Explanation:
Explanation
The answer is,
1.if department is not None:
2. #Execute code
3.else:
4. pass
NEW QUESTION # 107
A table is registered with the following code:
Bothusersandordersare Delta Lake tables. Which statement describes the results of queryingrecent_orders?
- A. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
- B. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
- C. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
- D. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
- E. All logic will execute when the table is definedand store the result of joiningtables to the DBFS; this stored data will be returned when the table is queried.
Answer: D
Explanation:
Explanation
This is the correct answer because Delta Lake supports time travel, which allows users to query data as of a specific version or timestamp. The code uses the VERSION AS OF syntax to specify the version of each source table to be used in the join. The result of querying recent_orders will be the same as joining those versions of the source tables at query time. The query will use snapshot isolation, which means it will use a consistent snapshot of the table at the time the query began, regardless of any concurrent updates or deletes.
Verified References: [Databricks Certified Data Engineer Professional], under "Delta Lake" section; Databricks Documentation, under "Query an older snapshot of a table (time travel)" section.
NEW QUESTION # 108
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