Databricks Databricks-Certified-Professional-Data-Engineer 問題集

質問 1：
A table in the Lakehouse named customer_churn_params is used in churn prediction by the machine learning team. The table contains information about customers derived from a number of upstream sources. Currently, the data engineering team populates this table nightly by overwriting the table with the current valid values derived from upstream data sources.
The churn prediction model used by the ML team is fairly stable in production. The team is only interested in making predictions on records that have changed in the past 24 hours.
Which approach would simplify the identification of these changed records?
A. Replace the current overwrite logic with a merge statement to modify only those records that have changed; write logic to make predictions on the changed records identified by the change data feed.
B. Calculate the difference between the previous model predictions and the current customer_churn_params on a key identifying unique customers before making new predictions; only make predictions on those customers not in the previous predictions.
C. Convert the batch job to a Structured Streaming job using the complete output mode; configure a Structured Streaming job to read from the customer_churn_params table and incrementally predict against the churn model.
D. Apply the churn model to all rows in the customer_churn_params table, but implement logic to perform an upsert into the predictions table that ignores rows where predictions have not changed.
E. Modify the overwrite logic to include a field populated by calling spark.sql.functions.
current_timestamp() as data are being written; use this field to identify records written on a particular date.
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 2：
A junior data engineer has manually configured a series of jobs using the Databricks Jobs UI. Upon reviewing their work, the engineer realizes that they are listed as the "Owner" for each job. They attempt to transfer
"Owner" privileges to the "DevOps" group, but cannot successfully accomplish this task.
Which statement explains what is preventing this privilege transfer?
A. Other than the default "admins" group, only individual users can be granted privileges on jobs.
B. A user can only transfer job ownership to a group if they are also a member of that group.
C. Only workspace administrators can grant "Owner" privileges to a group.
D. Databricks jobs must have exactly one owner; "Owner" privileges cannot be assigned to a group.
E. The creator of a Databricks job will always have "Owner" privileges; this configuration cannot be changed.
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 3：
A Delta Lake table was created with the below query:

Realizing that the original query had a typographical error, the below code was executed:
ALTER TABLE prod.sales_by_stor RENAME TO prod.sales_by_store
Which result will occur after running the second command?
A. All related files and metadata are dropped and recreated in a single ACID transaction.
B. The table reference in the metastore is updated and no data is changed.
C. The table name change is recorded in the Delta transaction log.
D. The table reference in the metastore is updated and all data files are moved.
E. A new Delta transaction log Is created for the renamed table.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 4：
A DLT pipeline includes the following streaming tables:
Raw_lot ingest raw device measurement data from a heart rate tracking device.
Bgm_stats incrementally computes user statistics based on BPM measurements from raw_lot.
How can the data engineer configure this pipeline to be able to retain manually deleted or updated records in the raw_iot table while recomputing the downstream table when a pipeline update is run?
A. Set the pipelines, reset, allowed property to false on bpm_stats
B. Set the SkipChangeCommits flag to true raw_lot
C. Set the pipelines, reset, allowed property to false on raw_iot
D. Set the skipChangeCommits flag to true on bpm_stats
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 5：
Given the following error traceback (from display(df.select(3*"heartrate"))) which shows AnalysisException:
cannot resolve 'heartrateheartrateheartrate', which statement describes the error being raised?
A. There is a type error because a DataFrame object cannot be multiplied.
B. There is no column in the table named heartrateheartrateheartrate.
C. There is a type error because a column object cannot be multiplied.
D. There is a syntax error because the heartrate column is not correctly identified as a column.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 6：
A user new to Databricks is trying to troubleshoot long execution times for some pipeline logic they are working on. Presently, the user is executing code cell-by-cell, using display() calls to confirm code is producing the logically correct results as new transformations are added to an operation. To get a measure of average time to execute, the user is running each cell multiple times interactively.
Which of the following adjustments will get a more accurate measure of how code is likely to perform in production?
A. Calling display () forces a job to trigger, while many transformations will only add to the logical query plan; because of caching, repeated execution of the same logic does not provide meaningful results.
B. The only way to meaningfully troubleshoot code execution times in development notebooks Is to use production-sized data and production-sized clusters with Run All execution.
C. Scala is the only language that can be accurately tested using interactive notebooks; because the best performance is achieved by using Scala code compiled to JARs. all PySpark and Spark SQL logic should be refactored.
D. Production code development should only be done using an IDE; executing code against a local build of open source Spark and Delta Lake will provide the most accurate benchmarks for how code will perform in production.
E. The Jobs Ul should be leveraged to occasionally run the notebook as a job and track execution time during incremental code development because Photon can only be enabled on clusters launched for scheduled jobs.
正解：A
解説: (Topexam メンバーにのみ表示されます)