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

質問 1：
The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. Therecent_sensor_recordingstable contains an identifyingsensor_idalongside thetimestampandtemperaturefor the most recent 5 minutes of recordings.
The below query is used to create the alert:

The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger whenmean (temperature) > 120. Notifications are triggered to be sent at most every 1 minute.
If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?
A. The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query
B. The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query
C. Therecent_sensor_recordingstable was unresponsive for three consecutive runs of the query
D. The total average temperature across all sensors exceeded 120 on three consecutive executions of the query
E. The source query failed to update properly for three consecutive minutes and then restarted
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 2：
An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the fieldpk_id.
For auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour.
Which solution meets these requirements?
A. Use Delta Lake's change data feed to automatically process CDC data from an external system, propagating all changes to all dependent tables in the Lakehouse.
B. Use merge into to insert, update, or delete the most recent entry for each pk_id into a bronze table, then propagate all changes throughout the system.
C. Create a separate history table for each pk_id resolve the current state of the table by running a union all filtering the history tables for the most recent state.
D. Ingest all log information into a bronze table; use merge into to insert, update, or delete the most recent entry for each pk_id into a silver table to recreate the current table state.
E. Iterate through an ordered set of changes to the table, applying each in turn; rely on Delta Lake's versioning ability to create an audit log.
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 3：
A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:
SELECT COUNT (*) FROM table -
Which of the following describes how results are generated each time the dashboard is updated?
A. The total count of records is calculated from the Delta transaction logs
B. The total count of records is calculated from the Hive metastore
C. The total count of records is calculated from the parquet file metadata
D. The total count of rows is calculated by scanning all data files
E. The total count of rows will be returned from cached results unless REFRESH is run
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 4：
A data architect has designed a system in which two Structured Streaming jobs will concurrently write to a single bronze Delta table. Each job is subscribing to a different topic from an Apache Kafka source, but they will write data with the same schema. To keep the directory structure simple, a data engineer has decided to nest a checkpoint directory to be shared by both streams.
The proposed directory structure is displayed below:

Which statement describes whether this checkpoint directory structure is valid for the given scenario and why?
A. Yes; Delta Lake supports infinite concurrent writers.
B. Yes; both of the streams can share a single checkpoint directory.
C. No; Delta Lake manages streaming checkpoints in the transaction log.
D. No; only one stream can write to a Delta Lake table.
E. No; each of the streams needs to have its own checkpoint directory.
正解：E
解説: (Topexam メンバーにのみ表示されます)

質問 5：
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 6：
Review the following error traceback:

Which statement describes the error being raised?
A. There is a type error because a DataFrame object cannot be multiplied.
B. The code executed was PvSoark but was executed in a Scala notebook.
C. There is no column in the table named heartrateheartrateheartrate
D. There is a type error because a column object cannot be multiplied.
E. There is a syntax error because the heartrate column is not correctly identified as a column.
正解：C
解説: (Topexam メンバーにのみ表示されます)