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

質問 1：
The viewupdatesrepresents an incremental batch of all newly ingested data to be inserted or updated in the customerstable.
The following logic is used to process these records.

Which statement describes this implementation?
A. The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.
B. The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
C. The customers table is implemented as a Type 3 table; old values are maintained as a new column alongside the current value.
D. The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.
E. The customers table is implemented as a Type 2 table; old values are maintained but marked as no longer current and new values are inserted.
正解：E
解説: (Topexam メンバーにのみ表示されます)

質問 2：
A platform engineer is creating catalogs and schemas for the development team to use.
The engineer has created an initial catalog, catalog_A, and initial schema, schema_A. The engineer has also granted USE CATALOG, USE SCHEMA, and CREATE TABLE to the development team so that the engineer can begin populating the schema with new tables.
Despite being owner of the catalog and schema, the engineer noticed that they do not have access to the underlying tables in Schema_A.
What explains the engineer's lack of access to the underlying tables?
A. Users granted with USE CATALOG can modify the owner's permissions to downstream tables.
B. Permissions explicitly given by the table creator are the only way the Platform Engineer could access the underlying tables in their schema.
C. The owner of the schema does not automatically have permission to tables within the schema, but can grant them to themselves at anypoint.
D. The platform engineer needs to execute a REFRESH statement as the table permissions did not automatically update for owners.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 3：
A Databricks job has been configured with 3 tasks, each of which is a Databricks notebook. Task A does not depend on other tasks. Tasks B and C run in parallel, with each having a serial dependency on task A.
If tasks A and B complete successfully but task C fails during a scheduled run, which statement describes the resulting state?
A. All logic expressed in the notebook associated with tasks A and B will have been successfully completed; any changes made in task C will be rolled back due to task failure.
B. All logic expressed in the notebook associated with tasks A and B will have been successfully completed; some operations in task C may have completed successfully.
C. Because all tasks are managed as a dependency graph, no changes will be committed to the Lakehouse until ail tasks have successfully been completed.
D. Unless all tasks complete successfully, no changes will be committed to the Lakehouse; because task C failed, all commits will be rolled back automatically.
E. All logic expressed in the notebook associated with task A will have been successfully completed; tasks B and C will not commit any changes because of stage failure.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 4：
The downstream consumers of a Delta Lake table have been complaining about data quality issues impacting performance in their applications. Specifically, they have complained that invalidlatitudeandlongitudevalues in theactivity_detailstable have been breaking their ability to use other geolocation processes.
A junior engineer has written the following code to addCHECKconstraints to the Delta Lake table:

A senior engineer has confirmed the above logic is correct and the valid ranges for latitude and longitude are provided, but the code fails when executed.
Which statement explains the cause of this failure?
A. The activity details table already contains records; CHECK constraints can only be added prior to inserting values into a table.
B. The activity details table already contains records that violate the constraints; all existing data must pass CHECK constraints in order to add them to an existing table.
C. The current table schema does not contain the field valid coordinates; schema evolution will need to be enabled before altering the table to add a constraint.
D. The activity details table already exists; CHECK constraints can only be added during initial table creation.
E. Because another team uses this table to support a frequently running application, two-phase locking is preventing the operation from committing.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 5：
A Delta Lake table in the Lakehouse named customer_parsams 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.
Immediately after each update succeeds, the data engineer team would like to determine the difference between the new version and the previous of the table.
Given the current implementation, which method can be used?
A. Parse the Delta Lake transaction log to identify all newly written data files.
B. Execute a query to calculate the difference between the new version and the previous version using Delta Lake's built-in versioning and time travel functionality.
C. Execute DESCRIBE HISTORY customer_churn_params to obtain the full operation metrics for the update, including a log of all records that have been added or modified.
D. Parse the Spark event logs to identify those rows that were updated, inserted, or deleted.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 6：
A nightly job ingests data into a Delta Lake table using the following code:

The next step in the pipeline requires a function that returns an object that can be used to manipulate new records that have not yet been processed to the next table in the pipeline.
Which code snippet completes this function definition?
def new_records():
A. return spark.readStream.load("bronze")
B.

C. return spark.read.option("readChangeFeed", "true").table ("bronze")
D.

E. return spark.readStream.table("bronze")
正解：B
解説: (Topexam メンバーにのみ表示されます)