Databricks Certified-Data-Engineer-Professional

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Databricks Certified-Data-Engineer-Professional 試験シラバストピック:

Databricks Certified Data Engineer Professional 認定 Certified-Data-Engineer-Professional 試験問題：

問題 #1
A data engineering workspace was automatically enabled for Unity Catalog, creating a workspace catalog. New team members report they can create tables in the default schema but cannot access table in other schemas within the same workspace catalog. Why are the new team members unable to access tables in other schemas?

A. Workspace users receive USE CATALOG and specific privileges on default schema only.
B. Workspace catalog permissions are not subject to inheritance rules.
C. New users only receive CREATE TABLE privileges on the default schema.
D. Tables in other schemas require additional BROWSEprivileges that new users don't receive automatically

問題 #2
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 invalid latitude and longitude values in the activity_details table have been breaking their ability to use other geolocation processes.
A junior engineer has written the following code to add CHECK constraints 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 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.
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 activity details table already exists; CHECK constraints can only be added during initial table creation.
D. The activity details table already contains records; CHECK constraints can only be added prior to inserting values into a table.
E. Because another team uses this table to support a frequently running application, two-phase locking is preventing the operation from committing.

問題 #3
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.

B. return spark.readStream.load("bronze")
C. return spark.readStream.table("bronze")
D. return spark.read.option("readChangeFeed", "true").table ("bronze")
E.

問題 #4
While reviewing a query's execution in the Databricks Query Profiler, a data engineer observes that the Top Operators panel shows a Sort operator with high Time Spent and Memory Peak metrics. The Spark UI also reports frequent data spilling. How should the data engineer address this issue?

A. Repartition the DataFrame to a single partition before sorting.
B. Convert the sort operation to a filter operation.
C. Increase the number of shuffle partitions to better distribute data.
D. Switch to a broadcast join to reduce memory usage.

問題 #5
A security team wants to enforce data protection for a customer table containing customer PII data. To comply with local policies, sales team members should only see customers from their region, while non-admin users should have email addresses masked. Which implementation approach should be used when using Unity Catalog row filters and column masks?

A. Use table ACLs to restrict access using tags with GRANT SELECT ON table_name WITH TAG command, and rely on application-level filtering for sensitive data based on user region.
B. Create a view with dynamic WHERE clauses for region filtering and use string replacement functions for email masking using ALTER COLUMN SET MASK command.
C. Implement row filters with SQL UDFs based on user region only since column masks cannot be combined with row filters on the same table, then apply them be recreating the table with DROP TABLE and CREATE TABLE SET ROW FILTER commands.
D. Create SQL UDFs for row filtering based on user region and column masking based on group membership, then apply them using ALTER TABLE SET ROW FILTER and ALTER COLUMN SET MASK commands.

解説：