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

1. A data pipeline uses Structured Streaming to ingest data from kafka to Delta Lake. Data is being stored in a bronze table, and includes the Kafka_generated timesamp, key, and value. Three months after the pipeline is deployed the data engineering team has noticed some latency issued during certain times of the day.
A senior data engineer updates the Delta Table's schema and ingestion logic to include the current timestamp (as recoded by Apache Spark) as well the Kafka topic and partition. The team plans to use the additional metadata fields to diagnose the transient processing delays.
Which limitation will the team face while diagnosing this problem?

A) New fields cannot be added to a production Delta table.
B) New fields not be computed for historic records.
C) Updating the table schema requires a default value provided for each file added.
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D) Updating the table schema will invalidate the Delta transaction log metadata.
E) Spark cannot capture the topic partition fields from the kafka source.

2. A CHECK constraint has been successfully added to the Delta table named activity_details using the following logic:

A batch job is attempting to insert new records to the table, including a record where latitude =
45.50 and longitude = 212.67.
Which statement describes the outcome of this batch insert?

A) The write will insert all records except those that violate the table constraints; the violating records will be reported in a warning log.
B) The write will insert all records except those that violate the table constraints; the violating records will be recorded to a quarantine table.
C) The write will fail completely because of the constraint violation and no records will be inserted into the target table.
D) The write will fail when the violating record is reached; any records previously processed will be recorded to the target table.
E) The write will include all records in the target table; any violations will be indicated in the boolean column named valid_coordinates.

3. The DevOps team has configured a production workload as a collection of notebooks scheduled to run daily using the Jobs Ul. A new data engineering hire is onboarding to the team and has requested access to one of these notebooks to review the production logic. What are the maximum notebook permissions that can be granted to the user without allowing accidental changes to production code or data?

A) Can edit
B) Can Read
C) Can manage
D) Can run

4. An external object storage container has been mounted to the location /mnt/finance_eda_bucket.
The following logic was executed to create a database for the finance team:

After the database was successfully created and permissions configured, a member of the finance team runs the following code:

If all users on the finance team are members of the finance group, which statement describes how the tx_sales table will be created?

A) A logical table will persist the physical plan to the Hive Metastore in the Databricks control plane.
B) A managed table will be created in the DBFS root storage container.
C) A logical table will persist the query plan to the Hive Metastore in the Databricks control plane.
D) An managed table will be created in the storage container mounted to /mnt/finance_eda_bucket.
E) An external table will be created in the storage container mounted to /mnt/finance eda bucket.

5. A task orchestrator has been configured to run two hourly tasks. First, an outside system writes Parquet data to a directory mounted at /mnt/raw_orders/. After this data is written, a Databricks job containing the following code is executed:
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Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order, and that the time field indicates when the record was queued in the source system.
If the upstream system is known to occasionally enqueue duplicate entries for a single order hours apart, which statement is correct?

A) The orders table will not contain duplicates, but records arriving more than 2 hours late will be ignored and missing from the table.
B) Duplicate records arriving more than 2 hours apart will be dropped, but duplicates that arrive in the same batch may both be written to the orders table.
C) All records will be held in the state store for 2 hours before being deduplicated and committed to the orders table.
D) Duplicate records enqueued more than 2 hours apart may be retained and the orders table may contain duplicate records with the same customer_id and order_id.
E) The orders table will contain only the most recent 2 hours of records and no duplicates will be present.

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