最新的Databricks Databricks-Certified-Professional-Data-Engineer免費考試真題

問題1

A Data Engineer is building a simple data pipeline using Lakeflow Declarative Pipelines (LDP) in Databricks to ingest customer data. The raw customer data is stored in a cloud storage location in JSON format. The task is to create Lakeflow Declarative Pipelines that read the raw JSON data and write it into a Delta table for further processing.
Which code snippet will correctly ingest the raw JSON data and create a Delta table using LDP?

A. import dlt
@dlt.table
def raw_customers():
return spark.read.json( " s3://my-bucket/raw-customers/ " )

B. import dlt
@dlt.table
def raw_customers():
return spark.read.format( " csv " ).load( " s3://my-bucket/raw-customers/ " )

C. import dlt
@dlt.table
def raw_customers():
return spark.read.format( " parquet " ).load( " s3://my-bucket/raw-customers/ " )

D. import dlt
@dlt.view
def raw_customers():
return spark.format.json( " s3://my-bucket/raw-customers/ " )

正確答案: A

說明：（僅 Fast2test 成員可見）

問題2

The Databricks CLI is used to trigger a run of an existing job by passing the job_id parameter. The response indicating the job run request was submitted successfully includes a field run_id. Which statement describes what the number alongside this field represents?

A. The globally unique ID of the newly triggered run.

B. The job_id is returned in this field.

C. The job_id and number of times the job has been run are concatenated and returned.

D. The number of times the job definition has been run in this workspace.

正確答案: A

說明：（僅 Fast2test 成員可見）

問題3

A Delta Lake table representing metadata about content from user has the following schema:
user_id LONG, post_text STRING, post_id STRING, longitude FLOAT, latitude FLOAT, post_time TIMESTAMP, date DATE Based on the above schema, which column is a good candidate for partitioning the Delta Table?

A. User_id

B. Post_id

C. Post_time

D. Date

正確答案: D

說明：（僅 Fast2test 成員可見）

問題4

A transactions table has been liquid clustered on the columns product_id, user_id, and event_date.
Which operation lacks support for cluster on write?

A. CTAS and RTAS statements

B. spark.writestream.format( ' delta ' ).mode( ' append ' )

C. INSERT INTO operations

D. spark.write.format( ' delta ' ).mode( ' append ' )

正確答案: B

說明：（僅 Fast2test 成員可見）

問題5

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. No; Delta Lake manages streaming checkpoints in the transaction log.

B. No; only one stream can write to a Delta Lake table.

C. Yes; both of the streams can share a single checkpoint directory.

D. Yes; Delta Lake supports infinite concurrent writers.

E. No; each of the streams needs to have its own checkpoint directory.

正確答案: E

說明：（僅 Fast2test 成員可見）

問題6

A Spark job is taking longer than expected. Using the Spark UI, a data engineer notes that the Min, Median, and Max Durations for tasks in a particular stage show the minimum and median time to complete a task as roughly the same, but the max duration for a task to be roughly 100 times as long as the minimum.
Which situation is causing increased duration of the overall job?

A. Credential validation errors while pulling data from an external system.

B. Spill resulting from attached volume storage being too small.

C. Network latency due to some cluster nodes being in different regions from the source data

D. Task queueing resulting from improper thread pool assignment.

E. Skew caused by more data being assigned to a subset of spark-partitions.

正確答案: E

說明：（僅 Fast2test 成員可見）

問題7

What statement is true regarding the retention of job run history?

A. It is retained for 90 days or until the run-id is re-used through custom run configuration

B. It is retained for 60 days, after which logs are archived

C. t is retained for 60 days, during which you can export notebook run results to HTML

D. It is retained until you export or delete job run logs

E. It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3

正確答案: C

問題8

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. The creator of a Databricks job will always have " Owner " privileges; this configuration cannot be changed.

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. Other than the default " admins " group, only individual users can be granted privileges on jobs.

E. Databricks jobs must have exactly one owner; " Owner " privileges cannot be assigned to a group.

正確答案: E

說明：（僅 Fast2test 成員可見）

問題9

Which is a key benefit of an end-to-end test?

A. It closely simulates real world usage of your application.

B. It provides testing coverage for all code paths and branches.

C. It makes it easier to automate your test suite

D. It pinpoint errors in the building blocks of your application.

正確答案: A

說明：（僅 Fast2test 成員可見）

問題10

A data organization has adopted Delta Sharing to securely distribute curated datasets from a Unity Catalog- enabled workspace . The data engineering team shares large Delta tables internally via Databricks-to- Databricks and externally via Open Sharing for aggregated reports. While testing, they encounter challenges related to access control, data update visibility, and shareable object types.
What is a limitation of the Delta Sharing protocol or implementation when used with Databricks-to- Databricks or Open Sharing?

A. Delta Sharing does not support Unity Catalog-enabled tables; only legacy Hive Metastore tables are shareable.

B. Delta Sharing (both Databricks-to-Databricks and Open Sharing) allows recipients to modify the source data if they have select privileges.

C. With Open Sharing, recipients cannot access Volumes, Models, or notebooks - only static Delta tables are supported.

D. With Databricks-to-Databricks sharing, Unity Catalog recipients must re-ingest data manually using COPY INTO or REST APIs.

正確答案: C

說明：（僅 Fast2test 成員可見）

最新的Databricks Certified Professional Data Engineer - Databricks-Certified-Professional-Data-Engineer免費考試真題

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