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最新的 Databricks Certification Databricks-Certified-Professional-Data-Engineer 免費考試真題 (Q152-Q157):

問題 #152
A workspace admin has created a new catalog called finance_data and wants to delegate permission management to a finance team lead without giving them full admin rights.
Which privilege should be granted to the finance team lead?

A. Make the finance team lead a metastore admin.
B. GRANT OPTION privilege on the finance_data catalog.
C. ALL PRIVILEGES on the finance_data catalog.
D. MANAGE privilege on the finance_data catalog.

答案：D

解題說明：
Comprehensive and Detailed Explanation From Exact Extract of Databricks Data Engineer Documents:
The MANAGE privilege in Unity Catalog provides the ability to grant and revoke privileges on the specified object (in this case, a catalog) without giving full administrative access or ownership.
This is the Databricks-recommended approach for delegating governance responsibilities while preserving the principle of least privilege.
By contrast, the ALL PRIVILEGES option grants excessive access (including read and write permissions), and metastore admin status provides global control over all catalogs-far exceeding the requirement. The MANAGE privilege enables the finance team lead to control access to objects within finance_data responsibly while limiting overall administrative exposure.

問題 #153
When you drop an external DELTA table using the SQL Command DROP TABLE table_name, how does it impact metadata(delta log, history), and data stored in the storage?

A. Drops table from metastore, but keeps metadata(delta log, history)and data in storage
B. Drops table from metastore, metadata(delta log, history)and data in storage
C. Drops table from metastore, metadata(delta log, history)but keeps the data in storage
D. Drops table from metastore, data but keeps metadata(delta log, history) in storage
E. Drops table from metastore and data in storage but keeps metadata(delta log, history)

答案：A

解題說明：
Explanation
The answer is Drops table from metastore, but keeps metadata and data in storage.
When an external table is dropped, only the table definition is dropped from metastore everything including data and metadata(Delta transaction log, time travel history) remains in the storage. Delta log is considered as part of metadata because if you drop a column in a delta table(managed or external) the column is not physically removed from the parquet files rather it is recorded in the delta log. The delta log becomes a key metadata layer for a Delta table to work.
Please see the below image to compare the external delta table and managed delta table and how they differ in how they are created and what happens if you drop the table.
Diagram Description automatically generated

問題 #154
Which statement characterizes the general programming model used by Spark Structured Streaming?

A. Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.
B. Structured Streaming is implemented as a messaging bus and is derived from Apache Kafka.
C. Structured Streaming leverages the parallel processing of GPUs to achieve highly parallel data throughput.
D. Structured Streaming relies on a distributed network of nodes that hold incremental state values for cached stages.
E. Structured Streaming uses specialized hardware and I/O streams to achieve sub-second latency for data transfer.

答案：B

解題說明：
This is the correct answer because it characterizes the general programming model used by Spark Structured Streaming, which is to treat a live data stream as a table that is being continuously appended. This leads to a new stream processing model that is very similar to a batch processing model, where users can express their streaming computation using the same Dataset/DataFrame API as they would use for static data. The Spark SQL engine will take care of running the streaming query incrementally and continuously and updating the final result as streaming data continues to arrive. Verified References: [Databricks Certified Data Engineer Professional], under "Structured Streaming" section; Databricks Documentation, under "Overview" section.

問題 #155
You were asked to write python code to stop all running streams, which of the following command can be used to get a list of all active streams currently running so we can stop them, fill in the blank.
1.for s in _______________:
2. s.stop()

A. spark.streams.getActive
B. Spark.getActiveStreams()
C. getActiveStreams()
D. spark.streams.active
E. activeStreams()

答案：D

問題 #156
A junior data engineer has configured a workload that posts the following JSON to the Databricks REST API endpoint2.0/jobs/create.

Assuming that all configurations and referenced resources are available, which statement describes the result of executing this workload three times?

A. Three new jobs named "Ingest new data" will be defined in the workspace, but no jobs will be executed.
B. The logic defined in the referenced notebook will be executed three times on new clusters with the configurations of the provided cluster ID.
C. One new job named "Ingest new data" will be defined in the workspace, but it will not be executed.
D. Three new jobs named "Ingest new data" will be defined in the workspace, and they will each run once daily.
E. The logic defined in the referenced notebook will be executed three times on the referenced existing all purpose cluster.

答案：A

解題說明：
Explanation
This is the correct answer because the JSON posted to the Databricks REST API endpoint 2.0/jobs/create defines a new job with a name, an existing cluster id, and a notebook task. However, it does not specify any schedule or trigger for the job execution. Therefore, three new jobs with the same name and configuration will be created in the workspace, but none of them will be executed until they are manually triggered or scheduled.
Verified References: [Databricks Certified Data Engineer Professional], under "Monitoring & Logging" section; [Databricks Documentation], under "Jobs API - Create" section.

問題 #157
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