Online Access Free Databricks.Databricks-Certified-Professional-Data-Engineer.v2023-03-10.q102 Practice Test (Page 7)

Databricks-Certified-Professional-Data-Engineer Exam Question 26

Which of the following is correct for the global temporary view?

A.global temporary views cannot be accessed once the notebook is detached and attached

B.global temporary views can be accessed across many clusters

C.global temporary views can be still accessed even if the notebook is detached and at-tached

D.global temporary views can be still accessed even if the cluster is restarted

E.global temporary views are created in a database called temp database

Databricks-Certified-Professional-Data-Engineer Exam Question 27

What is the purpose of a silver layer in Multi hop architecture?

A.Replaces a traditional data lake

B.Efficient storage and querying of full and unprocessed history of data

C.A schema is enforced, with data quality checks.

D.Refined views with aggregated data

E.Optimized query performance for business-critical data

Databricks-Certified-Professional-Data-Engineer Exam Question 28

How are Delt tables stored?

A.A Directory where parquet data files are stored, a sub directory _delta_log where meta data, and the transaction log is stored as JSON files.

B.A Directory where parquet data files are stored, all of the meta data is stored in memory

C.A Directory where parquet data files are stored in Data plane, a sub directory _delta_log where meta data, history and log is stored in control pane.

D.A Directory where parquet data files are stored, all of the metadata is stored in parquet files

E.Data is stored in Data plane and Metadata and delta log are stored in control pane

Databricks-Certified-Professional-Data-Engineer Exam Question 29

The Delta Live Table Pipeline is configured to run in Production mode using the continuous Pipe-line Mode.
what is the expected outcome after clicking Start to update the pipeline?

A.All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated

B.All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will be deployed for the update and terminated when the pipeline is stopped

C.All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist after the pipeline is stopped to allow for additional testing

D.All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing

E.All datasets will be updated continuously and the pipeline will not shut down. The compute resources will persist with the pipeline (Correct)

Correct Answer: E

Explanation
The answer is,
All datasets will be updated continuously and the pipeline will not shut down. The compute re-sources will persist with the pipeline until it is shut down since the execution mode is chosen to be continuous. It does not matter if the pipeline mode is development or production, pipeline mode only matters during the pipeline initialization.
DLT pipeline supports two modes Development and Production, you can switch between the two based on the stage of your development and deployment lifecycle.
Development and production modes
Development:
When you run your pipeline in development mode, the Delta Live Tables system:
*Reuses a cluster to avoid the overhead of restarts.
*Disables pipeline retries so you can immediately detect and fix errors.
Production:
In production mode, the Delta Live Tables system:
*Restarts the cluster for specific recoverable errors, including memory leaks and stale cre-dentials.
*Retries execution in the event of specific errors, for example, a failure to start a cluster.
Use the buttons in the Pipelines UI to switch between develop-ment and production modes. By default,

pipelines run in development mode.
Switching between development and production modes only controls cluster and pipeline execution behavior.
Storage locations must be configured as part of pipeline settings and are not affected when switching between modes.
Delta Live Tables supports two different modes of execution:
Triggered pipelines update each table with whatever data is currently available and then stop the cluster running the pipeline. Delta Live Tables automatically analyzes the dependencies between your tables and starts by computing those that read from external sources. Tables within the pipe-line are updated after their dependent data sources have been updated.
Continuous pipelines update tables continuously as input data changes. Once an update is started, it continues to run until manually stopped. Continuous pipelines require an always-running cluster but ensure that downstream consumers have the most up-to-date data Please review additional DLT concepts using the below link
https://docs.databricks.com/data-engineering/delta-live-tables/delta-live-tables-concepts.html#delta-live-tables-c