Explanation
The answer isSELECT * FROM streadming_view order by id Please Note: Sorting with Group by will work without any issues see below explanation for each option of the options, Graphical user interface, text, application Description automatically generated

Certain operations are not allowed on streaming data, please see highlighted in bold.
https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#unsupported-operations
* Multiple streaming aggregations (i.e. a chain of aggregations on a streaming DF) are not yet supported on streaming Datasets.
* Limit and take the first N rows are not supported on streaming Datasets.
* Distinct operations on streaming Datasets are not supported.
* Deduplication operation is not supported after aggregation on a streaming Datasets.
* Sorting operations are supported on streaming Datasets only after an aggregation and in Complete Output Mode.
Note: Sorting without aggregation function is not supported.
Here is the sample code to prove this,
Setup test stream
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Sum aggregation function has no issues on stream
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Max aggregation function has no issues on stream
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Group by with Order by has no issues on stream

Group by has no issues on stream

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Order by without group by fails.
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Explanation
The answer is 2,
Count(DISTINCT *) removes rows with any column with a NULL value

Explanation
This is the correct answer because it describes a limitation of Databricks Secrets. Databricks Secrets is a module that provides tools to store sensitive credentials and avoid accidentally displaying them in plain text.
Databricks Secrets allows creating secret scopes, which are collections of secrets that can be accessed by users or groups. Databricks Secrets also allows creating and managing secrets using the Databricks CLI or the Databricks REST API. However, a limitation of Databricks Secrets is that the Databricks REST API can be used to list secrets in plain text if the personal access token has proper credentials. Therefore, users should still be careful with which credentials are stored in Databricks Secrets and which users have access to using these secrets. Verified References: [Databricks Certified Data Engineer Professional], under "Databricks Workspace" section; Databricks Documentation, under "List secrets" section.

Explanation
The answer is Databricks Web Application
Azure Databricks architecture overview - Azure Databricks | Microsoft Docs Databricks operates most of its services out of a control plane and a data plane, please note serverless features like SQL Endpoint and DLT compute use shared compute in Control pane.
Control Plane: Stored in Databricks Cloud Account
* The control plane includes the backend services that Databricks manages in its own Azure account.
Notebook commands and many other workspace configurations are stored in the control plane and encrypted at rest.
Data Plane: Stored in Customer Cloud Account
* The data plane is managed by your Azure account and is where your data resides. This is also where data is processed. You can use Azure Databricks connectors so that your clusters can connect to external data sources outside of your Azure account to ingest data or for storage.
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Explanation
Medallion Architecture - Databricks
Gold Layer:
1. Powers Ml applications, reporting, dashboards, ad hoc analytics
2. Refined views of data, typically with aggregations
3. Reduces strain on production systems
4. Optimizes query performance for business-critical data
Exam focus: Please review the below image and understand the role of each layer(bronze, silver, gold) in medallion architecture, you will see varying questions targeting each layer and its purpose.
Sorry I had to add the watermark some people in Udemy are copying my content.
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