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Microsoft DP-800 Exam Syllabus Topics:
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Microsoft Developing AI-Enabled Database Solutions Sample Questions (Q26-Q31):
NEW QUESTION # 26
You have a SQL database in Microsoft Fabric that contains a table named WebSite. Logs. WebSite.Logs stores application telemetry data. Website.Logs contains a nvarehar(iMx) column named log that stores JSON documents You have a daily report that filters by the $.severity JSON property and returns Logld. LogDateTime, and log.
The report frequently causes full table scans.
You need to modify Website. Logs to support efficient filtering by $. severity and avoid key lookups for the columns returned by the report.
How should you complete the Transact-SQL code to avoid full table scans? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The correct way to avoid full table scans here is to add a computed column that extracts the JSON scalar property with JSON_VALUE , and then create a nonclustered index on that computed column with the report's returned columns in the INCLUDE list. Microsoft's JSON indexing guidance specifically recommends creating a computed column that exposes the JSON property you filter on, using the same expression as in the query, and then indexing that computed column.
So the computed column must be:
AS JSON_VALUE([log], ' $.severity ' ) PERSISTED
This is correct because $.severity is a scalar JSON value, so JSON_VALUE is the proper function.
JSON_QUERY would be for extracting an object or array, not a scalar property. Microsoft also notes that persisted computed columns can improve access speed for JSON-derived values.
The index should then include:
INCLUDE (LogId, LogDateTime, [log])
That is the right covering strategy because the report filters by severity but returns LogId, LogDateTime, and log. Microsoft's guidance on included columns explains that nonkey included columns let a nonclustered index cover more queries and reduce extra lookups to the base table.
So the completed code is:
ALTER TABLE WebSite.Logs
ADD severity AS JSON_VALUE([log], ' $.severity ' ) PERSISTED;
GO
CREATE INDEX ix_severity
ON WebSite.Logs(severity)
INCLUDE (LogId, LogDateTime, [log]);
GO
NEW QUESTION # 27
You need to create a table in the database to store the telemetry data. You have the following Transact-SQL code.

Answer:
Explanation:
Explanation:
The first statement is No . The requirement says telemetry data must be stored in a partitioned table to provide predictable performance for ingestion and retention operations. However, the shown CREATE TABLE statement does not define a partition function or partition scheme, and the table is created with a regular clustered primary key on TelemetryId. Microsoft's partitioning guidance states that creating a partitioned table requires a partition function , a partition scheme , and creating the table or index on that partition scheme using a partitioning column. None of that appears in the code, so the table is not partitioned.
The second statement is Yes . The code creates a JSON index named JI_VehicleTelemetry_Location on LocationJson for these specific JSON paths: $.location.latitude, $.location.longitude, and $.location.accuracy.
That matches the requirement that those JSON properties must be filterable by using an index seek .
Microsoft documents that JSON indexing is used to optimize filtering and sorting on JSON properties, and the index only helps for the properties included in the index definition.
The third statement is No . The JSON index is defined only for latitude, longitude, and accuracy. A query filtering on $.location.heading references a different path that is not included in the index definition, so that query would not use JI_VehicleTelemetry_Location for that predicate. JSON indexes are path-specific; they do not automatically cover unrelated properties in the same JSON document.
NEW QUESTION # 28
You have an Azure SQL database that contains a table named dbo.Orders.
You have an application that calls a stored procedure named dbo.usp_tresteOrder to insert rows into dbo.
Orders.
When an insert fails, the application receives inconsistent error details.
You need to implement error handling to ensure that any failures inside the procedure abort the transaction and return a consistent error to the caller.
How should you complete the stored procedure? To answer, drag the appropriate values to the correct targets, tach value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* After the INSERT # SET @OrderId = SCOPE_IDENTITY()
* Inside CATCH # IF @@TRANCOUNT > 0 ROLLBACK TRANSACTION
The correct drag-and-drop choices are:
* SET @OrderId = SCOPE_IDENTITY()
* IF @@TRANCOUNT > 0 ROLLBACK TRANSACTION
After the INSERT, the procedure should assign the newly generated identity value to the output parameter by using SCOPE_IDENTITY() . Microsoft documents that SCOPE_IDENTITY() returns the last identity value inserted in the same scope, which makes it the correct choice for returning the new OrderId from the procedure.
Inside the CATCH block, the procedure should use IF @@TRANCOUNT > 0 ROLLBACK TRANSACTION before THROW. This ensures any open transaction is rolled back only when one actually exists, which prevents transaction-state issues and guarantees the failure aborts the transaction cleanly.
Keeping THROW after the rollback is also the correct modern pattern because THROW re-raises the error to the caller with the original error information intact, giving consistent error behavior. This matches SQL Server best practice for TRY...CATCH transaction handling.
NEW QUESTION # 29
You have a SQL database in Microsoft Fabric that contains a column named Payload. pay load stores customer data in JSON documents that have the following format.
Data analysis shows that some customers have subaddressing in their email address, for example, [email protected].
You need to return a normalized email value that removes the subaddressing, for example, user! + [email protected] must be normalized to [email protected].
Which Transact SQL expression should you use?
- A. REGEXP_REPLACE(JSON_VALUE(Payload, ' $.customer_email ' ), ' +.*$ ' , ' ' )
- B. REGEXP_SUBSTR(JSON_VALUE(Payload, ' $.customer_email ' ), ' Report this wiki page