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| Section | Weight | Objectives |
|---|---|---|
| Implement AI capabilities in database solutions (25–30%) | 25-30% | - Implement AI features
|
| Design and develop database solutions (35–40%) | 35-40% | - Implement data management
|
| Secure, optimize, and deploy database solutions (35–40%) | 35-40% | - Optimize database performance
|
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NEW QUESTION # 18
Hotspot Question
You have an Azure SQL database that has Query Store enabled.
Query Performance Insight shows that one stored procedure has the longest runtime. The procedure runs the following parameterized query.
The dbo.Orders table has approximately 120 million rows. CustomerId is highly selective, and OrderDate is used for range filtering and sorting.
You have the following indexes:
- Clustered index: PK_Orders on (OrderId)
- Nonclustered index: IX_Orders_OrderDate on (OrderDate) with no
included columns
An actual execution plan captured from Query Store for slow runs shows the following:
- An index seek on IX_Orders_OrderDate followed by a Key Lookup
(Clustered) on PK_Orders for CustomerId, Status, and TotalAmount
- A sort operator before Top (50), because the results are ordered by
OrderDate DESC
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 19
Hotspot Question
You have a Microsoft Fabric workspace named Workspace1 that contains a SQL database named SalesDB and an API for GraphQL item named SalesApi.
You have a Microsoft Entra group named SqlUsers.
From Workspace1, you assign permission to SalesApi as shown in the following exhibit.
The connection to SalesDB has the connectivity option configured as shown in the following exhibit.
SqlUsers has the Viewer role for Workspace1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 20
You have an Azure SQL database that supports an OLTP application.
You need to write Transact-SQL code that returns blocking chain details. The output must return only sessions that ate blocked or are blocking other sessions.
How should you complete the code? 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:
* CTE inner source # FROM sys.dm_exec_requests
* Join after sys.dm_exec_sessions AS s # LEFT OUTER JOIN sys.dm_exec_requests
* Text retrieval # OUTER APPLY sys.dm_exec_sql_text(r.sql_handle)
* Input buffer retrieval # OUTER APPLY sys.dm_exec_input_buffer(r.session_id, r.request_id) The correct drag-and-drop choices are based on how blocking-chain details are normally assembled in Azure SQL Database.
The CTE must read from sys.dm_exec_requests because the alias er is used with er.session_id and er.
blocking_session_id, and those columns come from sys.dm_exec_requests. Microsoft documents that sys.
dm_exec_requests returns information about executing requests and includes the blocking_session_id column used to identify blockers.
After FROM sys.dm_exec_sessions AS s, the correct join is LEFT OUTER JOIN sys.dm_exec_requests so the query can still return sessions from sys.dm_exec_sessions even when a current request row is missing.
This is useful when showing sessions that are blocked or blocking, while still attempting to attach current request details when available.
For batch text, use OUTER APPLY sys.dm_exec_sql_text(r.sql_handle) because Microsoft documents sys.
dm_exec_sql_text(sql_handle) as the function that returns the SQL batch text for the specified sql_handle.
For the input buffer, use OUTER APPLY sys.dm_exec_input_buffer(r.session_id, r.request_id) because Microsoft documents that sys.dm_exec_input_buffer takes session_id and request_id and returns event_info, which is commonly used when sys.dm_exec_sql_text is null or when you want the last command text.
So the completed code uses:
* FROM sys.dm_exec_requests
* LEFT OUTER JOIN sys.dm_exec_requests
* OUTER APPLY sys.dm_exec_sql_text(r.sql_handle)
* OUTER APPLY sys.dm_exec_input_buffer(r.session_id, r.request_id)
NEW QUESTION # 21
You need to meet the development requirements for the FeedbackJson column How should you complete the Transact SQL query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
JSON_VALUE(f.FeedbackJson, ' $.text ' ) AS FeedbackText
CONTAINS(FeedbackJson, @Keyword)
SimilarityScore
These three selections are the correct way to complete the query because they align exactly with the stated requirements for the FeedbackJson column.
First, to extract the customer feedback text from the JSON document , the correct expression is JSON_VALUE(f.FeedbackJson, ' $.text ' ) AS FeedbackText . Microsoft documents that JSON_VALUE is used to extract a scalar value from JSON, while JSON_QUERY is used for returning an object or array .
Since $.text is the textual feedback string, JSON_VALUE is the correct function.
Second, to filter rows where the JSON text contains a keyword , the best choice is CONTAINS (FeedbackJson, @Keyword) . The scenario explicitly states that FeedbackJson already has a full-text index
, and Microsoft documents that CONTAINS is the full-text predicate used in the WHERE clause to search full-text indexed character data. That makes it more appropriate than using EDIT_DISTANCE for keyword filtering.
Third, to order the results by similarity score, highest first , the correct item is SimilarityScore in the ORDER BY clause, which would be paired with DESC in the query. This matches the requirement to sort by the computed fuzzy similarity value. The DP-800 study guide specifically includes writing queries that use fuzzy string matching functions such as EDIT_DISTANCE, which supports the earlier computed SimilarityScore expression in the query.
NEW QUESTION # 22
Hotspot Question
You have an Azure SQL database named ProductsDB.
You deploy Data API builder (DAB) to Azure Container Apps.
You discover that the container app cannot connect to ProductsDB.
Your development team reports that the container app is unreachable from the internet for integration tests.
You need to update Azure SQL Database and Container Apps to meet the following requirements:
- Ensure that the Azure SQL logical server allows connections from
Azure services.
- Ensure that the Container Apps environment accepts inbound requests
from the public internet.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 23
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