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NEW QUESTION # 56
You have an Azure SQL database that contains a table named dbo.ManualChunks. dbo.HonualChunks contains product manuals A retrieval query already returns the top five matching chunks as nvarchar(max) text.
You need to call an Azure OpenAI REST endpomt for chat completions. The request body must include both the user question and theretiieved chunks.
You write the following Transact-SQL code.
What should you insert at line 22?
Answer: C
Explanation:
The correct insertion at line 22 is FOR JSON PATH, WITHOUT_ARRAY_WRAPPER .
The request body for the Azure OpenAI chat completions call must be a single JSON object containing the messages array with both the system/user content and the retrieved chunks. Microsoft documents that FOR JSON PATH is the preferred way to shape JSON output, especially when you want precise control over nested property names like messages[0].role and messages[1] .content.
The key detail is WITHOUT_ARRAY_WRAPPER . By default, FOR JSON returns results enclosed in square brackets as a JSON array. Microsoft documents that WITHOUT_ARRAY_WRAPPER removes those brackets so a single JSON object is produced instead. That is exactly what is needed here for @payload, because the stored procedure is building one request body, not an array of request bodies.
NEW QUESTION # 57
You have an Azure SQL database named SalesDB on a logical server named sales-sql01.
You have an Azure App Service web app named OrderApi that connects to SalesDB by using SQL authentication.
You enable a user-assigned managed identity named OrderApi-Id for OrderApi.
You need to configure OrderApi to connect to SalesDB by using Microsoft Entra authentication. The managed identity must have read and write permissions to SalesDB.
Which Transact-SQL statements should you run in SalesDB?
Answer: D
Explanation:
For an Azure App Service using a user-assigned managed identity to connect to Azure SQL Database with Microsoft Entra authentication , the required database-side step is to create a database user from the external provider , then grant the needed database roles. Microsoft's Azure SQL documentation for managed identities states that to let a managed identity access the target database, you create a SQL user for that identity by using:
CREATE USER [ < identity-name > ] FROM EXTERNAL PROVIDER;
and then assign the appropriate roles.
That makes db_datareader and db_datawriter the right role grants here, because the requirement says the identity must have read and write permissions to SalesDB.
The other options are incorrect:
* A uses CREATE LOGIN ... FROM EXTERNAL PROVIDER, which is not the right choice for this Azure SQL Database scenario; the documented pattern is to create a database user from the external provider.
* B and D create SQL-authentication principals with passwords, which does not meet the Microsoft Entra managed-identity requirement.
* D also grants sysadmin, which is a server-level overgrant and not appropriate for the stated read/write requirement.
NEW QUESTION # 58
Drag and Drop Question
You have an Azure AI Search service and an index named hotels that includes a vector field named DescriptionVector.
You query hotels by using the Search Documents REST API.
You need to implement a hybrid search query that uses DescriptionVector and includes captions.
How should you complete the REST request body? 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:
NEW QUESTION # 59
You have an Azure SQL database that contains the following tables and columns.
Embeddings in the NotesEnbeddings and DescriptionEabeddings tables have been generated from values in the Description and notes columns of the Articles table by using different chunk sizes.
You need to perform approximate nearest neighbor (ANN) queries across both embedding tables. The solution must minimize the impact of using different chunk sizes.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The correct function is VECTOR_SEARCH because the requirement is to perform approximate nearest neighbor (ANN) queries. Microsoft's SQL documentation states that VECTOR_SEARCH is the function used for vector similarity search, and that an ANN index is used only with VECTOR_SEARCH when a compatible vector index exists on the target column. By contrast, VECTOR_DISTANCE calculates an exact distance and does not use a vector index for ANN retrieval.
The correct distance metric is cosine distance. Microsoft documents that VECTOR_SEARCH supports cosine, dot, and euclidean metrics, and Microsoft guidance specifically notes that cosine similarity is commonly used for text embeddings. It also states that retrieval of the most similar texts to a given text typically functions better with cosine similarity, and that Azure OpenAI embeddings rely on cosine similarity to compute similarity between a query and documents. Since both NotesEmbeddings and DescriptionEmbeddings are text-derived embeddings and the goal is to minimize the impact of different chunk sizes, cosine is the best choice because it compares direction/angle rather than being as sensitive to vector magnitude as Euclidean distance.
NEW QUESTION # 60
Drag and Drop Question
You have an Azure SQL database named SalesDB that supports an ecommerce application.
SalesDB contains a table named dbo.Orders that has a clustered index on a column named OrderId.
dbo.Orders receives continuous OLTP inserts and updates during business hours.
Your analytics team runs hourly aggregate queries that scan dbo.Orders to calculate revenue trends for recent dates.
You need to improve the performance of the hourly analytics queries without significantly affecting OLTP throughput. The solution must meet the following requirements:
- Support near-real-time (NRT) analytics on the dbo.Orders table.
- Reduce read time when retrieving analytical data from dbo.Orders.
- Support indexing only rows that match a predicate, such as Active =
1.
Which type of index should you use for each requirement? To answer, drag the appropriate index types to the correct requirements. Each index type 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:
NEW QUESTION # 61
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