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질문 # 80
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a SQL database in Microsoft Fabric that contains a table named dbo.Orders.
dbo.Orders has a clustered index, contains three years of data, and is partitioned by a column named OrderDate by month.
You need to remove all the rows for the oldest month. The solution must minimize the impact on other queries that access the data in dbo.Orders.
Solution: Identify the partition scheme for the oldest month, and then run the following Transact- SQL statement.
ALTER TABLE dbo.Orders
DROP PARTITION SCHEME (partition_scheme_name);
Does this meet the goal?
정답：A
설명：
Correct:
* Identify the partition number for the oldest month, and then run the following Transact-SQL statement.
TRUNCATE TABLE dbo.Orders
WITH (PARTITIONS (partition number));
The best Transact-SQL statement to remove all rows for the oldest month while minimizing the impact on other queries is TRUNCATE TABLE with a WITH (PARTITIONS (...)) clause.
Why TRUNCATE TABLE ... WITH (PARTITIONS (...)) is Best
Efficiency: TRUNCATE TABLE is a Data Definition Language (DDL) operation that removes data by deallocating the data pages, which is a metadata operation and is very fast, regardless of the amount of data in the partition.
Minimal Logging: It uses less transaction log space compared to a DELETE statement, which logs each row deletion individually.
Low Impact on Concurrency: It performs a quick, partition-specific operation. A row-by-row DELETE would be a long-running transaction and could cause locking and blocking issues for other queries accessing the table.
Data Integrity: Because the table has a clustered index and is partitioned by the same column (aligned indexes), the TRUNCATE PARTITION operation is a fast, partition-level maintenance operation that targets only that specific data subset.
Incorrect:
* : Identify the partition scheme for the oldest month, and then run the following Transact-SQL statement.
ALTER TABLE dbo.Orders
DROP PARTITION SCHEME (partition_scheme_name);
The DROP PARTITION SCHEME statement removes the partition scheme object from the database but does not remove the data itself or free up the space, and it requires all tables to be moved off the scheme first, which is a complex operation. This does not meet the goal of removing the data efficiently.
* Run the following Transact-SQL statement.
DELETE FROM dbo.Orders
WHERE OrderDate < DATEADD(month, -36, SYSUTCDATETIME());
A standard DELETE statement, even with a WHERE clause that uses the partition column, can be a time-consuming, logged operation that causes locking and blocking on the main table, negatively impacting performance.
Reference:
https://stackoverflow.com/questions/63632963/truncate-partition-vs-drop-partition-performace- wise-which-one-is-efficient-an
질문 # 81
You have a SQL database in Microsoft Fabric that contains a table named dbo.Products. dbo.Products contains product catalog data.
You need to create a stored procedure that performs hybrid search. The solution must meet the following requirements:
* Use approximate nearest neighbor (ANN) to retrieve the top 20 candidate products.
* Re-rank only the candidates that also match a full-text query.
* Generate the query embedding.
How should you complete the Transact-SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
질문 # 82
You have a Microsoft SQL Server 2025 instance that has a managed identity enabled.
You have a database that contains a table named dbo.ManualChunks. dbo.ManualChunks 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 endpoint for chat completions. The solution must provide the highest level of security.
You write the following Transact-SG1 code.
What should you insert at line 02?
정답：D
설명：
The correct answer is Option B because the requirement is to call an Azure OpenAI REST endpoint from SQL Server 2025 while providing the highest level of security , and the instance already has a managed identity enabled . For Microsoft's SQL AI features, the preferred secure pattern is to use a database scoped credential with IDENTITY = ' Managed Identity ' instead of storing an API key. Microsoft documents that SQL Server 2025 supports managed identity for external AI endpoints, and for Azure OpenAI the credential secret uses the Cognitive Services resource identifier: { " resourceid " : " https://cognitiveservices.azure.
com " } .
So line 02 should be:
WITH IDENTITY = ' Managed Identity ' ,
SECRET = ' { " resourceid " : " https://cognitiveservices.azure.com " } ' ; Why the other options are incorrect:
* A and D use HTTP header or query-string credentials with an API key , which is less secure than managed identity because a secret key must be stored and rotated manually. Microsoft recommends managed identity where supported to avoid embedded secrets.
* C mixes Managed Identity with an api-key secret, which is not the correct pattern for Azure OpenAI managed-identity authentication.
* E uses an invalid identity value for this scenario. The accepted credential identities for external REST endpoint calls include HTTPEndpointHeaders , HTTPEndpointQueryString , Managed Identity , and Shared Access Signature .
Because the endpoint is Azure OpenAI and the question explicitly asks for the highest security , managed identity with the Cognitive Services resource ID is the Microsoft-aligned answer.
질문 # 83
You have a database that contains production data. The schema is stored in a Git repository as an SDK-style SQL database project and contains the following reference data.
A deployment pipeline can be rerun automatically when a transient failure occurs.
You need to deploy the reference data as part of the same CI/CD process. Rerunning the pipeline must produce the same outcome and must NOT create duplicate rows.
What should you do?
정답：B
설명：
To ensure your reference data deployment is idempotent (safe to rerun) and prevents duplicates within an SDK-style SQL project, you should use a Post-Deployment Script combined with a MERGE statement.
The Core Strategy: MERGE Statement
The MERGE command allows you to synchronize a target table with a source (your hardcoded data) in a single atomic operation. It checks for existing records based on a unique key and decides whether to insert, update, or delete.
Implementation Steps
1. Create a Seed Script
Add a file named Script.PostDeployment.sql to your project.
Set the Build Action to PostDeploy in the file properties.
2. Handle the Identity Column
Since RefID is an IDENTITY column, you must use SET IDENTITY_INSERT [Table] ON to specify exact IDs.
This ensures RefID values remain consistent across environments.
3. Write the Idempotent Logic
Define your reference data in a Common Table Expression (CTE) or a virtual table.
Use the sCode or RefID as the join key to find matches.
Reference:
https://www.mssqltips.com/sqlservertip/5648/including-predetermined-datasets-in-a-microsoft- database-project/
질문 # 84
Case Study 2 - Fabrikam
Existing Environment
Azure Environment
Fabrikam has a single Azure subscription in the East US 2 Azure region. The subscription contains an Azure SQL database named DB1. DB1 contains the following tables:
* Patients
* Employees
* Procedures
* Transactions
* UsefulPrompts
* ProcedureDocuments
You store a column master key as a secret in Azure Key Vault.
You have an on-premises application named TransactionProcessing that uses a hard-coded username and password in a connection string to access DB1.
Problem Statements
Users report that after executing a long-running stored procedure named sp_UpdateProcedureForPatient, updates to the underlying data are sometimes inconsistent.
Requirements
Planned Changes
Fabrikam plans to manage all changes to Azure SQL Database objects by using source control in GitHub. Every pull request submitted to production will be validated before it can be merged.
Deployments must use the Release configuration.
Security Requirements
Fabrikam identifies the following security requirements:
* The TransactionProcessing application must use a passwordless connection to DB1.
* The Employees table contains two columns named TaxID and Salary that must be encrypted at rest.
* Auditors must have a tamper-evident history of transactions with cryptographic proof of changes to the employee data.
Database Performance Requirements
Records accessed by using sp_UpdateProcedureForPatient must NOT be changed by other transactions while the stored procedure runs.
AI Search, Embeddings, and Vector Indexing
Fabrikam identifies the following AI-related requirements:
* Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF).
* Users must be able to query the data in DB1 by using prompts in Copilot in Microsoft Fabric.
* The UsefulPrompts table will store prompts that doctors can use to help diagnose patient illness by connecting to an Azure OpenAI endpoint.
Development Requirements
Fabrikam identifies the following development requirements:
* Provide the functionality to retrieve all the transactions of a given patient between two dates, showing a running total.
* Expose a Data API builder (DAB) configuration file to enable Azure services to perform the following operations over a REST API:
- Read data from the procedures table without authentication.
- Read and insert data into the Transactions table once authenticated.
- Execute the sp_UpdateProcedurePatient stored procedure.
* Provide the functionality to retrieve a list of the names of patients who underwent medical procedures during the last 30 days.
* Information for each medical procedure will be stored in a table. The table will be used with a large language model (LLM) for user querying and will have the following structure.
DAB
You create a DAB configuration file that meets the development requirements for DB1 and includes the following entities.
You implement ProcedureDocuments to support the planned changes.
When users consume data through the Retrieval Augmented Generation (RAG) pattern, they experience data retrieval delays.
You need to improve the data retrieval performance and reduce the number of tokens per retrieval.
What should you implement?
정답：C
설명：
Scenario: Fabrikam identifies the following AI-related requirements: Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF).
To remedy data retrieval delays in a Retrieval Augmented Generation (RAG) pattern using Reciprocal Rank Fusion (RRF) on an Azure SQL Database table, you should use embeddings.
In a RAG architecture, retrieval delays often stem from inefficient or computationally heavy search processes. While RRF is excellent for merging results from multiple sources (like combining keyword and vector searches), the core of the speed problem typically lies in how the initial data is indexed and retrieved.
Role of Embeddings
Vector Search Acceleration: Embeddings convert text into high-dimensional vectors. Azure SQL Database can perform similarity searches on these vectors much faster than complex semantic text matching.
Hybrid Search Synergy: RRF is most effective when it fuses results from a keyword search (fast) and a vector search (powered by embeddings). Using embeddings ensures that the "semantic" side of the retrieval is streamlined.
Pre-computation: Since embeddings are generated once during ingestion, the retrieval phase only requires a distance calculation (e.g., Cosine Similarity), which is significantly faster than real- time natural language parsing during each query.
Reference:
https://pratikbarjatya.medium.com/unlocking-the-power-of-language-with-retrieval-augmented- generation-rag-14123cc275e6
질문 # 85
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