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NEW QUESTION # 25
Your team is developing an Azure SQL database solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
You need to ensure that GitHub Copilot Chat uses the team's coding standards when generating Transact-SQL code in Visual Studio Code.
What should you use?
Answer: B
Explanation:
o ensure GitHub Copilot Chat adheres to your team's specific Transact-SQL (T-SQL) standards while deploying an Azure SQL database from VS Code, you should focus on Custom Instructions and Workspace Context.
Required Setup
Create a .github/copilot-instructions.md File
This is the most effective way to enforce standards.
Create this file in the root of your repository.
Copilot automatically reads this file to understand project-specific rules.
Include sections for:
Naming conventions (e.g., PascalCase for tables, proc_ prefix for stored procedures).
Formatting rules (e.g., keywords in UPPERCASE, use of 4 spaces).
Security practices (e.g., always use schema prefixes, avoid SELECT *).
Reference:
https://nikolay-dev.medium.com/master-web-development-with-github-spark-ai-b0b874525418
NEW QUESTION # 26
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: Run the following Transact-SQL statement.
DELETE FROM dbo.Orders
WHERE OrderDate < DATEADD(month, -36, SYSUTCDATETIME());
Does this meet the goal?
Answer: A
Explanation:
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
NEW QUESTION # 27
What is the benefit of using embeddings over keyword search?
Answer: A
Explanation:
Embeddings capture semantic meaning, enabling context-based retrieval.
NEW QUESTION # 28
Hotspot Question
You have a SQL database in Microsoft Fabric that uses the default settings for a newly created database and contains a table named Sales.Orders.
You have an application that uses two stored procedures to access Sales.Orders.
While monitoring database activity, you discover the following:
- sys.dm_exec_requests shows multiple sessions in a suspended state
with wait_type = LCK_M_X. All the sessions show the same wait_resource, which maps to Sales.Orders, and the same nonzero blocking_session_id.
- sys.dm_exec_input_buffer(blocking_session_id, NULL) returns a last
submitted command of BEGIN TRANSACTION UPDATE Sales.Orders.
- sys.dm_exec_sessions for the blocking session shows status = sleeping and open_transaction_count = 1.
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 # 29
You need to recommend a solution for the development team to retrieve the live metadata. The solution must meet the development requirements.
What should you include in the recommendation?
Answer: A
Explanation:
The best recommendation is to use an MCP server . In the official DP-800 study guide , Microsoft explicitly lists skills such as configuring Model Context Protocol (MCP) tool options in a GitHub Copilot session and connecting to MCP server endpoints, including Microsoft SQL Server and Fabric Lakehouse . That makes MCP the exam-aligned mechanism for enabling AI-assisted tools to work with live database context rather than static snapshots.
This also matches the stated development requirement: the team will use Visual Studio Code and GitHub Copilot and needs to retrieve live metadata from the databases . Microsoft's documentation for GitHub Copilot with the MSSQL extension explains that Copilot works with an active database connection , provides schema-aware suggestions , supports chatting with a connected database, and adapts responses based on the current database context . Microsoft also documents MCP as the standard way for AI tools to connect to external systems and data sources through discoverable tools and endpoints.
The other options do not satisfy the "live metadata" requirement as well:
* A .dacpac is a point-in-time schema artifact, not live metadata.
* A Copilot instruction file provides guidance, not live database discovery.
* Including the database project in the repository helps source control and deployment, but it still does not provide live database metadata by itself.
NEW QUESTION # 30
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