テストが来るのを静かに待っている場合は、目を覚まして、別の方法でDP-800試験を受ける準備ができている必要があります。最近のDP-800ガイド急流の効果が資格試験を通じて受験者の秘密兵器になったことを示した後、DP-800トレーニング資料を勉強して「テストデータ」を書くことがあなたの選択に最適です。 DP-800ガイドトレントのユーザーは、DP-800試験で予期しない結果を得ることができます。
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
Topexamは君の成功のために、最も質の良いMicrosoftのDP-800試験問題と解答を提供します。もし君はいささかな心配することがあるなら、あなたはうちの商品を購入する前に、Topexamは無料でサンプルを提供することができます。あなたはTopexamのMicrosoftのDP-800問題集を購入した後、私たちは一年間で無料更新サービスを提供することができます。
質問 # 70
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?
正解：C
解説：
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
質問 # 71
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?
正解：A
解説：
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
質問 # 72
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 an SDK-style SQL database project stored in a Git repository. The project targets an Azure SQL database.
The CI build fails with unresolved reference errors when the project references system objects.
You need to update the SQL database project to ensure that dotnet build validates successfully by including the correct system objects in the database model for Azure SQL Database.
Solution: Build the project by running dotnet build -bl -flp:v=diag.
Does this meet the goal?
正解：A
解説：
Correct:
* Add the Microsoft.SqlServer.Dacpacs.Azure.Master NuGet package to the project.
To resolve system reference errors in an SDK-style SQL project targeting Azure SQL Database, you need to add a reference to the Microsoft.SqlServer.Dacpacs.Azure.Master NuGet package.
In your .sqlproj file, include the following item group:
<ItemGroup>
<PackageReference Include="Microsoft.SqlServer.Dacpacs.Azure.Master" Version="1.60.0" />
</ItemGroup>
Why this works:
System Objects: Standard SDK-style projects don't automatically include system views (like sys.database_principals or sys.dm_db_resource_stats). This package provides the necessary metadata for the compiler.
Azure Specifics: It includes Azure-only system objects that aren't present in the standard master database dacpac used for on-premises SQL Server.
CI/CD Friendly: Since it is a NuGet package, the dotnet build command will automatically restore it during the CI process without requiring manual file paths or local installations of Visual Studio.
Incorrect:
* Add an artifact reference to the Azure SQL Database master.dacpac file.
* Add the Microsoft.SqlServer.Dacpacs.Master NuGet package to the project.
* Build the project by running dotnet build -bl -flp:v=diag.
Reference:
https://learn.microsoft.com/en-us/sql/tools/sql-database-projects/concepts/system-objects
質問 # 73
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.
正解：
解説：
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
質問 # 74
You have an Azure SQL database that supports an AI-enabled product catalog API. The database contains a table named Sales.Orders. Sales.Orders contains 20 million rows and has a nonclustered index on a column named CreateDate.
The API passes a date parameter named @OrderDate.
You have a stored procedure named get_latest_day_orders that filters by running the following query.
WHERE CAST(CreateDate AS date) = @0rderDate.
A review of the query execution reveals that the query causes an index scan.
You need to modify the predicate to ensure that Microsoft SQL Server can use an index seek on CreateDate for a single day.
Which WHERE clause should you use?
正解：B
解説：
To achieve an Index Seek on your CreateDate column, you must remove the CAST function from the column side of the equation. Wrapping a column in a function makes the expression non- SARGable (Searchable Argument), forcing SQL Server to scan the entire index rather than jumping to a specific range.
The Recommended WHERE Clause
To capture all rows for a single day while remaining SARGable, use a range comparison:
WHERE CreateDate >= @OrderDate
AND CreateDate < DATEADD(day, 1, @OrderDate)
Why This Works
Eliminates Functions on Columns: By keeping CreateDate "naked," the query optimizer can use the nonclustered index to find the exact starting point.
Handles Time Components: Since CreatedDate likely contains time data (DATETIME or DATETIME2), this logic captures everything from 00:00:00.000 up to (but not including) midnight of the following day.
Single Day Precision: It creates a "half-open" interval that is the standard best practice for date filtering in SQL Server.
Reference:
https://medium.com/@c.charalambos1998/how-to-design-indexes-in-sql-server-for-faster-query- performance-4a2279a9b512
質問 # 75
......
これらすべてのDP-800学習教材で、あなたの成功は100％保証されます。さらに、無料のデモがあります。無料のデモでは、練習資料の内容について証明された経験に基づいた推測を提供します。 DP-800試験の知識を、あなたのように成功することに熱心な熱心な試験受験者に伝えることで、彼らはそれを助けを提供する責任として扱います。あなたの情報の次の特徴を備えたDP-800学習ガイドを入手できる場合は、驚くべき進歩を遂げる準備をしてください。
DP-800真実試験: https://www.topexam.jp/DP-800_shiken.html