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NEW QUESTION # 208
Task 8
You plan to perform performance testing of db1.
You need prevent db1 from reverting to the last known good query plan.
Answer:
Explanation:
See the explanation part for the complete Solution.
Explanation:
To prevent db1 from reverting to the last known good query plan, you need to disable the automatic plan correction feature for the database. This feature is enabled by default and allows the Query Store to detect and fix plan performance regressions by forcing the last good plan1. However, if you want to test the performance of different plans without interference from the Query Store, you can turn off this feature by using the ALTER DATABASE SCOPED CONFIGURATION statement2.
Here are the steps to disable the automatic plan correction feature for db1:
* Connect to db1 using SQL Server Management Studio, Azure Data Studio, or any other tool that supports Transact-SQL statements.
* Open a new query window and run the following command: ALTER DATABASE SCOPED CONFIGURATION SET AUTOMATIC_TUNING (FORCE_LAST_GOOD_PLAN = OFF); GO
* This command will disable the automatic plan correction feature for db1 and allow the Query Optimizer to choose the best plan based on the current statistics and parameters3.
* To verify that the automatic plan correction feature is disabled for db1, you can query the sys.database_scoped_configurations catalog view. The value of the force_last_good_plan column should be 0 for db1.
These are the steps to disable the automatic plan correction feature for db1.
NEW QUESTION # 209
You need to configure user authentication for the SERVER1 databases. The solution must meet the security and compliance requirements.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Scenario: Authenticate database users by using Active Directory credentials.
The configuration steps include the following procedures to configure and use Azure Active Directory authentication.
Create and populate Azure AD.
Optional: Associate or change the active directory that is currently associated with your Azure Subscription.
Create an Azure Active Directory administrator. (Step 1)
Configure your client computers.
Create contained database users in your database mapped to Azure AD identities. (Step 2) Connect to your database by using Azure AD identities. (Step 3) Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/authentication-aad-overview
NEW QUESTION # 210
You have a Microsoft SQL Server 2019 database named DB1 that uses the following database-level and
instance-level features.
* Clustered columnstore indexes
* Automatic tuning
* Change tracking
* PolyBase
You plan to migrate DB1 to an Azure SQL database.
What feature should be removed or replaced before DB1 can be migrated?
Answer: C
Explanation:
Section: [none]
Explanation:
This table lists the key features for PolyBase and the products in which they're available.
Incorrect Answers:
C: Change tracking is a lightweight solution that provides an efficient change tracking mechanism for
applications. It applies to both Azure SQL Database and SQL Server.
D: Azure SQL Database and Azure SQL Managed Instance automatic tuning provides peak performance and
stable workloads through continuous performance tuning based on AI and machine learning.
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/polybase/polybase-versioned-feature-summary
Testlet 1
This is a case study. Case studies are not timed separately. You can use as much exam time as you
would like to complete each case. However, there may be additional case studies and sections on this exam.
You must manage your time to ensure that you are able to complete all questions included on this exam in the
time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the
case study. Case studies might contain exhibits and other resources that provide more information about the
scenario that is described in the case study. Each question is independent of the other questions in this case
study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to
make changes before you move to the next section of the exam. After you begin a new section, you cannot
return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore
the content of the case study before you answer the questions. Clicking these buttons displays information such
as business requirements, existing environment, and problem statements. If the case study has an All
Information tab, note that the information displayed is identical to the information displayed on the subsequent
tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. is a renewable energy company that has a main office in Boston. The main office hosts a sales
department and the primary datacenter for the company.
Physical Locations
Existing Environment
Litware has a manufacturing office and a research office is separate locations near Boston. Each office has its
own datacenter and internet connection.
The manufacturing and research datacenters connect to the primary datacenter by using a VPN.
Network Environment
The primary datacenter has an ExpressRoute connection that uses both Microsoft peering and private peering.
The private peering connects to an Azure virtual network named HubVNet.
Identity Environment
Litware has a hybrid Azure Active Directory (Azure AD) deployment that uses a domain named litwareinc.com.
All Azure subscriptions are associated to the litwareinc.com Azure AD tenant.
Database Environment
The sales department has the following database workload:
* An on-premises named SERVER1 hosts an instance of Microsoft SQL Server 2012 and two 1-TB
databases.
* A logical server named SalesSrv01A contains a geo-replicated Azure SQL database named SalesSQLDb1.
SalesSQLDb1 is in an elastic pool named SalesSQLDb1Pool. SalesSQLDb1 uses database firewall rules
and contained database users.
* An application named SalesSQLDb1App1 uses SalesSQLDb1.
The manufacturing office contains two on-premises SQL Server 2016 servers named SERVER2 and
SERVER3. The servers are nodes in the same Always On availability group. The availability group contains a
database named ManufacturingSQLDb1
Database administrators have two Azure virtual machines in HubVnet named VM1 and VM2 that run Windows
Server 2019 and are used to manage all the Azure databases.
Licensing Agreement
Litware is a Microsoft Volume Licensing customer that has License Mobility through Software Assurance.
Current Problems
SalesSQLDb1 experiences performance issues that are likely due to out-of-date statistics and frequent blocking
queries.
Requirements
Planned Changes
Litware plans to implement the following changes:
* Implement 30 new databases in Azure, which will be used by time-sensitive manufacturing apps that have
varying usage patterns. Each database will be approximately 20 GB.
* Create a new Azure SQL database named ResearchDB1 on a logical server named ResearchSrv01.
ResearchDB1 will contain Personally Identifiable Information (PII) data.
* Develop an app named ResearchApp1 that will be used by the research department to populate and access
ResearchDB1.
* Migrate ManufacturingSQLDb1 to the Azure virtual machine platform.
* Migrate the SERVER1 databases to the Azure SQL Database platform.
Technical Requirements
Litware identifies the following technical requirements:
* Maintenance tasks must be automated.
* The 30 new databases must scale automatically.
* The use of an on-premises infrastructure must be minimized.
* Azure Hybrid Use Benefits must be leveraged for Azure SQL Database deployments.
* All SQL Server and Azure SQL Database metrics related to CPU and storage usage and limits must be
analyzed by using Azure built-in functionality.
Security and Compliance Requirements
Litware identifies the following security and compliance requirements:
* Store encryption keys in Azure Key Vault.
* Retain backups of the PII data for two months.
* Encrypt the PII data at rest, in transit, and in use.
* Use the principle of least privilege whenever possible.
* Authenticate database users by using Active Directory credentials.
* Protect Azure SQL Database instances by using database-level firewall rules.
* Ensure that all databases hosted in Azure are accessible from VM1 and VM2 without relying on public
endpoints.
Business Requirements
Litware identifies the following business requirements:
* Meet an SLA of 99.99% availability for all Azure deployments.
* Minimize downtime during the migration of the SERVER1 databases.
* Use the Azure Hybrid Use Benefits when migrating workloads to Azure.
* Once all requirements are met, minimize costs whenever possible.
NEW QUESTION # 211
Task 1
In an Azure SQL database named db1, you need to enable page compression on the PK_SalesOrderHeader_SalesOrderlD clustered index of the SalesLT.SalesOrderHeader table.
Answer:
Explanation:
See the explanation part for the complete Solution.
Explanation:
To enable page compression on the PK_SalesOrderHeader_SalesOrderlD clustered index of the SalesLT.
SalesOrderHeader table in db1, you can use the following Transact-SQL script:
-- Connect to the Azure SQL database named db1
USE db1;
GO
-- Enable page compression on the clustered index
ALTER INDEX PK_SalesOrderHeader_SalesOrderlD ON SalesLT.SalesOrderHeader REBUILD WITH (DATA_COMPRESSION = PAGE); GO This script will rebuild the clustered index with page compression, which can reduce the storage space and improve the query performance The script solution consists of three parts:
* The first part is USE db1; GO. This part connects to the Azure SQL database named db1, where the SalesLT.SalesOrderHeader table is located. The GO command separates the batches of Transact-SQL statements and sends them to the server.
* The second part is ALTER INDEX PK_SalesOrderHeader_SalesOrderlD ON SalesLT.
SalesOrderHeader REBUILD WITH (DATA_COMPRESSION = PAGE); GO. This part enables page compression on the clustered index named PK_SalesOrderHeader_SalesOrderlD, which is defined on the SalesLT.SalesOrderHeader table. The ALTER INDEX statement modifies the properties of an existing index. The REBUILD option rebuilds the index from scratch, which is required to change the compression setting. The DATA_COMPRESSION = PAGE option specifies that page compression is applied to the index, which means that both row and prefix compression are used. Page compression can reduce the storage space and improve the query performance by compressing the data at the page level. The GO command ends the batch of statements.
* The third part is optional, but it can be useful to verify the compression status of the index. It is SELECT name, index_id, data_compression_desc FROM sys.indexes WHERE object_id = OBJECT_ID('SalesLT.SalesOrderHeader');. This part queries the sys.indexes catalog view, which contains information about the indexes in the database. The SELECT statement returns the name, index_id, and data_compression_desc columns for the indexes that belong to the SalesLT.
SalesOrderHeader table. The OBJECT_ID function returns the object identification number for the table name. The data_compression_desc column shows the compression type of the index, which should be PAGE for the clustered index after the script is executed.
These are the steps of the script solution for enabling page compression on the clustered index of the SalesLT.
SalesOrderHeader table in db1.
NEW QUESTION # 212
You have an Azure Synapse Analytics dedicated SQL pool.
You run PDW_SHOWSPACEUSED('dbo.FactInternetSales'); and get the results shown in the following table.
Which statement accurately describes the dbo.FactInternetSales table?
Answer: C
Explanation:
The rows per distribution can vary up to 10% without a noticeable impact on performance. Here the distribution varies more than 10%. It is skewed.
Note: SHOWSPACEUSED displays the number of rows, disk space reserved, and disk space used for a specific table, or for all tables in a Azure Synapse Analytics or Parallel Data Warehouse database.
This is a very quick and simple way to see the number of table rows that are stored in each of the 60 distributions of your database. Remember that for the most balanced performance, the rows in your distributed table should be spread evenly across all the distributions.
ROUND_ROBIN distributed tables should not be skewed. Data is distributed evenly across the nodes by design.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables- distribute
https://github.com/rgl/azure-content/blob/master/articles/sql-data-warehouse/sql-data-warehouse-manage- distributed-data-skew.md
NEW QUESTION # 213
......
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