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NEW QUESTION: 1
Which of the following are true of multi-cluster Warehouses? Select all that apply below.
A. A multi-cluster Warehouse can automatically turn itself off after a period of inactivity
B. A multi-cluster Warehouse can automatically turn itself on when a query is executed against it
C. A multi-cluster Warehouse can scale down when query activity slows
D. A multi-cluster Warehouse can add clusters automatically based on query activity
Answer: A,B,C,D

NEW QUESTION: 2
You have an Azure subscription that contains the public load balancers shown in the following table.

You plan to create six virtual machines and to load balancer requests to the virtual machines. Each load balancer will load balance three virtual machines.
You need to create the virtual machines for the planned solution.
How should you create the virtual machines? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: be created in the same availability set or virtual machine scale set.
The Basic tier is quite restrictive. A load balancer is restricted to a single availability set, virtual machine scale set, or a single machine.
Box 2: be connected to the same virtual network
The Standard tier can span any virtual machine in a single virtual network, including blends of scale sets, availability sets, and machines.
References:
https://www.petri.com/comparing-basic-standard-azure-load-balancers

NEW QUESTION: 3
You need to implement a solution that solves the performance issues of
usp_GetOrdersAndItems.
Which statements should you execute?
A. CREATE INDEX IX_Orders_Active ON Orders(ShipDate, DeliveryDate) INCLUDE( Amount)
B. CREATE INDEX IX_Orders_Active ON Orders(DeliveryDate) INCLUDE(Amount) WHERE ShipDate IS NXXL
C. CREATE INDEX IX_Orders_Active ON Orders(DeliveryDate, Amount) WHERE ShipDate IS NULL
D. CREATE INDEX IX_Orders_Active ON Orders(ShipDate, DeliveryDate, Amount)
Answer: B
Explanation:
Topic 7, Fourth Coffee
Background
Corporate Information
Fourth Coffee is global restaurant chain. There are more than 5,000 locations worldwide.
Physical Locations
Currently a server at each location hosts a SQL Server 2012 instance. Each instance contains a database called StoreTransactions that stores all transactions from point of sale and uploads summary batches nightly.
Each server belongs to the COFFECORP domain. Local computer accounts access the StoreTransactions database at each store using sysadmin and datareaderwriter roles.
Planned changes
Fourth Coffee has three major initiatives:
The FT department must consolidate the point of sales database infrastructure.
The marketing department plans to launch a mobile application for micropayments.
The finance department wants to deploy an internal tool that will help detect fraud.
---
Initially, the mobile application will allow customers to make micropayments to buy coffee and other items on the company web site. These micropayments may be sent as gifts to other users and redeemed within an hour of ownership transfer. Later versions will generate profiles based on customer activity that will push texts and ads generated by an analytics application.
When the consolidation is finished and the mobile application is in production, the micropayments and point of sale transactions will use the same database.
Existing Environment
Existing Application Environment
Some stores have been using several pilot versions of the micropayment application. Each version currently is in a database that is independent from the point of sales systems. Some versions have been used in field tests at local stores, and others are hosted at corporate servers. All pilot versions were developed by using SQL Server 2012.
Existing Support Infrastructure
The proposed database for consolidating micropayments and transactions is called CoffeeTransactions. The database is hosted on a SQL Server 2014 Enterprise Edition instance and has the following file structures:

Business Requirements
General Application Solution Requirements
The database infrastructure must support a phased global rollout of the micropayment application and consolidation.
The consolidated micropayment and point of sales database will be into a CoffeeTransactions database. The infrastructure also will include a new CoffeeAnalytics database for reporting on content from CoffeeTransactions.
Mobile applications will interact most frequently with the micropayment database for the
following activities: - Retrieving the current status of a micropayment; - Modifying the status of the current micropayment; and - Canceling the micropayment.
The mobile application will need to meet the following requirements: - Communicate with web services that assign a new user to a micropayment by using a stored procedure named usp_AssignUser. - Update the location of the user by using a stored procedure named usp_AddMobileLocation.
The fraud detection service will need to meet the following requirements: - Query the current open micropayments for users who own multiple micropayments by using a stored procedure named usp.LookupConcurrentUsers. - Persist the current user locations by using a stored procedure named usp_Mobilel_ocationSnapshot. - Look at the status of micropayments and mark micropayments for internal investigations. - Move micropayments to dbo.POSException table by using a stored procedure named ups_DetectSuspiciousActivity. - Detect micropayments that are flagged with a StatusId value that is greater than 3 and that occurred within the last minute.
The CoffeeAnalytics database will combine imports of the POSTransaction and MobileLocation tables to create a UserActivity table for reports on the trends in activity. Queries against the UserActivity table will include aggregated calculations on all columns that are not used in filters or groupings.
Micropayments need to be updated and queried for only a week after their creation by the mobile application or fraud detection services.
Performance
The most critical performance requirement is keeping the response time for any queries of
the POSTransaction table predictable and fast.
Web service queries will take a higher priority in performance tuning decisions over the
fraud detection agent queries.
Scalability
Queries of the user of a micropayment cannot return while the micropayment is being updated, but can show different users during different stages of the transaction.
The fraud detection service frequently will run queries over the micropayments that occur over different time periods that range between 30 seconds and ten minutes.
The POSTransaction table must have its structure optimized for hundreds of thousands of active micropayments that are updated frequently.
All changes to the POSTransaction table will require testing in order to confirm the expected throughput that will support the first year's performance requirements.
Updates of a user's location can tolerate some data loss.
Initial testing has determined that the POSTransaction and POSException tables will be migrated to an in-memory optimized table.
Availability
In order to minimize disruption at local stores during consolidation, nightly processes will restore the databases to a staging server at corporate headquarters.
Technical Requirements
Security
The sensitive nature of financial transactions in the store databases requires certification of the COFFECORP\Auditors group at corporate that will perform audits of the data. Members of the COFFECORP\Auditors group cannot have sysadmin or datawriter access to the database. Compliance requires that the data stewards have access to any restored StoreTransactions database without changing any security settings at a database level.
Nightly batch processes are run by the services account in the COFFECORP\StoreAgent group and need to be able to restore and verify the schema of the store databases match.
No Windows group should have more access to store databases than is necessary.
Maintainability
You need to anticipate when POSTransaction table will need index maintenance.
When the daily maintenance finishes, micropayments that are one week old must be available for queries in UserActivity table but will be queried most frequently within their first week and will require support for in-memory queries for data within first week.
The maintenance of the UserActivity table must allow frequent maintenance on the day's most recent activities with minimal impact on the use of disk space and the resources available to queries. The processes that add data to the UserActivity table must be able to update data from any time period, even while maintenance is running.
The index maintenance strategy for the UserActivity table must provide the optimal structure for both maintainability and query performance.
All micropayments queries must include the most permissive isolation level available for the maximum throughput.
In the event of unexpected results, all stored procedures must provide error messages in text message to the calling web service.
Any modifications to stored procedures will require the minimal amount of schema changes necessary to increase the performance.
Performance
Stress testing of the mobile application on the proposed CoffeeTransactions database uncovered performance bottlenecks. The sys.dm_os_wait_stats Dynamic Management View (DMV) shows high wait_time values for WRTTELOG and PAGEIOLATCHJJP wait types when updating the MobileLocation table.
Updates to the MobileLocation table must have minimal impact on physical resources.
Supporting Infrastructure
The stored procedure usp_LookupConcurrentUsers has the current implementation:

The current stored procedure for persisting a user location is defined in the following code:

The current stored procedure for managing micropayments needing investigation is defined in the following code:

The current table, before implementing any performance enhancements, is defined as follows:

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