070-776 무료 덤프문제 온라인 액세스

You use Microsoft Azure Stream Analytics to analyze data from an Azure event hub in real time and send the output to a table named Table1 in an Azure SQL database. Table1 has three columns named Date, EventID, and User.
You need to prevent duplicate data from being stored in the database.
How should you complete the statement? 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.

정답:

You need to use the Cognition.Vision.FaceDetector() function in U-SQL to analyze images.
Which attribute can you detect by using the function?

• A.hair color
• B.race
• C.weight
• D.gender

You have a Microsoft Azure Stream Analytics solution that captures website visits and user interactions on the website.
You have the sample input data described in the following table.

You have the sample output described in the following table.

How should you complete the script? 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.

정답:

Explanation

References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-stream-analytics-query-patterns

You have IoT devices that produce the following output.

You need to use Microsoft Azure Stream Analytics to convert the output into the tabular format described in the following table.

How should you complete the Stream Analytics query? 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.

정답:

You have a Microsoft Azure SQL data warehouse that has a fact table named FactOrder. FactOrder contains three columns named CustomerId, OrderId, and OrderDateKey. FactOrder is hash distributed on CustomerId.
OrderId is the unique identifier for FactOrder. FactOrder contains 3 million rows.
Orders are distributed evenly among different customers from a table named dimCustomers that contains 2 million rows.
You often run queries that join FactOrder and dimCustomers by selecting and grouping by the OrderDateKey column.
You add 7 million rows to FactOrder. Most of the new records have a more recent OrderDateKey value than the previous records.
You need to reduce the execution time of queries that group on OrderDateKey and that join dimCustomers and FactOrder.
What should you do?

• A.Update the statistics for the OrderDateKey column.
• B.Change the distribution for the FactOrder table to round robin.
• C.Change the distribution for the FactOrder table to be based on OrderId.
• D.Change the distribution for the dimCustomers table to OrderDateKey.