070-475 무료 덤프문제 온라인 액세스

You are designing an Internet of Things (IoT) solution intended to identify trends. The solution requires the real-time analysis of data originating from sensors. The results of the analysis will be stored in a SQL database.
You need to recommend a data processing solution that uses the Transact-SQL language.
Which data processing solution should you recommend?

• A.Microsoft Azure HDInsight Hadoop clusters
• B.Microsoft Azure Stream Analytics
• C.Microsoft Azure HDInsight Spark clusters
• D.Microsoft Azure Event Hubs

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 states goals. Some question sets might have more than one correct solution, while the 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 Apache Spark system that contains 5 TB of data.
You need to write queries that analyze the data in the system. The queries must meet the following requirements:
* Use static data typing.
* Execute queries as quickly as possible.
* Have access to the latest language features.
Solution: You write the queries by using Scala.

• A.Yes
• B.No

You implement DB2.
You need to configure the tables in DB2 to host the data from DB1. The solution must meet the requirements for DB2.
Which type of table and history table storage should you use for the tables? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

정답:

Explanation

From Scenario: Relecloud plans to implement a data warehouse named DB2.
Box 1: Temporal table
From Scenario:
Relecloud identifies the following requirements for DB2:
Users must be able to view previous versions of the data in DB2 by using aggregates.
DB2 must be able to store more than 40 TB of data.
A system-versioned temporal table is a new type of user table in SQL Server 2017, designed to keep a full history of data changes and allow easy point in time analysis. A temporal table also contains a reference to another table with a mirrored schema. The system uses this table to automatically store the previous version of the row each time a row in the temporal table gets updated or deleted. This additional table is referred to as the history table, while the main table that stores current (actual) row versions is referred to as the current table or simply as the temporal table.

You need to create a query that identifies the trending topics.
How should you complete the 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:

Explanation

From scenario: Topics are considered to be trending if they generate many mentions in a specific country during a 15-minute time frame.
Box 1: TimeStamp
Azure Stream Analytics (ASA) is a cloud service that enables real-time processing over streams of data flowing in from devices, sensors, websites and other live systems. The stream-processing logic in ASA is expressed in a SQL-like query language with some added extensions such as windowing for performing temporal calculations.
ASA is a temporal system, so every event that flows through it has a timestamp. A timestamp is assigned automatically based on the event's arrival time to the input source but you can also access a timestamp in your event payload explicitly using TIMESTAMP BY:
SELECT * FROM SensorReadings TIMESTAMP BY time
Box 2: GROUP BY
Example: Generate an output event if the temperature is above 75 for a total of 5 seconds SELECT sensorId, MIN(temp) as temp FROM SensorReadings TIMESTAMP BY time GROUP BY sensorId, SlidingWindow(second, 5) HAVING MIN(temp) > 75 Box 3: SlidingWindow Windowing is a core requirement for stream processing applications to perform set-based operations like counts or aggregations over events that arrive within a specified period of time. ASA supports three types of windows: Tumbling, Hopping, and Sliding.
With a Sliding Window, the system is asked to logically consider all possible windows of a given length and output events for cases when the content of the window actually changes - that is, when an event entered or existed the window.

Your company has a data visualization solution that contains a customized Microsoft Azure Stream Analytics solution. The solution provides data to a Microsoft Power BI deployment.
Every 10 seconds, you need to query for instances that have more than three records.
How should you complete the 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:

Explanation

Box 1: TumblingWindow(second, 10)
Tumbling Windows define a repeating, non-overlapping window of time.
Example: Calculate the count of sensor readings per device every 10 seconds SELECT sensorId, COUNT(*) AS Count FROM SensorReadings TIMESTAMP BY time GROUP BY sensorId, TumblingWindow(second, 10) Box 2: [Count] >= 3 Count(*) returns the number of items in a group.