70-475日本語試験無料問題集「Microsoft Design and Implement Big Data Analytics Solutions (70-475日本語版) 認定」



解説: (GoShiken メンバーにのみ表示されます)

正解:

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.

解説: (GoShiken メンバーにのみ表示されます)

正解:

Explanation

Azure Data Factory can be used to orchestrate the execution of stored procedures. This allows more complex pipelines to be created and extends Azure Data Factory's ability to leverage the computational power of SQL Data Warehouse.
From scenario:
Relecloud has a Microsoft SQL Server database named DB1 that stores information about the advertisers.
DB1 is hosted on a Microsoft Azure virtual machine.
Relecloud identifies the following requirements for DB1:
* Data generated by the streaming analytics platform must be stored in DB1.
* The advertisers in DB1 must be stored in a table named Table1 and must be refreshed nightly.



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Explanation

A table created without the EXTERNAL clause is called a managed table because Hive manages its data.


* Azure Data Lake
* Azure Cosmos DB
* Azure Data Factory






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Explanation

Box 1: 3
Box 2: 3
Considerations for using gateway

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Explanation
1. Create Shared Access Signature policy2. Save the SAS policy token, storage account name, and container name. These values are used when associating the storage account with your HDInsight cluster.3. Update property of core-site4. Maintenance mode5. Restart all serviceshttps://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-storage-sharedaccesssignature-permissions