QUESTION: 26 Exam Topic: Design and develop data processing Questions

HOTSPOT (Drag and Drop is not supported)
You have an Azure SQL database named Database1 and two Azure event hubs named HubA and HubB. The data consumed from each source is shown in the following table.

You need to implement Azure Stream Analytics to calculate the average fare per mile by driver.

How should you configure the Stream Analytics input for each source? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.
Hot Area:

See Explanation section for answer.

Answer(s): A

Explanation:

HubA: Stream HubB: Stream
Database1: Reference
Reference data (also known as a lookup table) is a finite data set that is static or slowly changing in nature, used to perform a lookup or to augment your data streams. For example, in an IoT scenario, you could store metadata about sensors (which don’t change often) in reference data and join it with real time IoT data streams. Azure Stream Analytics loads reference data in memory to achieve low latency stream processing

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-use-reference-data

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QUESTION: 27 Exam Topic: Design and develop data processing Questions

You have an Azure Stream Analytics job that receives clickstream data from an Azure event hub.
You need to define a query in the Stream Analytics job. The query must meet the following requirements: Count the number of clicks within each 10-second window based on the country of a visitor.
Ensure that each click is NOT counted more than once. How should you define the Query?

SELECT Country, Avg(*) AS Average
FROM ClickStream TIMESTAMP BY CreatedAt
GROUP BY Country, SlidingWindow(second, 10)
SELECT Country, Count(*) AS Count
FROM ClickStream TIMESTAMP BY CreatedAt
GROUP BY Country, TumblingWindow(second, 10)
SELECT Country, Avg(*) AS Average
FROM ClickStream TIMESTAMP BY CreatedAt
GROUP BY Country, HoppingWindow(second, 10, 2)
SELECT Country, Count(*) AS Count
FROM ClickStream TIMESTAMP BY CreatedAt
GROUP BY Country, SessionWindow(second, 5, 10)

Answer(s): B

Explanation:

Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.
Example:

Incorrect Answers:
A: Sliding windows, unlike Tumbling or Hopping windows, output events only for points in time when the content of the window actually changes. In other words, when an event enters or exits the window. Every window has at least one event, like in the case of Hopping windows, events can belong to more than one sliding window.

C: Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as Tumbling windows that can overlap, so events can belong to more than one Hopping window result set. To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size.

D: Session windows group events that arrive at similar times, filtering out periods of time where there is no data.

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions

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QUESTION: 28 Exam Topic: Design and develop data processing Questions

HOTSPOT (Drag and Drop is not supported)
You are building an Azure Analytics query that will receive input data from Azure IoT Hub and write the results to Azure Blob storage. You need to calculate the difference in readings per sensor per hour.
How should you complete the query? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.
Hot Area:

See Explanation section for answer.

Answer(s): A

Explanation:

Box 1: LAG
The LAG analytic operator allows one to look up a “previous” event in an event stream, within certain constraints. It is very useful for computing the rate of growth of a variable, detecting when a variable crosses a threshold, or when a condition starts or stops being true.

Box 2: LIMIT DURATION
Example: Compute the rate of growth, per sensor:

SELECT sensorId,
growth = reading -
LAG(reading) OVER (PARTITION BY sensorId LIMIT DURATION(hour, 1))
FROM input

Reference:

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

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QUESTION: 29 Exam Topic: Design and develop data processing Questions

You need to schedule an Azure Data Factory pipeline to execute when a new file arrives in an Azure Data Lake Storage Gen2 container. Which type of trigger should you use?

on-demand
tumbling window
schedule
event

Answer(s): D

Explanation:

Event-driven architecture (EDA) is a common data integration pattern that involves production, detection, consumption, and reaction to events. Data integration scenarios often require Data Factory customers to trigger pipelines based on events happening in storage account, such as the arrival or deletion of a file in Azure Blob Storage account.

Reference:

https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-event-trigger

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QUESTION: 26 Exam Topic: Design and develop data processing Questions

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QUESTION: 27 Exam Topic: Design and develop data processing Questions

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QUESTION: 28 Exam Topic: Design and develop data processing Questions

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QUESTION: 29 Exam Topic: Design and develop data processing Questions

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