Send Active Users' Data on E-commerce Website for Last 20 Seconds

Correct Answer: A.

If you look at the options, you can find that only the window function is changing.

It is mentioned in the question that the data should be collected for an interval of 20 seconds and should be grouped by page.

All the options contain grouping by page.

So, finding the function type which collects stream data and changes into the time segments and does the function will be the right answer.

This is basically the functionality of the Tumbling window function.

Option A is correct: Tumbling function does this as the explanation says.

Option B is incorrect: This functions will output events only for points in time when there is a change in the content in the selected window.

Option C is incorrect: These types of functions hop forward in time by a constant period.

Option D is incorrect: It just groups the events based on timestamp and doesn't require specific value as input for window function.

To know more about Window Functions, please refer to the doc below:

Based on the given scenario, the objective is to set up a stream data processing solution that sends active users' data on the website for the last 20 seconds, segmented by the page they visited. The data processing solution will be backed by Azure Stream Analytics, which is a cloud-based service that allows users to analyze and process streaming data from various sources, such as IoT devices, social media, and application logs.

The query that would best match the given scenario is option A: SELECT productid, location(*) AS Count FROM websitevisitors TIMESTAMP BY CreatedAt GROUP BY Page, TumblingWindow(second, 10).

Let's break down the query and understand its components:

• SELECT: This clause specifies the columns that should be included in the output of the query. In this case, the query is selecting the productid and the count of website visitors' locations.
• FROM: This clause specifies the source of the data. In this case, the data is coming from the websitevisitors stream.
• TIMESTAMP BY: This clause specifies the column that should be used as the timestamp for the streaming data. In this case, the CreatedAt column is being used as the timestamp.
• GROUP BY: This clause specifies the grouping criteria for the data. In this case, the data is being grouped by the page that the user visited and a tumbling window of 10 seconds.
• TumblingWindow: This is a windowing function that groups the data into fixed-size, non-overlapping windows. In this case, the window size is 10 seconds, and the data is grouped into windows based on the timestamp.
• (*) AS Count: This clause specifies that the count of website visitors' locations should be returned as "Count".

Option A is the best match because it groups the data by the page the user visited and uses a tumbling window function that divides the data into fixed-size, non-overlapping windows of 10 seconds. This means that the data will be sent every 10 seconds to the marketing team segmented by the page they visited, which meets the requirement of sending data for the last 20 seconds.

Option B is incorrect because it uses a session window, which groups the data into windows based on the user's session, and does not meet the requirement of sending data for the last 20 seconds.

Option C is incorrect because it uses a hopping window, which groups the data into overlapping windows based on a hopping interval, and does not meet the requirement of sending data for the last 20 seconds.

Option D is incorrect because it uses a snapshot window, which takes a snapshot of the data at a specific point in time, and does not meet the requirement of sending data for the last 20 seconds.