HikeHills.com (HH) is an online specialty retailer that sells clothing and outdoor refreshment gear for trekking, go camping, boulevard biking, mountain biking, rock hiking, ice mountaineering, skiing, avalanche protection, snowboarding, fly fishing, kayaking, rafting, road and trace running, and many more. HHruns their entire online infrastructure on java based web applications running on AWS.
The HH is capturing clickstream data and use custom-build recommendation engine to recommend products which eventually improve sales, understand customer preferences and already using AWS Streaming capabilities to collect events and transaction logs and process the stream. HHis using kinesis analytics to build SQL querying capability on streaming and planning to use windowed Queries to process the data.
What kind of windows queries need to be used to aggregate data using keyed time-based windows that open as data arrives.
select 1 option.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: A.
Option A is correct -Stagger windows query, A query that aggregates data using keyed time-basedwindows that open as data arrives.
The keys allow for multiple overlapping windows.
This is the recommended way to aggregate data using time-based windows
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/stagger-window-Option B is incorrect - Tumbling Windows query, A query that aggregates data using distinct time-based windows that open and close at regular intervals.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/tumbling-window-Option C is incorrect - Sliding windows query, A query that aggregates data continuously, using a fixed time or rowcount interval.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/sliding-window-concepts.htmlOption D is incorrect - Continuous Query is a query over a stream executes continuously over streaming data.
This continuous execution enables scenarios, such as the ability for applications to continuously query a stream and generate alerts.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/continuous-queries-The kind of windowed queries that should be used to aggregate data using keyed time-based windows that open as data arrives is Sliding Windows queries.
Windowed queries are commonly used in stream processing to break down the stream into small sections (windows) for aggregation and analysis. Keyed time-based windows refer to the partitioning of data into separate groups or keys based on some criteria, such as a user ID, and then aggregating the data for each key over a specific time window.
Tumbling window queries divide the data into non-overlapping fixed-sized windows of a specific duration. Stagger windows queries divide the data into overlapping fixed-sized windows of a specific duration, with a specified offset. Continuous queries provide real-time updates and do not use windows.
In contrast, sliding windows queries divide the data into windows of a specific size and slide the window over the data stream by a fixed amount to provide overlapping windows. This allows for more continuous analysis of the stream as the data arrives, enabling near-real-time insights and rapid response to changing conditions.
Therefore, Sliding Windows queries should be used for aggregating data using keyed time-based windows that open as data arrives.