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 click stream 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 aggregates data using distinct time-based windows that open and close at regular intervals.
select 1 option.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: B.
Option A is incorrect - 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 correct - 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 type of windowed query needed to aggregate data using distinct time-based windows that open and close at regular intervals is B. Tumbling Windows queries.
Tumbling windows, also known as discrete windows, divide the data stream into non-overlapping fixed-sized windows. Each window covers a specific time duration, and the data within each window is processed as a batch. The windows are defined by their start time and end time, and they do not overlap.
Tumbling windows are suitable for use cases where there is a need to aggregate data at regular time intervals, and where data in each window is independent of the data in other windows. In HH's case, using tumbling windows would enable them to process the data stream in fixed-sized batches and aggregate it using SQL queries. This approach is particularly useful for real-time analytics and reporting.
Stagger windows are not a type of windowed query. Continuous queries are used for stream processing where the output is continuously updated as new data arrives. Sliding windows, also known as rolling windows, move across the data stream in fixed-sized steps and overlap with each other. Sliding windows are suitable for use cases where there is a need to analyze data across time intervals and identify trends and patterns.