-
Notifications
You must be signed in to change notification settings - Fork 192
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[#1296] Swinging Door Trending (SDT) Filter Processor #1306
Conversation
…vocation and onDetach
…ingFilterProcessor
PTAL, thanks! 🙏 @dominikriemer @tenthe @bossenti |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
thank you so much for this high-class contribution @SteveYurongSu 🤩
I'm really amazed how easily you get into StreamPipes and provide valuable contributions.
I skimmed through the PR and it really looks great.
In the upcoming days, I will take some time to understand the implementation in more detail.
Until then I only have one question: Where did to get the icon from? Did you create it by your own?
...-filters-jvm/src/main/resources/org.apache.streampipes.processors.filters.jvm.sdt/strings.en
Outdated
Show resolved
Hide resolved
PS: You can ignore the failed pr labeling run this simply does not work for fork-based PRs (in case you didn't already realized) 🙂 |
@bossenti Thanks for your reply! 😀 A friend of mine drew the swinging door for me on an iPad. I think it only took her about 5 minutes, but the picture looks really good to me haha :) |
@bossenti Thanks for your warm reminder! Maybe I can also take a look at it and help fix the failure on forks. |
Ah that's great! |
That would be great 🙂 |
.../org/apache/streampipes/processors/filters/jvm/processor/sdt/SwingingDoorTrendingFilter.java
Show resolved
Hide resolved
@SteveYurongSu The PR looks really good |
…ngingDoorTrendingFilter#forward
@bossenti Thanks for your careful review, which is great! |
Thank you @SteveYurongSu for this awesome contribution! |
Purpose
The Swinging Door Trending (SDT) algorithm is a linear trend compression algorithm. In essence, it replaces a series of continuous (timestamp, value) points with a straight line determined by the start and end points.
The Swinging Door Trending (SDT) Filter Processor can extract and forward the characteristic events of the original stream. In general, this filter can also be used to reduce the frequency of original data in a lossy way.
This PR is related to:
Remarks
PR introduces (a) breaking change(s): <yes/no>
no
PR introduces (a) deprecation(s): <yes/no>
no
Tests
I setup a workflow like the following:
Then I checked the consumed count / produced count of the SDT filter:


The SDT filter worked as expected.