At MOVUS we plot a lot of data, the main focus of our dashboard for most of our users are the real-time graphs that plot industrial equipment conditions over time. These graphs usually show about 8 properties over about 1000 timepoints, but it's easy to go back into historical data and load over 100,000+ graph points on a page. How do you handle such requests?
When you need to fetch 50+ pages of data
When you don't know where the next page is until you have the current page
When each page is ~500KB
When the order of the data is not guaranteed
When you want to cache the data for each page so a user can quickly see their 100+ graphs at any time (let's not put 2GB+ inside localStorage)
When 1 new data point comes in and now all your cached paging tokens are off-by-one
When the viewer is on a mobile
Find out how we handle all of these concerns at the same time while providing a good user experience.
Details
Title of the Talk
Loading large paged datasets into visualisations performantly
Description of the Talk
Large data visualisations are a great way to convey a lot of info concisely. But how do you get all that data in there? How can you keep your UI interactable while loading in pages of data? And how do you cache GBs of real-time, unordered data on a mobile?
This is my first time to propose or give a presentation anywhere, I'm not sure if this this is too much or too specific.
I think there's two main parts to this:
fetching, sorting, and storing the data performantly
displaying and interacting with the data performantly
I'd like to know what parts people might find interesting.
I like to discuss real-world data and code concerns, this is all production code and I can talk through the trade-offs made at each point of these solutions.
Summary of talk
At MOVUS we plot a lot of data, the main focus of our dashboard for most of our users are the real-time graphs that plot industrial equipment conditions over time. These graphs usually show about 8 properties over about 1000 timepoints, but it's easy to go back into historical data and load over 100,000+ graph points on a page. How do you handle such requests?
Find out how we handle all of these concerns at the same time while providing a good user experience.
Details
Title of the Talk
Loading large paged datasets into visualisations performantly
Description of the Talk
Large data visualisations are a great way to convey a lot of info concisely. But how do you get all that data in there? How can you keep your UI interactable while loading in pages of data? And how do you cache GBs of real-time, unordered data on a mobile?
My Info
I don't really do much on socials https://twitter.com/dib542 https://www.linkedin.com/in/david-uhlmann/
Notes
This is my first time to propose or give a presentation anywhere, I'm not sure if this this is too much or too specific.
I think there's two main parts to this:
I like to discuss real-world data and code concerns, this is all production code and I can talk through the trade-offs made at each point of these solutions.