Comments (4)
If your function returns a different style for every feature used, you have no way to improve the performance - whether you use rlayers or you use directly OpenLayers. In this case you have 2 choices: either reduce the number of features or use clustering.
If some features share the same styles - you can use the cache parameters - in this case rlayers wil call only your hashing function to check if a new style has to be computed and constructed.
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You got it - the function returns 3 different styles depending on the feature type. One of those types makes for 99% of the features rendered... what cache parameters are you making mention of, Do you mean I should build a cache layer depending on the 'feature' and 'resolution' parameters sent to the function, or is there a mechanism offered by rlayers/openlayers?
Unfortunately clustering does not seem to be an option for our use case (but I'll look into it more).
Thanks for such a fast response btw π
edit: I just noticed cacheSize
and cacheId
on the clustering example... I'll see what I can do with it.
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@vgrafe if one feature type represents 99% of the features, your best option, performance-wise, would be to move these features to a separate vector layer with a single fixed style
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Makes sense. Thank you for the help!
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