![]() ![]() We used such a distinction since most part of the time we won’t seed entirely the cache for a layer upfront but we will simply cache the landing areas and zoom levels and we will leave the cache grow lazily at runtime (this is a cost factor which is often forgotten).Īnyway, if you need help in estimating how much space a cache would need we have set up a spreadsheet which you can use to perform space oocupation estimates, you can find it here One cost factor to take into consideration when designing a tile cache is the space we need for caching the data we want to cache, or at least the maximum amount of space that the cache we are setting up might take. If chances that two different requests would hit the cache are low then you should not be caching.Īs mentioned above, caching comes with a cost, actually more than one. Layers with complex filtering, many styling, multiple dimensions might become a nightmare for the cache since a cache is as useful once if it gets reused a lot between different requests. Data doesn’t change frequently and/or where we can introduce a slight delay between the changes in the data and the changes in the cached content (e.g.Generally speaking, tile caching should be part of the plan for layers where: layers with no/few dynamic parameters (CQL filters, SLD params, SQL query params, time/elevation, format options) Tile caching is always useful for simple layers, i.e.layers that are not update often (once a week? once a month? once in a lifetime?) Tile caching is always useful for static layers, i.e.Tile caching is first class option for background layers. ![]() Protocols supported are peculiar: WMTS, TMS, WMS-C, Google Maps/Earth, Virtual EarthĪs usual the speed up you get is payed by the restrictions on the degrees of freedom that the protocols you expose offer the target clients.Īs a rule of thumb tile caching, these hints are worth to keep in mind:. ![]()
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