On Tue, Mar 11, 2008 at 12:11 PM, Brendan Meutzner <[EMAIL PROTECTED]> wrote: >
> The best workaround I've found is creating different aggregations of the > data being shown. A fair bit of functionality is involved in defining and > switching up the datasets, and would really only make sense for date based > datapoints. Concept would involve creating less granular datapoints > (weekly, vs daily) and show the weekly data when larger ranges are being > displayed. Shorten the range, and switch up to show daily data, and so > on... check out Google Finance for good examples on this. This is the approach we've taken on a set of graphs that can display everything from a few hours worth of data at 30 second intervals to a few years with a granularity of a week. Many of the documented recommendations for speeding up charts (e.g. removing the drop shadow) were very helpful as well. At this point, a lot of our lag seems to come from the process of incrementally fetching data as the user pans/zooms the chart. I'm curious if anybody has profiled returning chart data as XML vs JSON vs the binary formats and whether one of those approaches has a benefit in terms of rendering speed (or just transfer speed on the wire). Chris Hunter
