Hi - just investigating pytables from storing data from many distributed remote logging stations, each logging about 100 channels at 1 second frequency (a fair bit).
My questions; 1. How does one handle ordering timeseries data within a table? *Does* one actually order on the way in (eg re-shuffling data) or simply ignore it? Coming from a NetCDF background, the answer would be the former because at some point you'd want to efficiently serially read and plot it, but I've little experience with HDF and if this needs to be considered at all. 2. Has anyone contended with managing schema differences between sources? In other words, if I have say 500 loggers, each logging slightly different schemas (ie 100 different columns and so different table definitions), the suggested Pytables way of binding static data definitions for each logger could be unmaintainable. From memory I can dynamically bind class attributes in Python - is this ok? nick ------------------------------------------------------------------------- This SF.net email is sponsored by the 2008 JavaOne(SM) Conference Don't miss this year's exciting event. There's still time to save $100. Use priority code J8TL2D2. http://ad.doubleclick.net/clk;198757673;13503038;p?http://java.sun.com/javaone _______________________________________________ Pytables-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/pytables-users
