We keep getting questions on r-help about memory limits and I was curious to know what issues are involved in making common classes like dataframe work with disk and intelligent swapping? That is, sure you can always rely on OS for VM but in theory it should be possible to make a data structure that somehow knows what pieces you will access next and can keep thos somewhere fast. Now of course algorithms "should" act locally and be block oriented but in any case could communicate with data structures on upcoming access patterns, see a few ms into the future and have the right stuff prefetched. I think things like "bigmemory" exist but perhaps one issue was that this could not just drop in for data.frame or does it already solve all the problems? Is memory management just a non-issue or is there something that needs to be done to make large data structures work well? Thanks. -------------------
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