Andrus Adamchik commented on CAY-999:
-------------------------------------
yeah, #2 can get hairy pretty quickly. Although it may be important if a user needs to iterate through the huge lists of objects... Currently the only memory-sensitive way to do it is via ResultIterator. This may be a more user-friendly alternative. Whatever we do, we must ensure that this is an *optional* and not the default behavior.
> Scaling paginated list
> ----------------------
>
> Key: CAY-999
> URL: https://issues.apache.org/cayenne/browse/CAY-999
> Project: Cayenne
> Issue Type: Improvement
> Components: Cayenne Core Library
> Affects Versions: 3.0
> Reporter: Andrus Adamchik
> Assignee: Andrus Adamchik
>
> An idea for scaling IncrementalFaultList to store massive amount of objects, like hundreds of thousands.This pertains to the server-side IncrementalFaultList. The problems to solve are the speed of the initial list initialization and overall memory use.
> 1. Simplify ID representation:
> Even unresolved lists can take significant amount of memory... Each unresolved object slot currently stores a DataRow with N number of entries, where N is the number of PK columns for the entity. I.e. most often than not - 1 entry. Here is a memory use calculation for various representations of an unresolved entry, based on a single int PK DbEntity.
> a. DataRow - 120 bytes,
> b. HashMap - 104 bytes,
> c. Object[] - 32 bytes,
> d java.lang.Integer - 16 bytes
> [primitive int is even better, but it complicates the implementation, as we'd need a parallel int[] (long[], double[], etc.) , so all in all we may get no gain]
> 2. Swap out LRU pages
> For the very large lists, it would make sense to un-fault resolved pages when more pages are resolved , so that the list size doesn't grow beyond a certain fixed amount, no matter how many pages are resolved. These parameters will have to be configurable per query, as some users would prefer to keep the entire thing...
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