Improve Performance and Memory Consumption (KULRICE-6557)

[KULRICE-7005] Implement server paging of collection results Created: 26/Mar/12  Updated: 12/Aug/13  Resolved: 08/Aug/13

Status: Closed
Project: Kuali Rice Development
Component/s: Development
Affects Version/s: None
Fix Version/s: 2.3
Security Level: Public (Public: Anyone can view)

Type: Sub Task Priority: Major
Reporter: Jerry Neal (Inactive) Assignee: Peter Giles (Inactive)
Resolution: Fixed Votes: 0
Labels: None
Remaining Estimate: Not Specified
Time Spent: Not Specified
Original Estimate: Not Specified

Issue Links:
cloned from KULRICE-7004 Provide option of rendering component... Open
cloned to KULRICE-10112 docs and smoke test for server paging... Open
cloned to KULRICE-7006 Provide configuration on Collection G... Closed
Rice Module:
KAI Review Status: Not Required
KTI Review Status: Not Required


Currently the paging for large collections is done all client side, so all the data is sent and rendered initially. Performance could be improved by fetching and render each page as requested. This will involve hooking into the paging functionality of DataTables.

Comment by Jerry Neal (Inactive) [ 27/Mar/12 ]


Please starting looking into this one before the form memory Jira. I think this one is more practical. Do analysis at this point in how we might be able to accomplish this.


Comment by Heath Kesler (Inactive) [ 14/Jun/13 ]

The paging here is based on the collection of components in a page. The components for all pages are being loaded when the view is requested. Pagination is available out of the box from FreeMarker for grids but not for component collections. This will have to be done programmatically in Kuali or extend FreeMarker.

But this would provide a very large performance boost. The Lab Performance view has been tested with this theory and it looks like true server side paging would then make every page load at the same rate regardless of the number of components needed. It would also cut down on the number of objects being stored in memory, which will cut down on memory consumption.

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