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c# - Usage of Server Side Controls in MVC Frame work -

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i using asp.net 4.0 , mvc 2.0 web application. project requiremrnt have use server side control in application not possibl in noraml case. ideally want use adrotator control , datalist control. i saw few samples , references in codepleax mvc controllib howwver found less useful. can tell how utilize theese controls in asp.net application along mvc. note: please provide functionalities related adrotator , datalist controls not equivalent functionalities thanks in advace. mvc pages not use normal .net solution makes use of normal .net components impossible. a normal .net page use event driven solution call different methods service side mvc use actions , view completly different way handle things. also, mvc not use viewstate normal .net controlls require. found article discussing mixing of normal .net , mvc.
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What is the maximum recommended number of rows that a SQL 2008 R2 standalone server should store in a single table? -

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i'm designing db functionality , performance realtime ajax web applications, , don't have resources add db server redundancy or load-balancing.

unfortunately, have table in db potentially end storing hundreds of millions of rows, , need read , write prevent lagging web-interface.

most, if not all, of columns in table individually indexed, , i'd love know if there other ways ease burden on server when running querys on large tables. there cap size (in rows or gb) of table before single unclustered sql server starts choke?

my db has dozen tables, maybe couple dozen foriegn key relationships. none of tables have more 8 or columns, , 1 or 2 of these tables end storing large number of rows. simplicity of db make massive amounts of data in these couple tables ...

rows limited strictly amount of disk space have available. have sql servers hundreds of millions of rows of data in them. of course, servers rather large.

in order keep web interface snappy need think how access data.

one example stay away type of aggregate queries require processing large swaths of data. things sum() can killer depending on how data it's trying process. in these situations better off calculating summary or grouped data ahead of time , letting site query these analytic tables.

next you'll need partition data. split partitions across different drive arrays. when sql needs go disk makes easier parallelize reads. (@simon touched on this).

basically, problem boils down how data need access @ 1 time. main problem regardless of amount of data have on disk. small databases can choked if drives slow , amount of available ram in db server isn't enough keep enough of db in memory.

usually systems large amounts of data inert, meaning it's accessed. example, po system might maintain history of invoices ever created, deal active ones.

if system has similar requirements, might have table active records , archive them table part of nightly process. have statistics monthly averages (as example) recomputed part of archival.

just thoughts.


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