August 2008 - Posts
The OpenUp competition is ending in three weeks so time is running out on project submissions!
Up until now we received submissions for many cool and popular projects starting from games to frameworks and controls, all the way to environmental friendly projects.
The following projects have already won a Mobile Memory Mouse 8000:
The winner for July was:
Daniel Cohen – DNA Studio
Defrost Outlook
http://www.codeplex.com/defrostoutlook
The winners for June were:
Gil Shinnar and Simon Grinberg
WPF poker
http://www.codeplex.com/wpfPoker
The winner for May was:
Tamir Khason
Duplicate images finder
http://www.codeplex.com/DupliFinder
There is another mouse prize for this month, and the grand prize of a trip to PDC still waiting for you.
So post your project and you can also win a mouse and a trip to PDC!
Amit Talmor has release a cool new open source project to OpenUp called Live Hits Finder.
About Live Hits Finder- Many times when we are searching for some item in Google/Live/Yahoo/...
The top results do not satisfy us.
Sometimes the best results are hidden in the next search results pages.
By finding the BUZZ words related to the searched item we can:
- Modify our search.
- Get a better understanding on the searched item.
The project searches for BUZZ in Google's top 100 results and in Wikipedia relevant page (If any).
The results are ordered in a simple list.
After watching the results you can search again using the search item plus one of the found BUZZ words.
Thanks Amit!
Guy Eden has released a new project to OpenUp:
This solution deals with transferring huge DataTables over WCF and .NET Remoting.
When transporting large DataTables between a Server and a remote Client, there are several issues; that stem from .NET serialization. Serialization of a large DataTable is 
memory thirsty. A large enough DataTable will cause the client to get System.OutOfMemoryException, or System.InsufficientMemoryException. Those exceptions cannot be caught at the server side, as they occur in the innards of the framework code that deals with serialization and transport. If the DataTable is really large, the framework will throw the server process all together, with brute force. There is no way around that.
Another issue is throughput, which is not outstanding, and becomes noticeable when the table gets large. The solution at hand circumvents this problem by partitioning the DataTable to chunks and transferring the chunks in a multi-threaded fashion.
Thanks Guy!