I\'ve got multiple python processes (typically 1 per core) transforming large volumes of data that they are each reading from dedicated sources, and writing to a single output file that eac开发者_如何
I\'d like to begin thinking about how I can scale up my algorithms that I write for data analysis so that they can be applied to arbitrarily large sets of data. I wonder what are the relevant concepts
I have a web application that synchronizes with a central database four times per hour.T开发者_运维百科he process usually takes 2 minutes.I would like to run this process as a thread at X:55, X:10, X:
In an asp.net web application, say everytime the user makes the request, and the page loads, a thread is fired off that uses thread.join() to block exec开发者_运维百科ution until it\'s finished.
I currently have code that does the following: private final static ExecutorService pool = Executors.newCachedThreadPool();
I\'m using VS1010RC with the POCO self tracking T4 templates. In my WCF update service method I am using something similar to the following:
I need to create a simple Chat system like facebook chat an开发者_StackOverflowd a twitter-like app.
I have a NamedPipeClientStream instance in my application that is setup for duplex communication (PipeDirection.InOut).I also have two threads, a read thread and a write thread.
Our application needs a simple scheduling mechanism - we can schedule only one visit per room for the same time interval (but one visit can be using one or more rooms). Using SQL Server 2005, sample p
We know that DBMS harness many technique to ensure the data integrity and satisfying the ACID properties when there are many transactions running simultane开发者_C百科ously in a concurrency environmen
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