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    copied!<p>Tasks are not 1:1 with threads - tasks are assigned threads for execution out of a pool of threads, and the pool of threads is normally kept fairly small (number of threads == number of CPU cores) unless a task/thread is blocked waiting for a long-running synchronous result - such as perhaps a synchronous network call or file I/O.</p> <p>So spinning up 10,000 tasks should not result in the production of 10,000 actual threads. However, if every one of those tasks immediately dives into a blocking call, then you may wind up with more threads, but it still shouldn't be 10,000.</p> <p>What may be happening here is you are overwhelming the SQL db with too many requests all at once. Even if the system only sets up a handful of threads for your thousands of tasks, a handful of threads can still cause a pileup if the destination of the call is single-threaded. If every task makes a call into the SQL db, and the SQL db interface or the db itself coordinates multithreaded requests through a single thread lock, then all the concurrent calls will pile up waiting for the thread lock to get into the SQL db for execution. There is no guarantee of which threads will be released to call into the SQL db next, so you could easily end up with one "unlucky" thread that starts waiting for access to the SQL db early but doesn't get into the SQL db call before the blocking wait times out. </p> <p>It's also possible that the SQL back-end is multithreaded, but limits the number of concurrent operations due to licensing level. That is, a SQL demo engine only allows 2 concurrent requests but the fully licensed engine supports dozens of concurrent requests.</p> <p>Either way, you need to do something to reduce your concurrency to more reasonable levels. Jon Skeet's suggestion of using a TaskScheduler to limit the concurrency sounds like a good place to start.</p>
 

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