concurrency

问题 In Go, can we synchronize each key of a map using a lock per key? Is map level global lock always required? The documentation says that any access to map is not thread safe. But if a key exists, then can it be locked individually? 回答1: Not exactly, but if you are only reading pointers off a map and modifying the referents, then you aren't modifying the map itself. 回答2: This is a simple implementation of what you want: mapmutex. Basically, a mutex is used to guard the map and each item in the

问题 I have a spring component that calls AWS to do some stuff. It acquires temporary session credentials lasting for <=1h to initialize the AWS service client at the start of my app. The AWS service client is set as an instance property of the bean. Then after this hour, I need to block all threads using this bean and refresh the temporary session credentials used by the service client. Is there any recommended way to do this? Any hints/clues are appreciated 回答1: I think that it would be best

问题 I have an NSManagedObjectContext in the main queue (the default context provided in AppDelegate ), and I create another NSManagedObjectContext in a private queue to request data updates to web services. I use the main context to fetch all the objects to be shown and managed throughout the app, and I use the private context to insert the new objects I receive from services to avoid blocking the UI and to also avoid "interfering" with the objects in the main context in case the user and/or the

问题 Consider http://en.cppreference.com/w/cpp/experimental/when_any. The following is just a naive and simplified implementation: #include <future> template<typename Iterator> auto when_any(Iterator first, Iterator last) { while (true) { for (auto pos = first; pos != last; ++pos) { if (pos->is_ready()) { return std::move(*pos); } } } } I am not satisfied because it is a busy polling in an infinite loop. Is there a way to avoid busy polling? 回答1: A polling free version would launch 1 thread per

问题 1: I was trying this and it was working fine: start transaction; select * from orders where id = 21548 LOCK IN SHARE MODE; update orders set amount = 1500 where id = 21548; commit; According to the definition of LOCK IN SHARE MODE , it locks the table with IS lock and lock the selected rows with S lock. When a row is locked with S lock.How can it be modified without releasing lock? It needs X lock to modify it.Right? Or is it valid only for different connection transaction? 2: //session1

问题 It seems like there is a bug in the windows implementation of std::async. Under heavy load (on the order of 1000 threads launched async per second), async tasks are never scheduled and waiting on the returned futures leads to deadlocks. See this piece of code (modified with launch policy deferred instead of async): BundlingChunk(size_t numberOfInputs, Bundler* parent, ChunkIdType chunkId) : m_numberOfInputs(numberOfInputs), m_parent(parent), m_chunkId(chunkId) { const BundlerChunkDescription&

问题 It seems like there is a bug in the windows implementation of std::async. Under heavy load (on the order of 1000 threads launched async per second), async tasks are never scheduled and waiting on the returned futures leads to deadlocks. See this piece of code (modified with launch policy deferred instead of async): BundlingChunk(size_t numberOfInputs, Bundler* parent, ChunkIdType chunkId) : m_numberOfInputs(numberOfInputs), m_parent(parent), m_chunkId(chunkId) { const BundlerChunkDescription&

问题 I'm wondering how the concurrency in a web application actually works. Ive read several articles and to my understanding multiple instances of HttpApplication would be working at the same time. Now, I created a simple web app to test concurrency and put the following to global.asax: protected void Application_BeginRequest(object sender, EventArgs e) { Response.Write("Request started: " + DateTime.Now); System.Threading.Thread.Sleep(10000); Response.Write("<br />"); Response.Write("Request

问题 Consider the following code: import scala.concurrent.Future import scala.concurrent.ExecutionContext.Implicits.global import scala.concurrent.Await import scala.concurrent.duration._ object FutureFor { def getA(n: Int) = { val x: Future[String] = Future { println("I'm getA") for (i <- 1 to 5) { println(".") Thread.sleep(200) } s"A$n" } x } def getB(n: Int) = { val x: Future[String] = Future { println("I'm getB") for (i <- 1 to 5) { println(".") Thread.sleep(200) } s"B$n" } x } def main(args:

问题 Suppose in a C program I have P threads running on a 32 bit machine, and int MAX --a shared 32-bit integer Each thread can read/write to MAX. Requirement: the value a thread read should not be corrupted, e.g first 16bit and last 16bit are out of sync Question: Do I need a lock to protect the read and write? or Can I safely ignore the lock, because LOAD/SAVE assembly instruction is guaranteed to happen atomically? 回答1: Reads and writes are atomic when the int is aligned properly. It cannot