streamly-0.8.2: Dataflow programming and declarative concurrency
Copyright(c) 2017 Composewell Technologies
LicenseBSD-3-Clause
Maintainerstreamly@composewell.com
Stabilityexperimental
PortabilityGHC
Safe HaskellNone
LanguageHaskell2010

Streamly.Internal.Data.SVar.Dispatch

Description

 
Synopsis

Latency collection

Diagnostics

withDiagMVar :: SVar t m a -> String -> IO () -> IO () Source #

printSVar :: SVar t m a -> String -> IO () Source #

Thread accounting

delThread :: MonadIO m => SVar t m a -> ThreadId -> m () Source #

modifyThread :: MonadIO m => SVar t m a -> ThreadId -> m () Source #

allThreadsDone :: MonadIO m => SVar t m a -> m Bool Source #

This is safe even if we are adding more threads concurrently because if a child thread is adding another thread then anyway workerThreads will not be empty.

Dispatching

recordMaxWorkers :: MonadIO m => SVar t m a -> m () Source #

pushWorker :: MonadAsync m => Count -> SVar t m a -> m () Source #

pushWorkerPar :: MonadAsync m => SVar t m a -> (Maybe WorkerInfo -> m ()) -> m () Source #

In contrast to pushWorker which always happens only from the consumer thread, a pushWorkerPar can happen concurrently from multiple threads on the producer side. So we need to use a thread safe modification of workerThreads. Alternatively, we can use a CreateThread event to avoid using a CAS based modification.

sendWorkerWait :: MonadAsync m => (SVar t m a -> IO ()) -> (SVar t m a -> m Bool) -> SVar t m a -> m () Source #

sendFirstWorker :: MonadAsync m => SVar t m a -> t m a -> m (SVar t m a) Source #

sendWorkerDelay :: SVar t m a -> IO () Source #