{- | Copyright: (c) 2018-2020 Kowainik SPDX-License-Identifier: MPL-2.0 Maintainer: Kowainik __NOTE:__ Many thanks to Alexander Vershilov for the implementation. For the speed reasons you may want to dump logs asynchronously. This is especially useful when application threads are CPU bound while logs emitting is I/O bound. This approach allows to mitigate bottlenecks from the I/O. When writing an application user should be aware of the tradeoffs that concurrent log system can provide, in this module we explain potential tradeoffs and describe if certain building blocks are affected or not. 1. Unbounded memory usage - if there is no backpressure mechanism the user threads, they may generate more logs that can be written in the same amount of time. In those cases messages will be accumulated in memory. That will lead to extended GC times and application may be killed by the operating systems mechanisms. 2. Persistence requirement - sometimes application may want to ensure that logs were written before it can continue. This is not a case with concurrent log systems in general, and some logs may be lost when application exits before dumping all logs. 3. Non-precise logging - sometimes it may happen that there can be logs reordering (in case if thread was moved to another capability). In case if your application is a subject of those problems you may consider not using concurrent logging system in other cases concurrent logger may be a good default for you. -} module Colog.Concurrent ( -- $general -- * Simple API. -- $simple-api withBackgroundLogger , defCapacity -- * Extended API -- $extended-api -- ** Background worker -- $background-worker , BackgroundWorker , backgroundWorkerWrite , killBackgroundLogger -- ** Background logger , forkBackgroundLogger , convertToLogAction -- ** Worker thread -- $worker-thread , mkBackgroundThread , runInBackgroundThread -- *** Usage example -- $worker-thread-usage ) where import Control.Applicative (many) import Control.Concurrent (forkFinally, killThread) import Control.Concurrent.STM (atomically, check, newTVarIO, readTVar, writeTVar) import Control.Concurrent.STM.TBQueue (newTBQueueIO, readTBQueue, writeTBQueue) import Control.Exception (bracket, finally) import Control.Monad (forever, join) import Control.Monad.IO.Class (MonadIO (..)) import Data.Foldable (for_) import Colog.Concurrent.Internal (BackgroundWorker (..), Capacity (..)) import Colog.Core.Action (LogAction (..)) {- $general Concurrent logger consists of the basic parts (see schema below). 1. Logger in application thread. This logger is evaluated in the application thread and has an access to all the context available in that thread and monad, this logger can work in any @m@. 2. Communication channel with backpressure support. In addition to the channel we have a converter that puts the user message to the communication channel. This converter works in the user thread. Such a logger usually works in 'IO' but it's possible to make it work in 'Control.Concurrent.STM.STM' as well. At this point library provides only 'IO' version, but it can be lifted to any 'MonadIO' by the user. 3. Logger thread. This is the thread that performs actual write to the sinks. Loggers there do not have access to the users thread state, unless that state was passed in the message. @ +-------------------------+ +--------------------------------+ | | | Logger | Sink-1 | | Application Thread | | Thread +---> | | ----------------- | +-----------+ | | +----------------+ | | | | +---------+ | +----------------+ | +-------------+ | channel | | Shared +-----> Sink-2 | | | application|| | +----> logger | | | | | | logger +-----> | +---------+ | +----------------+ | +-------------+ | | | | +----------------+ | | +-----------+ | +---> Sink3 | | | | | | | | | +----------------+ | | | | +-------------------------+ +--------------------------------+ @ So usually user should write the logging system in the way that all 'LogAction' that populate and filter information should live in the application logger. All loggers that do serialization and formatting should live in shared logger. If more concurrency is needed it's possible to build multilayer systems: @ +-------------+ +-------+ | application |---+ +---| sink-1| +-------------+ | +---------+ | +-------+ +---| logger |---+ +---------+ | +-------+ +---| sink-2| +-------+ @ In this approach application will be concurrently write logs to the logger, then logger will be concurrently writing to all sinks. -} {- $simple-api Simple API provides a handy easy to use API that can be used directly in application without dealing with internals. Based on users feedback internal implementation of the simple API may change, especially in early versions of the library. But the guarantee that we give is that no matter what implementation is it will be kept with reasonable defaults and will be applicable to a generic application. -} {- | An exception safe way to create background logger. This method will fork a thread that will run 'shared worker', see schema above. @Capacity@ - provides a backpressure mechanism and tells how many messages in flight are allowed. In most cases 'defCapacity' will work well. See 'forkBackgroundLogger' for more details. @LogAction@ - provides a logger action, this action does not have access to the application state or thread info, so you should only pass methods that serialize and dump data there. @ main :: IO () main = 'withBackgroundLogger' 'defCapacity' 'Colog.Actions.logByteStringStdout' (\log -> 'Colog.Monad.usingLoggerT' log $ __do__ 'Colog.Monad.logMsg' \@ByteString "Starting application..." 'Colog.Monad.logMsg' \@ByteString "Finishing application..." ) @ -} withBackgroundLogger :: MonadIO m => Capacity -- ^ Capacity of messages to handle; bounded channel size -> LogAction IO msg -- ^ Action that will be used in a forked thread -> (LogAction m msg -> IO a) -- ^ Continuation action -> IO a withBackgroundLogger cap logger action = bracket (forkBackgroundLogger cap logger) killBackgroundLogger (action . convertToLogAction) -- | Default capacity size, (4096) defCapacity :: Capacity defCapacity = Capacity 4096 {- $extended-api Extended API explains how asynchronous logging is working and provides basic building blocks for writing your own combinators. This is the part of the public API and will not change without prior notice. -} {- $background-worker The main abstraction for the concurrent worker is 'BackgroundWorker'. This is a wrapper of the thread, that has communication channel to talk to, and threadId. Background worker may provide a backpressure mechanism, but does not provide notification of completeness unless it's included in the message itself. -} {- | Stop background logger thread. The thread is blocked until background thread will finish processing all messages that were written in the channel. -} killBackgroundLogger :: BackgroundWorker msg -> IO () killBackgroundLogger bl = do killThread (backgroundWorkerThreadId bl) atomically $ readTVar (backgroundWorkerIsAlive bl) >>= check . not {- $background-logger Background logger is specialized version of the 'BackgroundWorker' process. Instead of running any job it will accept @msg@ type instead and process it with a single logger defined at creation time. -} {- | Creates background logger with given @Capacity@, takes a 'LogAction' that should describe how to write logs. @capacity@ - parameter tells how many in flight messages are allowed, if that value is reached then user's thread that emits logs will be blocked until any message will be written. Usually if value should be chosen reasonably high and if this value is reached it means that the application environment experience severe problems. __N.B.__ The 'LogAction' will be run in the background thread so that logger should not add any thread specific context to the message. __N.B.__ On exit, even in case of exception thread will dump all values that are in the queue. But it will stop doing that in case if another exception will happen. -} forkBackgroundLogger :: Capacity -> LogAction IO msg -> IO (BackgroundWorker msg) forkBackgroundLogger (Capacity cap) logAction = do queue <- newTBQueueIO cap isAlive <- newTVarIO True tid <- forkFinally (forever $ do msg <- atomically $ readTBQueue queue unLogAction logAction msg) (\_ -> (do msgs <- atomically $ many $ readTBQueue queue for_ msgs $ unLogAction logAction) `finally` atomically (writeTVar isAlive False)) pure $ BackgroundWorker tid (writeTBQueue queue) isAlive {- | Convert a given 'BackgroundWorker msg' into a 'LogAction msg' that will send log message to the background thread, without blocking the thread. If logger dies for any reason then thread that emits logs will receive 'BlockedIndefinitelyOnSTM' exception. You can extend result worker with all functionality available with co-log. This logger will have an access to the thread state. -} convertToLogAction :: MonadIO m => BackgroundWorker msg -> LogAction m msg convertToLogAction logger = LogAction $ \msg -> liftIO $ atomically $ backgroundWorkerWrite logger msg {- $worker-thread While generic background logger is enough for the most of the usecases, sometimes you may want even more. There are at least two cases where that may happen: 1. You need to modify logger, for example different threads wants to write to different sources. Or you want to change lgo mechanism in runtime. 2. You may want to implement some notification machinery that allows you to guarantee that your logs were written before processing further. In order to solve those problems worker thread abstraction was introduced. This is a worker that accepts any action and performs that. -} {- | Create a background worker with a given capacity. If capacity is reached, then the thread that tries to write logs will be blocked. This method is more generic than 'forkBackgroundLogger' but it's less effective, as you have to pass entire closure to be run and that leads to extra memory usage and indirect calls happening. When closed it will dump all pending messages, unless another asynchronous exception will arrive, or synchronous exception will happen during the logging. -} mkBackgroundThread :: Capacity -> IO (BackgroundWorker (IO ())) mkBackgroundThread (Capacity cap) = do queue <- newTBQueueIO cap isAlive <- newTVarIO True tid <- forkFinally (forever $ join $ atomically $ readTBQueue queue) (\_ -> (sequence_ =<< atomically (many $ readTBQueue queue)) `finally` atomically (writeTVar isAlive False)) pure $ BackgroundWorker tid (writeTBQueue queue) isAlive {- | Run logger action asynchronously in the worker thread. Logger is executed in the other thread entirely, so if logger takes any thread related context it will be read from the other thread. -} runInBackgroundThread :: BackgroundWorker (IO ()) -> LogAction IO msg -> LogAction IO msg runInBackgroundThread bt logAction = LogAction $ \msg -> atomically $ backgroundWorkerWrite bt $ unLogAction logAction msg {- $worker-thread-usage Consider following example. (Leaving resource control aside). @ data M msg = M (MVar ()) msg notificationLogger :: MonadIO m => LoggerAction m msg -> LoggerAction m (M msg) notificationLogger logger = 'LogAction' $ \(M lock msg) -> (unLogger logger msg) `finally` (putMVar lock ()) example = __do__ worker <- 'mkBackgroundThread' 'defCapacity' lock <- newEmptyMVar -- Log message with default logger. 'unLogger' ('runInBackgroundThread' worker (notificationLogger $ 'Colog.Action.withLogByteStringFile' "\/var\/log\/myapp\/log") (M lock "my message") -- Log message with a different logger. 'unLogger' ('runInBackgroundThread' worker ('Colog.Action.withLogByteStringFile' "/var/log/myapp/log") ("another message") -- Block until first message is logged. _ <- takeMVar lock @ -}