Concurrent stack implementation using MVar - haskell

I am trying to implement a stack for use in a concurrent application. I would like the following semantics: push should never block, and pop should block the calling thread on an empty stack, but still permit pushes. I implemented it as follows (irrelevant bits at the bottom):
data Stream a = Stream a (MVar (Stream a))
data Stack a = Stack (MVar (Int, MVar (Stream a)))
popStack :: Stack a -> IO a
popStack (Stack stack) = do
(sz, mvar) <- takeMVar stack
mbStream <- tryTakeMVar mvar
case mbStream of
Nothing -> putMVar stack (sz, mvar) >> popStack (Stack stack)
Just (Stream x xs) -> putMVar stack (sz-1, xs) >> return x
If the stream MVar is empty I have to release the lock on the stack and try again. However, this seems like a kludge: if a thread calls pop on an empty stack, it could loop several times before being suspended, even though the MVar will not become full while that thread is being executed. Is there a better way utilizing MVars to write pop with the desired semantics?
import Control.Concurrent.MVar
import Control.Monad
import Control.Concurrent
import Text.Printf
newStack :: IO (Stack a)
newStack = do
stream <- newEmptyMVar
Stack <$> newMVar (0, stream)
pushStack :: Stack a -> a -> IO ()
pushStack (Stack stack) val = do
(sz, stream) <- takeMVar stack
stream' <- newMVar (Stream val stream)
putMVar stack (sz+1, stream')
test = do
s <- newStack
_ <- forkIO $ mapM_ (\a -> printf "pushing %c... " a >> pushStack s a >> threadDelay 100000) ['a' .. 'z']
_ <- forkIO $ do
replicateM 13 (popStack s) >>= printf "\npopped 13 elems: %s\n"
replicateM 13 (popStack s) >>= printf "\npopped 13 elems: %s\n"
threadDelay (5*10^6)
putStrLn "Done"

It's not very exciting, but the simplest solution would be to use STM (if you're using cabal you'll need the stm package in your dependencies list).
import Control.Concurrent.STM
newtype Stack a = Stack (TVar [a])
new :: STM (Stack a)
new = fmap Stack $ newTVar []
put :: a -> Stack a -> STM ()
put a (Stack v) = modifyTVar' v (a:)
get :: Stack a -> STM a
get (Stack v) = do
stack <- readTVar v
case stack of
[] -> retry
(a:as) -> do writeTVar v as
return a
You get the blocking behavior you want with retry, which is implemented in such a way that threads won't be awoken until the TVar changes to something other than []. This is also nice because you can now use your stack in larger composed atomic transactions, and you don't have to worry about making sure exceptions don't break your structure.
If you're trying to do high-performance concurrency with lots of threads contending for reads and/or writes, you might find that this isn't clever enough. In that case you might have fun designing a structure based around the fetch-and-add-based counter from atomic-primops, or seeing what else is available on hackage.

A quick critique:
"push should never block" is not something you are going to actually achieve. Though you may have a perdonal definition of "block" that is different than the GHC meaning. For instance, your pushStack does block.
popStack on an empty stack goes into a very busy loop, repeatedly taking and putting the Stack MVar. You do not want to do this, you even say "pop should block".
You use takeMVar and putMVar instead of withMVar or modifyMVar. This means you are not thinking about exceptions, and the Stack will not be good in a general library.
So you have learned about MVars, and you are using them with them to learn more.
Here StackData is either a stack with data (Full) or without data (Empty). When Empty, there is an initally empty MVar for hungry poppers to wait upon.
type Lock = MVar ()
type Some a = (a, [a]) -- non empty version of list
data StackData a = Full !(Some a)
| Empty !Lock
data Stack a = Stack { stack :: MVar (StackData a) }
pop s = do
x <- modifyMVar (stack s) $ \ sd ->
case sd of
Empty lock -> do
return (Empty lock, Left lock)
Full (a, []) -> do
lock <- newEmptyMVar
return (Empty lock, Right a)
Full (a, (b:bs)) -> return (Full (b, bs), Right a)
case x of
Left lock -> do
withMVar lock return -- wait on next pusher
pop s
Right a -> return a
push s a = modifyMVar_ (stack s) $ \ sd ->
case sd of
Empty lock -> do
tryPutMVar lock () -- should succeed, releases waiting poppers
evaluate Full (a,[]) -- do not accumulate lazy thunks
Full (b, bs) -> do
xs <- evaluate (b:bs) -- do not accumulate lazy thunks
evaluate (Full (a, xs)) -- do not accumulate lazy thunks
Note : I have not tried to compile this.
EDIT: A safer version of push needs to only put () into the lock when it has succeeded in modifying the stack from Empty to Full. This certainty can be achieved with the 'mask' operation. The 'restore' is used inside 'modifyMVar' but is not required:
push s a = mask $ \restore -> do
mLock <- modifyMVar (stack s) $ \ sd -> restore $
case sd of
Empty lock -> do
n <- evaluate Full (a,[]) -- do not accumulate lazy thunks
return (n, Just lock)
Full (b, bs) -> do
xs <- evaluate (b:bs) -- do not accumulate lazy thunks
n <- evaluate (Full (a, xs))
return (n, Nothing)
whenJust mLock $ \ lock -> tryPutMVar lock ()

Related

Convert IO callback to infinite list

I am using a library that I can provide with a function a -> IO (), which it will call occasionally.
Because the output of my function depends not only on the a it receives as input, but also on the previous a's, it would be much easier for me to write a function [a] -> IO (), where [a] is infinite.
Can I write a function:
magical :: ([a] -> IO ()) -> (a -> IO ())
That collects the a's it receives from the callback and passes them to my function as a lazy infinite list?
The IORef solution is indeed the simplest one. If you'd like to explore a pure (but more complex) variant, have a look at conduit. There are other implementations of the same concept, see Iteratee I/O, but I found myself conduit to be very easy to use.
A conduit (AKA pipe) is an abstraction of of program that can accept input and/or produce output. As such, it can keep internal state, if needed. In your case, magical would be a sink, that is, a conduit that accepts input of some type, but produces no output. By wiring it into a source, a program that produces output, you complete the pipeline and then ever time the sink asks for an input, the source is run until it produces its output.
In your case you'd have roughly something like
magical :: Sink a IO () -- consumes a stream of `a`s, no result
magical = go (some initial state)
where
go state = do
m'input <- await
case m'input of
Nothing -> return () -- finish
Just input -> do
-- do something with the input
go (some updated state)
This is not exactly what you asked for, but it might be enough for your purposes, I think.
magical :: ([a] -> IO ()) -> IO (a -> IO ())
magical f = do
list <- newIORef []
let g x = do
modifyIORef list (x:)
xs <- readIORef list
f xs -- or (reverse xs), if you need FIFO ordering
return g
So if you have a function fooHistory :: [a] -> IO (), you can use
main = do
...
foo <- magical fooHistory
setHandler foo -- here we have foo :: a -> IO ()
...
As #danidaz wrote above, you probably do not need magical, but can play the same trick directly in your fooHistory, modifying a list reference (IORef [a]).
main = do
...
list <- newIORef []
let fooHistory x = do
modifyIORef list (x:)
xs <- readIORef list
use xs -- or (reverse xs), if you need FIFO ordering
setHandler fooHistory -- here we have fooHistory :: a -> IO ()
...
Control.Concurrent.Chan does almost exactly what I wanted!
import Control.Monad (forever)
import Control.Concurrent (forkIO)
import Control.Concurrent.Chan
setHandler :: (Char -> IO ()) -> IO ()
setHandler f = void . forkIO . forever $ getChar >>= f
process :: String -> IO ()
process ('h':'i':xs) = putStrLn "hi" >> process xs
process ('a':xs) = putStrLn "a" >> process xs
process (x:xs) = process xs
process _ = error "Guaranteed to be infinite"
main :: IO ()
main = do
c <- newChan
setHandler $ writeChan c
list <- getChanContents c
process list
This seems like a flaw in the library design to me. You might consider an upstream patch so that you could provide something more versatile as input.

Updating MVar Throws Exception

Given:
λ: >let x = Control.Concurrent.MVar.newMVar ""
λ: >:t x
x :: IO (MVar [Char])
I tried to call putMVar:
λ: >:t putMVar
putMVar :: MVar a -> a -> IO ()
λ: >:t x
x :: IO (MVar [Char])
yet it failed
λ: >x >>= \y -> putMVar y "foo"
:^?^?
*** Exception: thread blocked indefinitely in an MVar operation
Why did it fail and how can I update x with "foo" rather than ""?
x is not an MVar. It is an action that creates an MVar, i.e. it's another name for newMVar "".
x >>= \y -> putMVar y "foo" is an action that creates an MVar and names it y. It then tries to put "foo" in the MVar. However, y already contains "", so putMVar blocks. It doesn't simply block forever because y is a local variable in this action, meaning no one else has access to it and no readers exist. putMVar detects this situation (deadlock) and throws an exception instead.
What you should do instead is start with:
x <- newMVar ""
This makes x an MVar.
Then you can take the old value ("") out:
takeMVar x
And put a new value in
putMVar x "foo"
(MVar doesn't support replacing the existing value in one step; you first have to take it out, then put a new value in.)
Let's look up the documentation:
data MVar a
An MVar (pronounced "em-var") is a synchronising variable, used for
communication between concurrent threads. It can be thought of as a a
box, which may be empty or full.
and
newMVar :: a -> IO (MVar a)
Create an MVar which contains the supplied value.
and
putMVar :: MVar a -> a -> IO ()
Put a value into an MVar. If the MVar is currently full, putMVar will
wait until it becomes empty.
There are two further important properties of putMVar:
putMVar is single-wakeup. That is, if there are multiple threads
blocked in putMVar, and the MVar becomes empty, only one thread will
be woken up. The runtime guarantees that the woken thread completes
its putMVar operation. When multiple threads are blocked on an MVar,
they are woken up in FIFO order. This is useful for providing fairness
properties of abstractions built using MVars.
melpomene's answer contains the correct explanation. I let my answer remain here for the cited documentation.

How does the RTS detect that a thread is blocked indefinitely on an MVar operation?

I have this code
mvarToList :: MVar (Maybe a) -> IO [a]
mvarToList mv = do
mby <- takeMVar mv
case mby of
Nothing -> return []
Just x -> do
xs <- unsafeInterleaveIO (mvarToList mv)
return (x : xs)
{-# NOINLINE mvarToList #-}
streamQuery_ :: FromRow a => Connection -> Query -> IO [a]
streamQuery_ conn q = do
mv <- newEmptyMVar
void $ forkIO $ do
fold_ conn q () (\_ x -> putMVar mv (Just x))
putMVar mv Nothing
mvarToList mv
It uses the postgresql-simple library which provides a fold_ function. It allows you to provide a function that's ran on every row of the query's result. The internal implementation is such that if the provided function blocks, the next result won't be fetched (modulo batching).
What I've done here is basically attached the evaluation of an element of the list to takeMVar which gives me a lazy list that streams results from the DB.
The problem here is leakage. The only way I can hope to avoid any leaks is if SOMEHOW garbage collecting the list results in the RTS determining that the fetching thread is blocked forever (since nothing will be taken from the MVar anymore) and throws an exception to it. Maybe I could even catch that exception and handle cleaning up?

theoretical deadlock in Control.Concurrent.Chan readChan

Browsing the source of readChan one finds the following implementation and comment, starting with version 4.6 of base:
-- |Read the next value from the 'Chan'.
readChan :: Chan a -> IO a
readChan (Chan readVar _) = do
modifyMVarMasked readVar $ \read_end -> do -- Note [modifyMVarMasked]
(ChItem val new_read_end) <- readMVar read_end
-- Use readMVar here, not takeMVar,
-- else dupChan doesn't work
return (new_read_end, val)
-- Note [modifyMVarMasked]
-- This prevents a theoretical deadlock if an asynchronous exception
-- happens during the readMVar while the MVar is empty. In that case
-- the read_end MVar will be left empty, and subsequent readers will
-- deadlock. Using modifyMVarMasked prevents this. The deadlock can
-- be reproduced, but only by expanding readMVar and inserting an
-- artificial yield between its takeMVar and putMVar operations.
Prior to base version 4.6, modifyMVar was used rather than modifyMVarMasked.
I don't understand what theoretical problem is solved for here. The last sentence states there is a problem if the thread yields between the takeMVar and putMVar that comprise readMVar. But as readMVar executes under mask_, how can an async exception prevent the put after successful take?
Any help understanding the issue here is appreciated.
Let's compare the source of modifyMVar and modifyMVarMasked, since the code changed from using one to using the other:
modifyMVar m io =
mask $ \restore -> do
a <- takeMVar m
(a',b) <- restore (io a) `onException` putMVar m a
putMVar m a'
return b
modifyMVarMasked m io =
mask_ $ do
a <- takeMVar m
(a',b) <- io a `onException` putMVar m a
putMVar m a'
return b
The key here is that modifyMVar calls restore before executing its second argument, whereas modifyMVarMasked does not. So readMVar was not called under mask_ in the old version of the code as you claim in your question! It was called under restore, instead, and therefore asynchronous exceptions could be enabled after all.
Here's me working through it.
So in readMVar...
readMVar :: MVar a -> IO a
readMVar m =
mask_ $ do
a <- takeMVar m
putMVar m a
return a
...despite the mask_ the runtime may raise an exception in a blocked takeMVar. Note in that function there's no need to actually handle that case; either the readMVar worked, in which case we're safe from async exceptions, or the takeMVar never succeeds; either way we never break the MVar by leaving it empty. (Is this correct? This is what I took away from the answer to my own related question.)
modifyMVar and modifyMVarMasked are:
modifyMVar :: MVar a -> (a -> IO (a,b)) -> IO b
modifyMVar m io =
mask $ \restore -> do
a <- takeMVar m
(a',b) <- restore (io a) `onException` putMVar m a
putMVar m a'
return b
modifyMVarMasked :: MVar a -> (a -> IO (a,b)) -> IO b
modifyMVarMasked m io =
mask_ $ do
a <- takeMVar m
(a',b) <- io a `onException` putMVar m a
putMVar m a'
return b
...where the difference is in modifyMVar the masking state is restored (i.e. async exceptions probably become unmasked) in io a, which in our case is more or less readMVar.
EDIT: Although readMVar is mask_-ed as well, so now I can't see why either choice of modifyMVarMasked or modifyMVar would make a difference...
The comment seems to imply that yield (inserted into readMVar) is interruptible (I can't find this documented anywhere) and so an async exception might be raised, in which case readVar would be restored (in both current and pre-4.6 versions), but in a non-empty queue readers would see an empty one and block.
You may be interested in reading the GHC trac on this commit, which has a sample program that consistently reproduces this bug when both Control.Concurrent.Chan and the test program are compiled -O0
https://ghc.haskell.org/trac/ghc/ticket/6153
In a similar vein:
https://ghc.haskell.org/trac/ghc/ticket/5870

Haskell - Actor based mutability

I'm working on a haskell network application and I use the actor pattern to manage multithreading. One thing I came across is how to store for example a set of client sockets/handles. Which of course must be accessible for all threads and can change when clients log on/off.
Since I'm coming from the imperative world I thought about some kind of lock-mechanism but when I noticed how ugly this is I thought about "pure" mutability, well actually it's kind of pure:
import Control.Concurrent
import Control.Monad
import Network
import System.IO
import Data.List
import Data.Maybe
import System.Environment
import Control.Exception
newStorage :: (Eq a, Show a) => IO (Chan (String, Maybe (Chan [a]), Maybe a))
newStorage = do
q <- newChan
forkIO $ storage [] q
return q
newHandleStorage :: IO (Chan (String, Maybe (Chan [Handle]), Maybe Handle))
newHandleStorage = newStorage
storage :: (Eq a, Show a) => [a] -> Chan (String, Maybe (Chan [a]), Maybe a) -> IO ()
storage s q = do
let loop = (`storage` q)
(req, reply, d) <- readChan q
print ("processing " ++ show(d))
case req of
"add" -> loop ((fromJust d) : s)
"remove" -> loop (delete (fromJust d) s)
"get" -> do
writeChan (fromJust reply) s
loop s
store s d = writeChan s ("add", Nothing, Just d)
unstore s d = writeChan s ("remove", Nothing, Just d)
request s = do
chan <- newChan
writeChan s ("get", Just chan, Nothing)
readChan chan
The point is that a thread (actor) is managing a list of items and modifies the list according to incoming requests. Since thread are really cheap I thought this could be a really nice functional alternative.
Of course this is just a prototype (a quick dirty proof of concept).
So my question is:
Is this a "good" way of managing shared mutable variables (in the actor world) ?
Is there already a library for this pattern ? (I already searched but I found nothing)
Regards,
Chris
Here is a quick and dirty example using stm and pipes-network. This will set up a simple server that allows clients to connect and increment or decrement a counter. It will display a very simple status bar showing the current tallies of all connected clients and will remove client tallies from the bar when they disconnect.
First I will begin with the server, and I've generously commented the code to explain how it works:
import Control.Concurrent.STM (STM, atomically)
import Control.Concurrent.STM.TVar
import qualified Data.HashMap.Strict as H
import Data.Foldable (forM_)
import Control.Concurrent (forkIO, threadDelay)
import Control.Monad (unless)
import Control.Monad.Trans.State.Strict
import qualified Data.ByteString.Char8 as B
import Control.Proxy
import Control.Proxy.TCP
import System.IO
main = do
hSetBuffering stdout NoBuffering
{- These are the internal data structures. They should be an implementation
detail and you should never expose these references to the
"business logic" part of the application. -}
-- I use nRef to keep track of creating fresh Ints (which identify users)
nRef <- newTVarIO 0 :: IO (TVar Int)
{- hMap associates every user (i.e. Int) with a counter
Notice how I've "striped" the hash map by storing STM references to the
values instead of storing the values directly. This means that I only
actually write the hashmap when adding or removing users, which reduces
contention for the hash map.
Since each user gets their own unique STM reference for their counter,
modifying counters does not cause contention with other counters or
contention with the hash map. -}
hMap <- newTVarIO H.empty :: IO (TVar (H.HashMap Int (TVar Int)))
{- The following code makes heavy use of Haskell's pure closures. Each
'let' binding closes over its current environment, which is safe since
Haskell is pure. -}
let {- 'getCounters' is the only server-facing command in our STM API. The
only permitted operation is retrieving the current set of user
counters.
'getCounters' closes over the 'hMap' reference currently in scope so
that the server never needs to be aware about our internal
implementation. -}
getCounters :: STM [Int]
getCounters = do
refs <- fmap H.elems (readTVar hMap)
mapM readTVar refs
{- 'init' is the only client-facing command in our STM API. It
initializes the client's entry in the hash map and returns two
commands: the first command is what the client calls to 'increment'
their counter and the second command is what the client calls to log
off and delete
'delete' command.
Notice that those two returned commands each close over the client's
unique STM reference so the client never needs to be aware of how
exactly 'init' is implemented under the hood. -}
init :: STM (STM (), STM ())
init = do
n <- readTVar nRef
writeTVar nRef $! n + 1
ref <- newTVar 0
modifyTVar' hMap (H.insert n ref)
let incrementRef :: STM ()
incrementRef = do
mRef <- fmap (H.lookup n) (readTVar hMap)
forM_ mRef $ \ref -> modifyTVar' ref (+ 1)
deleteRef :: STM ()
deleteRef = modifyTVar' hMap (H.delete n)
return (incrementRef, deleteRef)
{- Now for the actual program logic. Everything past this point only uses
the approved STM API (i.e. 'getCounters' and 'init'). If I wanted I
could factor the above approved STM API into a separate module to enforce
the encapsulation boundary, but I am lazy. -}
{- Fork a thread which polls the current state of the counters and displays
it to the console. There is a way to implement this without polling but
this gets the job done for now.
Most of what it is doing is just some simple tricks to reuse the same
console line instead of outputting a stream of lines. Otherwise it
would be just:
forkIO $ forever $ do
ns <- atomically getCounters
print ns
-}
forkIO $ (`evalStateT` 0) $ forever $ do
del <- get
lift $ do
putStr (replicate del '\b')
putStr (replicate del ' ' )
putStr (replicate del '\b')
ns <- lift $ atomically getCounters
let str = show ns
lift $ putStr str
put $! length str
lift $ threadDelay 10000
{- Fork a thread for each incoming connection, which listens to the client's
commands and translates them into 'STM' actions -}
serve HostAny "8080" $ \(socket, _) -> do
(increment, delete) <- atomically init
{- Right now, just do the dumb thing and convert all keypresses into
increment commands, with the exception of the 'q' key, which will
quit -}
let handler :: (Proxy p) => () -> Consumer p Char IO ()
handler () = runIdentityP loop
where
loop = do
c <- request ()
unless (c == 'q') $ do
lift $ atomically increment
loop
{- This uses my 'pipes' library. It basically is a high-level way to
say:
* Read binary packets from the socket no bigger than 4096 bytes
* Get the first character from each packet and discard the rest
* Handle the character using the above 'handler' function -}
runProxy $ socketReadS 4096 socket >-> mapD B.head >-> handler
{- The above pipeline finishes either when the socket closes or
'handler' stops looping because it received a 'q'. Either case means
that the client is done so we log them out using 'delete'. -}
atomically delete
Next up is the client, which simply opens a connections and forwards all key presses as single packets:
import Control.Monad
import Control.Proxy
import Control.Proxy.Safe
import Control.Proxy.TCP.Safe
import Data.ByteString.Char8 (pack)
import System.IO
main = do
hSetBuffering stdin NoBuffering
hSetEcho stdin False
{- Again, this uses my 'pipes' library. It basically says:
* Read characters from the console using 'commands'
* Pack them into a binary format
* send them to a server running at 127.0.0.1:8080
This finishes looping when the user types a 'q' or the connection is
closed for whatever reason.
-}
runSafeIO $ runProxy $ runEitherK $
try . commands
>-> mapD (\c -> pack [c])
>-> connectWriteD Nothing "127.0.0.1" "8080"
commands :: (Proxy p) => () -> Producer p Char IO ()
commands () = runIdentityP loop
where
loop = do
c <- lift getChar
respond c
unless (c == 'q') loop
It's pretty simple: commands generates a stream of Chars, which then get converted to ByteStrings and then sent as packets to the server.
If you run the server and a few clients and have them each type in a few keys, your server display will output a list showing how many keys each client typed:
[1,6,4]
... and if some of the clients disconnect they will be removed from the list:
[1,4]
Note that the pipes component of these examples will simplify greatly in the upcoming pipes-4.0.0 release, but the current pipes ecosystem still gets the job done as is.
First, I'd definitely recommend using your own specific data type for representing commands. When using (String, Maybe (Chan [a]), Maybe a) a buggy client can crash your actor simply by sending an unknown command or by sending ("add", Nothing, Nothing), etc. I'd suggest something like
data Command a = Add a | Remove a | Get (Chan [a])
Then you can pattern match on commands in storage in a save way.
Actors have their advantages, but also I feel that they have some drawbacks. For example, getting an answer from an actor requires sending it a command and then waiting for a reply. And the client can't be completely sure that it gets a reply and that the reply will be of some specific type - you can't say I want only answers of this type (and how many of them) for this particular command.
So as an example I'll give a simple, STM solution. It'd be better to use a hash table or a (balanced tree) set, but since Handle implements neither Ord nor Hashable, we can't use these data structures, so I'll keep using lists.
module ThreadSet (
TSet, add, remove, get
) where
import Control.Monad
import Control.Monad.STM
import Control.Concurrent.STM.TVar
import Data.List (delete)
newtype TSet a = TSet (TVar [a])
add :: (Eq a) => a -> TSet a -> STM ()
add x (TSet v) = readTVar v >>= writeTVar v . (x :)
remove :: (Eq a) => a -> TSet a -> STM ()
remove x (TSet v) = readTVar v >>= writeTVar v . delete x
get :: (Eq a) => TSet a -> STM [a]
get (TSet v) = readTVar v
This module implements a STM based set of arbitrary elements. You can have multiple such sets and use them together in a single STM transaction that succeeds or fails at once. For example
-- | Ensures that there is exactly one element `x` in the set.
add1 :: (Eq a) => a -> TSet a -> STM ()
add1 x v = remove x v >> add x v
This would be difficult with actors, you'd have to add it as another command for the actor, you can't compose it of existing actions and still have atomicity.
Update: There is an interesting article explaining why Clojure designers chose not to use actors. For example, using actors, even if you have many reads and only very little writes to a mutable structure, they're all serialized, which can greatly impact performance.

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