I'd like to create a program that runs a function on an interval. I'm still very new to Elixir and do not know really where to start with this. My idea is that since we can use GenServer to create a program to sit and wait in a loop for messages, I could provide it a message (maybe :kick) and when it receives this message it would run the function.
However, that leaves one problem - how do I kick it without a cron job? Can I fire up a thread and run a timer that kicks it on an interval? If the main thread dies - is there an easy way to be notified and restart it?
Thank you!
You can use timer:send_interval/2 with a GenServer. You'll need to call the function from the init/1 callback and then handle the tick messages from the handle_info callback. Here's an example that prints 0, 1, 2, ... every second:
defmodule A do
use GenServer
def init(_) do
:timer.send_interval(1000, :tick)
{:ok, 0}
end
def handle_info(:tick, state) do
IO.inspect state
{:noreply, state + 1}
end
end
iex(1)> GenServer.start_link(A, [])
{:ok, #PID<0.94.0>}
0
1
2
3
4
...
If the main thread dies - is there an easy way to be notified and restart it?
You should look into Supervisors. The GenServer above can be added as a "worker" to a Supervisor. The Supervisor can handle restarting the GenServer if it exits for any reason.
#Dogbert mentionned using using the send_interval function from Erlang, which would be used like so : :timer.send_interval(milliseconds, process, message).
A quick Google search however, netted me the quantum-elixir library which appears to be capable of cron like scheduling, as well as scheduling tasks at runtime.
I have the same situation like this: stop thread started by qtconcurrent::run
I need to close child thread (started with QtConcurrent::run) on closeEvent in QMainWindow.
But my function in child thread use code from *.dll: I can`t use loop because all that I do - is calling the external dll like
QFuture<void> = QtConcurrent::run(obj->useDllfunc_with_longTermJob());
And when I close the app with x-button my gui is closed, but second thread with_longTermJob() still worked and when is finished I have an error.
I know some decisions for this:
using other functions like map() or something else with
QFuture.cancel/stop functionality, not QtConcurrent::run().But I need only one function call. run() is what I need.
or use QThread instead Concurrent.But it`s not good for me.
What method more simple and better and how can I implement this? Is there a method that I don`t listed?
Could you provide small code sample for decision. Thx!
QtConcurrent::run isn't a problem here. You must have means of stopping the dllFuncWithLongTermJob. If you don't have such means, then the API you're using is broken, and you're out of luck. There's nothing you can do that'd be generally safe. Forcibly terminating a thread can leave the heap in an inconsistent state, etc. - if you need to terminate a thread, you need to immediately abort the application.
Hopefully, you can call something like stopLongTermJob that sets some flag that interrupts the dllFuncWithLongTermJob.
Then:
auto obj = new Worker;
auto objFuture = QtConcurrent::run([=]{obj->dllFuncWithLongTermJob();});
To interrupt:
obj->stopLongTermJob(); // must be thread-safe, sets a flag
objFuture.waitForFinished();
Hi need some help on my lua script. I have a script here that will run a server like application (infinite loop). Problem here is it doesn't execute the second coroutine.
Could you tell me whats wrong Thank you.
function startServer()
print( "...Running server" )
--run a server like application infinite loop
os.execute( "server.exe" )
end
function continue()
print("continue")
end
co = coroutine.create( startServer() )
co1 = coroutine.create( continue() )
Lua have cooperative multithreading. Threads are not swtiched automatically, but must yield to others. When one thread is running, every other thread is waiting for it to finish or yield. Your first thread in this example seems to run server.exe, which, I assume, never finishes until interrupted. Thus second thread never gets its turn to run.
You also run threads wrong. In your example you're not running any threads at all. You execute function and then would try to create coroutine with its output, which naturally would fail. But since you never get back from server.exe you didn't notice this problem yet. Remove those brackets after startServer and continue to fix it.
As already noted, there are several issues with the script that prevent you from getting what you want:
os.execute("...") is blocked until the command is completed and in your case it doesn't complete (as it runs an infinite loop). Solution: you need to detach that process from yours by using something like io.popen() instead of os.execute()
co = coroutine.create( startServer() ) doesn't create a coroutine in your case. coroutine.create call accepts a function reference and you pass it the result of startServer call, which is nil. Solution: use co = coroutine.create( startServer ) (note that parenthesis are dropped, so it's not a function call anymore).
You are not yielding from your coroutines; if you want several coroutines to work together, they need to be cooperating by giving control to each other when appropriate. That's what yield command is for and that's why it's called non-preemptive multithreading. Solution: you need to use a combination of resume and yield calls after you create your coroutine.
startServer doesn't need to be a coroutine as you are not giving control back to it; its only purpose is to start the server.
In your case, the solution may not even need coroutines as all you need to do is: (1) start the server and let it detach from your process (for example, using popen) and (2) work with your process using whatever communication protocol it requires (pipes, sockets, etc.).
There are more complex and complete solutions (like LuaLanes) and also several good descriptions on creating simple coroutine dispatchers.
Your coroutine is not yielding
I have a web application that requests a report that takes more than 10 minutes to run. Apart from improving that performance, I would for now prefer to set up a thread to run the report and mail it to the user, returning that decision message back to the user immediately.
I have been looking at cherrypy.process.plugins.Monitor, but I'm not clear if it is the correct choice (what to do with the frequency parameter?)
Monitor is not the correct choice; it's for running the same task repeatedly on a schedule. You're probably better off just calling threading.Thread(target=run_report).start(). You can then return 202 Accepted to the user, along with a URL for the client to watch the status and/or retrieve the newly-created report resource when it's ready.
The one caveat to that is that you might want your new thread to shut down gracefully when the cherrypy.engine stops. Have a look at the various plugins for examples of how to hook into the 'stop' channel on the bus. The other option would be to make your thread daemonic, if you don't care if it terminates abnormally.
Besides agreeing with fumanchu's answer, I would like to add that the frequency parameter is actually the period expressed in seconds.cherrypy.process.plugins.Monitor (the name is misleading).
Another possible solution could be having a monitor executed periodically, and a set of working computations which can be checked periodically for completion. The code would be something like
class Scheduler:
def __init__ (self):
self.lock = threading.Lock()
self.mon = Monitor(cherrypy.engine, check_computations, frequency=whatever)
self.mon.start()
self.computations = list() # on which we append stuff
def check_computations (self):
with self.lock:
for i in self.computations:
check(i) # Single check function
Caveats:
The computation time of check matters. You don't want to have workload on this perioic routine
Beware on how you use locks:
It is protecting the computations list;
If you access it (even indirectly) from with check your program gets into deadlock. This could be the case if you want to unsubscribe something from the computations list.
Coding in Lua, I have a triply nested loop that goes through 6000 iterations. All 6000 iterations are independent and can easily be parallelized. What threads package for Lua compiles out of the box and gets decent parallel speedups on four or more cores?
Here's what I know so far:
luaproc comes from the core Lua team, but the software bundle on luaforge is old, and the mailing list has reports of it segfaulting. Also, it's not obvious to me how to use the scalar message-passing model to get results ultimately into a parent thread.
Lua Lanes makes interesting claims but seems to be a heavyweight, complex solution. Many messages on the mailing list report trouble getting Lua Lanes to build or work for them. I myself have had trouble getting the underlying "Lua rocks" distribution mechanism to work for me.
LuaThread requires explicit locking and requires that communication between threads be mediated by global variables that are protected by locks. I could imagine worse, but I'd be happier with a higher level of abstraction.
Concurrent Lua provides an attractive message-passing model similar to Erlang, but it says that processes do not share memory. It is not clear whether spawn actually works with any Lua function or whether there are restrictions.
Russ Cox proposed an occasional threading model that works only for C threads. Not useful for me.
I will upvote all answers that report on actual experience with these or any other multithreading package, or any answer that provides new information.
For reference, here is the loop I would like to parallelize:
for tid, tests in pairs(tests) do
local results = { }
matrix[tid] = results
for i, test in pairs(tests) do
if test.valid then
results[i] = { }
local results = results[i]
for sid, bin in pairs(binaries) do
local outcome, witness = run_test(test, bin)
results[sid] = { outcome = outcome, witness = witness }
end
end
end
end
The run_test function is passed in as an argument, so a package can be useful to me only if it can run arbitrary functions in parallel. My goal is enough parallelism to get 100% CPU utilization on 6 to 8 cores.
Norman wrote concerning luaproc:
"it's not obvious to me how to use the scalar message-passing model to get results ultimately into a parent thread"
I had the same problem with a use case I was dealing with. I liked lua proc due to its simple and light implementation, but my use case had C code that was calling lua, which was triggering a co-routine that needed to send/receive messages to interact with other luaproc threads.
To achieve my desired functionality I had to add features to luaproc to allow sending and receiving messages from the parent thread or any other thread not running from the luaproc scheduler. Additionally, my changes allow using luaproc send/receive from coroutines created from luaproc.newproc() created lua states.
I added an additional luaproc.addproc() function to the api which is to be called from any lua state running from a context not controlled by the luaproc scheduler in order to set itself up with luaproc for sending/receiving messages.
I am considering posting the source as a new github project or contacting the developers and seeing if they would like to pull my additions. Suggestions as to how I should make it available to others are welcome.
Check the threads library in torch family. It implements a thread pool model: a few true threads (pthread in linux and windows thread in win32) are created first. Each thread has a lua_State object and a blocking job queue that admits jobs added from the main thread.
Lua objects are copied over from main thread to the job thread. However C objects such as Torch tensors or tds data structures can be passed to job threads via pointers -- this is how limited shared memory is achieved.
This is a perfect example of MapReduce
You can use LuaRings to accomplish your parallelization needs.
Concurrent Lua might seem like the way to go, but as I note in my updates below, it doesn't run things in parallel. The approach I tried was to spawn several processes that execute pickled closures received through the message queue.
Update
Concurrent Lua seems to handle first-class functions and closures without a hitch. See the following example program.
require 'concurrent'
local NUM_WORKERS = 4 -- number of worker threads to use
local NUM_WORKITEMS = 100 -- number of work items for processing
-- calls the received function in the local thread context
function worker(pid)
while true do
-- request new work
concurrent.send(pid, { pid = concurrent.self() })
local msg = concurrent.receive()
-- exit when instructed
if msg.exit then return end
-- otherwise, run the provided function
msg.work()
end
end
-- creates workers, produces all the work and performs shutdown
function tasker()
local pid = concurrent.self()
-- create the worker threads
for i = 1, NUM_WORKERS do concurrent.spawn(worker, pid) end
-- provide work to threads as requests are received
for i = 1, NUM_WORKITEMS do
local msg = concurrent.receive()
-- send the work as a closure
concurrent.send(msg.pid, { work = function() print(i) end, pid = pid })
end
-- shutdown the threads as they complete
for i = 1, NUM_WORKERS do
local msg = concurrent.receive()
concurrent.send(msg.pid, { exit = true })
end
end
-- create the task process
local pid = concurrent.spawn(tasker)
-- run the event loop until all threads terminate
concurrent.loop()
Update 2
Scratch all of that stuff above. Something didn't look right when I was testing this. It turns out that Concurrent Lua isn't concurrent at all. The "processes" are implemented with coroutines and all run cooperatively in the same thread context. That's what we get for not reading carefully!
So, at least I eliminated one of the options I guess. :(
I realize that this is not a works-out-of-the-box solution, but, maybe go old-school and play with forks? (Assuming you're on a POSIX system.)
What I would have done:
Right before your loop, put all tests in a queue, accessible between processes. (A file, a Redis LIST or anything else you like most.)
Also before the loop, spawn several forks with lua-posix (same as the number of cores or even more depending on the nature of tests). In parent fork wait until all children will quit.
In each fork in a loop, get a test from the queue, execute it, put results somewhere. (To a file, to a Redis LIST, anywhere else you like.) If there are no more tests in queue, quit.
In the parent fetch and process all test results as you do now.
This assumes that test parameters and results are serializable. But even if they are not, I think that it should be rather easy to cheat around that.
I've now built a parallel application using luaproc. Here are some misconceptions that kept me from adopting it sooner, and how to work around them.
Once the parallel threads are launched, as far as I can tell there is no way for them to communicate back to the parent. This property was the big block for me. Eventually I realized the way forward: when it's done forking threads, the parent stops and waits. The job that would have been done by the parent should instead be done by a child thread, which should be dedicated to that job. Not a great model, but it works.
Communication between parent and children is very limited. The parent can communicate only scalar values: strings, Booleans, and numbers. If the parent wants to communicate more complex values, like tables and functions, it must code them as strings. Such coding can take place inline in the program, or (especially) functions can be parked into the filesystem and loaded into the child using require.
The children inherit nothing of the parent's environment. In particular, they don't inherit package.path or package.cpath. I had to work around this by the way I wrote the code for the children.
The most convenient way to communicate from parent to child is to define the child as a function, and to have the child capture parental information in its free variables, known in Lua parlances as "upvalues." These free variables may not be global variables, and they must be scalars. Still, it's a decent model. Here's an example:
local function spawner(N, workers)
return function()
local luaproc = require 'luaproc'
for i = 1, N do
luaproc.send('source', i)
end
for i = 1, workers do
luaproc.send('source', nil)
end
end
end
This code is used as, e.g.,
assert(luaproc.newproc(spawner(randoms, workers)))
This call is how values randoms and workers are communicated from parent to child.
The assertion is essential here, as if you forget the rules and accidentally capture a table or a local function, luaproc.newproc will fail.
Once I understood these properties, luaproc did indeed work "out of the box", when downloaded from askyrme on github.
ETA: There is an annoying limitation: in some circumstances, calling fread() in one thread can prevent other threads from being scheduled. In particular, if I run the sequence
local file = io.popen(command, 'r')
local result = file:read '*a'
file:close()
return result
the read operation blocks all other threads. I don't know why this is---I assume it is some nonsense going on within glibc. The workaround I used was to call directly to read(2), which required a little glue code, but this works properly with io.popen and file:close().
There's one other limitation worth noting:
Unlike Tony Hoare's original conception of communicating sequential processing, and unlike most mature, serious implementations of synchronous message passing, luaproc does not allow a receiver to block on multiple channels simultaneously. This limitation is serious, and it rules out many of the design patterns that synchronous message-passing is good at, but it's still find for many simple models of parallelism, especially the "parbegin" sort that I needed to solve for my original problem.