I have a question on Mule threading profile Exhausted_Action. From the documentation, I understand that when the action is WAIT, any new request beyond the maxActive will wait for a thread to be available. Whereas action of RUN, would cause use the original thread to process the request. From my understanding, I thought WAIT is better way to do it, rather than RUN. However, it appears MULE has all default values set to RUN. Just want to hear for comments on my understanding and differences between these two actions and how to decide which one to use when.
Your undertanding about WAIT and RUN is correct.
Reason why all the default values are RUN is that, The message processing is not stopped because of unavailability of flow thread. Because the original thread(or receiver thread) is anyway waiting for the Flow thread to take the message and process, why not process it. (This is my opinion).
But there is a downside for using RUN.
Ex:
No of receiver threads are restricted to 2.
<asynchronous=processing-strategy name="customAsynchronous" maxThreads="1" />
<flow name="sample" processingStrategy="customAsynchronous" >
<file:inbound-endpoint ......>
............
..........
</flow>
File sizes: 1MB, 50MB, 100MB, 1MB, 5MB.
In the above flow when there are 5 files coming in. 3 files are processed as there is 1 flow thread available and 2 File Receiver threads (Exhausted_Action = RUN). The flow thread will finish the processing fast as the first file is small and keeps waiting for the next message. Unfortunately the receiver thread whose job is to pick the next file and give it to Flow thread to process is busy processing the BIG file. This way there is a chance of receiver threads getting struck in time consuming processing while the flow threads are waiting.
So it is always depending on the usecase you are dealing with.
Hope this helps.
Related
I have the following JMeter context:
In one Concurrency Thread Group 1, I have a JSR223 Sampler which sends request messages to an MQ queue1 and always gets the JMSMessageID and an epochTimestamp (derived from JMS_IBM_PutDate + JMS_IBM_PutTime) and puts them into one variable. Underneath this Sampler is an Inter-Thread Communication PostProcessor element which gets the data from this variable and puts it into a FIFO QUEUE.
In another Concurrency Thread Group 2, I have another JSR223 Sampler with code to get the response messages for all the messages sent on MQ queue 1 from an MQ queue2.
To do this, (and be able to calculate the response time fore each message) before the JSR223 Sampler executes, I use the Inter-Thread Communication PreProcessor element which gets a message ID and a timestamp from the FIFO queue (60 seconds timeout) and passes it over to a variable with which the JSR223 Sampler can work to calculate the request-response time for each message.
I want to stress-test the system, which is why I am gradually dynamically increasing the Requests per second at every 1 minute (for script testing purposes) in both thread groups, like so:
I use the tstFeedback function of Concurrency Thread Group for this:
${__tstFeedback(ThroughputShapingTimerIn,1,1000,10)}
My problem is this:
When I gradually increase the desired TPS load, during the first 4 target TPS steps, the Consumer threads keep up (synchronized) with the Producer threads, but as the time passes and load increases, the consumer threads seem to be taking more time to find and consume the messages. It's as though the load of the consumer treads is no longer able to keep up with the load of the producer threads, despite both thread groups having the same load pattern. This eventually causes the queue2 which is keeping the response messages to get full. Here is a visual representation of what I mean:
The Consumer samples end up being much less than the producer samples. My expectation is that they should be more or less equal...
I need to understand how I can go about to debug this script and isolate the cause:
I think that something happens at the inter-thread synchronization level because sometimes I am getting null values from the FIFO queue into the consumer threads - I need to understand what gets put into that FIFO queue and what gets taken off of that FIFO queue.
How can I print what is present in the FIFO list at each iteration?
Does anyone have any suggestions for what could be the cause of this behavior and how to mitigate it?
Any help/suggestion is greatly appreciated.
First of all take a look at jmeter.log file, you have at least 865 errors there so I strongly doubt your Groovy scripts are doing what they're supposed to be doing
Don't run your test in GUI mode, it's only for tests development and debugging, when it comes to execution you should be using command-line non-GUI mode
When you call __fifoPop() you can save the value into a JMeter Variable like ${__fifoPop(queue-name,some-variable)}, the variable can be visualized using Debug Sampler. The size of the queue can be checked using __fifoSize() function
Alternatively my expectation is that such a Groovy expert as you shouldn't have any problems printing queue items in Groovy code:
I want to run a small clean up process every few hours on an Erlang server.
I know of the timer module. I saw an example in a tutorial used chained timer:sleep commands to wait for an event that would occur multiple days later, which I found strange. I understand that Erlang process are unique compared to those in other languages, but the idea of a process/thread sleeping for days, weeks, and even months at a time seemed odd.
So I set out to find out the details of what sleeping actually does. The closest I found was a blog post mentioning that sleep is implemented with a receive timeout, but that still left the question:
What do these sleep/sleep-like functions actually do?
Is my process taking up resources as it sleeps? Would having thousands of sleeping process use as many resources, as say, thousands of process servicing a recursive call that did nothing? Is there any performance penalty from repeatedly sleeping within processes, or sleeping for long periods of time? Is the VM constantly expending resources to see if the conditions to end the processes' sleep are up?
And as a side note, I'd appreciate if someone could comment on if there is a better way than sleeping to pause for hours or days at a time?
That is the Karma of any erlang process: it waits or dies :o)
when a process is spawned, it start executing until the last execution line, and die, returning the last evaluation.
To keep a process alive, there is no other solution to recursively loop in a never ending succession of calls.
of course there are several conditions that make it stop or sleep:
end of the loop: the process received a message which tell him to
stop recursion
a receive bloc: the process will wait until a message
matching one entry in the receive bloc is posted in the message
queue.
The VM scheduler stop it temporarily to let access to the CPU
to other processes
in the 2 last cases the execution will restart under the responsibility of the VM scheduler.
while waiting it uses no CPU bandwidth, but keeps the exact same memory layout it had when it started waiting. The Erlang OTP offers some means to reduce this memory layout to the minimum using the hibernate option (see the documentation of gen_serevr or gen_fsm, but it is for advanced usage only in my mind).
a simple way to create a "signal" that will fire a process at regular (or almost regular) interval is effectively to use receive block with timout (The timeout is limited to 65535 ms), for example:
on_tick_sec(Module,Function,Arglist,Period) ->
on_tick(Module,Function,Arglist,1000,Period,0).
on_tick_mn(Module,Function,Arglist,Period) ->
on_tick(Module,Function,Arglist,60000,Period,0).
on_tick_hr(Module,Function,Arglist,Period) ->
on_tick(Module,Function,Arglist,60000,Period*60,0).
on_tick(Module,Function,Arglist,TimeBase,Period,Period) ->
apply(Module,Function,Arglist),
on_tick(Module,Function,Arglist,TimeBase,Period,0);
on_tick(Module,Function,Arglist,TimeBase,Period,CountTimeBase) ->
receive
stop -> stopped
after TimeBase ->
on_tick(Module,Function,Arglist,TimeBase,Period,CountTimeBase+1)
end.
and usage:
1> Pid = spawn(util,on_tick_sec,[io,format,["hello~n"],5]).
<0.40.0>
hello
hello
hello
hello
2> Pid ! stop.
stop
3>
[edit]
The timer module is a standard gen_server running in a separate process. All the function in the timer module are public interfaces that execute a hidden gen_server:call or gen_server:cast to the timer server. This is a common usage to hide the internal of a server and allow further evolutions without impact on existing applications.
The server uses internally a table (ets) to store all the actions it has to do along with each timer reference and it uses its own function to be awaken when needed (at the end, the VM must take care of this ?).
So you can hibernate a process without any effect on the timer server behavior. The hibernation mechanism is
tricky, see documentation at hibernate/3 definition, you will see that yo have to "rebuild" the context by yourself since everything was removed from the process context, and a tuple(Module,Function,Arguments} is stored by the system to restart your process when needed.
cost some time in garbage collecting and process restart
It is why I said that it is really an advance feature that need good reason to be used.
There is also erlang:hibernate/3 that puts a process in "deep sleep", minimizing memory usage for it.
I would like to synchronize threads with WINAPI calls only but I have no success.
The situation is to LOG activities with time and date as soon as my WNDPROC gets a message.
The problem is that my WNDPROC needs to write to the log and it will get out of hand since writing to a file takes time. I tried to enter a critical section as soon as WNDPROC starts and leave a critical section as soon as writing to a log is finished, but no luck. How can make them wait for each other?
Don't wait - queue.
A Windows message is so small, (within itself:), that copying the entire message into a producer-consumer queue is a reasonable approach. You could raise your own queue class, or you could maybe use the PostThreadMessage() API to copy and queue the received messages to a logger thread:
http://msdn.microsoft.com/en-gb/library/windows/desktop/ms644946%28v=vs.85%29.aspx
The snag with PTM() is that only the message data gets copied and queued up - no time/date. Thge time/date would have to be added in the logger thread when it gets the message copy. Check your requirements to see if this is acceptable. If not, you will have to use a different 'message' struct that has members for both the Windows message and date/time.
Queueing insulates the UI thread from the, possibly lengthy, disk logging write operation and allows extra flexibility to incorporate lazy-writes and other such optimizations, if required.
I've got a program which receives string messages from other applications and parses them using VCL.
Messages are sent as follows:
AtomId := GlobalAddAtom(PChar(s));
SendMessage(MyProgramHandle, WM_MSG, 0, AtomID);
GlobalDeleteAtom(AtomID);
My program receives this message, parses it for some time, and then returns control to an application.
It takes time to parse one message so perfomance of other applications worsens.
One possible solution is to create form with the same caption and the same class in other thread, and rename class of main form.
But as far as I know it isn't recommended to create forms in threads.
So, what are possible ways to improve perfomance?
The typical approach would be to create a worker thread (or a pool of worker threads). The main thread will continue to receive the messages, but instead of parsing them it will just add them to a queue (a linked list, for example).
The worker thread takes the first element in the queue and processes it. When done it goes back to the queue to get the next element.
Since the queue is a shared resource between multiple threads you have to control access to it. A mutex will ensure that only one thread gets access to the queue at any given time.
Good luck.
So the problem is that both the receiving of the messages and the VCL operations are done in the same thread (the main VCL thread)? And so the receiving and processing are serialized and as result the senders are blocked while your app is busy filling the grid? Then I can understand that you ask for a way to move the receiving to a different window message loop.
So I would create a window (not a VCL form) only for the purpose to receive messages and use its message loop to add message to a queue. So you only need to find this (non-VCL) window and SendMessage to its handle. In the VCL thread, a Timer could fetch the next "n" messages and add them to the grid.
Hi we are building an application that will have the possibility to register scheduled tasks.
Each task has an time interval when it should be executed
Each task should have an timeout
The amount of tasks can be infinite but around 100 in normal cases.
So we have an list of tasks that need to be executed in intervals, which are the best solution?
I have looked at giving each task their timer and when the timer elapses the work will be started, another timer keeps tracks on the timeout so if the timeout is reached the other timer stops the thread.
This feels like we are overusing timers? Or could it work?
Another solution is to use timers for each task, but when the time elapses we are putting the task on a queue that will be read with some threads that executes the work?
Any other good solutions I should look for?
There is not too much information but it looks like that you can consider RX as well - check more at MSDN.com.
You can think about your tasks as generated events which should be composed (scheduled) in some way. So you can do the following:
Spawn cancellable tasks with Observable.GenerateWithDisposable and your own Scheduler - check more at Rx 101 Sample
Delay tasks with Observable.Delay
Wait for tasks with 'Observable.Timeout
Compose tasks in any preferable way
Once again you can check more at specified above links.
You should check out Quartz.NET.
Quartz.NET is a full-featured, open
source job scheduling system that can
be used from smallest apps to large
scale enterprise systems.
I believe you would need to implement your timeout requirement by yourself but all the plumbing needed to schedule tasks could be handled by Quartz.NET.
I have done something like this before where there were a lot of socket objects that needed periodic starts and timeouts. I used a 'TimedAction' class with 'OnStart' and 'OnTimeout' events, (socket classes etc. derived from this), and one thread that handled all the timed actions. The thread maintained a list of TimedAction instances ordered by the tick time of the next action required, (delta queue). The TimedAction objects were added to the list by queueing them to the thread input queue. The thread waitied on this input queue with a timeout, (this was Windows, so 'WaitForSingleObject' on the handle of the semaphore that managed the queue), set to the 'next action required' tick count of the first item in the list. If the queue wait timed out, the relevant action event of the first item in the list was called and the item removed from the list - the next queue wait would then be set by the new 'first item in the list', which would contain the new 'nearest action time'. If a new TimedAction arrived on the queue, the thread calculated its timeout tick time, (GetTickCount + ms interval from the object), and inserted it in the sorted list at the correct place, (yes, this sometimes meant moving a lot of objects up the list to make space).
The events called by the timeout handler thread could not take any lengthy actions in order to prevent delays to the handling of other timeouts. Typically, the event handlers would set some status enumeration, signal some synchro object or queue the TimedAction to some other P-C queue or IO completion port.
Does that make sense? It worked OK, processing thousands of timed actions in my server in a reasonably timely and efficient manner.
One enhancement I planned to make was to use multiple lists with a restricted set of timeout intervals. There were only three const timeout intervals used in my system, so I could get away with using three lists, one for each interval. This would mean that the lists would not need sorting explicitly - new TimedActions would always go to the end of their list. This would eliminate costly insertion of objects in the middle of the list/s. I never got around to doing this as my first design worked well enough and I had plenty other bugs to fix :(
Two things:
Beware 32-bit tickCount rollover.
You need a loop in the queue timeout block - there may be items on the list with exactly the same, or near-same, timeout tick count. Once the queue timeout happens, you need to remove from the list and fire the events of every object until the newly claculated timeout time is >0. I fell foul of this one. Two objects with equal timeout tick count arrived at the head of the list. One got its events fired, but the system tick count had moved on and so the calcualted timeout tick for the next object was -1: INFINITE! My server stopped working properly and eventually locked up :(
Rgds,
Martin