As i was working on my program, i noticed that, upon profiling, instruments was nice enough to point me to a Zombie object when it saw one. Does the fact that this message does not show up indicative of the fact that app contains no zombie processes?
Is there a way i can confirm that app contains no references to Zombie processes?
In my question, i am explicitly mentioning Xcode4, as i have not seen automatic Zombie behavior in 3 and suspect it may be a new feature.
No zombie messages showing up is a good sign. It means you weren't accessing any freed objects while Instruments was tracing. There's no way for Instruments to confirm that your application never accesses a freed object. All Instruments can do is tell you when you access a freed object.
Regarding automatic zombie behavior, detecting zombies is not new behavior in Xcode 4. Instruments has a Zombies template in both Xcode 3.2 and 4 that detects zombies. You can also configure the Allocations instrument to detect zombies by clicking the Info button next to the instrument, which the zombie message is blocking in your screenshot.
Related
We have a problem on our website, seemingly at random (every day or so, up to once every 7-10 days) the website will become unresponsive.
We have two web servers on Azure, and we use Redis.
I've managed to run DotNetMemory and caught it when it crashes, and what I observe is under Event handlers leak two items seem to increase in count into the thousands before the website stops working. Those two items are CaliEventHandlerDelegateProxy and ArglessEventHandlerProxy. Once the site crashes, we get lots of Redis exceptions that it can't connect to the Redis server. According to Azure Portal, our Redis server load never goes above 10% in peak times and we're following all best practises.
I've spent a long time going through our website ensuring that there are no obvious memory leaks, and have patched a few cases that went under the radar. Anecdotally, these seem to of improved the website stability a little. Things we've checked:
All iDisposable objects are now wrapped in using blocks (we did this strictly before but we did find a few not disposed properly)
Event handlers are unsubscribed - there are very few in our code base
We use WebUserControls pretty heavily. Each one had the current master page passed in as a parameter. We've removed the dependency on this as we thought it could cause GC to not collect the page perhaps
Our latest issue is that when the web server runs fine, but then we run DotNetMemory and attach it to the w3wp.exe process it causes the CaliEventHandlerDelegateProxy and ArglessEventHandlerProxy event leaks to increase rapidly until the site crashes! So the crash is reproducible just by running DotNetMemory. Here is a screenshot of what we saw:
I'm at a loss now, I believe I've exhausted all possibilities of memory leaks in our code base, and our "solution" is to have the app pools recycle every several hours to be on the safe side.
We've even tried upgrading Redis to the Premium tier, and even upgraded all drives on the webservers to SSDs to see if it helps things which it doesn't appear to.
Can anyone shed any light on what might be causing these issues?
All iDisposable objects are now wrapped in using blocks (we did this
strictly before but we did find a few not disposed properly)
We can't say a lot about crash without any information about it, but I have some speculations about it.
I see 10 000 (!) not disposed objects handled by finalization queue. Let start with them, find all of them and add Dispose call in your app.
Also I would recommend to check how many system handles utilized by your application. There is an OS limit on number of handles and if they are exceeded no more file handles, network sockets, etc can be created. I recommend it especially since the number of not disposed objects.
Also if you have a timeout on accessing Redis get performance profiler and look why so. I recommend to get JetBrains dotTrace and use TIMELINE mode to get a profile of your app, it will show thread sleeping, threads contention and many many more information what will help you to find a problem root. You can use command line tool to obtain profile data, in order not to install GUI application on the server side.
it causes the CaliEventHandlerDelegateProxy and
ArglessEventHandlerProxy event leaks to increase rapidly
dotMemory doesn't change your application code and doesn't allocate any managed objects in profiled process. Microsoft Profiling API injects a dll (written in c++) into the profiling process, it's a part of dotMemory, named Profilng Core, playing the role of the "server" (where standalone dotMemory written in C# is a client). Profiling Core doing some work with gathered data before sending it to the client side, it requires some memory, which allocated, of course, in the address space of the profiling process but it doesn't affect managed memory.
Memory profiling may affect performance of your application. For example, profiling API disables concurrent GC when application is under profiling or memory allocation data collecting can significantly slow down your application.
Why do you thing that CaliEventHandlerDelegateProxy and ArglessEventHandlerProxy are allocated only under dotMemory profiling? Could you please describe how you explored this?
Event handlers are unsubscribed - there are very few in our code base
dotMemory reports an event handler as a leak means there is only one reference to it - from event source at there is no possibility to unsubscribe from this event. Check all these leaks, find yours at look at the code how it is happened. Anyway, there are only 110.3 KB retained by these objects, why do you decide your site crashed because of them?
I'm at a loss now, I believe I've exhausted all possibilities of memory leaks in our code base
Take several snapshots in a period of time when memory consumption is growing, open full comparison of some of these snapshots and look at all survived objects which should not survive and find why they survived. This is the only way to prove that your app doesn't have memory leak, looking the code doesn't prove it, sorry.
Hope if you perform all the activities I recommend you to do (performance profiling, full snapshots and snapshots comparison investigation, not only inspections view, checking why there are huge amount of not disposed objects) you will find and fix the root problem.
I'm running into serious productivity issues when debugging flows. I can only assume at this point is due to a lack of knowledge on my part; particularly effective debugging techniques of flows. The problems arise when I have one flow which needs to "wait" for a consumption of a specific state. What seems to happen is the waiting flow starts and waits for the consumption of the specified state, but despite implemented as a listening future with an associated call back (at this point I'm simply using getOrThrow on the future returned from 'WhenConsumed'), the flows just hang and I see hundreds of Artemis send/write messages in the console window. If I stop the debug session, delete the node build directory, redeploy the nodes and start again the flows restart and I can return to the point of failure. However if I simply stop and detach the debugger from the node and attempt to run the calling test (calling the flow via RPC), nothing seems to happen. It's almost as if the flow code (probably incorrect at this point) results in the StateMachine/messaging layer becoming stuck in some kind of stateful loop which is only resolved by wiping the node build directories and redeploying. Simply restarting the node results in the flow no longer executing at all. This is a real productivity killer, and so I'm writing this question in the hope and assumption I've missed an obvious trick in how to effectively test/debug flows in such a way which avoids repeatedly re-deploying the nodes.
It would be great if someone could explain how to effectively debug flows; especially flows which are dependent on vault updates and thus wait on a valut update event. I have considered using a subflow, but this would ultimately, (I believe?) not result in quite the functionality required; namely to have a flow triggered when an identified state is consumed by a node. Or maybe it would? Perhaps this issue is due to not using a subFlow??? I look forward to your thoughts anyway!!
Not sure about your specific use case. But in general,
I would do as much unit testing as possible before physically running the nodes and see if the flow works.
Corda provides three levels of unit testing: transaction/ledger DSL, mock network and driver DSL. So if done right, most if not all bugs in the flows should be resolved by the time of runnodes. Actual runnodes mostly just reveal configuration issues.
I'm developing an app for a client and one of his devices (2nd gen iTouch on iOS4) is having issues starting the application. I've run a few allocation/leak tests and I concluded that there isn't anything wrong with my app's code. I noticed that there is an allocation spike at startup and I concluded that it's because of dyld which is dynamically linking the libraries on start up. How would I go about pre-binding the application in xcode4?
OS X forum seemed to be extremely non informative in that they assume you'd be able to find it. :/
Any help would be appreciated.
Thanks!
(I also wish I could make a new tag for "prebinding")
According to Apple, you shouldn't need to prebind your iOS applications. If you are getting big allocation spikes, I'm guessing it's due to your app's architecture rather than the underlying OS itself.
The memory allocated by dyld should pale in insignificance compared to even the most basic allocations made by the earliest stages of the runtime. The Objective-C runtime and other system frameworks/libraries allocate a bunch of internal structures that are required for things to work correctly.
For instance, a quick test of an app that does nothing in main but make one call to NSLog(#"FooBar"); and then sleep (i.e. never even spools up UIApplication) performed 373 allocations for a total of 52K living.
To take it a step further, if you actually start up UIKit, like this...
UIApplicationMain(argc, argv, nil, NSStringFromClass([MyAppDelegate class]));
... you'll see ~600K in ~7800 living allocations once the app reaches quiescent state. This is all unavoidable stuff. No amount of prebinding will save you this. I suggest not worrying about it.
If you're seeing orders of magnitude more memory being allocated then, as Nik Reiman said, it's your application. At the end of the day, the memory allocated by the dynamic linker is totally insignificant.
I've programmed in a number of languages, but I am not aware of deadlocks in my code.
I took this to mean it doesn't happen.
Does this happen frequently (in programming, not in the databases) enough that I should be concerned about it?
Deadlocks could arise if two conditions are true: you have mutilple theads, and they contend for more than one resource.
Do you write multi-threaded code? You might do this explicitly by starting your own threads, or you might work in a framework where the threads are created out of your sight, and so you're running in more than one thread without you seeing that in your code.
An example: the Java Servlet API. You write a servlet or JSP. You deploy to the app server. Several users hit your web site, and hence your servlet. The server will likely have a thread per user.
Now consider what happens if in servicing the requests you want to aquire some resources:
if ( user Is Important ){
getResourceA();
}
getResourceB();
if (today is Thursday ) {
getResourceA();
}
// some more code
releaseResourceA();
releaseResoruceB();
In the contrived example above, think about what might happen on a Thursday when an important user's request arrives, and more or less simultaneously an unimportant user's request arrives.
The important user's thread gets Resoruce A and wants B. The less important user gets resource B and wants A. Neither will let go of the resource that they already own ... deadlock.
This can actually happen quite easily if you are writing code that explicitly uses synchronization. Most commonly I see it happen when using databases, and fortunately databases usually have deadlock detection so we can find out what error we made.
Defense against deadlock:
Acquire resources in a well defined order. In the aboce example, if resource A was always obtained before resource B no deadlock would occur.
If possible use timeouts, so that you don't wait indefinately for a resource. This will allow you to detect contention and apply defense 1.
It would be very hard to give an idea of how often it happens in reality (in production code? in development?) and that wouldn't really give a good idea of how much code is vulnerable to it anyway. (Quite often a deadlock will only occur in very specific situations.)
I've seen a few occurrences, although the most recent one I saw was in an Oracle driver (not in the database at all) due to a finalizer running at the same time as another thread trying to grab a connection. Fortunately I found another bug which let me avoid the finalizer running in the first place...
Basically deadlock is almost always due to trying to acquire one lock (B) whilst holding another one (A) while another thread does exactly the same thing the other way round. If one thread is waiting for B to be released, and the thread holding B is waiting for A to be released, neither is willing to let the other proceed.
Make sure you always acquire locks in the same order (and release them in the reverse order) and you should be able to avoid deadlock in most cases.
There are some odd cases where you don't directly have two locks, but it's the same basic principle. For example, in .NET you might use Control.Invoke from a worker thread in order to update the UI on the UI thread. Now Invoke waits until the update has been processed before continuing. Suppose your background thread holds a lock with the update requires... again, the worker thread is waiting for the UI thread, but the UI thread can't proceed because the worker thread holds the lock. Deadlock again.
This is the sort of pattern to watch out for. If you make sure you only lock where you need to, lock for as short a period as you can get away with, and document the thread safety and locking policies of all your code, you should be able to avoid deadlock. Like all threading topics, however, it's easier said than done.
If you get a chance take a look at first few chapters in Java Concurrency in Practice.
Deadlocks can occur in any concurrent programming situation, so it depends how much concurrency you deal with. Several examples of concurrent programming are: multi-process, multi-thread, and libraries introducing multi-thread. UI frameworks, event handling (such as timer event) could be implemented as threads. Web frameworks could spawn threads to handle multiple web requests simultaneously. With multicore CPUs you might see more concurrent situations visibly than before.
If A is waiting for B, and B is waiting for A, the circular wait causes the deadlock. So, it also depends on the type of code you write as well. If you use distributed transactions, you can easily cause that type of scenario. Without distributed transactions, you risk bank accounts from stealing money.
All depends on what you are coding. Traditional single threaded applications that do not use locking. Not really.
Multi-threaded code with multiple locks is what will cause deadlocks.
I just finished refactoring code that used seven different locks without proper exception handling. That had numerous deadlock issues.
A common cause of deadlocks is when you have different threads (or processes) acquire a set of resources in different order.
E.g. if you have some resource A and B, if thread 1 acquires A and then B, and thread 2 acquires B and then A, then this is a deadlock waiting to happen.
There's a simple solution to this problem: have all your threads always acquire resources in the same order. E.g. if all your threads acquire A and B in that order, you will avoid deadlock.
A deadlock is a situation with two processes are dependent on each other - one cannot finish before the other. Therefore, you will likely only have a deadlock in your code if you are running multiple code flows at any one time.
Developing a multi-threaded application means you need to consider deadlocks. A single-threaded application is unlikely to have deadlocks - but not impossible, the obvious example being that you may be using a DB which is subject to deadlocking.
Deadlocks are hard to find and very uncomfortable to remove.
How can I find error sources for deadlocks in my code? Are there any "deadlock patterns"?
In my special case, it deals with databases, but this question is open for every deadlock.
Update: This recent MSDN article, Tools And Techniques to Identify Concurrency Issues, might also be of interest
Stephen Toub in the MSDN article Deadlock monitor states the following four conditions necessary for deadlocks to occur:
A limited number of a particular resource. In the case of a monitor in C# (what you use when you employ the lock keyword), this limited number is one, since a monitor is a mutual-exclusion lock (meaning only one thread can own a monitor at a time).
The ability to hold one resource and request another. In C#, this is akin to locking on one object and then locking on another before releasing the first lock, for example:
lock(a)
{
...
lock(b)
{
...
}
}
No preemption capability. In C#, this means that one thread can't force another thread to release a lock.
A circular wait condition. This means that there is a cycle of threads, each of which is waiting for the next to release a resource before it can continue.
He goes on to explain that the way to avoid deadlocks is to avoid (or thwart) condition four.
Joe Duffy discusses several techniques
for avoiding and detecting deadlocks,
including one known as lock leveling.
In lock leveling, locks are assigned
numerical values, and threads must
only acquire locks that have higher
numbers than locks they have already
acquired. This prevents the
possibility of a cycle. It's also
frequently difficult to do well in a
typical software application today,
and a failure to follow lock leveling
on every lock acquisition invites
deadlock.
The classic deadlock scenario is A is holding lock X and wants to acquire lock Y, while B is holding lock Y and wants to acquire lock X. Since neither can complete what they are trying to do both will end up waiting forever (unless timeouts are used).
In this case a deadlock can be avoided if A and B acquire the locks in the same order.
No deadlock patterns to my knowledge (and 12 years of writing heavily multithreaded trading applications).. But the TimedLock class has been of great help in finding deadlocks that exist in code without massive rework.
http://www.randomtree.org/eric/techblog/archives/2004/10/multithreading_is_hard.html
basically, (in dotnet/c#) you search/replace all your "lock(xxx)" statements with "using TimedLock.Lock(xxx)"
If a deadlock is ever detected (lock unable to be obtained within the specified timeout, defaults to 10 seconds), then an exception is thrown. My local version also immediately logs the stacktrace. Walk up the stacktrace (preferably debug build with line numbers) and you'll immediately see what locks were held at the point of failure, and which one it was attempting to get.
In dotnet 1.1, in a deadlock situation as described, as luck would have it all the threads which were locked would throw the exception at the same time. So you'd get 2+ stacktraces, and all the information necessary to fix the problem. (2.0+ may have changed the threading model internally enough to not be this lucky, I'm not sure)
Making sure all transactions affect tables in the same order is the key to avoiding the most common of deadlocks.
For example:
Transaction A
UPDATE Table A SET Foo = 'Bar'
UPDATE Table B SET Bar = 'Foo'
Transaction B
UPDATE Table B SET Bar = 'Foo'
UPDATE Table A SET Foo = 'Bar'
This is extremely likely to result in a deadlock as Transaction A gets a lock on Table A, Transaction B gets a lock on table B, therefore neither of them get a lock for their second command until the other has finished.
All other forms of deadlocks are generally caused through high intensity use and SQL Server deadlocking internally whilst allocated resources.
Yes - deadlocks occur when processes try to acquire resources in random order. If all your processes try to acquire the same resources in the same order, the possibilities for deadlocks are greatly reduced, if not eliminated.
Of course, this is not always easy to arrange...
The most common (according to my unscientific observations) DB deadlock scenario is very simple:
Two processes read something (a DB record for example), both acquire a shared lock on the associated resource (usually a DB page),
Both try to make an update, trying to upgrade their locks to exclusive ones - voila, deadlock.
This can be avoided by specifying the "FOR UPDATE" clause (or similar, depending on your particular RDBMS) if the read is to be followed by an update. This way the process gets the exclusive lock from the start, making the above scenario impossible.
I recommend reading this article by Herb Sutter. It explains the reasons behind deadlocking issues and puts forward a framework in this article to tackle this problem.
The typical scenario are mismatched update plans (tables not always updated in the same order). However it is not unusual to have deadlocks when under high processing volume.
I tend to accept deadlocks as a fact of life, it will happen one day or another so I have my DAL prepared to handle and retry a deadlocked operation.
A condition that occure whene two process are each waiting for the othere to complete befoure preceding.the result is both procedure is hang.
its most comonelly multitasking and clint/server.
Deadlock occurs mainly when there are multiple dependent locks exist. In a thread and another thread tries to lock the mutex in reverse order occurs. One should pay attention to use a mutex to avoid deadlocks.
Be sure to complete the operation after releasing the lock. If you have multiple locks, such as access order is ABC, releasing order should also be ABC.
In my last project I faced a problem with deadlocks in an sql Server Database. The problem in finding the reason was, that my software and a third party software are using the same Database and are working on the same tables. It was very hard to find out, what causes the deadlocks. I ended up writing an sql-query to find out which processes an which sql-Statements are causing the deadlocks. You can find that statement here: Deadlocks on SQL-Server
To avoid the deadlock there is a algorithm called Banker's algorithm.
This one also provides helpful information to avoid deadlock.