The Flash Builder (4.6) profiler shows a current memory usage of about 24000k (so 24MB if I'm not mistaken) for my app, which simply cannot be.
The live object view, however, shows for example that the object with the highest memory consumption, 80 live instances, consumes 119000bytes, or 10% of the overall memory consumption.
That doesn't really sum up to 24MB now, does it? Can someone explain to me how the profiler calculates the memory consumption?
With the Profiler, there are filters in place by default and that includes hiding certain Flash and Flex classes from the display. Be sure that you've removed all filters.
As stated in the comments on the main question, in this case you had not removed the filter for flash.display; meaning that those classes were not displayed in your class list, yet their memory usage were still calculated in the memory usage.
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I have application, have set around 8GB of Max heap memory, it does lots of message processing. when I am taking jmap -heap for my application, it shows me very huge MaxMetaspaceSize memory, something like below,
MaxMetaspaceSize = 17592186044415 MB
If I have to put the limit on MaxMetaspaceSize, what could be optimal value for that?
Note* - I have read on pros and cons of putting limit of MaxMetaspaceSize
Measure how much metaspace your program needs once it has settled into a steady state. Add some safety margin, then configure that as your max.
Should your program change behavior, e.g. load additional classes without unloading old ones you'll be notified about that through OOMEs.
it shows me very huge MaxMetaspaceSize memory
Note that that is just the upper limit enforced by the JVM, not the actual size.
Im trying to work around an issue which has been bugging me for a while. In a nutshell: on which basis should one assign a max heap space for resource-hogging application and is there a downside for tit being too large?
I have an application used to visualize huge medical datas, which can eat up to several gigabytes of memory if several imaging volumes are opened size by side. Caching the data to be viewed is essential for fluent workflow. The software is supported with windows workstations and is started with a bootloader, which assigns the heap size and launches the main application. The actual memory needed by main application is directly proportional to the data being viewed and cannot be determined by the bootloader, because it would require reading the data, which would, ultimately, consume too much time.
So, to ensure that the JVM has enough memory during launch we set up xmx as large as we dare based, by current design, on the max physical memory of the workstation. However, is there any downside to this? I've read (from a post from 2008) that it is possible for native processes to hog up excess heap space, which can lead to memory errors during runtime. Should I maybe also sniff for free virtualmemory or paging file size prior to assigning heap space? How would you deal with this situation?
Oh, and this is my first post to these forums. Nice to meet you all and be gentle! :)
Update:
Thanks for all the answers. I'm not sure if I put my words right, but my problem rose from the fact that I have zero knowledge of the hardware this software will be run on but would, nevertheless, like to assign as much heap space for the software as possible.
I came to a solution of assigning a heap of 70% of physical memory IF there is sufficient amount of virtual memory available - less otherwise.
You can have heap sizes of around 28 GB with little impact on performance esp if you have large objects. (lots of small objects can impact GC pause times)
Heap sizes of 100 GB are possible but have down sides, mostly because they can have high pause times. If you use Azul Zing, it can handle much larger heap sizes significantly more gracefully.
The main limitation is the size of your memory. If you heap exceeds that, your application and your computer will run very slower/be unusable.
A standard way around these issues with mapping software (which has to be able to map the whole world for example) is it break your images into tiles. This way you only display the image which is one the screen (or portions which are on the screen) If you need to be able to zoom in and out you might need to store data at two to four levels of scale. Using this approach you can view a map of the whole world on your phone.
Best to not set JVM max memory to greater than 60-70% of workstation memory, in some cases even lower, for two main reasons. First, what the JVM consumes on the physical machine can be 20% or more greater than heap, due to GC mechanics. Second, the representation of a particular data entity in the JVM heap may not be the only physical copy of that entity in the machine's RAM, as the OS has caches and buffers and so forth around the various IO devices from which it grabs these objects.
In our app running on Jdk 8 we use VisualVM to track the usage of loaded classes and the usage of the metaspace.
At some point in time while our app is running we see that the number of loaded classes don't increase any more but the metaspace still increases in it's size while our program is running. So what else apart from classes is stored in metaspace, that could cause that?
While your program is running, some parts of your code may be determined as "hot" by HotSpot's JIT compiler. This will cause those parts to be transformed/compiled to native code, and also some other code may be inlined into it. This native code representation has to go somewhere, and it goes into the same place as other class metadata - the Metaspace.
It explains continuous growth you're seeing: hot parts are determined over time using a simple metric of how much times did that piece of code got executed. Over time more and more code pieces will be JIT'ed as they'll hit threshold set by -XX:CompileThreshold (defaults to 10000)
i am not sure but hier (http://java.dzone.com/articles/java-8-permgen-metaspace) i fund this
Garbage collection of the dead classes and classloaders is triggered once the class metadata usage reaches the “MaxMetaspaceSize”.
maybe is this the cause for increasing metaspace size.
I have this app written in VB.Net with winforms that shows some stats and pictures on a bigscreen monitor. I also monitor the memory usage of sad app by using this.
Process.WorkingSet64
I know windows does not always report the correct usage but I just wanted to know if I didn't have any little memory leaks which I had but are solved now. But the first week the memory usage was around 100MB and the second week the memory usage showed around 50MB.
So why did it all of a sudden drop while still running the exact same code?
I can hardly imagine that the garbage collector kicked in this late since the app refreshes every 10 seconds and it has ample time in between those periods to do it's thing.
Or perhaps there is just better way to get memory usage for a process that is more reliable.
Process.WrokingSet64 doesn't report the memory usage, it omits the memory that is swapped to disk:
The value returned by this property represents the current size of working set memory used by the process. The working set of a process is the set of memory pages currently visible to the process in physical RAM memory. These pages are resident and available for an application to use without triggering a page fault. (MSDN)
Even if your system was never low on free memory, you may have minimized the application window, which caused Windows to trim its working set.
If you want to look for memory leaks you should probably use Process.PrivateMemorySize64 instead. Your shared memory is going to contain just executable code and it's going to remain more or less constant throughout the life of the process, so you should focus on the private memory.
just as the topic suggests I've come across a slight issue with boost::serialization when serializing a huge amount of data to a file. The problem consists of the memory footprint of the serialization part of the application taking around 3 to 3.5 times the memory of my objects being serialized.
It is important to note that the data structure I have is a three dimensional vector of base class pointers and a pointer to that structure. Like this:
using namespace std;
vector<vector<vector<MyBase*> > >* data;
This is later serialised with a code analog to this one:
ar & BOOST_SERIALIZATION_NVP(data);
boost/serialization/vector.hpp is included.
Classes being serialised all inherit from "MyBase".
Now, since the start of my project I've used different archives for serialization from typical binary_archive, text, xml and finally polymorphic binary/xml/text. Every single one of these acts exactly the same way.
Typically this wouldn't be a problem if I had to serialize small amounts of data but the number of classes I have are in the milions (ideally around 10 milion) and the memory usage as I've been able to test it shows consistently that the memory allocated by boost::serialization part of the code is around 2/3 of the application whole memory footprint while writing the file.
This amounts to around 13.5 GB of RAM taken for 4 milion objects where the objects themselves take 4.2GB. Now this is as far as I've been able to take my code since I don't have access to a machine with more than 8GB of physical RAM. I should also note that this is a 64bit application being run on a Windows 7 professional x64 edition but the situation is similar on an Ubuntu box.
Anyone has any idea how I would go about troubleshooting this as it is unacceptable for me to have such high memory requirements for an application that will not use as much memory while running as it does while serializing.
Deserialization isn't as bad, as it allocates around 1.5 times the needed memory. This is something I could live with.
Tried turning tracking off with boost::archive::archive_flags::no_tracking but it acts exactly the same.
Anyone have any idea what I should do?
Using valgrind I found that the main reason of memory consumption is a map inside the library to track pointers. If you are certain that you do not need pointer tracking ( it means you are sure that there is no pointer aliasing) disable tracking. You can find here the main concepts of disable tracking. In short you must do something like this:
BOOST_CLASS_TRACKING(vector<vector<vector<MyBase*> > >, boost::serialization::track_never)
In my question I wrote a version of this macro that you could disable tracking of a template class. This must have a significant impact on your memory consumption.
Also notice that there are pointers inside any containers If you want tracking never you must disable tracking of them too. Currently I could not find any way to do this properly.