Showing posts with label jvm. Show all posts
Showing posts with label jvm. Show all posts

Thursday, February 6, 2014

Run time data areas - JVM Memory model

I love to share an excellent article from Point software, It's just a brilliant composition and easy to understand with diagrams.

 Every developer gets once confronted by Java memory questions like: What size should I define for the Heap space? An OutOfMemoryError covers which part of the runtime data area? In the Heap, PermGen, or Thread? And how do I solve it?

Java Memory Model

The Java memory model is specified in the latest JVM specification, Java SE 7 Edition, and mainly in the chapters “2.5 Runtime Data Areas” and “2.6 Frames”. In a nutshell primitive, object and class data are stored in 3 different memory areas: heap space, method area and native are.
The heap space holds object data, the method area holds class code, and the native area holds references to the code and object data.
The method area is also known as the permanent generation space (PermGen). All class data are loaded into this memory space. This includes the field and method data and the code for the methods and constructors.
[UPDATE]
Oracle has planned in JDK 7 to completely remove the PermGen space from the JVM. Reason is the consolidation of HotSpot and JRockit. As a result the method area will be part of the operating system’s native heap.
All objects being instantiated during runtime are stored in the heap space. The heap space again is divided into several parts: eden, survivor, and old generation Space.
Method executions are within a thread. Local variables of primitive types and references are stored here. The references for example points to Objects like String stored in the Heap space. Here is a video demonstrating the interaction between a stack and the heap.
For a better understanding let’s have a look at another example code:
The data are then stored like this:
With the JConsole tool it is possible to view the memory allocations in the heap, the number of threads and loaded classes of a running Java application (e.g. Eclipse):

Java Memory Architecture

There is an excellent white paper about Memory Management in the Java
HotSpot™ Virtual Machine. It describes about the automatic memory management handle using garbage collection.
The Java memory architecture consists of the following parts:

Heap memory

Since objects are stored in the heap part it is worth to have a closer look. The heap space itself is again separated into several spaces:
  • Young generation with eden and survivor space
  • Old Generation with tenured space
Each space harbors objects with different life cycles:
  • New/short-term objects are instantiated in the eden space.
  • Survived/mid-term objects are copied from the eden space to the survivor space.
  • Tenured/long-term objects are copied from the survivor to the old generation space.
By separating objects by their life time allows a shorter time consumption of the minor garbage collection and in return there is more cpu time for the application.
The reason is that in Java – unlike C – memory is freed (by destroying objects) automatically by two different garbage collectors: a minor and major garbage collection.
Instead of validating all objects in the heap – whether it can be destroyed or not – the minor garbage collector marks undestroyed objects with a garbage count. After a certain count the object is move to the old generation space.
A more detailed blog of the garbage collection will be discussed in another blog. For now it is sufficient to know that there are two garbage collectors.

OutOfMemoryError – but where?

Having this memory architecture in mind also helps to understand the different OutOfMemoryErrors like:
  1. Exception in thread “main”: java.lang.OutOfMemoryError: Java heap space
    Reason: an object could not be allocated into the heap space.

  3. Exception in thread “main”: java.lang.OutOfMemoryError: PermGen space
    Reason: classes and methods could not be loaded into the PermGen space. This occurs when an application requires a lot of classes e.g. in various 3rd party libraries.

  5. Exception in thread “main”: java.lang.OutOfMemoryError: Requested array size exceeds VM limit
    Reason: this occurs when an arrays is created larger than the heap size.

  7. Exception in thread “main”: java.lang.OutOfMemoryError: request bytes for . Out of swap space?
    Reason: this occurs when an allocation from the native heap failed and might be close to its limit. The indicates the source of the module where this error occurs.

  9. Exception in thread “main”: java.lang.OutOfMemoryError: (Native method)
    Reason: this error indicates that the problem originates from a native call rather than in the JVM.

Useful Links

Resources:
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Friday, October 18, 2013

JVM: Permgen is a non-heap


In Oracle's JVM, the permanent generation is not part of the heap. It's a separate space for class definitions and related data. In Java 6 and earlier, interned strings were also stored in the permanent generation. In Java 7, interned strings are stored in the main object heap.


From above link, we can understand these terms:

Eden Space (heap): The pool from which memory is initially allocated for most objects.

Survivor Space (heap): The pool containing objects that have survived the garbage collection of the Eden space.

Tenured Generation (heap): The pool containing objects that have existed for some time in the survivor space.

Permanent Generation (non-heap): The pool containing all the reflective data of the virtual machine itself, such as class and method objects. With Java VMs that use class data sharing, this generation is divided into read-only and read-write areas.

Code Cache (non-heap): The HotSpot Java VM also includes a code cache, containing memory that is used for compilation and storage of native code.



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Troubleshooting Memory Leaks

http://docs.oracle.com/javase/7/docs/webnotes/tsg/TSG-VM/html/memleaks.html


Meaning of OutOfMemoryError

One common indication of a memory leak is the java.lang.OutOfMemoryError error. This error is thrown when there is insufficient space to allocate an object in the Java heap or in a particular area of the heap. The garbage collector cannot make any further space available to accommodate a new object, and the heap cannot be expanded further.
When the java.lang.OutOfMemoryError error is thrown, a stack trace is printed also.
A java.lang.OutOfMemoryError can also be thrown by native library code when a native allocation cannot be satisfied, for example, if swap space is low.
An early step to diagnose an OutOfMemoryError is to determine what the error means. Does it mean that the Java heap is full, or does it mean that the native heap is full? To help you answer this question, the following subsections explain some of the possible error messages, with reference to the detail part of the message:
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Sizing the Java heap


Size your Java heap so that your application runs with a minimum heap usage of 40%, and a maximum heap usage of 70%.
Introduction
An incorrectly sized Java heap can lead to OutOfMemoryError exceptions or to a reduction in the performance of the Java application.
If the Java heap is smaller than the memory requirements of the application, OutOfMemoryError exceptions are generated because of Java heap exhaustion. If the Java heap is slightly larger than the requirements of the application, garbage collection runs very frequently and affects the performance of the application.
You must correctly size the Java heap based on the real memory usage of the Java application.
Sizing the heap based on application memory utilization
Set the maximum Java heap size, using the -Xmx command-line option, to a value that allows the application to run with 70% occupancy of the Java heap.
The Java heap occupancy often varies over time as the load applied to the application varies. For applications where occupancy varies, set the maximum Java heap size so that there is 70% occupancy at the highest point, and set the minimum heap size, using the -Xms command line option, so that the Java heap is 40% occupied at its lowest memory usage. If these values are set, the Java memory management algortihms can modify the heap size over time according to the application load, while maintaining usage in the optimal area of between 40% and 70% occupancy.
Maximum possible heap size and maximum recommended heap size (32-bit Java)
The memory space provided by the operating system to the Java process varies by operating system and is used for two separate memory areas: the Java heap and the native heap. Because a finite amount of memory is provided by the operating system, and that memory is shared between the two heaps, the larger the amount of memory that is allocated to the Java heap, using the -Xmx setting, the smaller the native heap becomes. If the native heap is too small, an OutOfMemoryError occurs when it is exhausted, in the same way as for the Java heap.
PlatformAdditional optionsMaximum heap sizeRecommended heap size limitAdditional notes
AIXNone3.25 GB2.5 GBMaximum heap size is not required to be, but should ideally be, a multiple of 256 MB
LinuxNone2 GB1.5 GB
Hugemem Kernel3 GB2.5 GB
WindowsNone1.8 GB1.5 GB
/3GB1.8 GB1.8 GB
The table shows both the maximum Java heap possible and a recommended limit for the maximum Java heap size setting. The use of a maximum Java heap setting up to the recommended limit is unlikely to reduce the native heap size to a point that the native heap is exhausted.
Before setting a Java heap size greater than the recommended limit, you must understand the level of usage of the native heap, to ensure that the native heap does not become exhausted.
If you are running an application that has particularly high numbers of threads or makes heavy use of Java Native Interface (JNI) code, for example, Type 2 JDBC drivers, you might experience problems relating to the native heap with smaller Java heap sizes than the recommended limit.
Maximum possible heap size and maximum recommended heap size (64-bit Java)
When running 64-bit Java, the memory space provided by the operating system to the Java process is very large. You can therefore assume that no limit is imposed on the maximum size of the Java heap because of the contention of memory resource between the Java heap and the native heap.
Java heap size and amount of physical memory available
It is important to have more physical memory than is required by all of the processes on the machine combined to prevent paging or swapping. Paging reduces the performance of the system and affects the performance of the Java memory management system.
When increasing the Java heap size, ensure that enough unused physical memory is available on the machine to cover the increase. If sufficient physical memory is not available, either install additional memory or take into account the effect on overall performance that occurs.
This requirement does not apply to operating systems running on System z.

Size your Java heap so that your application runs with a minimum heap usage of 40%, and a maximum heap usage of 70%.



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Understanding 32-bit vs. 64-bit systems with Java Heap

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Thursday, August 1, 2013

Heap Memory Analysis # SHALLOW HEAP

HOW MUCH MEMORY DO I NEED  – WHAT IS SHALLOW HEAP?

In the first post we pushed a whole lot of complexity away by stating that calculating shallow heap size is easy – it consists of only the heap occupied by the object itself. But how do you calculate how much memory does the object “itself” require?  Apparently there is a formula for it:

Shallow Heap Size = [reference to the class definition] + space for superclass fields + space for instance fields + [alignment]

Does not seem too helpful, eh? Let’s try to apply the formula using the following sample code:
class X {
   int a;
   byte b;
   java.lang.Integer c = new java.lang.Integer();
}
class Y extends X {
   java.util.List d;
   java.util.Date e;
}
Now, the question we strive to answer is – how much shallow heap size does an instance of a Y require? Lets start calculating it, assuming that we are on a 32-bit x86 architecture:
As a starting point – Y is a subclass of X, so its size includes “something” from the superclass. Thus, before calculating the size of Y, we look into calculating the shallow size of X.
Jumping into the calculations on X, first 8 bytes are used to refer its class definition. This reference is always present in all Java objects and is used by JVM to define the memory layout of the following state. It also has three instance variables – an int, an Integer and a byte. Those instance variables require heap as follows:

  • a byte is what it is supposed to be. 1 byte in a memory.
  • an int in our 32bit architecture requires 4 bytes.
  • a reference to the Integer requires also 4 bytes. Note that when calculating retained heap, we should also take into account the size of a primitive wrapped into the Integer object, but as we are calculating shallow heap here, we only use the reference size of 4 bytes in our calculations.

So – is that it? Shallow heap of X = 8 bytes from reference to the class definition + 1 byte (the byte) + 4 bytes (the int) + 4 bytes (reference to the Integer) = 17 bytes? In fact – no. What now comes into play is called alignment (also called padding). It means that the JVM allocates the memory in multiples of 8 bytes, so instead of 17 bytes we would allocate 24 bytes if we would create an instance of X.

 If you could follow us until here, good, but now we try to get things even more complex. We are NOT creating an instance of X, but an instance of Y. What this means is – we can deduct the 8 bytes from the reference to the class definition and the alignment. It might not be too obvious at first place but – did you note that while calculating the shallow size of X we did not take into account that it also extends java.lang.Object as all classes do even if you do not explicitly state it in your source code? We do not have to take into account the header sizes of superclasses, because JVM is smart enough to check it from the class definitions itself, instead of having to copy it into the object headers all the time.

 The same goes for alignment – when creating an object you only align once, not at the boundaries of superclass/subclass definitions. So we are safe to say that when creating a subclass to X you will only inherit 9 bytes from the instance variables.

 Finally we can jump to the initial task and start calculating the size of Y. As we saw, we have already lost 9 bytes to the superclass fields. Let’s see what will be added when we actually construct an instance of Y.

  • Y’s headers referring to its class definition consume 8 bytes. The same as with previous ones.
  • The Date is a reference to an object. 4 bytes. Easy.
  • The List is a reference to a collection. Again 4 bytes. Trivial.

So in addition to the 9 bytes from the superclass we have 8 bytes from the header, 2×4 bytes from the two references (the List and the Date). The total shallow size for the instance of Y would be 25 bytes, which get aligned to 32.


While writing this article, the following online resources were used for inspiration:
- See more at: http://plumbr.eu/blog/how-much-memory-do-i-need-part-2-what-is-shallow-heap#sthash.LThS3oJX.dpuf

 PS: I have added this topic here for my reference, you can find many more interesting articles by Nikita Salnikov-Tarnovski @ plumber.eu
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Heap Memory Analysis # RETAINED HEAP

HOW MUCH MEMORY DO I NEED  – WHAT IS RETAINED HEAP?

How much memory will I need? This is a question you might have asked yourself (or others) when building a solution, creating a data structure or choosing an algorithm. Will this graph of mine fit in my 3G heap if it contains 1,000,000 edges and I use a HashMap to store it? Can I use the standard Collections API while building my custom caching solution.

Apparently, the answer to the simple question is a bit more complex. In this post we’ll take a first peek at it and see how deep the rabbit hole actually is.

The answer to the question in the headline comes in several parts. At first we need to understand whether you are interested in shallow or retained heap sizes.

The shallow heap is easy – it consists of only the heap occupied by the object itself. There are some nuances to how to calculate it, but for the scope of this article we leave it as is. Stay tuned for future posts on the same topic.

The retained heap is in many ways more interesting. Only rarely are you interested in the shallow heap, in most cases your actual question can be translated to “If I remove this object from the memory, how much memory can now be freed by the garbage collector”.

Now, as we all remember, all Java garbage collection (GC) algorithms follow this logic:
  1. There are some objects which are considered “important” by the GC. These are called GC roots and are (almost) never discarded. They are, for example, currently executing method’s local variables and input parameters, application threads, references from native code and similar “global” objects.
  2. Any objects referenced from those GC roots are assumed to be in use and hence not discarded by the GC. One object can reference another in different ways in Java, in the most common case an object A is stored in a field of an object B. In such case we say  “B references A”.
  3. The process is repeated until all objects that can be transitively reached from GC roots are visited and marked as “in use”.
  4. Everything else is unused and can be thrown away.
Now to illustrate how to calculate the retained heap, let’s follow the aforementioned algorithm with the following example objects:
Calculating Retained Heap Size 
To simplify the sample, let’s estimate that all the objects O1-O4 have the shallow heap of 1024B = 1kB. Lets start calculating the retained sizes of those objects.
  • O4 has no references to other objects, so its retained size is equal to its shallow size of 1kB.
  • O3 has a reference to O4. Garbage collecting O3 would thus mean O4 would also be eligible for garbage collection and so we can say that O3 retained heap is 2kB.
  • O2 has a reference to O3. But it is now important to note that removing the pointer from O2 to O3 does not make O3 eligible for GC, as O1 still has got a pointer to it. So O2 retained heap is only 1kB.
  • O1 on the other hand is the object keeping all the references in this small graph, so if we would remove O1, everything on this graph would be garbage collected. So O1 retained heap is 4kB.
Which implications does this have in practice? In fact, understanding the differences between shallow and retained heap sizes makes it possible to work with tools such as memory profilers and heap dump analyzers – for example digging into Eclipse MAT might prove to be impossible if you don’t know how to distinguish these two types of heap size measurements.

Full disclosure: this post was inspired by Patrick Dubroy’s talk on Google I/O, which you can watch in full length here.


Resources at: http://plumbr.eu/blog/how-much-memory-what-is-retained-heap#sthash.e5Swh4xR.dpuf

PS: I have added this article here for my reference, you can find many more interesting articles by Nikita Salnikov-Tarnovski @ plumber.eu
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Heap Memory Analysis # Shallow heap vs Retained Heap

Shallow heap
The amount of memory that is consumed by one object. An object requires different amounts of memory depending on the operating system architecture. For example, 32 bits or 64 bits for a reference, 4 bytes for an integer, or 8 bytes for an object of type "Long". Depending on the heap dump format, the size might be adjusted to provide a more realistic consumption of the JVM.

Retained Set
One or more objects plus any objects that are referenced, directly or indirectly, only from those original objects. The retained set is the set of objects that would be removed by garbage collection when an object, or multiple objects, is garbage collected.

Retained set of X is the set of objects which would be removed by GC when X is garbage collected.

Retained heap of X is the sum of shallow sizes of all objects in the retained set of X, i.e. memory kept alive by X.

Retained heap, or retained size
The total heap size of all the objects in the retained set. This value is the amount of memory that is consumed by all the objects that are kept alive by the objects at the root of the retained set

Generally speaking, shallow heap of an object is its size in the heap and retained size of the same object is the amount of heap memory that will be freed when the object is garbage collected.

The retained set for a leading set of objects, such as all objects of a particular class or all objects of all classes loaded by a particular class loader or simply a bunch of arbitrary objects, is the set of objects that is released if all objects of that leading set become unaccessible. The retained set includes these objects as well as all other objects only accessible through these objects. The retained size is the total heap size of all objects contained in the retained set.


Example object graph



Example, if you remove C, then C, D, E, F, G, H are eligible for garbage collection.

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Thursday, May 9, 2013

OutOfMemoryError: unable to create new native thread

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