Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

How to deal with "java.lang.OutOfMemoryError: Java heap space" error?

I am writing a client-side Swing application (graphical font designer) on Java 5. Recently, I am running into java.lang.OutOfMemoryError: Java heap space error because I am not being conservative on memory usage. The user can open unlimited number of files, and the program keeps the opened objects in the memory. After a quick research I found Ergonomics in the 5.0 Java Virtual Machine and others saying on Windows machine the JVM defaults max heap size as 64MB.

Given this situation, how should I deal with this constraint?

I could increase the max heap size using command line option to java, but that would require figuring out available RAM and writing some launching program or script. Besides, increasing to some finite max does not ultimately get rid of the issue.

I could rewrite some of my code to persist objects to file system frequently (using database is the same thing) to free up the memory. It could work, but it's probably a lot work too.

If you could point me to details of above ideas or some alternatives like automatic virtual memory, extending heap size dynamically, that will be great.

like image 539
Eugene Yokota Avatar asked Sep 01 '08 01:09

Eugene Yokota


People also ask

What causes Java Lang OutOfMemoryError Java heap space?

lang. OutOfMemoryError exception. Usually, this error is thrown when there is insufficient space to allocate an object in the Java heap. In this case, The garbage collector cannot make space available to accommodate a new object, and the heap cannot be expanded further.

What is Java heap space error?

Error 1 – Java heap space: This error arises due to the applications that make excessive use of finalizers. If a class has a finalize method, objects of that type do not have their space reclaimed at garbage collection time. Instead, after garbage collection, the objects are queued for finalization, which occurs later.

How do you solve heap memory problems?

There are several ways to eliminate a heap memory issue: Increase the maximum amount of heap available to the VM using the -Xmx VM argument. Use partitioning to distribute the data over additional machines. Overflow or expire the region data to reduce the heap memory footprint of the regions.


1 Answers

Ultimately you always have a finite max of heap to use no matter what platform you are running on. In Windows 32 bit this is around 2GB (not specifically heap but total amount of memory per process). It just happens that Java chooses to make the default smaller (presumably so that the programmer can't create programs that have runaway memory allocation without running into this problem and having to examine exactly what they are doing).

So this given there are several approaches you could take to either determine what amount of memory you need or to reduce the amount of memory you are using. One common mistake with garbage collected languages such as Java or C# is to keep around references to objects that you no longer are using, or allocating many objects when you could reuse them instead. As long as objects have a reference to them they will continue to use heap space as the garbage collector will not delete them.

In this case you can use a Java memory profiler to determine what methods in your program are allocating large number of objects and then determine if there is a way to make sure they are no longer referenced, or to not allocate them in the first place. One option which I have used in the past is "JMP" http://www.khelekore.org/jmp/.

If you determine that you are allocating these objects for a reason and you need to keep around references (depending on what you are doing this might be the case), you will just need to increase the max heap size when you start the program. However, once you do the memory profiling and understand how your objects are getting allocated you should have a better idea about how much memory you need.

In general if you can't guarantee that your program will run in some finite amount of memory (perhaps depending on input size) you will always run into this problem. Only after exhausting all of this will you need to look into caching objects out to disk etc. At this point you should have a very good reason to say "I need Xgb of memory" for something and you can't work around it by improving your algorithms or memory allocation patterns. Generally this will only usually be the case for algorithms operating on large datasets (like a database or some scientific analysis program) and then techniques like caching and memory mapped IO become useful.

like image 161
Ben Childs Avatar answered Sep 28 '22 01:09

Ben Childs