This is a very basic question. I will formulate it using C++ and Java, but it's really language-independent.
Consider a well-known problem in C++:
struct Obj
{
boost::shared_ptr<Obj> m_field;
};
{
boost::shared_ptr<Obj> obj1(new Obj);
boost::shared_ptr<Obj> obj2(new Obj);
obj1->m_field = obj2;
obj2->m_field = obj1;
}
This is a memory leak, and everybody knows it :). The solution is also well-known: one should use weak pointers to break the "refcount interlocking". It is also known that this problem cannot be resolved automatically in principle. It's solely programmer's responsibility to resolve it.
But there's a positive thing: a programmer has full control on refcount values. I can pause my program in debugger and examine refcount for obj1, obj2 and understand that there's a problem. I also can set a breakpoint in destructor of an object and observe a destruction moment (or find out that object has not been destroyed).
My question is about Java, C#, ActionScript and other "Garbage Collection" languages. I might be missing something, but in my opinion they
Do not let me examine refcount of objects
Do not let me know when object is destroyed (okay, when object is exposed to GC)
I often hear that these languages just do not allow a programmer to leak a memory and that's why they are great. As far as I understand, they just hide memory management problems and make it hard to solve them.
Finally, the questions themselves:
Java:
public class Obj
{
public Obj m_field;
}
{
Obj obj1 = new Obj();
Obj obj2 = new Obj();
obj1.m_field = obj2;
obj2.m_field = obj1;
}
Is it memory leak?
If yes: how do I detect and fix it?
If no: why?
Managed memory systems are built on the assumption that you don't want to be tracing memory leak issue in the first place. Instead of making them easier to solve you try to make sure they never happen in the first place.
Java does have a lose term for "Memory Leak" which means any growth in memory which could impact your application, but there is never a point that the managed memory cannot clean up all the memory.
JVM don't use reference counting for a number of reasons
it cannot handled circular references as you have observed.
it has significant memory and threading overhead to maintain accurately.
there are much better, simpler ways of handling such situations for managed memory.
While the JLS doesn't ban the use of reference counts, it is not used in any JVM AFAIK.
Instead Java keeps track of a number of root contexts (e.g. each thread stack) and can trace which objects need to be keeps and which can be discarded based on whether those objects are strongly reachable. It also provides the facility for weak references (which are retained as long as the objects are not cleaned up) and soft references (which are not generally cleaned up but can be at the garbage collectors discretion)
AFAIK, Java GC works by starting from a set of well-defined initial references and computing a transitive closure of objects which can be reached from these references. Anything not reachable is "leaked" and can be GC-ed.
Java has a unique memory management strategy. Everything (except a few specific things) are allocated on the heap, and isn't freed until the GC gets to work.
For example:
public class Obj {
public Object example;
public Obj m_field;
}
public static void main(String[] args) {
int lastPrime = 2;
while (true) {
Obj obj1 = new Obj();
Obj obj2 = new Obj();
obj1.example = new Object();
obj1.m_field = obj2;
obj2.m_field = obj1;
int prime = lastPrime++;
while (!isPrime(prime)) {
prime++;
}
lastPrime = prime;
System.out.println("Found a prime: " + prime);
}
}
C handles this situation by requiring you to manually free the memory of both 'obj', and C++ counts references to 'obj' and automatically destroys them when they go out of scope.
Java does not free this memory, at least not at first.
The Java runtime waits a while until it feels like there is too much memory being used. After that the Garbage collector kicks in.
Let's say the java garbage collector decides to clean up after the 10,000th iteration of the outer loop. By this time, 10,000 objects have been created (which would have already been freed in C/C++).
Although there are 10,000 iterations of the outer loop, only the newly created obj1 and obj2 could possibly be referenced by the code.
These are the GC 'roots', which java uses to find all objects which could possibly be referenced. The garbage collector then recursively iterates down the object tree, marking 'example' as active in addiction to the garbage collector roots.
All those other objects are then destroyed by the garbage collector.
This does come with a performance penalty, but this process has been heavily optimized, and isn't significant for most applications.
Unlike in C++, you don't have to worry about reference cycles at all, since only objects reachable from the GC roots will live.
With java applications you do have to worry about memory (Think lists holding onto the objects from all iterations), but it isn't as significant as other languages.
As for debugging: Java's idea of debugging high memory values are using a special 'memory-analyzer' to find out what objects are still on the heap, not worrying about what is referencing what.
The critical difference is that in Java etc you are not involved in the disposal problem at all. This may feel like a pretty scary position to be but it is surprisingly empowering. All the decisions you used to have to make as to who is responsible for disposing a created object are gone.
It does actually make sense. The system knows much more about what is reachable and what is not than you. It can also make much more flexible and intelligent decisions about when to tear down structures etc.
Essentially - in this environment you can juggle objects in a much more complex way without worrying about dropping one. The only thing you now need to worry about is if you accidentally glue one to the ceiling.
As an ex C programmer having moved to Java I feel your pain.
Re - your final question - it is not a memory leak. When GC kicks in everything is discarded except what is reachable. In this case, assuming you have released obj1 and obj2 neither is reachable so they will both be discarded.
Garbage collection is not simple ref counting.
The circular reference example which you demonstrate will not occur in a garbage collected managed language because the garbage collector will want to trace allocation references all the way back to something on the stack. If there isn't a stack reference somewhere it's garbage. Ref counting systems like shared_ptr are not that smart and it's possible (like you demonstrate) to have two objects somewhere in the heap which keep each other from being deleted.
Garbage collected languages don't let you inspect refcounter because they have no-one. Garbage collection is an entirely different thing from refcounted memory management. The real difference is in determinism.
{
std::fstream file( "example.txt" );
// do something with file
}
// ... later on
{
std::fstream file( "example.txt" );
// do something else with file
}
in C++ you have the guarantee that example.txt has been closed after the first block is closed, or if an exception is thrown. Caomparing it with Java
{
try
{
FileInputStream file = new FileInputStream( "example.txt" );
// do something with file
}
finally
{
if( file != null )
file.close();
}
}
// ..later on
{
try
{
FileInputStream file = new FileInputStream( "example.txt" );
// do something with file
}
finally
{
if( file != null )
file.close();
}
}
As you see, you have traded memory management for all other resources management. That is the real diffence, refcounted objects still keep deterministic destruction. In garbage collection languages you must manually release resources, and check for exception. One may argue that explicit memory management can be tedious and error prone, but in modern C++ you it is mitigated by smart pointers and standard containers. You still have some responsibilities (circular references, for example), but think at how many catch/finally block you can avoid using deterministic destruction and how much typing a Java/C#/etc. programmer must do instead (as they have to manually close/release resources other than memory). And I know that there's using syntax in C# (and something similar in the newest Java) but it covers only the block scope lifetime and not the more general problem of shared ownership.
I just had an interview where I was asked to create a memory leak with Java.
Needless to say, I felt pretty dumb, having no idea how to start creating one.
What would an example be?
Here's a good way to create a true memory leak (objects inaccessible by running code but still stored in memory) in pure Java:
The application creates a long-running thread (or use a thread pool to leak even faster).
The thread loads a class via an (optionally custom) ClassLoader.
The class allocates a large chunk of memory (e.g. new byte[1000000]), stores a strong reference to it in a static field, and then stores a reference to itself in a ThreadLocal. Allocating the extra memory is optional (leaking the class instance is enough), but it will make the leak work that much faster.
The application clears all references to the custom class or the ClassLoader it was loaded from.
Repeat.
Due to the way ThreadLocal is implemented in Oracle's JDK, this creates a memory leak:
Each Thread has a private field threadLocals, which actually stores the thread-local values.
Each key in this map is a weak reference to a ThreadLocal object, so after that ThreadLocal object is garbage-collected, its entry is removed from the map.
But each value is a strong reference, so when a value (directly or indirectly) points to the ThreadLocal object that is its key, that object will neither be garbage-collected nor removed from the map as long as the thread lives.
In this example, the chain of strong references looks like this:
Thread object → threadLocals map → instance of example class → example class → static ThreadLocal field → ThreadLocal object.
(The ClassLoader doesn't really play a role in creating the leak, it just makes the leak worse because of this additional reference chain: example class → ClassLoader → all the classes it has loaded. It was even worse in many JVM implementations, especially prior to Java 7, because classes and ClassLoaders were allocated straight into permgen and were never garbage-collected at all.)
A variation on this pattern is why application containers (like Tomcat) can leak memory like a sieve if you frequently redeploy applications which happen to use ThreadLocals that in some way point back to themselves. This can happen for a number of subtle reasons and is often hard to debug and/or fix.
Update: Since lots of people keep asking for it, here's some example code that shows this behavior in action.
Static field holding an object reference [especially a final field]
class MemorableClass {
static final ArrayList list = new ArrayList(100);
}
(Unclosed) open streams (file , network, etc.)
try {
BufferedReader br = new BufferedReader(new FileReader(inputFile));
...
...
} catch (Exception e) {
e.printStackTrace();
}
Unclosed connections
try {
Connection conn = ConnectionFactory.getConnection();
...
...
} catch (Exception e) {
e.printStackTrace();
}
Areas that are unreachable from JVM's garbage collector, such as memory allocated through native methods.
In web applications, some objects are stored in application scope until the application is explicitly stopped or removed.
getServletContext().setAttribute("SOME_MAP", map);
Incorrect or inappropriate JVM options, such as the noclassgc option on IBM JDK that prevents unused class garbage collection
See IBM JDK settings.
A simple thing to do is to use a HashSet with an incorrect (or non-existent) hashCode() or equals(), and then keep adding "duplicates". Instead of ignoring duplicates as it should, the set will only ever grow and you won't be able to remove them.
If you want these bad keys/elements to hang around you can use a static field like
class BadKey {
// no hashCode or equals();
public final String key;
public BadKey(String key) { this.key = key; }
}
Map map = System.getProperties();
map.put(new BadKey("key"), "value"); // Memory leak even if your threads die.
Below there will be a non-obvious case where Java leaks, besides the standard case of forgotten listeners, static references, bogus/modifiable keys in hashmaps, or just threads stuck without any chance to end their life-cycle.
File.deleteOnExit() - always leaks the string, if the string is a substring, the leak is even worse (the underlying char[] is also leaked) - in Java 7 substring also copies the char[], so the later doesn't apply; #Daniel, no needs for votes, though.
I'll concentrate on threads to show the danger of unmanaged threads mostly, don't wish to even touch swing.
Runtime.addShutdownHook and not remove... and then even with removeShutdownHook due to a bug in ThreadGroup class regarding unstarted threads it may not get collected, effectively leak the ThreadGroup. JGroup has the leak in GossipRouter.
Creating, but not starting, a Thread goes into the same category as above.
Creating a thread inherits the ContextClassLoader and AccessControlContext, plus the ThreadGroup and any InheritedThreadLocal, all those references are potential leaks, along with the entire classes loaded by the classloader and all static references, and ja-ja. The effect is especially visible with the entire j.u.c.Executor framework that features a super simple ThreadFactory interface, yet most developers have no clue of the lurking danger. Also a lot of libraries do start threads upon request (way too many industry popular libraries).
ThreadLocal caches; those are evil in many cases. I am sure everyone has seen quite a bit of simple caches based on ThreadLocal, well the bad news: if the thread keeps going more than expected the life the context ClassLoader, it is a pure nice little leak. Do not use ThreadLocal caches unless really needed.
Calling ThreadGroup.destroy() when the ThreadGroup has no threads itself, but it still keeps child ThreadGroups. A bad leak that will prevent the ThreadGroup to remove from its parent, but all the children become un-enumerateable.
Using WeakHashMap and the value (in)directly references the key. This is a hard one to find without a heap dump. That applies to all extended Weak/SoftReference that might keep a hard reference back to the guarded object.
Using java.net.URL with the HTTP(S) protocol and loading the resource from(!). This one is special, the KeepAliveCache creates a new thread in the system ThreadGroup which leaks the current thread's context classloader. The thread is created upon the first request when no alive thread exists, so either you may get lucky or just leak. The leak is already fixed in Java 7 and the code that creates thread properly removes the context classloader. There are few more cases (like ImageFetcher, also fixed) of creating similar threads.
Using InflaterInputStream passing new java.util.zip.Inflater() in the constructor (PNGImageDecoder for instance) and not calling end() of the inflater. Well, if you pass in the constructor with just new, no chance... And yes, calling close() on the stream does not close the inflater if it's manually passed as constructor parameter. This is not a true leak since it'd be released by the finalizer... when it deems it necessary. Till that moment it eats native memory so badly it can cause Linux oom_killer to kill the process with impunity. The main issue is that finalization in Java is very unreliable and G1 made it worse till 7.0.2. Moral of the story: release native resources as soon as you can; the finalizer is just too poor.
The same case with java.util.zip.Deflater. This one is far worse since Deflater is memory hungry in Java, i.e. always uses 15 bits (max) and 8 memory levels (9 is max) allocating several hundreds KB of native memory. Fortunately, Deflater is not widely used and to my knowledge JDK contains no misuses. Always call end() if you manually create a Deflater or Inflater. The best part of the last two: you can't find them via normal profiling tools available.
(I can add some more time wasters I have encountered upon request.)
Good luck and stay safe; leaks are evil!
Most examples here are "too complex". They are edge cases. With these examples, the programmer made a mistake (like don't redefining equals/hashcode), or has been bitten by a corner case of the JVM/JAVA (load of class with static...). I think that's not the type of example an interviewer want or even the most common case.
But there are really simpler cases for memory leaks. The garbage collector only frees what is no longer referenced. We as Java developers don't care about memory. We allocate it when needed and let it be freed automatically. Fine.
But any long-lived application tend to have shared state. It can be anything, statics, singletons... Often non-trivial applications tend to make complex objects graphs. Just forgetting to set a reference to null or more often forgetting to remove one object from a collection is enough to make a memory leak.
Of course all sort of listeners (like UI listeners), caches, or any long-lived shared state tend to produce memory leak if not properly handled. What shall be understood is that this is not a Java corner case, or a problem with the garbage collector. It is a design problem. We design that we add a listener to a long-lived object, but we don't remove the listener when no longer needed. We cache objects, but we have no strategy to remove them from the cache.
We maybe have a complex graph that store the previous state that is needed by a computation. But the previous state is itself linked to the state before and so on.
Like we have to close SQL connections or files. We need to set proper references to null and remove elements from the collection. We shall have proper caching strategies (maximum memory size, number of elements, or timers). All objects that allow a listener to be notified must provide both a addListener and removeListener method. And when these notifiers are no longer used, they must clear their listener list.
A memory leak is indeed truly possible and is perfectly predictable. No need for special language features or corner cases. Memory leaks are either an indicator that something is maybe missing or even of design problems.
The answer depends entirely on what the interviewer thought they were asking.
Is it possible in practice to make Java leak? Of course it is, and there are plenty of examples in the other answers.
But there are multiple meta-questions that may have been being asked?
Is a theoretically "perfect" Java implementation vulnerable to leaks?
Does the candidate understand the difference between theory and reality?
Does the candidate understand how garbage collection works?
Or how garbage collection is supposed to work in an ideal case?
Do they know they can call other languages through native interfaces?
Do they know to leak memory in those other languages?
Does the candidate even know what memory management is, and what is going on behind the scene in Java?
I'm reading your meta-question as "What's an answer I could have used in this interview situation". And hence, I'm going to focus on interview skills instead of Java. I believe you're more likely to repeat the situation of not knowing the answer to a question in an interview than you are to be in a place of needing to know how to make Java leak. So, hopefully, this will help.
One of the most important skills you can develop for interviewing is learning to actively listen to the questions and working with the interviewer to extract their intent. Not only does this let you answer their question the way they want, but also shows that you have some vital communication skills. And when it comes down to a choice between many equally talented developers, I'll hire the one who listens, thinks, and understands before they respond every time.
The following is a pretty pointless example if you do not understand JDBC. Or at least how JDBC expects a developer to close Connection, Statement, and ResultSet instances before discarding them or losing references to them, instead of relying on implementing the finalize method.
void doWork() {
try {
Connection conn = ConnectionFactory.getConnection();
PreparedStatement stmt = conn.preparedStatement("some query");
// executes a valid query
ResultSet rs = stmt.executeQuery();
while(rs.hasNext()) {
// ... process the result set
}
} catch(SQLException sqlEx) {
log(sqlEx);
}
}
The problem with the above is that the Connection object is not closed, and hence the physical Connection will remain open until the garbage collector comes around and sees that it is unreachable. GC will invoke the finalize method, but there are JDBC drivers that do not implement the finalize, at least not in the same way that Connection.close is implemented. The resulting behavior is that while the JVM will reclaim memory due to unreachable objects being collected, resources (including memory) associated with the Connection object might not be reclaimed.
As such, Connection's final method does not clean up everything. One might find that the physical Connection to the database server will last several garbage collection cycles until the database server eventually figures out that the Connection is not alive (if it does) and should be closed.
Even if the JDBC driver implemented finalize, the compiler can throw exceptions during finalization. The resulting behavior is that any memory associated with the now "dormant" object will not be reclaimed by the compiler, as finalize is guaranteed to be invoked only once.
The above scenario of encountering exceptions during object finalization is related to another scenario that could lead to a memory leak - object resurrection. Object resurrection is often done intentionally by creating a strong reference to the object from being finalized, from another object. When object resurrection is misused it will lead to a memory leak in combination with other sources of memory leaks.
There are plenty more examples that you can conjure up - like
Managing a List instance where you are only adding to the list and not deleting from it (although you should be getting rid of elements you no longer need), or
Opening Sockets or Files, but not closing them when they are no longer needed (similar to the above example involving the Connection class).
Not unloading Singletons when bringing down a Java EE application. The Classloader that loaded the singleton class will retain a reference to the class, and hence the singleton instance will never be collected by the JVM. When a new instance of the application is deployed, a new class loader is usually created, and the former class loader will continue to exist due to the singleton.
Probably one of the simplest examples of a potential memory leak, and how to avoid it, is the implementation of ArrayList.remove(int):
public E remove(int index) {
RangeCheck(index);
modCount++;
E oldValue = (E) elementData[index];
int numMoved = size - index - 1;
if (numMoved > 0)
System.arraycopy(elementData, index + 1, elementData, index,
numMoved);
elementData[--size] = null; // (!) Let gc do its work
return oldValue;
}
If you were implementing it yourself, would you have thought to clear the array element that is no longer used (elementData[--size] = null)? That reference might keep a huge object alive ...
Any time you keep references around to objects that you no longer need you have a memory leak. See Handling memory leaks in Java programs for examples of how memory leaks manifest themselves in Java and what you can do about it.
You are able to make memory leak with sun.misc.Unsafe class. In fact this service class is used in different standard classes (for example in java.nio classes). You can't create instances of this class directly, but you may use reflection to get an instance.
Code doesn't compile in the Eclipse IDE - compile it using command javac (during compilation you'll get warnings)
import java.lang.reflect.Constructor;
import java.lang.reflect.Field;
import sun.misc.Unsafe;
public class TestUnsafe {
public static void main(String[] args) throws Exception{
Class unsafeClass = Class.forName("sun.misc.Unsafe");
Field f = unsafeClass.getDeclaredField("theUnsafe");
f.setAccessible(true);
Unsafe unsafe = (Unsafe) f.get(null);
System.out.print("4..3..2..1...");
try
{
for(;;)
unsafe.allocateMemory(1024*1024);
} catch(Error e) {
System.out.println("Boom :)");
e.printStackTrace();
}
}
}
I can copy my answer from here:
Easiest way to cause memory leak in Java
"A memory leak, in computer science (or leakage, in this context), occurs when a computer program consumes memory but is unable to release it back to the operating system." (Wikipedia)
The easy answer is: You can't. Java does automatic memory management and will free resources that are not needed for you. You can't stop this from happening. It will always be able to release the resources. In programs with manual memory management, this is different. You can get some memory in C using malloc(). To free the memory, you need the pointer that malloc returned and call free() on it. But if you don't have the pointer any more (overwritten, or lifetime exceeded), then you are unfortunately incapable of freeing this memory and thus you have a memory leak.
All the other answers so far are in my definition not really memory leaks. They all aim at filling the memory with pointless stuff real fast. But at any time you could still dereference the objects you created and thus freeing the memory --> no leak. acconrad's answer comes pretty close though as I have to admit since his solution is effectively to just "crash" the garbage collector by forcing it in an endless loop).
The long answer is: You can get a memory leak by writing a library for Java using the JNI, which can have manual memory management and thus have memory leaks. If you call this library, your Java process will leak memory. Or, you can have bugs in the JVM, so that the JVM looses memory. There are probably bugs in the JVM, there may even be some known ones since garbage collection is not that trivial, but then it's still a bug. By design this is not possible. You may be asking for some Java code that is effected by such a bug. Sorry I don't know one and it might well not be a bug any more in the next Java version anyway.
Here's a simple/sinister one via http://wiki.eclipse.org/Performance_Bloopers#String.substring.28.29.
public class StringLeaker
{
private final String muchSmallerString;
public StringLeaker()
{
// Imagine the whole Declaration of Independence here
String veryLongString = "We hold these truths to be self-evident...";
// The substring here maintains a reference to the internal char[]
// representation of the original string.
this.muchSmallerString = veryLongString.substring(0, 1);
}
}
Because the substring refers to the internal representation of the original, much longer string, the original stays in memory. Thus, as long as you have a StringLeaker in play, you have the whole original string in memory, too, even though you might think you're just holding on to a single-character string.
The way to avoid storing an unwanted reference to the original string is to do something like this:
...
this.muchSmallerString = new String(veryLongString.substring(0, 1));
...
For added badness, you might also .intern() the substring:
...
this.muchSmallerString = veryLongString.substring(0, 1).intern();
...
Doing so will keep both the original long string and the derived substring in memory even after the StringLeaker instance has been discarded.
A common example of this in GUI code is when creating a widget/component and adding a listener to some static/application scoped object and then not removing the listener when the widget is destroyed. Not only do you get a memory leak, but also a performance hit as when whatever you are listening to fires events, all your old listeners are called too.
Take any web application running in any servlet container (Tomcat, Jetty, GlassFish, whatever...). Redeploy the application 10 or 20 times in a row (it may be enough to simply touch the WAR in the server's autodeploy directory.
Unless anybody has actually tested this, chances are high that you'll get an OutOfMemoryError after a couple of redeployments, because the application did not take care to clean up after itself. You may even find a bug in your server with this test.
The problem is, the lifetime of the container is longer than the lifetime of your application. You have to make sure that all references the container might have to objects or classes of your application can be garbage collected.
If there is just one reference surviving the undeployment of your web application, the corresponding classloader and by consequence all classes of your web application cannot be garbage collected.
Threads started by your application, ThreadLocal variables, logging appenders are some of the usual suspects to cause classloader leaks.
Maybe by using external native code through JNI?
With pure Java, it is almost impossible.
But that is about a "standard" type of memory leak, when you cannot access the memory anymore, but it is still owned by the application. You can instead keep references to unused objects, or open streams without closing them afterwards.
I have had a nice "memory leak" in relation to PermGen and XML parsing once.
The XML parser we used (I can't remember which one it was) did a String.intern() on tag names, to make comparison faster.
One of our customers had the great idea to store data values not in XML attributes or text, but as tagnames, so we had a document like:
<data>
<1>bla</1>
<2>foo</>
...
</data>
In fact, they did not use numbers but longer textual IDs (around 20 characters), which were unique and came in at a rate of 10-15 million a day. That makes 200 MB of rubbish a day, which is never needed again, and never GCed (since it is in PermGen). We had permgen set to 512 MB, so it took around two days for the out-of-memory exception (OOME) to arrive...
The interviewer was probably looking for a circular reference like the code below (which incidentally only leak memory in very old JVMs that used reference counting, which isn't the case anymore). But it's a pretty vague question, so it's a prime opportunity to show off your understanding of JVM memory management.
class A {
B bRef;
}
class B {
A aRef;
}
public class Main {
public static void main(String args[]) {
A myA = new A();
B myB = new B();
myA.bRef = myB;
myB.aRef = myA;
myA=null;
myB=null;
/* at this point, there is no access to the myA and myB objects, */
/* even though both objects still have active references. */
} /* main */
}
Then you can explain that with reference counting, the above code would leak memory. But most modern JVMs don't use reference counting any longer. Most use a sweep garbage collector, which will in fact collect this memory.
Next, you might explain creating an Object that has an underlying native resource, like this:
public class Main {
public static void main(String args[]) {
Socket s = new Socket(InetAddress.getByName("google.com"),80);
s=null;
/* at this point, because you didn't close the socket properly, */
/* you have a leak of a native descriptor, which uses memory. */
}
}
Then you can explain this is technically a memory leak, but really the leak is caused by native code in the JVM allocating underlying native resources, which weren't freed by your Java code.
At the end of the day, with a modern JVM, you need to write some Java code that allocates a native resource outside the normal scope of the JVM's awareness.
What's a memory leak:
It's caused by a bug or bad design.
It's a waste of memory.
It gets worse over time.
The garbage collector cannot clean it.
Typical example:
A cache of objects is a good starting point to mess things up.
private static final Map<String, Info> myCache = new HashMap<>();
public void getInfo(String key)
{
// uses cache
Info info = myCache.get(key);
if (info != null) return info;
// if it's not in cache, then fetch it from the database
info = Database.fetch(key);
if (info == null) return null;
// and store it in the cache
myCache.put(key, info);
return info;
}
Your cache grows and grows. And pretty soon the entire database gets sucked into memory. A better design uses an LRUMap (Only keeps recently used objects in cache).
Sure, you can make things a lot more complicated:
using ThreadLocal constructions.
adding more complex reference trees.
or leaks caused by 3rd party libraries.
What often happens:
If this Info object has references to other objects, which again have references to other objects. In a way you could also consider this to be some kind of memory leak, (caused by bad design).
I thought it was interesting that no one used the internal class examples. If you have an internal class; it inherently maintains a reference to the containing class. Of course it is not technically a memory leak because Java WILL eventually clean it up; but this can cause classes to hang around longer than anticipated.
public class Example1 {
public Example2 getNewExample2() {
return this.new Example2();
}
public class Example2 {
public Example2() {}
}
}
Now if you call Example1 and get an Example2 discarding Example1, you will inherently still have a link to an Example1 object.
public class Referencer {
public static Example2 GetAnExample2() {
Example1 ex = new Example1();
return ex.getNewExample2();
}
public static void main(String[] args) {
Example2 ex = Referencer.GetAnExample2();
// As long as ex is reachable; Example1 will always remain in memory.
}
}
I've also heard a rumor that if you have a variable that exists for longer than a specific amount of time; Java assumes that it will always exist and will actually never try to clean it up if cannot be reached in code anymore. But that is completely unverified.
I recently encountered a memory leak situation caused in a way by log4j.
Log4j has this mechanism called Nested Diagnostic Context(NDC) which is an instrument to distinguish interleaved log output from different sources. The granularity at which NDC works is threads, so it distinguishes log outputs from different threads separately.
In order to store thread specific tags, log4j's NDC class uses a Hashtable which is keyed by the Thread object itself (as opposed to say the thread id), and thus till the NDC tag stays in memory all the objects that hang off of the thread object also stay in memory. In our web application we use NDC to tag logoutputs with a request id to distinguish logs from a single request separately. The container that associates the NDC tag with a thread, also removes it while returning the response from a request. The problem occurred when during the course of processing a request, a child thread was spawned, something like the following code:
pubclic class RequestProcessor {
private static final Logger logger = Logger.getLogger(RequestProcessor.class);
public void doSomething() {
....
final List<String> hugeList = new ArrayList<String>(10000);
new Thread() {
public void run() {
logger.info("Child thread spawned")
for(String s:hugeList) {
....
}
}
}.start();
}
}
So an NDC context was associated with inline thread that was spawned. The thread object that was the key for this NDC context, is the inline thread which has the hugeList object hanging off of it. Hence even after the thread finished doing what it was doing, the reference to the hugeList was kept alive by the NDC context Hastable, thus causing a memory leak.
Create a static Map and keep adding hard references to it. Those will never be garbage collected.
public class Leaker {
private static final Map<String, Object> CACHE = new HashMap<String, Object>();
// Keep adding until failure.
public static void addToCache(String key, Object value) { Leaker.CACHE.put(key, value); }
}
Everyone always forgets the native code route. Here's a simple formula for a leak:
Declare a native method.
In the native method, call malloc. Don't call free.
Call the native method.
Remember, memory allocations in native code come from the JVM heap.
You can create a moving memory leak by creating a new instance of a class in that class's finalize method. Bonus points if the finalizer creates multiple instances. Here's a simple program that leaks the entire heap in sometime between a few seconds and a few minutes depending on your heap size:
class Leakee {
public void check() {
if (depth > 2) {
Leaker.done();
}
}
private int depth;
public Leakee(int d) {
depth = d;
}
protected void finalize() {
new Leakee(depth + 1).check();
new Leakee(depth + 1).check();
}
}
public class Leaker {
private static boolean makeMore = true;
public static void done() {
makeMore = false;
}
public static void main(String[] args) throws InterruptedException {
// make a bunch of them until the garbage collector gets active
while (makeMore) {
new Leakee(0).check();
}
// sit back and watch the finalizers chew through memory
while (true) {
Thread.sleep(1000);
System.out.println("memory=" +
Runtime.getRuntime().freeMemory() + " / " +
Runtime.getRuntime().totalMemory());
}
}
}
I don't think anyone has said this yet: you can resurrect an object by overriding the finalize() method such that finalize() stores a reference of this somewhere. The garbage collector will only be called once on the object so after that the object will never destroyed.
I came across a more subtle kind of resource leak recently.
We open resources via class loader's getResourceAsStream and it happened that the input stream handles were not closed.
Uhm, you might say, what an idiot.
Well, what makes this interesting is: this way, you can leak heap memory of the underlying process, rather than from JVM's heap.
All you need is a jar file with a file inside which will be referenced from Java code. The bigger the jar file, the quicker memory gets allocated.
You can easily create such a jar with the following class:
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.util.zip.ZipEntry;
import java.util.zip.ZipOutputStream;
public class BigJarCreator {
public static void main(String[] args) throws IOException {
ZipOutputStream zos = new ZipOutputStream(new FileOutputStream(new File("big.jar")));
zos.putNextEntry(new ZipEntry("resource.txt"));
zos.write("not too much in here".getBytes());
zos.closeEntry();
zos.putNextEntry(new ZipEntry("largeFile.out"));
for (int i=0 ; i<10000000 ; i++) {
zos.write((int) (Math.round(Math.random()*100)+20));
}
zos.closeEntry();
zos.close();
}
}
Just paste into a file named BigJarCreator.java, compile and run it from command line:
javac BigJarCreator.java
java -cp . BigJarCreator
Et voilà: you find a jar archive in your current working directory with two files inside.
Let's create a second class:
public class MemLeak {
public static void main(String[] args) throws InterruptedException {
int ITERATIONS=100000;
for (int i=0 ; i<ITERATIONS ; i++) {
MemLeak.class.getClassLoader().getResourceAsStream("resource.txt");
}
System.out.println("finished creation of streams, now waiting to be killed");
Thread.sleep(Long.MAX_VALUE);
}
}
This class basically does nothing, but create unreferenced InputStream objects. Those objects will be garbage collected immediately and thus, do not contribute to heap size.
It is important for our example to load an existing resource from a jar file, and size does matter here!
If you're doubtful, try to compile and start the class above, but make sure to chose a decent heap size (2 MB):
javac MemLeak.java
java -Xmx2m -classpath .:big.jar MemLeak
You will not encounter an OOM error here, as no references are kept, the application will keep running no matter how large you chose ITERATIONS in the above example.
The memory consumption of your process (visible in top (RES/RSS) or process explorer) grows unless the application gets to the wait command. In the setup above, it will allocate around 150 MB in memory.
If you want the application to play safe, close the input stream right where it's created:
MemLeak.class.getClassLoader().getResourceAsStream("resource.txt").close();
and your process will not exceed 35 MB, independent of the iteration count.
Quite simple and surprising.
As a lot of people have suggested, resource leaks are fairly easy to cause - like the JDBC examples. Actual memory leaks are a bit harder - especially if you aren't relying on broken bits of the JVM to do it for you...
The ideas of creating objects that have a very large footprint and then not being able to access them aren't real memory leaks either. If nothing can access it then it will be garbage collected, and if something can access it then it's not a leak...
One way that used to work though - and I don't know if it still does - is to have a three-deep circular chain. As in Object A has a reference to Object B, Object B has a reference to Object C and Object C has a reference to Object A. The GC was clever enough to know that a two deep chain - as in A <--> B - can safely be collected if A and B aren't accessible by anything else, but couldn't handle the three-way chain...
Another way to create potentially huge memory leaks is to hold references to Map.Entry<K,V> of a TreeMap.
It is hard to asses why this applies only to TreeMaps, but by looking at the implementation the reason might be that: a TreeMap.Entry stores references to its siblings, therefore if a TreeMap is ready to be collected, but some other class holds a reference to any of its Map.Entry, then the entire Map will be retained into memory.
Real-life scenario:
Imagine having a db query that returns a big TreeMap data structure. People usually use TreeMaps as the element insertion order is retained.
public static Map<String, Integer> pseudoQueryDatabase();
If the query was called lots of times and, for each query (so, for each Map returned) you save an Entry somewhere, the memory would constantly keep growing.
Consider the following wrapper class:
class EntryHolder {
Map.Entry<String, Integer> entry;
EntryHolder(Map.Entry<String, Integer> entry) {
this.entry = entry;
}
}
Application:
public class LeakTest {
private final List<EntryHolder> holdersCache = new ArrayList<>();
private static final int MAP_SIZE = 100_000;
public void run() {
// create 500 entries each holding a reference to an Entry of a TreeMap
IntStream.range(0, 500).forEach(value -> {
// create map
final Map<String, Integer> map = pseudoQueryDatabase();
final int index = new Random().nextInt(MAP_SIZE);
// get random entry from map
for (Map.Entry<String, Integer> entry : map.entrySet()) {
if (entry.getValue().equals(index)) {
holdersCache.add(new EntryHolder(entry));
break;
}
}
// to observe behavior in visualvm
try {
Thread.sleep(500);
} catch (InterruptedException e) {
e.printStackTrace();
}
});
}
public static Map<String, Integer> pseudoQueryDatabase() {
final Map<String, Integer> map = new TreeMap<>();
IntStream.range(0, MAP_SIZE).forEach(i -> map.put(String.valueOf(i), i));
return map;
}
public static void main(String[] args) throws Exception {
new LeakTest().run();
}
}
After each pseudoQueryDatabase() call, the map instances should be ready for collection, but it won't happen, as at least one Entry is stored somewhere else.
Depending on your jvm settings, the application may crash in the early stage due to a OutOfMemoryError.
You can see from this visualvm graph how the memory keeps growing.
The same does not happen with a hashed data-structure (HashMap).
This is the graph when using a HashMap.
The solution? Just directly save the key / value (as you probably already do) rather than saving the Map.Entry.
I have written a more extensive benchmark here.
There are many good examples of memory leaks in Java, and I will mention two of them in this answer.
Example 1:
Here is a good example of a memory leak from the book Effective Java, Third Edition (item 7: Eliminate obsolete object references):
// Can you spot the "memory leak"?
public class Stack {
private static final int DEFAULT_INITIAL_CAPACITY = 16;
private Object[] elements;
private int size = 0;
public Stack() {
elements = new Object[DEFAULT_INITIAL_CAPACITY];
}
public void push(Object e) {
ensureCapacity();
elements[size++] = e;
}
public Object pop() {
if (size == 0) throw new EmptyStackException();
return elements[--size];
}
/*** Ensure space for at least one more element, roughly* doubling the capacity each time the array needs to grow.*/
private void ensureCapacity() {
if (elements.length == size) elements = Arrays.copyOf(elements, 2 * size + 1);
}
}
This is the paragraph of the book that describes why this implementation will cause a memory leak:
If a stack grows and then shrinks, the objects that were popped off the
stack will not be garbage collected, even if the program using the
stack has no more references to them. This is because the
stack maintains obsolete references to these objects. An obsolete
reference is simply a reference that will never be dereferenced
again. In this case, any references outside of the “active portion” of
the element array are obsolete. The active portion consists of the
elements whose index is less than size
Here is the solution of the book to tackle this memory leak:
The fix for this sort of problem is simple: null out
references once they become obsolete. In the case of our Stack class,
the reference to an item becomes obsolete as soon as it’s popped
off the stack. The corrected version of the pop method looks like this:
public Object pop() {
if (size == 0) throw new EmptyStackException();
Object result = elements[--size];
elements[size] = null; // Eliminate obsolete reference
return result;
}
But how can we prevent a memory leak from happening? This is a good caveat from the book:
Generally speaking, whenever a class manages its own memory,
the programmer should be alert for memory leaks. Whenever an element
is freed, any object references contained in the element should be
nulled out.
Example 2:
The observer pattern also can cause a memory leak. You can read about this pattern in the following link: Observer pattern.
This is one implementation of the Observer pattern:
class EventSource {
public interface Observer {
void update(String event);
}
private final List<Observer> observers = new ArrayList<>();
private void notifyObservers(String event) {
observers.forEach(observer -> observer.update(event)); //alternative lambda expression: observers.forEach(Observer::update);
}
public void addObserver(Observer observer) {
observers.add(observer);
}
public void scanSystemIn() {
Scanner scanner = new Scanner(System.in);
while (scanner.hasNextLine()) {
String line = scanner.nextLine();
notifyObservers(line);
}
}
}
In this implementation, EventSource, which is Observable in the Observer design pattern, can hold links to Observer objects, but this link is never removed from the observers field in EventSource. So they will never be collected by the garbage collector. One solution to tackle this problem is providing another method to the client for removing the aforementioned observers from the observers field when they don't need those observers anymore:
public void removeObserver(Observer observer) {
observers.remove(observer);
}
Threads are not collected until they terminate. They serve as roots of garbage collection. They are one of the few objects that won't be reclaimed simply by forgetting about them or clearing references to them.
Consider: the basic pattern to terminate a worker thread is to set some condition variable seen by the thread. The thread can check the variable periodically and use that as a signal to terminate. If the variable is not declared volatile, then the change to the variable might not be seen by the thread, so it won't know to terminate. Or imagine if some threads want to update a shared object, but deadlock while trying to lock on it.
If you only have a handful of threads these bugs will probably be obvious because your program will stop working properly. If you have a thread pool that creates more threads as needed, then the obsolete/stuck threads might not be noticed, and will accumulate indefinitely, causing a memory leak. Threads are likely to use other data in your application, so will also prevent anything they directly reference from ever being collected.
As a toy example:
static void leakMe(final Object object) {
new Thread() {
public void run() {
Object o = object;
for (;;) {
try {
sleep(Long.MAX_VALUE);
} catch (InterruptedException e) {}
}
}
}.start();
}
Call System.gc() all you like, but the object passed to leakMe will never die.
The interviewer might have been looking for a circular reference solution:
public static void main(String[] args) {
while (true) {
Element first = new Element();
first.next = new Element();
first.next.next = first;
}
}
This is a classic problem with reference counting garbage collectors. You would then politely explain that JVMs use a much more sophisticated algorithm that doesn't have this limitation.