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Java theory and practice: Garbage collection and performance
By Brian Goetz - 2004-03-03 Page:  1 2 3 4 5 6

Helping the garbage collector . . . not

Because allocation and garbage collection at one time imposed significant performance costs on Java programs, many clever tricks were developed to reduce these costs, such as object pooling and nulling. Unfortunately, in many cases these techniques can do more harm than good to your program's performance.

Object pooling

Object pooling is a straightforward concept -- maintain a pool of frequently used objects and grab one from the pool instead of creating a new one whenever needed. The theory is that pooling spreads out the allocation costs over many more uses. When the object creation cost is high, such as with database connections or threads, or the pooled object represents a limited and costly resource, such as with database connections, this makes sense. However, the number of situations where these conditions apply is fairly small.

In addition, object pooling has some serious downsides. Because the object pool is generally shared across all threads, allocation from the object pool can be a synchronization bottleneck. Pooling also forces you to manage deallocation explicitly, which reintroduces the risks of dangling pointers. Also, the pool size must be properly tuned to get the desired performance result. If it is too small, it will not prevent allocation; and if it is too large, resources that could get reclaimed will instead sit idle in the pool. By tying up memory that could be reclaimed, the use of object pools places additional pressure on the garbage collector. Writing an effective pool implementation is not simple.

In his "Performance Myths Exposed" talk at JavaOne 2003 (see Resources), Dr. Cliff Click offered concrete benchmarking data showing that object pooling is a performance loss for all but the most heavyweight objects on modern JVMs. Add in the serialization of allocation and the dangling-pointer risks, and it's clear that pooling should be avoided in all but the most extreme cases.

Explicit nulling

Explicit nulling is simply the practice of setting reference objects to null when you are finished with them. The idea behind nulling is that it assists the garbage collector by making objects unreachable earlier. Or at least that's the theory.

There is one case where the use of explicit nulling is not only helpful, but virtually required, and that is where a reference to an object is scoped more broadly than it is used or considered valid by the program's specification. This includes cases such as using a static or instance field to store a reference to a temporary buffer, rather than a local variable (see Resources for a link to "Eye on performance: Referencing objects" for an example), or using an array to store references that may remain reachable by the runtime but not by the implied semantics of the program. Consider the class in Listing 3, which is an implementation of a simple bounded stack backed by an array. When pop() is called, without the explicit nulling in the example, the class could cause a memory leak (more properly called "unintentional object retention," or sometimes called "object loitering") because the reference stored in stack[top+1] is no longer reachable by the program, but still considered reachable by the garbage collector.

Listing 3. Avoiding object loitering in a stack implementation

public class SimpleBoundedStack {
  private static final int MAXLEN = 100;
  private Object stack[] = new Object[MAXLEN];
  private int top = -1;

  public void push(Object p) { stack [++top] = p;}

  public Object pop() {
    Object p = stack [top];
    stack [top--] = null;  // explicit null
    return p;

In the September 1997 "Java Developer Connection Tech Tips" column (see Resources), Sun warned of this risk and explained how explicit nulling was needed in cases like the pop() example above. Unfortunately, programmers often take this advice too far, using explicit nulling in the hope of helping the garbage collector. But in most cases, it doesn't help the garbage collector at all, and in some cases, it can actually hurt your program's performance.

Consider the code in Listing 4, which combines several really bad ideas. The listing is a linked list implementation that uses a finalizer to walk the list and null out all the forward links. We've already discussed why finalizers are bad. This case is even worse because now the class is doing extra work, ostensibly to help the garbage collector, but that will not actually help -- and might even hurt. Walking the list takes CPU cycles and will have the effect of visiting all those dead objects and pulling them into the cache -- work that the garbage collector might be able to avoid entirely, because copying collectors do not visit dead objects at all. Nulling the references doesn't help a tracing garbage collector anyway; if the head of the list is unreachable, the rest of the list won't be traced anyway.

Listing 4. Combining finalizers and explicit nulling for a total performance disaster -- don't do this!

public class LinkedList {

  private static class ListElement {
    private ListElement nextElement;
    private Object value;

  private ListElement head;


  public void finalize() { 
    try {
      ListElement p = head;
      while (p != null) {
        p.value = null;
        ListElement q = p.nextElement;
        p.nextElement = null;
        p = q;
      head = null;
    finally {

Explicit nulling should be saved for cases where your program is subverting normal scoping rules for performance reasons, such as the stack example in Listing 3 (a more correct -- but poorly performing -- implementation would be to reallocate and copy the stack array each time it is changed).

Explicit garbage collection

A third category where developers often mistakenly think they are helping the garbage collector is the use of System.gc(), which triggers a garbage collection (actually, it merely suggests that this might be a good time for a garbage collection). Unfortunately, System.gc() triggers a full collection, which includes tracing all live objects in the heap and sweeping and compacting the old generation. This can be a lot of work. In general, it is better to let the system decide when it needs to collect the heap, and whether or not to do a full collection. Most of the time, a minor collection will do the job. Worse, calls to System.gc() are often deeply buried where developers may be unaware of their presence, and where they might get triggered far more often than necessary. If you are concerned that your application might have hidden calls to System.gc() buried in libraries, you can invoke the JVM with the -XX:+DisableExplicitGC option to prevent calls to System.gc() and triggering a garbage collection.

Immutability, again

No installment of Java theory and practice would be complete without some sort of plug for immutability. Making objects immutable eliminates entire classes of programming errors. One of the most common reasons given for not making a class immutable is the belief that doing so would compromise performance. While this is true sometimes, it is often not -- and sometimes the use of immutable objects has significant, and perhaps surprising, performance advantages.

Many objects function as containers for references to other objects. When the referenced object needs to change, we have two choices: update the reference (as we would in a mutable container class) or re-create the container to hold a new reference (as we would in an immutable container class). Listing 5 shows two ways to implement a simple holder class. Assuming the containing object is small, which is often the case (such as a Map.Entry element in a Map or a linked list element), allocating a new immutable object has some hidden performance advantages that come from the way generational garbage collectors work, having to do with the relative age of objects.

Listing 5. Mutable and immutable object holders

public class MutableHolder {
  private Object value;
  public Object getValue() { return value; }
  public void setValue(Object o) { value = o; }

public class ImmutableHolder {
  private final Object value;
  public ImmutableHolder(Object o) { value = o; }
  public Object getValue() { return value; }

In most cases, when a holder object is updated to reference a different object, the new referent is a young object. If we update a MutableHolder by calling setValue(), we have created a situation where an older object references a younger one. On the other hand, by creating a new ImmutableHolder object instead, a younger object is referencing an older one. The latter situation, where most objects point to older objects, is much more gentle on a generational garbage collector. If a MutableHolder that lives in the old generation is mutated, all the objects on the card that contain the MutableHolder must be scanned for old-to-young references at the next minor collection. The use of mutable references for long-lived container objects increases the work done to track old-to-young references at collection time. (See last month's article and this month's Resources, which explain the card-marking algorithm used to implement the write barrier in the generational collector used by current Sun JVMs).

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First published by IBM developerWorks

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