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Know Your Worst Friend, the Garbage Collector

It can make or break performance

The first one is called incremental garbage collection. As its name suggests, this mode does a bit of major collecting every time a minor collection is run. Global performance suffers from this execution mode but you get rid of those nasty pauses caused by major collections. Incremental garbage collection also tends to leave the heap in a fragmented state. So it's a good idea to limit its use to applications with long-lived objects. It can help you in a subtle way to obtain more responsive Swing UIs.

The second mode is a parallel GC using many threads at once, at least one per processor, to do minor collections. If your target computer has less than three processors, it is unlikely you will ever notice a difference. This option is particularly well suited to heavy servers running applications spawning many short-lived objects like web servers.

Finally yet importantly, a concurrent GC can do incremental major collection without interrupting the application for long periods of time. A concurrent GC can also use parallel execution for minor collections. According to Sun Microsystems, this execution mode gets good results with interactive applications running on a single-processor computer. To choose among these three modes and set them up, you need to use the following command-line flags:

  • -Xincgc activates incremental garbage collection.
  • -XX:+UseParallelGC activates the parallel GC. The number of threads used to do minor collections is defined by the -XX:ParallelGCThreads=<a number> flag.
  • -XX:+UseConcMarkSweepGC activates the concurrent GC. Parallel minor collections can be activated as well by using the -XX:+UseParNewGC flag.
To measure the impact of your choice on your application, you'll want to use the –verbose:gc command-line flag. You'll then get a GC activity trace on the standard output. Redirecting the standard output to a file and running the following Python script will let you draw very useful charts as shown in Figure 2.

This script can be used by specifying a file name as the first parameter or by piping it directly to the Java command.


#!/usr/bin/env python
# -*- coding: ISO-8859-1 -*-

import fileinput
import re

print "%s\t%s\t%s\t%s" % ("Minor", "Major", "Alive", "Freed")

for line in fileinput.input():
match = re.match("\[(Full )?GC (\d+)K->(\d+)K\((\d+)K\), ([^ ]+) secs]", line)
if match is not None:
minor = match.group(1) == "Full " and "0.0" or match.group(5)
major = match.group(1) == "Full " and match.group(5) or "0.0"
alive = match.group(3)
freed = int(match.group(2)) - int(alive)
print "%s\t%s\t%s\t%s" % (minor, major, alive, freed)

The result is a CSV document using tabs as separators and containing four columns of data. The first one gives the time consumed by the GC to do a minor collection, the second one gives the same information for a major collection, the third one indicates the amount of memory used by the application after the execution of the GC and the last one gives the amount of memory reclaimed by the last collection. (This script was inspired by an AWK script written by Ken Gottry in the article Pick up performance with generational garbage collection published on javaworld.com.)

The chart presents the running time of each collection performed by the GC during the application life cycle. This chart was generated with the following command line and OpenOffice.org:


$ java -verbose:gc -Xms64m -Xmx128m -XX:NewRatio=2 -XX:+UseConcMarkSweepGC -jar ../lib/jext-5.0.jar > gclog
$ gclog2csv.py gclog > gclog.csv

Although simple, this small script can help you tune your application pretty quickly. As of J2SE 5.0, Sun Microsystems provides a more powerful tool called JConsole that will graphically monitor the state of the heap and the activity of the GC as shown in Figure 3.

Further Reading

  • Java HotSpot VM Options, Sun Microsystems, http://java.sun.com/docs/hotspot/VMOptions.html
  • A Collection of JVM Options, Joseph Mocker, http://blogs.sun.com/roller/resources/watt/jvm-options-list.html
  • Pick up performance with generational garbage collection, Ken Gottry, www.javaworld.com/javaworld/jw-01-2002/jw-0111-hotspotgc-p4.html
  • Garbage Collection in the Java HotSpot Virtual Machine, Tony Printezis, www.devx.com/Java/Article/21977?trk=DXRSS_JAVA
  • Garbage Collection Performance, Brian Goetz, www-106.ibm.com/developerworks/java/library/j-jtp01274.html
  • Using JConsole to Monitor Applications, Mandy Chung, http://java.sun.com/developer/technicalArticles/J2SE/jconsole.html
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    Most Recent Comments
    Suresh 05/31/05 01:44:21 PM EDT

    cannot go to page2!!!!

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