Read our updated post about collector types and advanced GC techniques here!

The 4 Java Garbage Collectors – How the Wrong Choice Dramatically Impacts Performance

When Garbage collection is one of those things that are generally known to impact performance, but beyond that – in terms of how it actually works – it’s pretty much a mystery to most of us. So, I thought I’d take a whack at covering the basics of GC, especially since this is an area that has seen some major changes and improvements with Java 8, especially with the removal of the PermGen and some new and exciting optimizations (more on this towards the end).

When we speak about garbage collection, the vast majority of us know the concept and employ it in our everyday programming. Even so, there’s much about it we don’t understand, and that’s when things get painful. One of the biggest misconceptions about the JVM is that it has one garbage collector, where in fact it provides four different ones, each with its own unique advantages and disadvantages. The choice of which one to use isn’t automatic and lies on your shoulders and the differences in throughput and application pauses can be dramatic.

What’s common about these four garbage collection algorithms is that they are generational, which means they split the managed heap into different segments, using the age-old assumptions that most objects in the heap are short lived and should be recycled quickly. As this too is a well-covered area, I’m going to jump directly into the different algorithms, along with their pros and their cons.

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1. The Serial Collector

The serial collector is the simplest one, and the one you probably won’t be using, as it’s mainly designed for single-threaded environments (e.g. 32 bit or Windows) and for small heaps. This collector freezes all application threads whenever it’s working, which disqualifies it for all intents and purposes from being used in a server environment.

How to use it: You can use it by turning on the -XX:+UseSerialGC JVM argument,

2. The Parallel / Throughput collector

Next off is the Parallel collector. This is the JVM’s default collector. Much like its name, its biggest advantage is that is uses multiple threads to scan through and compact the heap. The downside to the parallel collector is that it will stop application threads when performing either a minor or full GC collection. The parallel collector is best suited for apps that can tolerate application pauses and are trying to optimize for lower CPU overhead caused by the collector.

3. The CMS Collector

Following up on the parallel collector is the CMS collector (“concurrent-mark-sweep”). This algorithm uses multiple threads (“concurrent”) to scan through the heap (“mark”) for unused objects that can be recycled (“sweep”). This algorithm will enter “stop the world” (STW) mode in two cases: when initializing the initial marking of roots (objects in the old generation that are reachable from thread entry points or static variables) and when the application has changed the state of the heap while the algorithm was running concurrently, forcing it to go back and do some final touches to make sure it has the right objects marked.

The biggest concern when using this collector is encountering promotion failures which are instances where a race condition occurs between collecting the young and old generations. If the collector needs to promote young objects to the old generation, but hasn’t had enough time to make space clear it,  it will have to do so first which will result in a full STW collection – the very thing this CMS collector was meant to prevent. To make sure this doesn’t happen you would either increase the size of the old generation (or the entire heap for that matter) or allocate more background threads to the collector for him to compete with the rate of object allocation.

Another downside to this algorithm in comparison to the parallel collector is that it uses more CPU in order to provide the application with higher levels of continuous throughput, by using multiple threads to perform scanning and collection. For most long-running server applications which are adverse to application freezes, that’s usually a good trade off to make. Even so, this algorithm is not on by default. You have to specify XX:+USeParNewGC to actually enable it. If you’re willing to allocate more CPU resources to avoid application pauses this is the collector you’ll probably want to use, assuming that your heap is less than 4Gb in size.  However, if it’s greater than 4GB, you’ll probably want to use the last algorithm – the G1 Collector.

4. The G1 Collector

The Garbage first collector (G1) introduced in JDK 7 update 4 was designed to better support heaps larger than 4GB. The G1 collector utilizes multiple background threads to scan through the heap that it divides into regions, spanning from 1MB to 32MB (depending on the size of your heap). G1 collector is geared towards scanning those regions that contain the most garbage objects first, giving it its name (Garbage first). This collector is turned on using the –XX:+UseG1GC flag.

This strategy reduced the chance of the heap being depleted before background threads have finished scanning for unused objects, in which case the collector will have to stop the application which will result in a STW collection. The G1 also has another advantage that is that it compacts the heap on-the-go, something the CMS collector only does during full STW collections.

Large heaps have been a fairly contentious area over the past few years with many developers moving away from the single JVM per machine model to more micro-service, componentized architectures with multiple JVMs per machine. This has been driven by many factors including the desire to isolate different application parts, simplifying deployment and avoiding the cost which would usually come with reloading application classes into memory (something which has actually been improved in Java 8).

Even so, one of the biggest drivers to do this when it comes to the JVM stems from the desire to avoid those long “stop the world” pauses (which can take many seconds in a large collection) that occur with large heaps. This has also been accelerated by container technologies like Docker that enable you to deploy multiple apps on the same physical machine with relative ease.

Java 8 and the G1 Collector

Another beautiful optimization which was just out with Java 8 update 20 for is the G1 Collector String deduplication. Since strings (and their internal char[] arrays) takes much of our heap, a new optimization has been made that enables the G1 collector to identify strings which are duplicated more than once across your heap and correct them to point into the same internal char[] array, to avoid multiple copies of the same string from residing inefficiently within the heap. You can use the -XX:+UseStringDeduplicationJVM argument to try this out.

Java 8 and PermGen

One of the biggest changes made in Java 8 was removing the permgen part of the heap that was traditionally allocated for class meta-data, interned strings and static variables. This would traditionally require developers with applications that would load significant amount of classes (something common with apps using enterprise containers) to optimize and tune for this portion of the heap specifically. This has over the years become the source of many OutOfMemory exceptions, so having the JVM (mostly) take care if it is a very nice addition. Even so, that in itself will probably not reduce the tide of developers decoupling their apps into multiple JVMs.

Each of these collectors is configured and tuned differently with a slew of toggles and switches, each with the potential to increase or decrease throughput, all based on the specific behavior of your app. We’ll delve into the key strategies of configuring each of these in our next posts.

In the meanwhile, what are the things you’re most interested in learning about regarding the differences between the different collectors? Hit me up in the comments section 🙂

Additional reading –

1. A really great in-depth review of the G1 Collector on InfoQ.

2. The Complete Guide to Java Performance Monitoring

3. More about String deduplication on the CodeCentric blog.

Tal is the CTO of OverOps. Tal has been designing scalable, real-time Java and C++ applications for the past 15 years. He still enjoys analyzing a good bug though, and instrumenting code. In his free time Tal plays Jazz drums.
  • Pablo Fernandez

    It should be noted that these 4 work on the old generation and that the new generation is always collected in STW fashion.

  • Xiaodong Xie

    Great summary! But I found 2 places that are slightly not that accurate.

    1. CMS should be enabled by “-XX:+UseConcMarkSweepGC”? “XX:+USeParNewGC” is to use “parNew” GC algorithm in the young generation, since CMS is for the old generation.

    2. Interned strings should be moved to the heap in stead of placing in perm generation in Java 7, if I remembered correctly.

    Thanks for all the great articles!

    • kupci

      Looks like that was corrected.

  • Gil Tene

    I would note that these are not features or options of Java 8. They are options available in specific JVMs, some of which appeared in the same JVM version that added support for Java 8. None of this stuff is in the Java 8 Spec.

    The above choices are better described as options available in OpenJDK 8 distributions (like Zulu or IcedTea) and in the Oracle HotSpot JDK. There are other JDKs that these choices do not apply to (like IBM’s J9, and Azul’s Zing). As you note right at the start, making the right (or wrong) choice for your Garbage Collection settings can be critical to application behavior and performance, and often making the right choice for Garbage Collection starts with making the right choice in JVMs. I would expect such an overview of GC options in Java 8 to cover the field of options (including C4 in Zing, and collectors like balanced and gencon in J9), or to clearly note that major additional GC options not covered in your list exist for Java 8 users (with some specifics named if not described in detail).

  • Mike Brunt

    What I have found is that concentrated analysis of GC logs is always key in determining the best garbage collector and arguments.

  • Malcolm Greaves

    What does this sentence mean? It’s not grammatically correct: “This strategy the chance of the heap being depleted before background threads have finished scanning for unused objects, in which case the collector will have to stop the application which will result in a STW collection.”

    • Arya Irani

      I’m guessing they accidentally a word: “This strategy reduces the chance of .”

      • Malcolm Greaves

        Ah, that makes more sense. Thank you!

      • Stijn de Witt

        “I’m guessing they accidentally a word”

        LOL @ recursive grammar problem

  • kupci

    “Next off is the Parallel collector. This is the JVM’s default collector. ” Are you sure? For Java 8, the collectors are selected based on various settings – unless explicitly set: For example: ” -XX:+UseParallelGC

    Enables the use of the parallel scavenge garbage collector (also known as the throughput collector) to improve the performance of your application by leveraging multiple processors.

    By default, this option is disabled and the collector is chosen automatically based on the configuration of the machine and type of the JVM. If it is enabled, then the -XX:+UseParallelOldGC option is automatically enabled, unless you explicitly disable it. ”

  • Ayaskant Swain

    A correction needed in the above post- The CMS collector is enabled with the command-line option -XX:+UseConcMarkSweepGC.

  • willowandy

    > Hit me up in the comments section

    Do all of these now support passing freed memory back to the OS or only G1GC, or somewhere in between? Thank you.

  • Surya b

    very nice… I really like your blog…Universal Garbage Collection log analyzer that parses any format of Garbage collection logs and generates WOW graphs & AHA metrics. Inbuilt intelligence has ability to discover any sort of memory problems.Excellence & Simplicity Devops tools for cloud. Gceasy