Recently I was asked in one the interviews :
What is the cost of Garbage collection in java ?
I answered as : By collecting ununsed objects, we can free up the heap space , in order to avoid OutOfMemoryError.
but it seemed to me like , the interviewer was not satisfied.
Kindly help me in knowing costs of GC in Java.
Garbage collection involves complex memory management and may requires important CPU resources ... There are various GC strategies based on the type of application and the JVM you are running.
If your application creates and releases large amounts of memory, garbage collection may take "some" non negligible amount of CPU and may even lock your application for some time.
Depending on the purpose of your application, this may be acceptable or not. You have to chose a GC strategy based on your needs. This article explains the 5 strategies of OpenJDK (https://dzone.com/articles/choosing-the-right-gc).
Choosing the correct GC strategy is a compromise between periodical JVM blocking and overall efficiency and performance.
According to:
9 Garbage-First Garbage Collector
and:
G1: Java's Garbage First Garbage Collector
G1 targeted for multiprocessor machines with large memories.
Those 2 papers (and other web papers), does not describe why we need:
a. large memories
b. multiprocessor (I assume this need due to concurrent & parallel)
What is the technical explanation for those requirements ?
It's other way around. G1 is not targeted for large memories. If your application demands large heap size, G1 is effective.
Why your application demands large heaps? It's depend on business requirements and specific needs of application. You may load huge set of master data Or you may use in - memory caching to reduce response times. Think of big data applications,(Spark,Hadoop) which are processing teta bytes of data and use memory for processing.
Multiprocessors machines have more processing powers and effective for parallel execution of different tasks. Large heap applications obviously demands more processing power.
By setting Max pause time goal, G1GC try to meet that goal. Compared to other algorithms, by default G1GC spends 10% of time in garbage collection activities. You have to fine tune the parameters properly to achieve your pause time goals.
This related question is helpful to get some more insight into G1GC: Java 7 (JDK 7) garbage collection and documentation on G1
G1 is the only collection algorithm in the hotspot VM that can deal with very large heaps efficiently. However, a large heap is NOT a requirement but instead the G1 is built for situations where your application needs a very large heap. In low-heap situations, it is still outperformed by older algorithms. The same is true for the number of processors.
Almost everyone eventually runs into GC issues with Java.
Is there a cookbook guide or semi-automated tool to tune GC for Java?
My rationale is this:
Almost anyone eventually has these problems
There are many possible factors (say 20) out of which only a few affect your problem.
Most people don't know how to identify the key factors so GC tuning is more like a black art than a science.
Not everyone uses a HotSpot VM. Different Sun versions have different GC characteristics.
There is little incentive to experiment (like run the VM with slightly different settings every day to see how they play out).
So the question really is: Is there something that I can use in a check-list manner? Or maybe even a tool that analyzes GC logs or heap dumps and gives me specific hints where to look (instead of telling me "95% of the data is allocated in objects of the type byte[]" which is basically useless).
Related questions:
Appropriate Tomcat 5.5 start-up parameters to tune JVM for extremely high demand, large heap web application? which is very specific. My question is more wide.
What are the best garbage collection settings for client side? Again very narrow scope
Does anyone know of a good guide to configure GC in Java? HotSpot only
JVM memory management & garbage collection book? is 80% there but I'm missing the checklist/cookbook/for-dummies approach.
Out of various resources I have compiled a sanity checklist that I use to analyze GC behavior and performance of my applications. These guidelines are general and apply to any vendor-specific JVM but contain also HotspotVM-specific information for illustration.
Disable Explicit GC. Explicit GC is a bad coding practice, it never helps. Use -XX:+DisableExplicitGC.
Enable Full GC logging. Lightweight yet powerful.
Compute Live Data Set, Allocation Rate, and Promotion Rate. This will tell you if you need a bigger Heap or if your eg. Young Gen is too small, or if your Survivor spaces are overflowing, etc.
Compute total GC time, it should be <5% of total running time.
Use -XX:+PrintTenuringDistribution -XX:+UnlockDiagnosticVMOptions -XX:+LogVMOutput -XX:LogFile=jvm.log -XX:+HeapDumpOnOutOfMemoryError -Xloggc:gc.log -XX:+PrintGCTimeStamps -XX:+PrintGCDetails -showversion
Consider additional means of collecting information about your GC. Logging is fine but there are sometimes available lightweight command-line tools that will give you even more insight. Eg. jstat for Hotspot which will show you occupation/capacity of Eden, Survivor and Old Gen.
Collect Class Histograms These are lightweigh and will show you the content of the heap. You can take snapshots whenever you notice some strange GC activity, or you can take them before/after Full GC:
Content of the OldGen space: You can find out which objects reside in the OldGen. You need to print histograms before and after Full GC. And since a YoungGen collection is executed before the Full GC, these Histograms will show you the content of the Old generation. Use -XX:+PrintClassHistogramBeforeFullGC -XX:+PrintClassHistogramAfterFullGC.
Detecting prematurely promoted objects: To determine if any instances are promoted early, you need to study the Histograms to see which classes are expected to reside in the OldGen and which classes should be seen only in the YoungGen. This cannot be done automatically, you need to reason about the purpose of each class and its instance to determine if the object is temporary or not.
Consider different GC Algorithm. The VMs usually come with several different GC implementations that are providing various tradeoffs : throughput, footprint, pause-less/short-pauses, real-time, etc. Consider the options you have and pick the one that suites your needs.
Beware of finalize(). Check that GC keeps up with classes using finalize(). The execution of this method may be quite costly and this can impact GC and application throughput.
Heap Dumps. This is the first step that is heavyweight and will impact the running application. Collect the Heap Dump to further study the heap content or to confirm a hypothesis observed in step 4.
Resources used:
Books:
Java Performance - practical guide
The Garbage Collection Handbook - theory explained
Talks/Articles:
Java One 2012 Advanced JVM Tuning
From Java code to Java heap
Java One 2012 G1 Garbage Collector Performance Tuning
Garbage Collection Tuning Guide
Mailing Lists:
OpenJDK Hotspot GC Use
References for various GC information:
Oracle
Tuning Garbage Collection with the 5.0 Java[tm] Virtual Machine
and this also
Java SE 6 HotSpot[tm] Virtual Machine Garbage Collection Tuning
IBM
Fine Tuning Garbage Collection [link dead]
Extensible Verbose Toolkit
SAP JVM
Memory Management (Garbage Collection)
Detecting Memory Leaks
Detecting Hanging / Looping VMs
Analyzing Out-of-Memory Situations
Sorry I don't know much about SAP but have provided some things I have found.
As for a cookbook, tuning is most likely application specific at this level, but it is an interesting topic.
ADDENDUM
You also mentioned analysis tools. Some candidates are listed here:
Know of any Java garbage collection log analysis tools?
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Does anyone have experience with using very large heaps, 12 GB or higher in Java?
Does the GC make the program unusable?
What GC params do you use?
Which JVM, Sun or BEA would be better suited for this?
Which platform, Linux or Windows, performs better under such conditions?
In the case of Windows is there any performance difference to be had between 64 bit Vista and XP under such high memory loads?
If your application is not interactive, and GC pauses are not an issue for you, there shouldn't be any problem for 64-bit Java to handle very large heaps, even in hundreds of GBs. We also haven't noticed any stability issues on either Windows or Linux.
However, when you need to keep GC pauses low, things get really nasty:
Forget the default throughput, stop-the-world GC. It will pause you application for several tens of seconds for moderate heaps (< ~30 GB) and several minutes for large ones (> ~30 GB). And buying faster DIMMs won't help.
The best bet is probably the CMS collector, enabled by -XX:+UseConcMarkSweepGC. The CMS garbage collector stops the application only for the initial marking phase and remarking phases. For very small heaps like < 4 GB this is usually not a problem, but for an application that creates a lot of garbage and a large heap, the remarking phase can take quite a long time - usually much less then full stop-the-world, but still can be a problem for very large heaps.
When the CMS garbage collector is not fast enough to finish operation before the tenured generation fills up, it falls back to standard stop-the-world GC. Expect ~30 or more second long pauses for heaps of size 16 GB. You can try to avoid this keeping the long-lived garbage production rate of you application as low as possible. Note that the higher the number of the cores running your application is, the bigger is getting this problem, because the CMS utilizes only one core. Obviously, beware there is no guarantee the CMS does not fall back to the STW collector. And when it does, it usually happens at the peak loads, and your application is dead for several seconds. You would probably not want to sign an SLA for such a configuration.
Well, there is that new G1 thing. It is theoretically designed to avoid the problems with CMS, but we have tried it and observed that:
Its throughput is worse than that of CMS.
It theoretically should avoid collecting the popular blocks of memory first, however it soon reaches a state where almost all blocks are "popular", and the assumptions it is based on simply stop working.
Finally, the stop-the-world fallback still exists for G1; ask Oracle, when that code is supposed to be run. If they say "never", ask them, why the code is there. So IMHO G1 really doesn't make the huge heap problem of Java go away, it only makes it (arguably) a little smaller.
If you have bucks for a big server with big memory, you have probably also bucks for a good, commercial hardware accelerated, pauseless GC technology, like the one offered by Azul. We have one of their servers with 384 GB RAM and it really works fine - no pauses, 0-lines of stop-the-world code in the GC.
Write the damn part of your application that requires lots of memory in C++, like LinkedIn did with social graph processing. You still won't avoid all the problems by doing this (e.g. heap fragmentation), but it would be definitely easier to keep the pauses low.
I am CEO of Azul Systems so I am obviously biased in my opinion on this topic! :) That being said...
Azul's CTO, Gil Tene, has a nice overview of the problems associated with Garbage Collection and a review of various solutions in his Understanding Java Garbage Collection and What You Can Do about It presentation, and there's additional detail in this article: http://www.infoq.com/articles/azul_gc_in_detail.
Azul's C4 Garbage Collector in our Zing JVM is both parallel and concurrent, and uses the same GC mechanism for both the new and old generations, working concurrently and compacting in both cases. Most importantly, C4 has no stop-the-world fall back. All compaction is performed concurrently with the running application. We have customers running very large (hundreds of GBytes) with worse case GC pause times of <10 msec, and depending on the application often times less than 1-2 msec.
The problem with CMS and G1 is that at some point Java heap memory must be compacted, and both of those garbage collectors stop-the-world/STW (i.e. pause the application) to perform compaction. So while CMS and G1 can push out STW pauses, they don't eliminate them. Azul's C4, however, does completely eliminate STW pauses and that's why Zing has such low GC pauses even for gigantic heap sizes.
We have an application that we allocate 12-16 Gb for but it really only reaches 8-10 during normal operation. We use the Sun JVM (tried IBMs and it was a bit of a disaster but that just might have been ignorance on our part...I have friends that swear by it--that work at IBM). As long as you give your app breathing room, the JVM can handle large heap sizes with not too much GC. Plenty of 'extra' memory is key.
Linux is almost always more stable than Windows and when it is not stable it is a hell of a lot easier to figure out why. Solaris is rock solid as well and you get DTrace too :)
With these kind of loads, why on earth would you be using Vista or XP? You are just asking for trouble.
We don't do anything fancy with the GC params. We do set the minimum allocation to be equal to the maximum so it is not constantly trying to resize but that is it.
I have used over 60 GB heap sizes on two different applications under Linux and Solaris respectively using 64-bit versions (obviously) of the Sun 1.6 JVM.
I never encountered garbage collection problems with the Linux-based application except when pushing up near the heap size limit. To avoid the thrashing problems inherent to that scenario (too much time spent doing garbage collection), I simply optimized memory usage throughout the program so that peak usage was about 5-10% below a 64 GB heap size limit.
With a different application running under Solaris, however, I encountered significant garbage-collection problems which made it necessary to do a lot of tweaking. This consisted primarily of three steps:
Enabling/forcing use of the parallel garbage collector via the -XX:+UseParallelGC -XX:+UseParallelOldGC JVM options, as well as controlling the number of GC threads used via the -XX:ParallelGCThreads option. See "Java SE 6 HotSpot Virtual Machine Garbage Collection Tuning" for more details.
Extensive and seemingly ridiculous setting of local variables to "null" after they are no longer needed. Most of these were variables that should have been eligible for garbage collection after going out of scope, and they were not memory leak situations since the references were not copied. However, this "hand-holding" strategy to aid garbage collection was inexplicably necessary for some reason for this application under the Solaris platform in question.
Selective use of the System.gc() method call in key code sections after extensive periods of temporary object allocation. I'm aware of the standard caveats against using these calls, and the argument that they should normally be unnecessary, but I found them to be critical in taming garbage collection when running this memory-intensive application.
The three above steps made it feasible to keep this application contained and running productively at around 60 GB heap usage instead of growing out of control up into the 128 GB heap size limit that was in place. The parallel garbage collector in particular was very helpful since major garbage-collection cycles are expensive when there are a lot of objects, i.e., the time required for major garbage collection is a function of the number of objects in the heap.
I cannot comment on other platform-specific issues at this scale, nor have I used non-Sun (Oracle) JVMs.
12Gb should be no problem with a decent JVM implementation such as Sun's Hotspot.
I would advice you to use the Concurrent Mark and Sweep colllector ( -XX:+UseConcMarkSweepGC) when using a SUN VM.Otherwies you may face long "stop the world" phases, were all threads are stopped during a GC.
The OS should not make a big difference for the GC performance.
You will need of course a 64 bit OS and a machine with enough physical RAM.
I recommend also considering taking a heap dump and see where memory usage can be improved in your app and analyzing the dump in something such as Eclipse's MAT . There are a few articles on the MAT page on getting started in looking for memory leaks. You can use jmap to obtain the dump with something such as ...
jmap -heap:format=b pid
As mentioned above, if you have a non-interactive program, the default (compacting) garbage collector (GC) should work well. If you have an interactive program, and you (1) don't allocate memory faster than the GC can keep up, and (2) don't create temporary objects (or collections of objects) that are too big (relative to the total maximum JVM memory) for the GC to work around, then CMS is for you.
You run into trouble if you have an interactive program where the GC doesn't have enough breathing room. That's true regardless of how much memory you have, but the more memory you have, the worse it gets. That's because when you get too low on memory, CMS will run out of memory, whereas the compacting GCs (including G1) will pause everything until all the memory has been checked for garbage. This stop-the-world pause gets bigger the more memory you have. Trust me, you don't want your servlets to pause for over a minute. I wrote a detailed StackOverflow answer about these pauses in G1.
Since then, my company has switched to Azul Zing. It still can't handle the case where your app really needs more memory than you've got, but up until that very moment it runs like a dream.
But, of course, Zing isn't free and its special sauce is patented. If you have far more time than money, try rewriting your app to use a cluster of JVMs.
On the horizon, Oracle is working on a high-performance GC for multi-gigabyte heaps. However, as of today that's not an option.
If you switch to 64-bit you will use more memory. Pointers become 8 bytes instead of 4. If you are creating lots of objects this can be noticeable seeing as every object is a reference (pointer).
I have recently allocated 15GB of memory in Java using the Sun 1.6 JVM with no problems. Though it is all only allocated once. Not much more memory is allocated or released after the initial amount. This was on a Linux but I imagine the Sun JVM will work just as well on 64-bit Windows.
You should try running visualgc against your app. It´s a heap visualization tool that´s part of the jvmstat download at http://java.sun.com/performance/jvmstat/
It is a lot easier than reading GC logs.
It quickly helps you understand how the parts (generations) of the heap are working. While your total heap may be 10GB, the various parts of the heap will be much smaller. GCs in the Eden portion of the heap are relatively cheap, while full GCs in the old generation are expensive. Sizing your heap so that that the Eden is large and the old generation is hardly ever touched is a good strategy. This may result in a very large overall heap, but what the heck, if the JVM never touches the page, it´s just a virtual page, and doesn´t have to take up RAM.
A couple of years ago, I compared JRockit and the Sun JVM for a 12G heap. JRockit won, and Linux hugepages support made our test run 20% faster. YMMV as our test was very processor/memory intensive and was primarily single-threaded.
here's an article on gc FROM one of Java Champions --
http://kirk.blog-city.com/is_your_concurrent_collector_failing_you.htm
Kirk, the author writes
"Send me your GC logs
I'm currently interested in studying Sun JVM produced GC logs. Since these logs contain no business relevent information it should be ease concerns about protecting proriatary information. All I ask that with the log you mention the OS, complete version information for the JRE, and any heap/gc related command line switches that you have set. I'd also like to know if you are running Grails/Groovey, JRuby, Scala or something other than or along side Java. The best setting is -Xloggc:. Please be aware that this log does not roll over when it reaches your OS size limit. If I find anything interesting I'll be happy to give you a very quick synopsis in return. "
An article from Sun on Java 6 can help you: https://www.oracle.com/java/technologies/javase/troubleshooting-javase.html
The max memory that XP can address is 4 gig(here). So you may not want to use XP for that(use a 64 bit os).
sun has had an itanium 64-bit jvm for a while although itanium is not a popular destination. The solaris and linux 64-bit JVMs should be what you should be after.
Some questions
1) is your application stable ?
2) have you already tested the app in a 32 bit JVM ?
3) is it OK to run multiple JVMs on the same box ?
I would expect the 64-bit OS from windows to get stable in about a year or so but until then, solaris/linux might be better bet.
I'm exploring the possibility of running a Java app on a machine with very large amounts of RAM (anywhere from 300GB to 15TB, probably on an SGI Altix 4700 machine), and I'm curious as to how Java's GC is likely to perform in this scenario.
I've heard that IBM's or JRockit's JVMs may be better suited to this than Sun's. Does anyone know of any research or data on JVM performance in this situation?
On the Sun JVM, you can use the option -XX:UseConcMarkSweepGC to turn on the Concurrent mark and sweep Collector, which will avoid the "stop the world" phases of the default GC algorithm almost completely, at the cost of a little bit more overhead.
The advise to use more than on VM on such a machine is IMHO outdated.
In real world applications you often have enough shared data so that the performance with the CMS and one JVM is better.
The question is: do you want to run within a single process (JVM) or not? If you do, then you're going to have a problem. Refer to Tuning Java Virtual Machines, Oracle Coherence User Guide and similar documentation. The rule of thumb I've operated by is try and avoid heaps larger than 1GB. Whereas a 512MB-1GB full GC might take less than a second. A 2-4GB full GC could potentially take 5 seconds or longer. Obvioiusly this depends on many factors but the moral of the story is that GC overhead does not scale linearly and once you get into the one second range performance then degrades rapidly.
Sun's JVM allows you to configure and optimize the heck out of garbage collection, but it's a science unto itself:
http://java.sun.com/javase/technologies/hotspot/gc/gc_tuning_6.html
You might have to do some reading and research, but for that kind of machine, GC settings optimized for the machine and application probably make a big difference.
Since 5.0 the Hotspot JVM uses a concept know as Ergonomics to try to optimise the memory usage. This is based on more than just the sheer amount of memory available and effects heap sizes, generation sizes and garbage collection algorithms.
Start by having a read of this, which explains Ergonomics and more:
https://www.oracle.com/technetwork/java/javase/memorymanagement-whitepaper-150215.pdf
There's also a guy called Brian Goetz that's written numerous articles about how Java allocates and uses memory, all of which and more can be found here:
http://www.briangoetz.com/pubs.html
This is not at all answering your question, but if you plan do deploy a huge Java app you might be interested in looking into Azul Systems appliances. They say to be able to garbage-collect without creating a pause in the application up to a single 670 GB heap.
You might want to consider running a virtual Terracotta cluster on this machine.
The only people who can really tell you are SGI. Super computers don't behave like regular servers only bigger.
However, I have found that Java performs best when memory is local to the processors accessing it. Note: the GC needs to be able to walk the whole memory end to end. This means it doesn't scale well if you have a design which is like lots of computers stuck together which may be the case here. The memory module size is 32 GB, so you may get better performance if you limit your JVM to comfortably fit into this size.
The accepted answer for this post is rather old and is now outdated. As of September 2014, if you are using Java 7, you should probably switch to the GC1 collector. From the Java 7 update 4 release notes:
http://www.oracle.com/technetwork/java/javase/7u4-relnotes-1575007.html
"The G1 collector is targeted for applications that fully utilize the large amount of memory available in today's multiprocessor servers, while still keeping garbage collection latencies under control. Applications that require a large heap, have a big active data set, have bursty or non-uniform workloads or suffer from long Garbage Collection induced latencies should benefit from switching to G1."
Surely the answer as to how the GC's going to perform is "who cares?" ;-)