In Java, the concurrent mode failure means that the concurrent collector failed to free up enough memory space form tenured and permanent gen and has to give up and let the full stop-the-world gc kicks in. The end result could be very expensive.
I understand this concept but never had a good comprehensive understanding of
A) what could cause a concurrent mode failure and
B) what's the solution?.
This sort of unclearness leads me to write/debug code without much of hints in mind and often has to shop around those performance flags from Foo to Bar without particular reasons, just have to try.
I'd like to learn from developers here how your experience is? If you had encountered such performance issue, what was the cause and how you addressed it?
If you have coding recommendations, please don't be too general. Thanks!
The first thing about CMS that I have learned is it needs more memory than the other collectors, about 25 to 50% more is a good starting point. This helps you avoid fragmentation, since CMS does not do any compaction like the stop the world collectors would. Second, do things that help the garbage collector; Integer.valueOf instead of new Integer, get rid of anonymous classes, make sure inner classes are not accessing inaccessible things (private in the outer class) stuff like that. The less garbage the better. FindBugs and not ignoring warnings will help a lot with this.
As far as tuning, I have found that you need to try several things:
-XX:+UseConcMarkSweepGC
Tells JVM to use CMS in tenured gen.
Fix the size of your heap: -Xmx2048m -Xms2048m This prevents GC from having to do things like grow and shrink the heap.
-XX:+UseParNewGC
use parallel instead of serial collection in the young generation. This will speed up your minor collections, especially if you have a very large young gen configured. A large young generation is generally good, but don't go more than half of the old gen size.
-XX:ParallelCMSThreads=X
set the number of threads that CMS will use when it is doing things that can be done in parallel.
-XX:+CMSParallelRemarkEnabled remark is serial by default, this can speed you up.
-XX:+CMSIncrementalMode allows application to run more by pasuing GC between phases
-XX:+CMSIncrementalPacing allows JVM to figure change how often it collects over time
-XX:CMSIncrementalDutyCycleMin=X Minimm amount of time spent doing GC
-XX:CMSIncrementalDutyCycle=X Start by doing GC this % of the time
-XX:CMSIncrementalSafetyFactor=X
I have found that you can get generally low pause times if you set it up so that it is basically always collecting. Since most of the work is done in parallel, you end up with basically regular predictable pauses.
-XX:CMSFullGCsBeforeCompaction=1
This one is very important. It tells the CMS collector to always complete the collection before it starts a new one. Without this, you can run into the situation where it throws a bunch of work away and starts again.
-XX:+CMSClassUnloadingEnabled
By default, CMS will let your PermGen grow till it kills your app a few weeks from now. This stops that. Your PermGen would only be growing though if you make use of Reflection, or are misusing String.intern, or doing something bad with a class loader, or a few other things.
Survivor ratio and tenuring theshold can also be played with, depending on if you have long or short lived objects, and how much object copying between survivor spaces you can live with. If you know all your objects are going to stick around, you can configure zero sized survivor spaces, and anything that survives one young gen collection will be immediately tenured.
Quoted from "Understanding Concurrent Mark Sweep Garbage Collector Logs"
The concurrent mode failure can either
be avoided by increasing the tenured
generation size or initiating the CMS
collection at a lesser heap occupancy
by setting
CMSInitiatingOccupancyFraction to a
lower value
However, if there is really a memory leak in your application, you're just buying time.
If you need fast restart and recovery and prefer a 'die fast' approach I would suggest not using CMS at all. I would stick with '-XX:+UseParallelGC'.
From "Garbage Collector Ergonomics"
The parallel garbage collector
(UseParallelGC) throws an
out-of-memory exception if an
excessive amount of time is being
spent collecting a small amount of the
heap. To avoid this exception, you can
increase the size of the heap. You can
also set the parameters
-XX:GCTimeLimit=time-limit and -XX:GCHeapFreeLimit=space-limit
Sometimes OOM pretty quick and got killed, sometime suffers long gc period (last time was over 10 hours).
It sounds to me like a memory leak is at the root of your problems.
A CMS failure won't (as I understand it) cause an OOM. Rather a CMS failure happens because the JVM needs to do too many collections too quickly, and CMS could not keep up. One situation where lots of collection cycles happen in a short period is when your heap is nearly full.
The really long GC time sounds weird ... but is theoretically possible if your machine was thrashing horribly. However, a long period of repeated GCs is quite plausible if your heap is very nearly full.
You can configure the GC to give up when the heap is 1) at max size and 2) still close to full after a full GC has completed. Try doing this if you haven't done so already. It won't cure your problems, but at least your JVM will get the OOM quickly, allowing a faster service restart and recovery.
EDIT - the option to do this is -XX:GCHeapFreeLimit=nnn where nnn is a number between 0 and 100 giving the minimum percentage of the heap that must be free after the GC. The default is 2. The option is listed in the aptly titled "The most complete list of -XX options for Java 6 JVM" page. (There are lots of -XX options listed there that don't appear in the Sun documentation. Unfortunately the page provides few details on what the options actually do.)
You should probably start looking to see if your application / webapp has memory leaks. If it has, your problems won't go away unless those leaks are found and fixed. In the long term, fiddling with the Hotspot GC options won't fix memory leaks.
I've found using -XX:PretenureSizeThreshold=1m to make 'large' object go immediately to tenured space greatly reduced my young GC and concurrent mode failures since it tends not to try to dump the young + 1 survivor amount of data (xmn=1536m survivorratio=3 maxTenuringThreashould=5) before a full CMS cycle can complete. Yes my survivor space is large, but about once ever 2 days something comes in the app that will need it (and we run 12 app servers each day for 1 app).
Related
We inherited a system which runs in production and started to fail every 10 hours recently. Basically, our internal software marks the system that is has failed if it is unresponsive for a minute. We found that our problem that our Full GC cycles last for 1.5 minutes, we use 30 GB heap. Now the problem is that we cannot optimize a lot in a short period of time and we cannot partition of our service quickly but we need to get rid of 1.5 minutes pauses as soon as possible as our system fails because of these pauses in production. For us, an acceptable delay is 20 milliseconds but not more. What will be the quickest way to tweak the system? Reduce the heap to trigger GCs frequently? Use System.gc() hints? Any other solutions? We use Java 8 default settings and we have more and more users - i.e. more and more objects created.
Some GC stat
You have a lot of retained data. There is a few options which are worth considering.
increase the heap to 32 GB, this has little impact if you have free memory. Looking again at your totals it appears you are using 32 GB rather than 30 GB, so this might not help.
if you don't have plenty of free memory, it is possible a small portion of your heap is being swapped as this can increase full GC times dramatically.
there might be some simple ways to make the data structures more compact. e.g. use compact strings, use primitives instead of wrappers e.g. long for a timestamp instead of Date or LocalDateTime. (long is about 1/8th the size)
if neither of these help, try moving some of the data off heap. e.g. Chronicle Map is a ConcurrentMap which uses off heap memory can can reduce you GC times dramatically. i.e. there is no GC overhead for data stored off heap. How easy this is to add highly depends on how your data is structured.
I suggest analysing how your data is structured to see if there is any easy ways to make it more efficient.
There is no one-size-fits-all magic bullet solution to your problem: you'll need to have a good handle on your application's allocation and liveness patterns, and you'll need to know how that interacts with the specific garbage collection algorithm you are running (function of version of Java and command line flags passed to java).
Broadly speaking, a Full GC (that succeeds in reclaiming lots of space) means that lots of objects are surviving the minor collections (but aren't being leaked). Start by looking at the size of your Eden and Survivor spaces: if the Eden is too small, minor collections will run very frequently, and perhaps you aren't giving an object a chance to die before its tenuring threshold is reached. If the Survivors are too small, objects are going to be promoted into the Old gen prematurely.
GC tuning is a bit of an art: you run your app, study the results, tweak some parameters, and run it again. As such, you will need a benchmark version of your application, one which behaves as close as possible to the production one but which hopefully doesn't need 10 hours to cause a full GC.
As you stated that you are running Java 8 with the default settings, I believe that means that your Old collections are running with a Serial collector. You might see some very quick improvements by switching to a Parallel collector for the Old generation (-XX:+UseParallelOldGC). While this might reduce the 1.5 minute pause to some number of seconds (depending on the number of cores on your box, and the number of threads you specify for GC), this will not reduce your max pause to to 20ms.
When this happened to me, it was due to a memory leak caused by a static variable eating up memory. I would go through all recent code changes and look for any possible memory leaks.
I have a Java application that waits for the user to hit a key and then runs a task. Once done, it goes back and waits again. I was looking at memory profile for this application with jvisualvm, and it showed an increasing pattern.
Committed memory size is 16MB.
Used memory, on application startup, was 2.7 MB, and then it climbed with intermediate drops (garbage collection). Once this sawtooth pattern approached close to 16MB, a major drop occurred and the memory usage fell close to 4 MB. This major drop point has been increasing though. 4MB, 6MB, 8MB. The usage never goes beyond 16 MB but the whole sawtooth pattern is on a climb towards 16 MB.
Do I have a memory leak?
Since this is my first time posting to StackOverflow, do not have enough reputation to post an image.
Modern SunOracle JVMs use what is called a generational garbage collector:
When the collector runs it first tries a partial collection only releases memory that was allocated recently
recently created objects that are still active get 'promoted'
Once an object has been promoted a few times, it will no longer get cleaned up by partial collections even after it is ready for collection
These objects, called tenured, are only cleaned up when a full collection becomes necessary in order to make enough room for the program to continue running
So basically, bits of your program that stick around long enough to get missed by the fast 'partial' collections will hang around until JVM decides it has to do a full collection. If you let it go long enough you should eventually see the full collection happen and usage drop back down to your original starting point.
If that never happens and you eventually get an Out Of Memory exception, then you probably have a memory leak :)
That kind of sawtooth pattern is commonly observed and is not an indication of memory leak.
Because garbage collecting in big chunks is more efficient than constantly collecting small amounts, the JVM does the collecting in batches. That's why you see this pattern.
As stated by others, this behavior is normal. This is a good description of the garbage collection process. To summarize, the JVM usese a generational garbage collector. The vast majority of objects are very short-lived, and those that survive longer tend to last much longer. Knowing this, the GC will check the newer generation first to avoid having to repeatedly check the older objects which are less likely to be inaccessible. After a period of time, the survivors move to the older generation. This increasing saw-tooth is exactly what you're seeing- the rising troughs are due to the older generation growing larger as the survivors are being moved to it. If your program ran long enough eventually checking the newer generation wouldn't free up enough memory and it would have to GC the old generation as well.
Hope that helps.
I am unsure whether there is a generic answer for this, but I was wondering what the normal Java GC pattern and java heap space usage looks like. I am testing my Java 1.6 application using JMeter. I am collecting JMX GC logs and plotting them with JMeter JMX GC and Memory plugin extension. The GC pattern looks quite stable with most GC operations being 30-40ms, occasional 90ms. The memory consumption goes in a saw-tooth pattern. The JHS usage grows constantly upwards e.g. to 3GB and every 40 minutes the memory usage does a free-fall drop down to around 1GB. The max-min delta however grows, so the sawtooth height constantly grows. Does it do a full GC every 40mins?
Most of your descriptions in general, are how the GC works. However, none of your specific observations, especially numbers, hold for general case.
To start with, each JVM has one or several GC implementations and you could choose which one to use. Take the mostly applied one i.e. SUN JVM (I like to call it this way) and the common server GC pattern as example.
Firstly, the memory are divided into 4 regions.
A young generation which holds all of the recently created objects. When this generation is full, GC does a stop-the-world collection by stopping your program from working, execute a black-gray-white algorithm and get the obselete objects and remove them. So this is your 30-40 ms.
If an object survived a certain rounds of GC in the young gen, it would be moved into a swap generation. The swap generation holds the objects until another number of GCs - then move them to the old generation. There are 2 swap generations which does a double buffering kind of thing to facilitate the young gen to work faster. If young gen dumps stuff to swap gen and found swap gen is mostly full, a GC would happen on swap gen and potentially move the survived objects to old gen. This most likely makes your 90ms, though I am not 100% sure how swap gen works. Someone correct me if I am wrong.
All the objects survived swap gen would be moved to the old generation. The old generation would only be GC-ed until it's mostly full. In your case, every 40 min.
There is another "permanent gen" which is used to load your jar target byte code and resources.
All size of the areas can be adjusted by JVM parameters.
You can try to use VisualVM which would give you a dynamic idea of how it works.
P.S. not all JVM / GC works the same way. If you use G1 collector, or JRocket, it might happens slightly different, but the general idea holds.
Java GC work in terms of generations of objects. There are young, tenure and permament generations. It seems like in your case: every 30-40ms GC process only young generation (and transfers survived objects into tenure generation). And every 40 mins it performs full collecting (it causes stop-the-world pause). Note: it happens not by time, but by percentage of used memory.
There are several JVM options, which allows you to chose generation's sizes, type of GC (there are several algorithms for GC, in java 1.6 Serial GC is used by default, for example -XX:-UseConcMarkSweepGC), parameters of GC work.
You'd better try to find good articles about generations and different types of GC (algorithms are really different, some of them allow to avoid stop-the-world pauses at all!)
yes, most likely. Instead of guessing you can use jstat to monitor your GCs.
I suggest you use a memory profiler to ensure there is nothing simple you can do ti improve the amount of garbage you are producing.
BTW, If you increase the size of the young generation, you can reduce how much garbage makes it into the tenured space reducing the frequency of full collections. You may find you less than one full collection per day if you tune it enough.
For a more extreme case, I have tuned a trading system to less than one collection per day (minor or major)
Page 6 of the the document Memory Management in the Java
HotSpot™ Virtual Machine contains the following paragraphs:
Young generation collections occur relatively frequently and are
efficient and fast because the young generation space is usually small
and likely to contain a lot of objects that are no longer referenced.
Objects that survive some number of young generation collections are
eventually promoted, or tenured, to the
old generation. See Figure 1. This generation is typically larger than the young generation and its occupancy
grows more slowly. As a result, old generation collections are infrequent, but take significantly longer to
complete
Could someone please define what "frequent" and "infrequent" mean in the statements above? Are we talking microseconds, milliseconds, minutes, days?
It is not possible to give a definite answer to this. It really depends on a lot of factors, including the platform (JVM version, settings, etc), the application, and the workload.
At one extreme, it is possible for an application to never trigger a garbage collector. It might simply sit there doing nothing, or it might perform an extremely long computation in which no objects are created after the JVM initialization and application startup.
At the other extreme it is theoretically possible for one garbage collection end and another one to start within few nanoseconds. For example, this could happen if your application is in the last stages of dying from a full heap, or if it is allocating pathologically large arrays.
So:
Are we talking microseconds, milliseconds, minutes, days?
Possibly all of the above, though the first two would definitely be troubling if you observed them in practice.
A well behaved application should not run the GC too often. If your application is triggering a young space collection more than once or twice a second, then this could lead to performance problems. And too frequent "full" collections is worse because their impact is greater. However, it is certainly plausible for a poorly designed / implemented application to behave like this.
There is also the issue that the interval between GC runs is not always meaningful. For instance some of the HotSpot GCs actually have GC threads running concurrently with normal application threads. If you have enough cores, enough RAM and enough memory bus bandwidth, then a constantly running concurrent GC may not appreciably affect application performance.
Terminology note:
Strictly speaking a concurrent GC is one where the GC can run at the same time as the application threads.
Strictly speaking a parallel GC is one where the GC itself uses multiple threads.
A GC can be concurrent without being parallel, and vice versa.
Its a relative term. Young collections could be many times a seconds up to a few hours. Old generations collections can be every few seconds, up to daily. You should expect to have many more young collections than old collections in a most systems.
Its highly unlikely to be many days. If the GC occurs too often e.g. << 100 ms apart you get get a OutOfMemoryError: GC Overhead Exceeded as the JVM prevenets that from happening.
As it is, the terms "frequent" , "infrequent" are relative. And the timings are, in fact, not fixed. It depends on the system in question. It depends on lots of things like:
Your heap size and settings for different parts of the heap (young, old gen, perm gen)
Your application's memory behaviour. How many objects does it create and how fast? how long those objects are referenced etc?
If your application is monster memory eater, gc would run as if its running for its life. If your application does not demand too much of memory, then gc would run at intervals decided by how full the memory is.
TL DL: "Frequent" and "infrequent" are relative terms that depends on the memory allocation rate and the heap size. If you want a precise answer, you need to measure it yourself for your particular application.
Let's say your app has two modes, mode-1 allocates memory and does computation and mode-2 sits idle.
If mode-1 allocation is smaller than the heap available, no gc need to occur until it finishes. Maybe it used so little RAM that it could do a second round of mode-1 without collection. However, eventually you'll run out of free heap, and jvm will perform an "infrequent" collection.
However, if mode-1 allocation is a significant fraction of, or larger, than the young-generation heap, collection would happen more "frequently". During the young gen collection, allocations that survive (imagine data is needed through the entire mode-1 operation), will be promoted to old-gen, giving the young-gen more room. Young-gen allocation and collection can now continue. Eventually old-gen heap would run out, and must be collected, thus "infrequently".
So then, how frequent is frequent? It depends on the allocation rate and the heap size. If jvm is bumping into the heap limit often, it'll collect often. If there is plenty of heap (let's say 100GB), then jvm doesn't need to collect for a long long time. The down side is that when it finally does a collection, it might take a long time to free 100GB, stopping the jvm for many seconds (or minutes!). The current JVMs are smarter than that and would occasionanlly force a collection (preferably in mode-2). And with parallel collectors, it could happen all the time if necessary.
Ultimately, the frequency is task and heap dependent, as well as how various vm parameters are set. If you want a precise answer, you must measure them yourself for your particular application.
Because spec says "relatively frequently" and infrequent (regarding Young generation), we can't estimate the frequency in absolute units like microseconds, milliseconds, minutes or days
I am building a Java web app, using the Play! Framework. I'm hosting it on playapps.net. I have been puzzling for a while over the provided graphs of memory consumption. Here is a sample:
The graph comes from a period of consistent but nominal activity. I did nothing to trigger the falloff in memory, so I presume this occurred because the garbage collector ran as it has almost reached its allowable memory consumption.
My questions:
Is it fair for me to assume that my application does not have a memory leak, as it appears that all the memory is correctly reclaimed by the garbage collector when it does run?
(from the title) Why is java waiting until the last possible second to run the garbage collector? I am seeing significant performance degradation as the memory consumption grows to the top fourth of the graph.
If my assertions above are correct, then how can I go about fixing this issue? The other posts I have read on SO seem opposed to calls to System.gc(), ranging from neutral ("it's only a request to run GC, so the JVM may just ignore you") to outright opposed ("code that relies on System.gc() is fundamentally broken"). Or am I off base here, and I should be looking for defects in my own code that is causing this behavior and intermittent performance loss?
UPDATE
I have opened a discussion on PlayApps.net pointing to this question and mentioning some of the points here; specifically #Affe's comment regarding the settings for a full GC being set very conservatively, and #G_H's comment about settings for the initial and max heap size.
Here's a link to the discussion, though you unfortunately need a playapps account to view it.
I will report the feedback here when I get it; thanks so much everyone for your answers, I've already learned a great deal from them!
Resolution
Playapps support, which is still great, didn't have many suggestions for me, their only thought being that if I was using the cache extensively this may be keeping objects alive longer than need be, but that isn't the case. I still learned a ton (woo hoo!), and I gave #Ryan Amos the green check as I took his suggestion of calling System.gc() every half day, which for now is working fine.
Any detailed answer is going to depend on which garbage collector you're using, but there are some things that are basically the same across all (modern, sun/oracle) GCs.
Every time you see the usage in the graph go down, that is a garbage collection. The only way heap gets freed is through garbage collection. The thing is there are two types of garbage collections, minor and full. The heap gets divided into two basic "areas." Young and tenured. (There are lots more subgroups in reality.) Anything that is taking up space in Young and is still in use when the minor GC comes along to free up some memory, is going to get 'promoted' into tenured. Once something makes the leap into tenured, it sits around indefinitely until the heap has no free space and a full garbage collection is necessary.
So one interpretation of that graph is that your young generation is fairly small (by default it can be a fairly small % of total heap on some JVMs) and you're keeping objects "alive" for comparatively very long times. (perhaps you're holding references to them in the web session?) So your objects are 'surviving' garbage collections until they get promoted into tenured space, where they stick around indefinitely until the JVM is well and good truly out of memory.
Again, that's just one common situation that fits with the data you have. Would need full details about the JVM configuration and the GC logs to really tell for sure what's going on.
Java won't run the garbage cleaner until it has to, because the garbage cleaner slows things down quite a bit and shouldn't be run that frequently. I think you would be OK to schedule a cleaning more frequently, such as every 3 hours. If an application never consumes full memory, there should be no reason to ever run the garbage cleaner, which is why Java only runs it when the memory is very high.
So basically, don't worry about what others say: do what works best. If you find performance improvements from running the garbage cleaner at 66% memory, do it.
I am noticing that the graph isn't sloping strictly upward until the drop, but has smaller local variations. Although I'm not certain, I don't think memory use would show these small drops if there was no garbage collection going on.
There are minor and major collections in Java. Minor collections occur frequently, whereas major collections are rarer and diminish performance more. Minor collections probably tend to sweep up stuff like short-lived object instances created within methods. A major collection will remove a lot more, which is what probably happened at the end of your graph.
Now, some answers that were posted while I'm typing this give good explanations regarding the differences in garbage collectors, object generations and more. But that still doesn't explain why it would take so absurdly long (nearly 24 hours) before a serious cleaning is done.
Two things of interest that can be set for a JVM at startup are the maximum allowed heap size, and the initial heap size. The maximum is a hard limit, once you reach that, further garbage collection doesn't reduce memory usage and if you need to allocate new space for objects or other data, you'll get an OutOfMemoryError. However, internally there's a soft limit as well: the current heap size. A JVM doesn't immediately gobble up the maximum amount of memory. Instead, it starts at your initial heap size and then increases the heap when it's needed. Think of it a bit as the RAM of your JVM, that can increase dynamically.
If the actual memory use of your application starts to reach the current heap size, a garbage collection will typically be instigated. This might reduce the memory use, so an increase in heap size isn't needed. But it's also possible that the application currently does need all that memory and would exceed the heap size. In that case, it is increased provided that it hasn't already reached the maximum set limit.
Now, what might be your case is that the initial heap size is set to the same value as the maximum. Suppose that would be so, then the JVM will immediately seize all that memory. It will take a very long time before the application has accumulated enough garbage to reach the heap size in memory usage. But at that moment you'll see a large collection. Starting with a small enough heap and allowing it to grow keeps the memory use limited to what's needed.
This is assuming that your graph shows heap use and not allocated heap size. If that's not the case and you are actually seeing the heap itself grow like this, something else is going on. I'll admit I'm not savvy enough regarding the internals of garbage collection and its scheduling to be absolutely certain of what's happening here, most of this is from observation of leaking applications in profilers. So if I've provided faulty info, I'll take this answer down.
As you might have noticed, this does not affect you. The garbage collection only kicks in if the JVM feels there is a need for it to run and this happens for the sake of optimization, there's no use of doing many small collections if you can make a single full collection and do a full cleanup.
The current JVM contains some really interesting algorithms and the garbage collection itself id divided into 3 different regions, you can find a lot more about this here, here's a sample:
Three types of collection algorithms
The HotSpot JVM provides three GC algorithms, each tuned for a specific type of collection within a specific generation. The copy (also known as scavenge) collection quickly cleans up short-lived objects in the new generation heap. The mark-compact algorithm employs a slower, more robust technique to collect longer-lived objects in the old generation heap. The incremental algorithm attempts to improve old generation collection by performing robust GC while minimizing pauses.
Copy/scavenge collection
Using the copy algorithm, the JVM reclaims most objects in the new generation object space (also known as eden) simply by making small scavenges -- a Java term for collecting and removing refuse. Longer-lived objects are ultimately copied, or tenured, into the old object space.
Mark-compact collection
As more objects become tenured, the old object space begins to reach maximum occupancy. The mark-compact algorithm, used to collect objects in the old object space, has different requirements than the copy collection algorithm used in the new object space.
The mark-compact algorithm first scans all objects, marking all reachable objects. It then compacts all remaining gaps of dead objects. The mark-compact algorithm occupies more time than the copy collection algorithm; however, it requires less memory and eliminates memory fragmentation.
Incremental (train) collection
The new generation copy/scavenge and the old generation mark-compact algorithms can't eliminate all JVM pauses. Such pauses are proportional to the number of live objects. To address the need for pauseless GC, the HotSpot JVM also offers incremental, or train, collection.
Incremental collection breaks up old object collection pauses into many tiny pauses even with large object areas. Instead of just a new and an old generation, this algorithm has a middle generation comprising many small spaces. There is some overhead associated with incremental collection; you might see as much as a 10-percent speed degradation.
The -Xincgc and -Xnoincgc parameters control how you use incremental collection. The next release of HotSpot JVM, version 1.4, will attempt continuous, pauseless GC that will probably be a variation of the incremental algorithm. I won't discuss incremental collection since it will soon change.
This generational garbage collector is one of the most efficient solutions we have for the problem nowadays.
I had an app that produced a graph like that and acted as you describe. I was using the CMS collector (-XX:+UseConcMarkSweepGC). Here is what was going on in my case.
I did not have enough memory configured for the application, so over time I was running into fragmentation problems in the heap. This caused GCs with greater and greater frequency, but it did not actually throw an OOME or fail out of CMS to the serial collector (which it is supposed to do in that case) because the stats it keeps only count application paused time (GC blocks the world), application concurrent time (GC runs with application threads) is ignored for those calculations. I tuned some parameters, mainly gave it a whole crap load more heap (with a very large new space), set -XX:CMSFullGCsBeforeCompaction=1, and the problem stopped occurring.
Probably you do have memory leaks that's cleared every 24 hours.