I'm guessing this isn't possible...but here goes. My understanding is that eden space is cheaper to collect than old gen space, especially when you start getting into very large heaps. Large heaps tend to come up with long running applications (server apps) and server apps a lot of the time want to use some kind of caches. Caches with some kind of eviction (LRU) tend to defeat some assumptions that GC makes (temporary objects die quickly). So cache evictions end up filling up old gen faster than you'd like and you end up with a more costly old gen collection.
Now, it seems like this sort of thing could be avoided if java provided a way to mark a reference as about to die (delete keyword)? The difference between this and c++ is that the use is optional. And calling delete does not actually delete the object, but rather is a hint to the GC that it should demote the object back to Eden space (where it will be more easily collected). I'm guessing this feature doesn't exist, but, why not (is there a reason it's a bad idea)?
Actually the eden space is the zone of memory in which objects are newly created. Once an object leaves the eden space it cannot be placed there again, then the GC implementation of Java is so much opaque that there is usually not much to do.
It would break some constrains in any case, the eden space is easily garbage collected in the sense that keep care of removing items that have a short life span. If an object survived enough time then it has to be moved somewhere else, it would be like trying to go against the rules imposed by the GC itself, which is something that is never easily obtainable in Java..
Related
I am trying to understand minor, major, and full GC in java. As per my understanding, a threshold is set for young generation objects and when that age is met, the object gets moved to the old generation. This means all objects in the old generation are referenced objects. When there is no space left in the old generation are all the referenced objects removed? If so, what happens to the running application? Will it be stopped?
First of all, major and full is the same thing; people just use different notions to express the same concepts.
Yes, there is a threshold for which objects survive and then are moved to the old regions. As to:
When there is no space left in the old generation are all the referenced objects removed?
When there is no space in old regions, the application is stopped, yes; this is called a stop-the-world event, since every thread is stopped. GC will try to move things around to make space at this point in time.
If there is not enough space left, even after Full GC happens - your application is going to die with an OutOfMemory ( unless you catch it, which is not recommended )
A garbage collector is not going to reclaim live instances. Something that is reachable is not going to disappear just so that you have space; if that would be the case, absolutely no one on this planet would have used java (any other programming language that has automatic garbage collection).
For example in a service adapter you might:
a. have an input data model and an output data model, maybe even immutable, with different classes and use Object Mappers to transform between classes and create some short-lived objects along the way
b. have a single data model, some of the classes might be mutable, but the same object that was created for the input is also sent as output
There are other use-cases when you'd have to choose between clear code with many objects and less clear code with less objects and I would like to know if Garbage Collection still has a weight in this decision.
I should make this a comment as IMO it does not qualify as an answer, but it will not fit.
Even if the answer(s) are going to most probably be - do whatever makes your code more readable (and to be honest I still follow that all the time); we have faced this issue of GC in our code base.
Suppose that you want to create a graph of users (we had to - around 1/2 million) and load all their properties in memory and do some aggregations on them and filtering, etc. (it was not my decision), because these graph objects where pretty heavy - once loaded even with 16GB of heap the JVM would fail with OOM or GC would take huge pauses. And it's understandable - lots of data requires lots of memory, you can't run away from it. The solution proposed and that actually worked was to model that with simple BitSets - where each bit would be a property and a potential linkage to some other data; this is by far not readable and extremely complicated to maintain to this day. Lots of shifts, lots of intrinsics of the data - you have to know at all time what the 3-bit means for example, there's no getter for usernameIncome let's say - you have to do quite a lot shifts and map that to a search table, etc. But it would keep the GC pretty low, at least in the ranges where we were OK with that.
So unless you can prove that GC is taken your app time so much - you probably are even safer simply adding more RAM and increasing it(unless you have a leak). I would still go for clear code like 99.(99) % of the time.
Newer versions of Java have quite sophisticated mechanisms to handle very short-living objects so it's not as bad as it was in the past. With a modern JVM I'd say that you don't need to worry about garbage collection times if you create many objects, which is a good thing since there are now many more of them being created on the fly that this was the case with older versions of Java.
What's still valid is to keep the number of created objects low if the creation is coming with high costs, e.g. accessing a database to retrieve data from, network operations, etc.
As other people have said I think it's better to write your code to solve the problem in an optimum way for that problem rather than thinking about what the garbage collector (GC) will do.
The key to working with the GC is to look at the lifespan of your objects. The heap is (typically) divided into two main regions called generations to signify how long objects have been alive (thus young and old generations). To minimise the impact of GC you want your objects to become eligible for collection while they are still in the young generation (either in the Eden space or a survivor space, but preferably Eden space). Collection of objects in the Eden space is effectively free, as the GC does nothing with them, it just ignores them and resets the allocation pointer(s) when a minor GC is finished.
Rather than explicitly calling the GC via System.gc() it's much better to tune your heap. For example, you can set the size of the young generation using command line options like -XX:NewRatio=n, where n signifies the ratio of new to old (e.g. setting it to 3 will make the ratio of new:old 1:3 so the young generation will be 1 quarter of the heap). Alternatively, you can set the size explicitly using -XX:NewSize=n and -XX:MaxNewSize=m. The GC may resize the heap during collections so setting these values to be the same will keep it at a fixed size.
You can profile your code to establish the rate of object creation and how long your objects typically live for. This will give you the information to (ideally) configure your heap to minimise the number of objects being promoted into the old generation. What you really don't want is objects being promoted and then becoming garbage shortly thereafter.
Alternatively, you may want to look at the Zing JVM from Azul (full disclosure, I work for them). This uses a different GC algorithm, called C4, which enables compaction of the heap concurrently with application threads and so eliminates most of the impact of the GC on application latency.
I am trying to understand how Garbage collection process works. Came across good link .
Most of the articles says that during minor GC collection object is moved from eden to survivor space and during major GC collection
object is moved from survivor to tenured space otherwise all unreachable objects memory is reclaimed. I have three questions(need to ask
in single go as they are related) based on above statements :-
1)Minor vs Major GC collection ? What is the difference between two that one is called major and other is called minor collection?
As per my understanding during minor collection happens in parallel to application run while major collection makes application to
pause during that period.
2) What actually happens when object is moved from eden to survivor space ? Does the memory location of object is changed internally?
3) Why not just one space exist instead of three i.e eden, survivor and tenured space exist ? I know there is must be a reason behind it but i am missing it.
My point is when GC runs , collect unreachable object and leaves the reachable ones in that space only. Just one space seems to be sufficient. So what advantage three different
spaces are proving over one?
1) Minor GC occurs on new generation, major GC occurs on old generation. Whether it is parallel to the application or not depends on the kind of GC, only CMS and G1 can work concurrently
2) Yes, moving object during GC changes its physical location so all pointers to this object will be updated
3) This is to avoid often and long application freezing during GC. If it was one big heap then application would often freeze for long periods of time. JVM creates objects in small young generation, GCs in it occur frequently but quickly. Most objects created by JVM die quickly and they never get to old generation, so major GC happens rarily or it may never happen at all.
Source for my answers is this Oracle article on GC basics, so these answers would apply for HotSpot. No clue as to other VMs, although I would guess that the general idea might remain the same if the same implementation techniques were used in other VMs.
Minor vs Major GC collection? What is the difference between two that one is called major and other is called minor collection?
Minor GC is GC of the young generation, where new objects are allocated. Major GC is GC of all live objects, including the permanent generation (which is a bit interesting to me, but that's what the article says). Also, it appears that both major and minor GC are stop-the-world events.
What actually happens when object is moved from eden to survivor space? Does the memory location of object is changed internally?
I can't seem to find a reference at the moment, but I would assume so. Allowing for memory location to be changed lets compaction be performed, which improves memory allocation performance and ease. Allowing each space to be compacted separately makes sense, so I would guess that moving an object from one part of the heap to another would involve physically moving the object from one memory location to another.
Why not just one space exist instead of three (i.e eden, survivor and tenured space) exist?
Short answer: efficiency. If you have only one space, you'd have to check all objects when you GC, which becomes inefficient if you have lots of long-lived objects (and you're almost guaranteed to have a decent number in a long-running application), as those long-lived objects are likely to still be reachable from one GC to the next. Splitting the heap allows for GC to be optimized, as most of the GC efforts can be concentrated where object life can be assumed to be short (i.e. young generation), with longer-living objects being GC'd less frequently.
In other words:
I need to know if after calling System.gc() object instances (that are not collected) are distributed between generations in the same way as before calling System.gc().
Thanks,
After a Full GC, which a System.gc() may or may not trigger,
the Eden space will be empty, so anything in there will be moved out or cleaned up.
the Survivor spaces will swap objects from the one which has objects to the empty one, and
the Tenured space will have the same retained objects it had before but some may have been cleaned up and some may be new to that generation.
In short, the only time System.gc() won't change objects between generations is when
it doesn't do anything because it is ignored
no objects have been created or discarded since the last Full GC.
if this could be another reason why calling System.gc() is evil
Mostly because it hurts performance and you gain very little in return. Note: the RMI can trigger a full collection periodically to ensure distributed objects are cleaned up but it tries to keep this to a minimum.
First of all, System.gc() is only a hint to the JVM that you want a GC, it might not trigger one (if using -XX:+DisableExplicitGC with Hotspot for example), and you should not rely on it doing anything -- the JVM usually knows better anyway.
If it does trigger a GC, then it's just like any other GC, and objects might get promoted from the young to the old generation if they satisfy the criteria (enough generations spent in the survivor spaces for example).
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.