So, the jest of it is, a version of an application at my company is having some memory issues lately, and I'm not fully sure the best way to fix it that isn't just "Allocate more memory", so I wanted to get some guidance.
For the application, It looks like the eden heap is getting full pretty quickly when it has a concurrent users, so objects that won't be alive very long end up in the old heap. After running for a while, the old heap simply gets fulls, and never seems to automatically clean up, but manually running the garbage collection in VisualVM will clear it out (So I assume this means the old heap is full of dead objects)
Is there any setting suggested I could add so garbage collection gets run on the old heap once it gets to a certain threshold? And is there any pitfalls from changing the old/edin ratio from the stock 2:1 to 1:1? For the application, the majority of objects created are what I would consider short lived (From milliseconds to a few minutes)
It looks like the eden heap is getting full pretty quickly when it has a concurrent users, so objects that won't be alive very long end up in the old heap.
This is called "premature promotion"
After running for a while, the old heap simply gets fulls,
When it fills, the GC triggers a major or even a full collection.
never seems to automatically clean up
In which case, it is either used or it is not completely full. It might appear to be almost full, but the GC will be performed when it is actually full.
but manually running the garbage collection in VisualVM will clear it out
So the old gen wasn't almost but not actually full.
I could add so garbage collection gets run on the old heap once it gets to a certain threshold?
You can run System.gc() but this means more work for you application and slow it down. You don't want to be doing this.
If you use the CMS collector you can change the threshold at which it kicks in but unless you need low latency you might be better off leaving your settings as they are.
And is there any pitfalls from changing the old/edin ratio from the stock 2:1 to 1:1?
You reduce the old gen, you you may half the number of GCs you perform and double the amount of time an object can live and not end up in the old gen.
I work in the low latency space and usually set the young space to 24 GB and the old gen to 2 GB. I also use a lot of off heap data so I don't need much old gen. This is not an average use case, but it can work depending on your requirements.
If you are using < 32 GB, just adding a few more GB may be the simplest answer. Also you can use something like -Xmn4g -Xms6g to set the young space and maximum heap not worry about ratios.
For the application, the majority of objects created are what I would consider short lived (From milliseconds to a few minutes)
In that case, ideally you want your eden space large enough so you have a minor collection every few minutes. This way most of your objects will die in the eden space, and not be copied around.
Note: in extreme cases it is possible to have an application produce less than one GB per hour of garbage and run all day with a 24 GB Eden space without even a minor collection.
Related
I've a AKKA-HTTP based service which is written in scala. This service works as a proxy for an API call. It creates a host connection pool for calling API using
https://doc.akka.io/docs/akka-http/current/client-side/host-level.html
The service is integrated with NewRelic and has the attached snapshots
I would like to understand the reasons for this kind of zig-zag patterns even when there is no traffic on the service and the connections in the host-pool gets terminated because of idle-timeout.
Moreover, I would also like to know Does the FULL GC will only occur after it reached a threshold say 7GB? or it can also occur at some other time when there is no traffic?
The service has XmX of 8GB. Moreover, there are also multiple dispatchers(fork-join-executor) which performs multiple tasks.
First, your graphs show a very healthy application. This "chainsaw" pattern is overall seen as a very good thing, without much to worry about.
When exactly a Full GC is going to happen is a bit hard to predict (I would use the word impossible, too). When your "live" objects have nowhere to move (because there is simply no space for that), a Full GC may be triggered. There are certain thresholds of when a concurrent phase (marking) is going to be initiated, but if that results in a Full GC or not is decided later.
Considering that G1 also re-sizes regions (makes them less/more) based on heuristics, and the fact that it can also shrink or grow your heap (up to -Xmx), the exact conditions when a Full GC might happen is not easy to predict (I guess some GC experts that know the exact internal details might be able to do that). Also, G1GC can do partial collections: when it collects young regions + some of the old regions (not all), still making it far better than a Full GC time-wise.
Unfortunately, your point about no traffic is correct. When there is very limited traffic, you might not get a Full GC, but immediately as traffic comes in, such a thing might happen. Old regions might slowly build up during your "limited traffic" and as soon as you have a spike - surprise. There are ways to trigger a Full GC on demand, and though I have heard of such applications that do this - I have not worked with one in practice.
In general with a GC that's not reference-counting, you'll see that zig-zag pattern because memory is only reclaimed when a GC runs.
G1 normally only collects areas of the heap where it expects to find a lot of garbage relative to live objects ("garbage collection" is a bit of a misnomer: it actually involves collecting the live objects and (in the case of a relocating garbage collector like G1) moving the live objects to a different area of the heap, which allows the area it collected in to then be declared ready for new allocations; therefore the fewer live objects it needs to handle, the less work it needs to do relative to the memory freed up).
At a high-level, G1 works by defining an Eden (a young generation) where newly created objects where newly created objects are allocated and it divides Eden into multiple regions with each thread being mapped to a region. When a region fills up, only that region is collected, with the survivors being moved into an older generation (this is simplifying). This continues until the survivor generation is full, at which point the survivor and eden generations are collected, with the surviving survivors being promoted to the old generation, and when the old generation fills up, you have a full GC.
So there isn't necessarily a fixed threshold where a full GC will get triggered, but in general the more heap gets used up, the more likely it becomes that a full GC will run. Beyond that, garbage collectors on the JVM tend to be more or less autonomous: most will ignore System.gc and/or other attempts to trigger a GC.
Conceivably with G1, if you allocated a multi-GiB array at startup, threw away the reference, and then after every period of idleness reallocated an array of the same size as the one you allocated at startup and then threw away the reference, you'd have a decent chance of triggering a full GC. This is because that array is big enough to bypass eden and go straight to the old generation where it will consume heap until the next full GC. Eventually there won't be enough contiguous free space in the old generation to allocate these arrays, and that will trigger a full GC. The only complications to this approach are that:
You'll eventually have to outsmart the JIT optimizer, which will see that you're allocating this array and throwing it away and decide that it doesn't actually have to allocate the array
If you have a long enough busy time that a full GC ran since the last allocate-and-throw-away, there's no guarantee that the allocation of the large array will succeed after a full GC, which will cause an OOM.
I know many things about what should be perceived from gc.logs like
you should check how frequently "Full GC" runs, if it is running frequently then it is sign of problem
you should also check how much memory "Full GC" is able to reclaim while finishes, if it is not much then again it is sign of problem as it would force "Full GC" to run again
you should revisit your heap space allocated for java process if "Full GC" runs frequently.
These are some points on which I am working on, I would be interested to know what else should be taken care, when I look at gc logs.
FYI, I have already gone through following threads....
What does "GC--" in gc.log mean?
What does "GC--" mean in a java garbage collection log?
How to analyse and monitor gc.log garbage collector log files from the JVM
Is gc.log writing asynchronous? safe to put gc.log on NFS mount?
First you need to know what wrong can GC do to your program. Depending on the type of collectors that you use for tenured and old gen contents of GC logs may vary. But all in all the baseline inference that we need to derive from gc logs is mostly concentrated to the following:
How long are the minor collections taking?
How long are the major collections taking?
What is the frequency of minor collections?
What is the frequency of major collections?
How much does a minor collection reclaim?
How much does a major collection reclaim?
Combinations of the above
Most Program have a very frequent minor collections that claim about 90-95% of heap and pass the rest to Survivor spaces. Subsequent collections clean up survivors by about 80% again and in essence just 2% to 4% of you actual minor collection makes it to old gen and tis cycles keeps on going no matter which Collector you use.
Now the pain areas are when you have hundreds of small sized minor collections per application request or thread and when added up they make a sizable time mostly in double digit seconds. Since in modern collectors minor pass and sweep are not stop the world cases so somethings this is bearable. With Old gen the problems come when collectors run but don't reclaim anything major. e.g: normally a collector runs when the old gen is about 80-85% full. This may be a stop the world episode since new data cannot be saved on heap unless the heap has more space which is probably the case here. So app threads are paused to let GC threads cleanup the space first. but once the collector finishes the heap fill ratio doesn't come down much as it should. A good sizing should reduce your heap by more than 40% in a single go. If it doesn't that means you need more heap to save your long lived objects.
So in essence GC analysis is not a 'do it based of a set of predefined steps' things. Its more of a hti and trial analysis. It more of an experiment were you set the initial sizes and settings and then note or monitor the GC activity and record findings. Then after say 8-10 runs you compare notes and see what works for your app and what doesn't. Its really an interesting hard work to do.
I wonder whether or not GC time will always be guaranteed to reduce if the heap size is set to be higher.
Thanks!
No, it does not.
What you really care about is the old generation delays (Stop-The-World events). Take CMS for example, increasing the heap you will delay the garbage collection in the old generation, but when it happens it will take a lot of time, since your old generation is big. It takes about 1 second per GB for the CMS this still has to be measured.
Many applications do this kind of things though (personal experience); i.e. increase the heap.
Why?
Well because we could push the old generation collection towards the night in this way, when the application was used by 0.02% of total usage/users.
I have a Java client which consumes a large amount of data from a server. If the client does not keep up with the data stream at a fast enough rate, the server disconnects the socket connection. My client gets disconnected a few times per day. I ran jconsole to see the memory usage, and the heap space graph looks like a fairly well defined sawtooth pattern, oscillating between about 0.5GB and 1.8GB (2GB of heap space is allocated). But every time I get disconnected is during a full GC (but not on every full GC). I see the full GC takes a bit over 1 second on average. Depending on the time of day, full GC happens as often as every 5 minutes when busy, or up to 30 minutes can go by in between full GCs during the slow periods.
I suspect if I can reduce the full GC time, the client will be able to better keep up with the incoming data, but I do not have much experience with GC tuning. Does anyone have some insight on if this might be a good idea, and how to do it? Or is there an alternative idea which may work as well?
** UPDATE **
I used -XX:+UseConcMarkSweepGC and it improved, but I still got disconnected during the very busy moments. So I increased the heap allocation to 3GB to help weather through the busy moments and it seems to be chugging along pretty well now, but it's only been 1 day without a disconnection. Maybe if I get some time I will go through and try to reduce the amount of garbage created which I'm confident will help as well. Thanks for all the suggestions.
Full GC could take very long to complete, and is not that easy to tune.
One way to (easily) tune it is to increase the heap space - generally speaking, double the heap space can double the interval between two GCs, but will double the time consumed by a GC. If the program you are running has very clear usage patterns, maybe you can consider increase the heap space to make the interval so large that you can guarantee to have some idle time to try to make the system perform a GC. On the other hand, following this logic, if the heap is small a full garbage collection will finish in a instant, but that seems like inviting more troubles than helping.
Also, -XX:+UseConcMarkSweepGC might help since it will try to perform the GC operations concurrently (not stopping your program; see here).
Here's a very nice talk by Til Gene (CTO of Azul systems, maker of high performance JVM, and published several GC algos), about GC in JVM in general.
It is not easy to tune away the Full GC. A much better approach is to produce less garbage. Producing less garbage reduces pressure on the collection to pass objects into the tenured space where they are more expensive to collect.
I suggest you use a memory profiler to
reduce the amount of garbage produced. In many applications this can be reduce by a factor of 2 - 10x relatively easily.
reduce the size of the objects you are creating e.g. use primitive and smaller datatypes like double instead of BigDecimal.
recycle mutable object instead of discarding them.
retain less data on the client if you can.
By reducing the amount of garbage you create, objects are more likely to die in the eden, or survivor spaces meaning you have far less Full collections, which can be shorter as well.
Don't take it for granted you have to live with lots of collections, in extreme cases you can avoid it almost completely http://vanillajava.blogspot.ro/2011/06/how-to-avoid-garbage-collection.html
Take out calls to Runtime.getRuntime().gc() - When garbage collection is triggered manually it either does nothing or it does a full stop-the-world garbage collection. You want incremental GC to happen.
Have you tried using the server jvm from a jdk install? It changes a bunch of the default configuration settings (including garbage collection) and is easy to try - just add -server to your java command.
java -server
What is all the garbage that gets created? Can you generate less of it? Where possible, try to use the valueOf methods. By using less memory you'll save yourself time in gc AND in memory allocation.
When I run a java program with the starting heap size of 3G (set by -Xms3072m VM argument), JVM doesn't start with that size. It start with 400m or so and then keeps on acquiring more memory as required.
This is a serious problem for me. I know JVM is going to need the said amount after some time. And when JVM increases is its memory as per the need, it slows down. During the time when JVM acquires more memory, considerable amount of time is spent in garbage collection. And I suppose memory acquisition is an expensive task.
How do I ensure that JVM actually respects the start heap size parameter?
Update: This application creates lots of objects, most of which die quickly. Some resulting objects are required to stay in memory (which get transferred out of young heap.) During this operation, all these objects need to be in memory. After the operation, I can see that all the objects in young heap are claimed successfully. So there are no memory leaks.
The same operation runs smoothly when the heap size reaches 3G. That clearly indicates the extra time required is spent in acquiring memory.
This Sun JDK 5.
If I am not mistaken, Java tries to get the reservation for the memory from the OS. So if you ask for 3 GB as Xms, Java will ask the OS, if this is available but not start with all the memory right away... it might even reserve it (not allocate it). But these are details.
Normally, the JVM runs up to the Xms size before it starts serious old generation garbage collection. Young generation GC runs all the time. Normally GC is only noticeable when old gen GC is running and the VM is in between Xms and Xmx or, in case you set it to the same value, hit roughly Xmx.
If you need a lot of memory for short lived objects, increase that memory area by setting the young area to... let's say 1 GB -XX:NewSize=1g because it is costly to move the "trash" from the young "buckets" into the old gen. Because in case it has not turned into real trash yet, the JVM checks for garbage, does not find any, copies it between the survivor spaces, and finally moves into the old gen. So try to suppress the check for the garbage in the young gen, when you know that you do not have any and postpone this somehow...
Give it a try!
I believe your problem is not coming from where you think.
It looks like what's costing you the most are the GC cycles, and not the allocation of heap size. If you are indeed creating and deleting lots of objects.
You should be focusing your effort on profiling, to find out exactly what is costing you so much, and work on refactoring that.
My hunch - object creation and deletion, and GC cycles.
In any case, -Xms should be setting minimum heap size (check this with your JVM if it is not Sun). Double-check to see exactly why you think it's not the case.
i have used sun's vm and started with minimum set to 14 gigs and it does start off with that.
maybe u should try setting both the xms and xmx values to the same amt, ie try this-
-Xms3072m -Xmx3072m
Why do you think the heap allocation is not right? Taking any operating system tool that shows only 400m does not mean it isn't allocated.
I don't get really what you are after. Is the 400m and above already a problem or is your program supposed to need that much? If you really have the need to deal with that much memory and it seems you need a lot of objects than you can do several things:
If the memory consumption doesn't match your gut feeling it is the right amount than you probably are leaking memory. That would explain why it "slows down" over time. Maybe you missed to remove objects from one structure so they don't get garbage collected and are slowing lookups and such down.
Your memory settings are maybe the trouble in itself. Garbage collection is not run per se. It is only called if there is some threshold reached. If you give it a big heap setting and your operating system has plenty of memory the garbage collection runs not often.
The characteristics you mentioned would be a scenario where a lot of objects are created and shortly after they would be deleted again. Otherwise the garbage collection wouldn't be a problem (some sort of generational gc). That means you have only "young" objects. Consider using an object pool if you are needing objects only a short period of time. That would eliminate the garbage collection at all.
If you know there are good times in your code for running gc you can consider running it manually to be able to see if it changes anything. This is what you would need
Runtime r = Runtime.getRuntime();
r.gc();
This is just for debugging purposes. The gc is doing a great job most of the time so there shouldn't be the need to invoke the gc on your own.