Here is a picture of CPU monitoring provided by VisualVm profiler. I'm confused because I can't understand what does percentage means?As you can see for CPU the number is 24,1 of what?overall cpu time?and gc - 21,8 the same question.What is 100% in both cases?Please clarify this data.
CPU usage is the total CPU usage of your system. The GC activity shows how much of the CPU is spent by the GC threads.
In your example, it looks like the GC was executing and thus contributing to the majority of the total CPU usage in the system. After the GC finished, there was no CPU used.
You should check if this observation is consistent with your GC logs, the logs will shows you the activity around the 19:50 time.
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I have a Openjdk 11.0.17 + Spring Boot application and this is my GC Configuration --XX:+UseG1GC -XX:MaxGCPauseMillis=1000 -Xms512m -Xmx8400m. When the application is running and the heap usage increases as per the incoming web traffic. But I am noticing that when there is no incoming traffic and no processing going on the total heap usage stays the same (high say 7gigs out of 8gig max heap) for longer times. When I take a heap dump the total usage reduces to less than 2% (say 512m). If the heap usage increases it kills the application with OOM (out of memory) error.
How to make G1GC garbage collector run more frequently ? or Is there a way to tune the GC to not make the application oom killed.
But I am noticing that when there is no incoming traffic and no processing going on the total heap usage stays the same (high say 7gigs out of 8gig max heap) for longer times.
By default G1GC only triggers a collection when some of its regions exceed some thresholds, i.e. only tiggers while its allocating objects. Lowering the InitiatingHeapOccupancyPercent can trigger those earlier.
Alternatively, if you upgrade to JDK12 or newer you can use G1PeriodicGCInterval for time-triggered collections in addition to allocation-triggered ones.
Another option is to switch to ZGC or Shenandoah which have options to trigger idle/background GCs to reduce heap size during idle periods.
or Is there a way to tune the GC to not make the application oom killed.
That problem generally is separate from high heap occupancy during idle periods. The GCs will try to perform emergency collections before issuing an OOM. So even if there was lots of floating garbage before the attempted allocation it would have been collected before throwing that error.
One possibility is that there's enough heap for steady-state operation but some load spike caused a large allocation that exceeded the available memory.
But you should enable GC logging to figure out the exact cause and what behavior lead up to it. There are multiple things that can cause OOMs, a few aren't even heap-related.
I'm using htop to monitor the CPU usage of my task. However, the CPU% value exceed 100% sometimes, which really confused me.
Some blogs explain that this is because I'm using a multi-core machine(this is true). If there are 8 (logic) cores, the max value of CPU% is gonna be 800%. CPU% over 100% means that my task is occupying more than one core.
But my question is: there is a column named CPU in htop window which shows the id of the core my task is running on. So how can the usage of this single core exceed 100%.
This is the screenshot. You can see the 84th core's usage is 375%!
Im using java melody to monitor memory usage in production environment.
The requirement is memory not should exceed 256MB/512MB .
I have done maximum of code optimized but still the usage is 448MB/512MB but when i executed garbage collector in java melody manually the memory consumption is 109MB/512MB.
You can invoke the garbage collection using one of these two calls in your code (they're equivalent):
System.gc();
Runtime.getRuntime().gc();
It's better if you place the call in a Runnable that gets invoked periodically, depending on how fast your memory limit is reached.
Why you actually care about heap usage? as long as you set XMS (maximum heap) you are fine. Let java invoke GC when it seems fit. As long as you have free heap it is no point doing GC and freeing heap just for sake of having a lot of free heap.
If you want to limit memory allocated by process XMX is not enough. You should also limit native memory.
What you should care about is
Memory leaks, consecutive Full GCs, GC starvation
GC KPIs: Latency, throughput, footprint
Object creation rate, promotion rate, reclamation rate…
GC Pause time statistics: Duration distribution, average, count, average interval, min/max, standard deviation
GC Causes statistics: Duration, Percentage, min/max, total
GC phases related statistics: Each GC algorithm has several sub-phases. Example for G1: initial-mark, remark, young, full, concurrent mark, mixed
See https://blog.gceasy.io/2017/05/30/improving-your-performance-reports/ https://blog.gceasy.io/2017/05/31/gc-log-analysis-use-cases/ for more technical details. You could also analyze your GC logs using https://blog.gceasy.io/ it will help you understand how your JVM is using memory.
I have an app that processes 3+GB of data into 300MB of data. Run each independent dataset sequentially on the main thread, its memory usage tops out at about 3.5GB and it works fine.
If I run each dataset concurrently on 10 threads, I see the following:
Virtual memory usage climbs steadily until allocations fail and it crashes. I can see GC is trying to run in the stack trace)
CPU utilization is 1000% for periods, then goes down to 100% for minutes, and then cycles back up. The app is easily 10x slower when run with multiple threads, even though they are completely independent.
This is mono 4.2.2 build for Linux with large heap support, running on 128GB RAM with 40 logical processors. I am running mono-sgen and have tried all the custom GC settings I could think of (concurrent mark-sweep, max heap size, etc).
These problems do not happen on Windows. If I rewrite code to do significant object pooling, I get farther in the dataset before running OOM, but the fate is the same. I have verified that I have no memory leaks using multiple tools and good-old printf-debugging.
My best theory is that lots of allocations across lots of threads are a weak case for the GC, and most of that wall-clock time is spent with my work threads suspended.
Does anyone have any experience with this? Is there a way I can help the GC get out of that 100% rut it gets stuck in, and to not run out of memory?
So i have a Node application which slow down every minute.
I used some profilers (nodetime, StrongLoop, memwatch) to find where this degraded performance come from : garbage collection operations takes longer after each request.
According to StrongLoop, my heap size and memory post V8 full GC are almost constant, heap instance count and heap memory usage do not grow.
However, the RSS (Resident Set Size) never stop growing. I believe this is the trigger for the nearly 120 cycles of GC / HTTP request, consuming nearly all CPU.
Any idea where this RSS can come from, and if this has anything to do with increased GC cycles?
graphs