Using a fast approach to see the heap

Sometimes taking a heap dump will be too long for the production environment, on this cases, it is possible to wait for the load to reduce and then take the heap dump.

However, it is possible to use the quick java diagnostics tool to see the some quick information. Basic usage is just run jcmd, and then see the processes running get the name or PID, then jcmd PID help. To see the operations available, in JDK 11+ there are so many operations that can be done, like jcmd PID VM.metaspace

If one does `GC.class_histogram`, which does not depend of +UnlockDiagnosticVMOptions, it can see the list of instances and retention based on the heap usage, example <— like seriously you don’t need to use it

GC.class_stats$ jdk-11.0.1/bin/jcmd 1568 GC.class_histogram
  num     #instances         #bytes  class name
 1:       2725548       87217536  java.util.HashMap$Node
    2:        101237       56724056  [B
    3:       2706313       43301008  org.infinispan.server.some.Class <--- some clas takes 433k bytes, so then 43mb
    4:         13443       17843296  [Ljava.util.HashMap$Node;
    5:         21725       16866280  [Ljava.lang.Object;
    6:          8658        5679648  io.netty.util.internal.shaded.org.jctools.queues.MpscArrayQueue
    7:         62530        5015664  [C
    8:         79376        2540032  java.util.concurrent.ConcurrentHashMap$Node

So we can see that the class `org.infinispan.server.some.Class` takes 2706313bytes, so 27mb of the heap, very easily.

This is a very powerful and pretty simple, you can use jcmd to get a heap dump with: `jcmd PID GC.heap_dump` but then you need to set a tool to analyse the Heap itself, like MAT.

Of course this quick usage is not for beginners, you need to know a bit of your application/stack so then one can see how it gets some data. But for a quick investigation it is pretty useful.

JCMD GC histogram

Just be careful with the histogram ( I will write a blog post specifically about it) but basically the histogram would only show memory directly used by those classes. Not all the other memory retained in their graph. So for instance, you’d see a lot of individual objects, but wouldn’t see that one particular collection is using 90% of the heap –> can lead to false positives. But it is really helpful for those scenarios that heap is not that possible and you have a clear knowledge of what you doing and can investigate the code if necessary. Histogram will perform Full GC operation btw.

The example below shows that, you think is the actual object that is taking 244 mb but there is a major object used by Infinispan/DataGrid for cache processing that holds it:

 num     #instances         #bytes  class name (module)
   1:        505686      856288432  [B (java.base@11.0.12)
   2:        808426      806075760  [Ljava.lang.Object; (java.base@11.0.12)
   4:        765492       24495744  io.netty.buffer.PoolThreadCache$SubPageMemoryRegionCache <-------- 244 mb
   5:        333316       15999168  java.util.concurrent.locks.StampedLock (java.base@11.0.12)
   6:        394052       15762080  java.util.WeakHashMap$Entry (java.base@11.0.12)
   7:        138136       12155968  io.netty.buffer.PooledUnsafeDirectByteBuf
   8:        309118        9891776  io.netty.util.Recycler$DefaultHandle
   9:        386970        9287280  java.lang.String (java.base@11.0.12)
  10:        115820        9264848  [Ljava.util.HashMap$Node; (java.base@11.0.12)
Total       7081360     2396918072 <------------------------------ 2.4 gb

I will be presenting some quick jcmd usage in a conference: TDC. This is my second time presenting at the TDC and I’m very glad to share my knowledge on jcmd and live gc observations. In 2014 went to Florianopolis to present about EEG but now I will be presenting in Porto Alegre, RS, Brazil:

TDC 2020 Porto Alegre

I will add slides/presentation here and some extra comments right after, of course.

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