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1. Overview

The Java Virtual Machine (JVM) is a virtual machine that enables a computer to run Java programs. In this article, we'll see how we can diagnose a running JVM with ease.

We have many tools available in the JDK itself which can be used for various development, monitoring, and troubleshooting activities. Let's have a look at jcmd, which is quite easy to use and can provide a variety of information about a running JVM. In addition, jcmd is a recommended tool from JDK 7 onwards for enhanced JVM diagnostics with no or minimum performance overhead.

2. What Is jcmd?

This is a utility that sends diagnostic command requests to a running JVM. However, it must be used on the same machine on which JVM is running. Additional details are available in its documentation.

Let's see how we can use this utility with a sample Java application running on a server.

3. How to Use jcmd?

Let's create a quick demo web application using Spring Initializr with JDK11. Now, let's start the server and diagnose it using jcmd.

3.1. Getting the PID

We know that each process has an associated process id known as PID. Hence to get the associated PID for our application, we can use jcmd which will list all applicable Java processes as below:

[email protected]:/# jcmd
65 jdk.jcmd/sun.tools.jcmd.JCmd
18 /home/pgm/demo-0.0.1-SNAPSHOT.jar
[email protected]:/# 

Here, we can see the PID of our running application is 18.

3.2. Get List of Possible jcmd Usage

Let's find out possible options available with the jcmd PID help command to start with:

[email protected]:/# jcmd 18 help
The following commands are available:

The available diagnostic commands may be different in different versions of HotSpot VM.

4. jcmd Commands

Let's explore some of the most useful jcmd command options to diagnose our running JVM.

4.1. VM.version

This is to get JVM basic details as shown below:

[email protected]:/# jcmd 18 VM.version
OpenJDK 64-Bit Server VM version 11.0.11+9-Ubuntu-0ubuntu2.20.04
JDK 11.0.11
[email protected]:/# 

Here we can see that we are using OpenJDK 11 for our sample application.

4.2. VM.system_properties

This will print all the system properties set for our VM. There can be several hundred lines of information displayed:

[email protected]:/# jcmd 18 VM.system_properties
#Thu Jul 22 10:56:13 IST 2021

4.3. VM.flags

For our sample application, this will print all VM arguments used, either given by us or used default by JVM. Here, we can notice various default VM arguments as below:

[email protected]:/# jcmd 18 VM.flags            
-XX:CICompilerCount=3 -XX:CompressedClassSpaceSize=260046848 -XX:ConcGCThreads=1 -XX:G1ConcRefinementThreads=4 -XX:G1HeapRegionSize=1048576 -XX:GCDrainStackTargetSize=64 -XX:InitialHeapSize=536870912 -XX:MarkStackSize=4194304 -XX:MaxHeapSize=536870912 -XX:MaxMetaspaceSize=268435456 -XX:MaxNewSize=321912832 -XX:MinHeapDeltaBytes=1048576 -XX:NonNMethodCodeHeapSize=5830732 -XX:NonProfiledCodeHeapSize=122913754 -XX:ProfiledCodeHeapSize=122913754 -XX:ReservedCodeCacheSize=251658240 -XX:+SegmentedCodeCache -XX:ThreadStackSize=256 -XX:+UseCompressedClassPointers -XX:+UseCompressedOops -XX:+UseFastUnorderedTimeStamps -XX:+UseG1GC 
[email protected]:/#

Similarly, other commands, like VM.command_line, VM.uptime, VM.dynlibs, also provide other basic and useful details about various other properties used.

All of the above commands are to majorly get different JVM-related details. Now let's look into some more commands that can help in some troubleshooting related to JVM.

4.4. Thread.print

This command is to get the instant thread dump. Hence, it will print the stack trace of all running threads. Following is the way to use it, which can give long output depending on the number of threads in use:

[email protected]:/# jcmd 18 Thread.print
2021-07-22 10:58:08
Full thread dump OpenJDK 64-Bit Server VM (11.0.11+9-Ubuntu-0ubuntu2.20.04 mixed mode, sharing):

Threads class SMR info:
_java_thread_list=0x00007f21cc0028d0, length=25, elements={
0x00007f2210244800, 0x00007f2210246800, 0x00007f221024b800, 0x00007f221024d800,
0x00007f221024f800, 0x00007f2210251800, 0x00007f2210253800, 0x00007f22102ae800,
0x00007f22114ef000, 0x00007f21a44ce000, 0x00007f22114e3800, 0x00007f221159d000,
0x00007f22113ce800, 0x00007f2210e78800, 0x00007f2210e7a000, 0x00007f2210f20800,
0x00007f2210f22800, 0x00007f2210f24800, 0x00007f2211065000, 0x00007f2211067000,
0x00007f2211069000, 0x00007f22110d7800, 0x00007f221122f800, 0x00007f2210016000,

"Reference Handler" #2 daemon prio=10 os_prio=0 cpu=2.32ms elapsed=874.34s tid=0x00007f2210244800 nid=0x1a waiting on condition  [0x00007f221452a000]
   java.lang.Thread.State: RUNNABLE
	at java.lang.ref.Reference.waitForReferencePendingList([email protected]/Native Method)
	at java.lang.ref.Reference.processPendingReferences([email protected]/Reference.java:241)
	at java.lang.ref.Reference$ReferenceHandler.run([email protected]/Reference.java:213)

"Finalizer" #3 daemon prio=8 os_prio=0 cpu=0.32ms elapsed=874.34s tid=0x00007f2210246800 nid=0x1b in Object.wait()  [0x00007f22144e9000]
   java.lang.Thread.State: WAITING (on object monitor)
	at java.lang.Object.wait([email protected]/Native Method)
	- waiting on <0x00000000f7330898> (a java.lang.ref.ReferenceQueue$Lock)
	at java.lang.ref.ReferenceQueue.remove([email protected]/ReferenceQueue.java:155)
	- waiting to re-lock in wait() <0x00000000f7330898> (a java.lang.ref.ReferenceQueue$Lock)
	at java.lang.ref.ReferenceQueue.remove([email protected]/ReferenceQueue.java:176)
	at java.lang.ref.Finalizer$FinalizerThread.run([email protected]/Finalizer.java:170)

"Signal Dispatcher" #4 daemon prio=9 os_prio=0 cpu=0.40ms elapsed=874.33s tid=0x00007f221024b800 nid=0x1c runnable  [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

Detailed discussion on capturing a thread dump using other options can be found here.

4.5. GC.class_histogram

Let's use another jcmd command that will provide important information about heap usage. Additionally, this will list all classes (either external or application-specific) with many instances. Again, the list can be of hundreds of lines depending on the number of classes in use:

[email protected]:/# jcmd 18 GC.class_histogram
 num     #instances         #bytes  class name (module)
   1:         41457        2466648  [B ([email protected])
   2:         38656         927744  java.lang.String ([email protected])
   3:          6489         769520  java.lang.Class ([email protected])
   4:         21497         687904  java.util.concurrent.ConcurrentHashMap$Node ([email protected])
   5:          6570         578160  java.lang.reflect.Method ([email protected])
   6:          6384         360688  [Ljava.lang.Object; ([email protected])
   7:          9668         309376  java.util.HashMap$Node ([email protected])
   8:          7101         284040  java.util.LinkedHashMap$Entry ([email protected])
   9:          3033         283008  [Ljava.util.HashMap$Node; ([email protected])
  10:          2919         257000  [I ([email protected])
  11:           212         236096  [Ljava.util.concurrent.ConcurrentHashMap$Node; ([email protected])

However, if this doesn't give a clear picture, we can get a heap dump. Let's look at it next.

4.6. GC.heap_dump

This command will give an instant JVM heap dump. Therefore we can extract heap dump into a file to analyze later as below:

[email protected]:/# jcmd 18 GC.heap_dump ./demo_heap_dump
Heap dump file created
[email protected]:/# 

Here, demo_heap_dump is the heap dump file name. In addition, this will be created at the same location where our application jar is located.

4.7. JFR Command Options

In our earlier article, we discussed Java application monitoring using JFR and JMC. Now, let's look into the jcmd commands that we can use to analyze performance issues with our application.

JFR (or Java Flight Recorder) is a profiling and event collection framework built into the JDK. JFR allows us to gather detailed low-level information about how JVM and Java applications are behaving. In addition, we can use JMC to visualize the data collected by JFR. Hence, JFR and JMC together create a complete toolchain to continuously collect low-level and detailed runtime information.

Although how to use JMC is not in the scope of this article, we will see how we can create a JFR file using jcmd. JFR is a commercial feature. Hence by default, it's disabled.  However, that can be enabled using ‘jcmd PID VM.unlock_commercial_features‘.

However, we have used OpenJDK for our article. Hence JFR is enabled for us. Now let's generate a JFR file using the jcmd command as below:

[email protected]:/# jcmd 18 JFR.start name=demo_recording settings=profile delay=10s duration=20s filename=./demorecording.jfr
Recording 1 scheduled to start in 10 s. The result will be written to:

[email protected]:/# jcmd 18 JFR.check
Recording 1: name=demo_recording duration=20s (delayed)
[email protected]:/# jcmd 18 JFR.check
Recording 1: name=demo_recording duration=20s (running)
[email protected]:/# jcmd 18 JFR.check
Recording 1: name=demo_recording duration=20s (stopped)

We have created a sample JFR recording file name demorecording.jfr at the same location where our jar application is located. Additionally, this recording is of 20seconds and configured as per requirements.

In addition, we can check the status of the JFR recording using the JFR.check command. And, we can instantly stop and discard the recording using the JFR.stop command. On the other hand, the JFR.dump command can be used to instantly stop and dump the recording.

4.8. VM.native_memory

This is one of the best commands that can provide a lot of useful details about heap and non-heap memory on a JVM. Therefore, this can be used to tune memory usage and detect any memory leak. As we know, JVM memory can be broadly classified as heap and non-heap memory. And to get the details of complete JVM memory usage, we can use this utility. In addition, this can be useful in defining memory size for a container-based application.

To use this feature we need to restart our application with additional VM argument i.e. –XX:NativeMemoryTracking=summary   or  -XX:NativeMemoryTracking=detail. Note that enabling NMT causes a 5% -10% performance overhead.

This will give us a new PID to diagnose:

[email protected]:/# jcmd 19 VM.native_memory

Native Memory Tracking:

Total: reserved=1159598KB, committed=657786KB
-                 Java Heap (reserved=524288KB, committed=524288KB)
                            (mmap: reserved=524288KB, committed=524288KB) 
-                     Class (reserved=279652KB, committed=29460KB)
                            (classes #6425)
                            (  instance classes #5960, array classes #465)
                            (malloc=1124KB #15883) 
                            (mmap: reserved=278528KB, committed=28336KB) 
                            (  Metadata:   )
                            (    reserved=24576KB, committed=24496KB)
                            (    used=23824KB)
                            (    free=672KB)
                            (    waste=0KB =0.00%)
                            (  Class space:)
                            (    reserved=253952KB, committed=3840KB)
                            (    used=3370KB)
                            (    free=470KB)
                            (    waste=0KB =0.00%)
-                    Thread (reserved=18439KB, committed=2699KB)
                            (thread #35)
                            (stack: reserved=18276KB, committed=2536KB)
                            (malloc=123KB #212) 
                            (arena=39KB #68)
-                      Code (reserved=248370KB, committed=12490KB)
                            (malloc=682KB #3839) 
                            (mmap: reserved=247688KB, committed=11808KB) 
-                        GC (reserved=62483KB, committed=62483KB)
                            (malloc=10187KB #7071) 
                            (mmap: reserved=52296KB, committed=52296KB) 
-                  Compiler (reserved=146KB, committed=146KB)
                            (malloc=13KB #307) 
                            (arena=133KB #5)
-                  Internal (reserved=460KB, committed=460KB)
                            (malloc=428KB #1421) 
                            (mmap: reserved=32KB, committed=32KB) 
-                     Other (reserved=16KB, committed=16KB)
                            (malloc=16KB #3) 
-                    Symbol (reserved=6593KB, committed=6593KB)
                            (malloc=6042KB #72520) 
                            (arena=552KB #1)
-    Native Memory Tracking (reserved=1646KB, committed=1646KB)
                            (malloc=9KB #113) 
                            (tracking overhead=1637KB)
-        Shared class space (reserved=17036KB, committed=17036KB)
                            (mmap: reserved=17036KB, committed=17036KB) 
-               Arena Chunk (reserved=185KB, committed=185KB)
-                   Logging (reserved=4KB, committed=4KB)
                            (malloc=4KB #191) 
-                 Arguments (reserved=18KB, committed=18KB)
                            (malloc=18KB #489) 
-                    Module (reserved=124KB, committed=124KB)
                            (malloc=124KB #1521) 
-              Synchronizer (reserved=129KB, committed=129KB)
                            (malloc=129KB #1089) 
-                 Safepoint (reserved=8KB, committed=8KB)
                            (mmap: reserved=8KB, committed=8KB) 

Here, we can notice details about different memory types apart from Java Heap Memory. The Class defines the JVM memory used to store class metadata. Similarly, the Thread defines the memory that our application threads are using. And the Code gives the memory used to store JIT-generated code, the Compiler itself has some space usage, and GC occupies some space too.

In addition, the reserved can give an estimation of the memory required for our application. And the committed shows the minimum allocated memory.

5. Diagnose Memory Leak

Let's see how we can identify if there is any memory leak in our JVM. Hence to start with, we need to first have a baseline. And then need to monitor for some time to understand if there is any consistent increase in memory in any of the memory types mentioned above.

Let's first baseline the JVM memory usage as below:

[email protected]:/# jcmd 19 VM.native_memory baseline
Baseline succeeded

Now, use the application for normal or heavy usage for some time. In the end, just use diff to identify the change since baseline as below:

[email protected]:/# jcmd 19 VM.native_memory summary.diff

Native Memory Tracking:

Total: reserved=1162150KB +2540KB, committed=660930KB +3068KB

-                 Java Heap (reserved=524288KB, committed=524288KB)
                            (mmap: reserved=524288KB, committed=524288KB)
-                     Class (reserved=281737KB +2085KB, committed=31801KB +2341KB)
                            (classes #6821 +395)
                            (  instance classes #6315 +355, array classes #506 +40)
                            (malloc=1161KB +37KB #16648 +750)
                            (mmap: reserved=280576KB +2048KB, committed=30640KB +2304KB)
                            (  Metadata:   )
                            (    reserved=26624KB +2048KB, committed=26544KB +2048KB)
                            (    used=25790KB +1947KB)
                            (    free=754KB +101KB)
                            (    waste=0KB =0.00%)
                            (  Class space:)
                            (    reserved=253952KB, committed=4096KB +256KB)
                            (    used=3615KB +245KB)
                            (    free=481KB +11KB)
                            (    waste=0KB =0.00%)
-                    Thread (reserved=18439KB, committed=2779KB +80KB)
                            (thread #35)
                            (stack: reserved=18276KB, committed=2616KB +80KB)
                            (malloc=123KB #212)
                            (arena=39KB #68)
-                      Code (reserved=248396KB +21KB, committed=12772KB +213KB)
                            (malloc=708KB +21KB #3979 +110)
                            (mmap: reserved=247688KB, committed=12064KB +192KB)
-                        GC (reserved=62501KB +16KB, committed=62501KB +16KB)
                            (malloc=10205KB +16KB #7256 +146)
                            (mmap: reserved=52296KB, committed=52296KB)
-                  Compiler (reserved=161KB +15KB, committed=161KB +15KB)
                            (malloc=29KB +15KB #341 +34)
                            (arena=133KB #5)
-                  Internal (reserved=495KB +35KB, committed=495KB +35KB)
                            (malloc=463KB +35KB #1429 +8)
                            (mmap: reserved=32KB, committed=32KB)
-                     Other (reserved=52KB +36KB, committed=52KB +36KB)
                            (malloc=52KB +36KB #9 +6)
-                    Symbol (reserved=6846KB +252KB, committed=6846KB +252KB)
                            (malloc=6294KB +252KB #76359 +3839)
                            (arena=552KB #1)
-    Native Memory Tracking (reserved=1727KB +77KB, committed=1727KB +77KB)
                            (malloc=11KB #150 +2)
                            (tracking overhead=1716KB +77KB)
-        Shared class space (reserved=17036KB, committed=17036KB)
                            (mmap: reserved=17036KB, committed=17036KB)
-               Arena Chunk (reserved=186KB, committed=186KB)
-                   Logging (reserved=4KB, committed=4KB)
                            (malloc=4KB #191)
-                 Arguments (reserved=18KB, committed=18KB)
                            (malloc=18KB #489)
-                    Module (reserved=124KB, committed=124KB)
                            (malloc=124KB #1528 +7)
-              Synchronizer (reserved=132KB +3KB, committed=132KB +3KB)
                            (malloc=132KB +3KB #1111 +22)
-                 Safepoint (reserved=8KB, committed=8KB)
                            (mmap: reserved=8KB, committed=8KB)

Over time as GC works, we'll notice an increase and decrease in memory usage. However, if there is an uncontrolled increase in memory usage, then this could be a memory leak issue. Hence, we can identify the memory leak area, like Heap, Thread, Code, Class, etc., from these stats. And if our application needs more memory, we can tune corresponding VM arguments respectively.

If the memory leak is in Heap, we can take a heap dump (as explained earlier) or maybe just tune Xmx. Similarly, if the memory leak is in Thread, we can look for unhandled recursive instructions or tune Xss.

6. Conclusion

In this article, we've covered a utility to diagnose JVM for different scenarios.

We also covered the jcmd command and its various usage to get heap dump, thread dump, JFR recording for various performance-related analyses. In the end, we also looked at a way to diagnose a memory leak using jcmd.

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