For my application, the memory used by the Java process is much more than the heap size.
The system where the containers are running starts to have memory problem because the container is taking much more memory than the heap size.
The heap size is set to 128 MB (-Xmx128m -Xms128m) while the container takes up to 1GB of memory. Under normal condition, it needs 500MB. If the docker container has a limit below (e.g. mem_limit=mem_limit=400MB) the process gets killed by the out of memory killer of the OS.
Could you explain why the Java process is using much more memory than the heap? How to size correctly the Docker memory limit? Is there a way to reduce the off-heap memory footprint of the Java process?
I gather some details about the issue using command from Native memory tracking in JVM.
From the host system, I get the memory used by the container.
$ docker stats --no-stream 9afcb62a26c8
CONTAINER ID NAME CPU % MEM USAGE / LIMIT MEM % NET I/O BLOCK I/O PIDS
9afcb62a26c8 xx-xxxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.0acbb46bb6fe3ae1b1c99aff3a6073bb7b7ecf85 0.93% 461MiB / 9.744GiB 4.62% 286MB / 7.92MB 157MB / 2.66GB 57
From inside the container, I get the memory used by the process.
$ ps -p 71 -o pcpu,rss,size,vsize
%CPU RSS SIZE VSZ
11.2 486040 580860 3814600
$ jcmd 71 VM.native_memory
71:
Native Memory Tracking:
Total: reserved=1631932KB, committed=367400KB
- Java Heap (reserved=131072KB, committed=131072KB)
(mmap: reserved=131072KB, committed=131072KB)
- Class (reserved=1120142KB, committed=79830KB)
(classes #15267)
( instance classes #14230, array classes #1037)
(malloc=1934KB #32977)
(mmap: reserved=1118208KB, committed=77896KB)
( Metadata: )
( reserved=69632KB, committed=68272KB)
( used=66725KB)
( free=1547KB)
( waste=0KB =0.00%)
( Class space:)
( reserved=1048576KB, committed=9624KB)
( used=8939KB)
( free=685KB)
( waste=0KB =0.00%)
- Thread (reserved=24786KB, committed=5294KB)
(thread #56)
(stack: reserved=24500KB, committed=5008KB)
(malloc=198KB #293)
(arena=88KB #110)
- Code (reserved=250635KB, committed=45907KB)
(malloc=2947KB #13459)
(mmap: reserved=247688KB, committed=42960KB)
- GC (reserved=48091KB, committed=48091KB)
(malloc=10439KB #18634)
(mmap: reserved=37652KB, committed=37652KB)
- Compiler (reserved=358KB, committed=358KB)
(malloc=249KB #1450)
(arena=109KB #5)
- Internal (reserved=1165KB, committed=1165KB)
(malloc=1125KB #3363)
(mmap: reserved=40KB, committed=40KB)
- Other (reserved=16696KB, committed=16696KB)
(malloc=16696KB #35)
- Symbol (reserved=15277KB, committed=15277KB)
(malloc=13543KB #180850)
(arena=1734KB #1)
- Native Memory Tracking (reserved=4436KB, committed=4436KB)
(malloc=378KB #5359)
(tracking overhead=4058KB)
- Shared class space (reserved=17144KB, committed=17144KB)
(mmap: reserved=17144KB, committed=17144KB)
- Arena Chunk (reserved=1850KB, committed=1850KB)
(malloc=1850KB)
- Logging (reserved=4KB, committed=4KB)
(malloc=4KB #179)
- Arguments (reserved=19KB, committed=19KB)
(malloc=19KB #512)
- Module (reserved=258KB, committed=258KB)
(malloc=258KB #2356)
$ cat /proc/71/smaps | grep Rss | cut -d: -f2 | tr -d " " | cut -f1 -dk | sort -n | awk '{ sum += $1 } END { print sum }'
491080
The application is a web server using Jetty/Jersey/CDI bundled inside a fat far of 36 MB.
The following version of OS and Java are used (inside the container). The Docker image is based on openjdk:11-jre-slim.
$ java -version
openjdk version "11" 2018-09-25
OpenJDK Runtime Environment (build 11+28-Debian-1)
OpenJDK 64-Bit Server VM (build 11+28-Debian-1, mixed mode, sharing)
$ uname -a
Linux service1 4.9.125-linuxkit #1 SMP Fri Sep 7 08:20:28 UTC 2018 x86_64 GNU/Linux
https://gist.github.com/prasanthj/48e7063cac88eb396bc9961fb3149b58
Virtual memory used by a Java process extends far beyond just Java Heap. You know, JVM includes many subsytems: Garbage Collector, Class Loading, JIT compilers etc., and all these subsystems require certain amount of RAM to function.
JVM is not the only consumer of RAM. Native libraries (including standard Java Class Library) may also allocate native memory. And this won't be even visible to Native Memory Tracking. Java application itself can also use off-heap memory by means of direct ByteBuffers.
So what takes memory in a Java process?
JVM parts (mostly shown by Native Memory Tracking)
1. Java Heap
The most obvious part. This is where Java objects live. Heap takes up to -Xmx amount of memory.
2. Garbage Collector
GC structures and algorithms require additional memory for heap management. These structures are Mark Bitmap, Mark Stack (for traversing object graph), Remembered Sets (for recording inter-region references) and others. Some of them are directly tunable, e.g. -XX:MarkStackSizeMax, others depend on heap layout, e.g. the larger are G1 regions (-XX:G1HeapRegionSize), the smaller are remembered sets.
GC memory overhead varies between GC algorithms. -XX:+UseSerialGC and -XX:+UseShenandoahGC have the smallest overhead. G1 or CMS may easily use around 10% of total heap size.
3. Code Cache
Contains dynamically generated code: JIT-compiled methods, interpreter and run-time stubs. Its size is limited by -XX:ReservedCodeCacheSize (240M by default). Turn off -XX:-TieredCompilation to reduce the amount of compiled code and thus the Code Cache usage.
4. Compiler
JIT compiler itself also requires memory to do its job. This can be reduced again by switching off Tiered Compilation or by reducing the number of compiler threads: -XX:CICompilerCount.
5. Class loading
Class metadata (method bytecodes, symbols, constant pools, annotations etc.) is stored in off-heap area called Metaspace. The more classes are loaded - the more metaspace is used. Total usage can be limited by -XX:MaxMetaspaceSize (unlimited by default) and -XX:CompressedClassSpaceSize (1G by default).
6. Symbol tables
Two main hashtables of the JVM: the Symbol table contains names, signatures, identifiers etc. and the String table contains references to interned strings. If Native Memory Tracking indicates significant memory usage by a String table, it probably means the application excessively calls String.intern.
7. Threads
Thread stacks are also responsible for taking RAM. The stack size is controlled by -Xss. The default is 1M per thread, but fortunately things are not so bad. The OS allocates memory pages lazily, i.e. on the first use, so the actual memory usage will be much lower (typically 80-200 KB per thread stack). I wrote a script to estimate how much of RSS belongs to Java thread stacks.
There are other JVM parts that allocate native memory, but they do not usually play a big role in total memory consumption.
Direct buffers
An application may explicitly request off-heap memory by calling ByteBuffer.allocateDirect. The default off-heap limit is equal to -Xmx, but it can be overridden with -XX:MaxDirectMemorySize. Direct ByteBuffers are included in Other section of NMT output (or Internal before JDK 11).
The amount of direct memory in use is visible through JMX, e.g. in JConsole or Java Mission Control:
Besides direct ByteBuffers there can be MappedByteBuffers - the files mapped to virtual memory of a process. NMT does not track them, however, MappedByteBuffers can also take physical memory. And there is no a simple way to limit how much they can take. You can just see the actual usage by looking at process memory map: pmap -x <pid>
Address Kbytes RSS Dirty Mode Mapping
...
00007f2b3e557000 39592 32956 0 r--s- some-file-17405-Index.db
00007f2b40c01000 39600 33092 0 r--s- some-file-17404-Index.db
^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^
Native libraries
JNI code loaded by System.loadLibrary can allocate as much off-heap memory as it wants with no control from JVM side. This also concerns standard Java Class Library. In particular, unclosed Java resources may become a source of native memory leak. Typical examples are ZipInputStream or DirectoryStream.
JVMTI agents, in particular, jdwp debugging agent - can also cause excessive memory consumption.
This answer describes how to profile native memory allocations with async-profiler.
Allocator issues
A process typically requests native memory either directly from OS (by mmap system call) or by using malloc - standard libc allocator. In turn, malloc requests big chunks of memory from OS using mmap, and then manages these chunks according to its own allocation algorithm. The problem is - this algorithm can lead to fragmentation and excessive virtual memory usage.
jemalloc, an alternative allocator, often appears smarter than regular libc malloc, so switching to jemalloc may result in a smaller footprint for free.
Conclusion
There is no guaranteed way to estimate full memory usage of a Java process, because there are too many factors to consider.
Total memory = Heap + Code Cache + Metaspace + Symbol tables +
Other JVM structures + Thread stacks +
Direct buffers + Mapped files +
Native Libraries + Malloc overhead + ...
It is possible to shrink or limit certain memory areas (like Code Cache) by JVM flags, but many others are out of JVM control at all.
One possible approach to setting Docker limits would be to watch the actual memory usage in a "normal" state of the process. There are tools and techniques for investigating issues with Java memory consumption: Native Memory Tracking, pmap, jemalloc, async-profiler.
Update
Here is a recording of my presentation Memory Footprint of a Java Process.
In this video, I discuss what may consume memory in a Java process, how to monitor and restrain the size of certain memory areas, and how to profile native memory leaks in a Java application.
https://developers.redhat.com/blog/2017/04/04/openjdk-and-containers/:
Why is it when I specify -Xmx=1g my JVM uses up more memory than 1gb
of memory?
Specifying -Xmx=1g is telling the JVM to allocate a 1gb heap. It’s not
telling the JVM to limit its entire memory usage to 1gb. There are
card tables, code caches, and all sorts of other off heap data
structures. The parameter you use to specify total memory usage is
-XX:MaxRAM. Be aware that with -XX:MaxRam=500m your heap will be approximately 250mb.
Java sees host memory size and it is not aware of any container memory limitations. It doesn't create memory pressure, so GC also doesn't need to release used memory. I hope XX:MaxRAM will help you to reduce memory footprint. Eventually, you can tweak GC configuration (-XX:MinHeapFreeRatio,-XX:MaxHeapFreeRatio, ...)
There is many types of memory metrics. Docker seems to be reporting RSS memory size, that can be different than "committed" memory reported by jcmd (older versions of Docker report RSS+cache as memory usage).
Good discussion and links: Difference between Resident Set Size (RSS) and Java total committed memory (NMT) for a JVM running in Docker container
(RSS) memory can be eaten also by some other utilities in the container - shell, process manager, ... We don't know what else is running in the container and how do you start processes in container.
TL;DR
The detail usage of the memory is provided by Native Memory Tracking (NMT) details (mainly code metadata and garbage collector). In addition to that, the Java compiler and optimizer C1/C2 consume the memory not reported in the summary.
The memory footprint can be reduced using JVM flags (but there is impacts).
The Docker container sizing must be done through testing with the expected load the application.
Detail for each components
The shared class space can be disabled inside a container since the classes won't be shared by another JVM process. The following flag can be used. It will remove the shared class space (17MB).
-Xshare:off
The garbage collector serial has a minimal memory footprint at the cost of longer pause time during garbage collect processing (see Aleksey Shipilëv comparison between GC in one picture). It can be enabled with the following flag. It can save up to the GC space used (48MB).
-XX:+UseSerialGC
The C2 compiler can be disabled with the following flag to reduce profiling data used to decide whether to optimize or not a method.
-XX:+TieredCompilation -XX:TieredStopAtLevel=1
The code space is reduced by 20MB. Moreover, the memory outside JVM is reduced by 80MB (difference between NMT space and RSS space). The optimizing compiler C2 needs 100MB.
The C1 and C2 compilers can be disabled with the following flag.
-Xint
The memory outside the JVM is now lower than the total committed space. The code space is reduced by 43MB. Beware, this has a major impact on the performance of the application. Disabling C1 and C2 compiler reduces the memory used by 170 MB.
Using Graal VM compiler (replacement of C2) leads to a bit smaller memory footprint. It increases of 20MB the code memory space and decreases of 60MB from outside JVM memory.
The article Java Memory Management for JVM provides some relevant information the different memory spaces.
Oracle provides some details in Native Memory Tracking documentation. More details about compilation level in advanced compilation policy and in disable C2 reduce code cache size by a factor 5. Some details on Why does a JVM report more committed memory than the Linux process resident set size? when both compilers are disabled.
Java needs a lot a memory. JVM itself needs a lot of memory to run. The heap is the memory which is available inside the virtual machine, available to your application. Because JVM is a big bundle packed with all goodies possible it takes a lot of memory just to load.
Starting with java 9 you have something called project Jigsaw, which might reduce the memory used when you start a java app(along with start time). Project jigsaw and a new module system were not necessarily created to reduce the necessary memory, but if it's important you can give a try.
You can take a look at this example: https://steveperkins.com/using-java-9-modularization-to-ship-zero-dependency-native-apps/. By using the module system it resulted in CLI application of 21MB(with JRE embeded). JRE takes more than 200mb. That should translate to less allocated memory when the application is up(a lot of unused JRE classes will no longer be loaded).
Here is another nice tutorial: https://www.baeldung.com/project-jigsaw-java-modularity
If you don't want to spend time with this you can simply get allocate more memory. Sometimes it's the best.
How to size correctly the Docker memory limit?
Check the application by monitoring it for some-time. To restrict container's memory try using -m, --memory bytes option for docker run command - or something equivalant if you are running it otherwise
like
docker run -d --name my-container --memory 500m <iamge-name>
can't answer other questions.
I have an application that has an allocated heap memory of 20GB. But even though the Heap memory is barely or less than 50% used, my server swap space gets used up totally. Java is the process that is consuming 90% of the swap.
The swap gets released only after restarting the application with a below warning. Looking for finding out the root cause and any impact due to this. Will my app fail to start if the swap is filled?
Warning i see during App startup in logs:
There is insufficient memory for the Java Runtime Environment to continue.
Native memory allocation (mmap) failed to map 17895718912 bytes for committing reserved memory.. Out of swap space or heap resource limit exceeded (check with limits or ulimit)?
An error report with more information is generated,
it is saved as a file at this location:
/XX/myapp/apache-tomcat-7.0.90/bin/hs_err_pid86282.log
2020-01-14T05:17:18.742+0100 [INFO] [o.s.c.s.PostProcessorRegistrationDelegate$BeanPostProcessorChecker] Bean '(inner bean)#1814a032' of type [org.springframework.aop.aspectj.AspectJAroundAdvice] is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying)
***Warning: INFO: os::commit_memory(0x00000003fjgh0000, 17895718912, 0) failed; error='Not enough space' (errno=12)
There is insufficient memory for the Java Runtime Environment to continue.
Native memory allocation (mmap) failed to map 17895718912 bytes for committing reserved memory.. Out of
swap space or heap resource limit exceeded (check with limits or ulimit)?
An error report with more information is generated,
it is saved as a file at this location:
My JVM properties:
/XX/java/bin/java -Djava.util.logging.config.file=/XX/myapp/tomcat/conf/logging.properties -Djava.util.logging.manager=org.apache.juli.ClassLoaderLogManager -javaagent:/xx/myapp/newrelic/newrelic.jar -Djdk.tls.ephemeralDHKeySize=2048 -Xms20g -Xmx20g -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:+AlwaysPreTouch -XX:+DisableExplicitGC -XX:+CMSIncrementalMode -XX:+CMSIncrementalPacing -Djava.net.preferIPv4Stack=true -Dignore.endorsed.dirs= -classpath /XX/myapp/tomcat/bin/bootstrap.jar:/XX/myapp/tomcat/bin/tomcat-juli.jar -Dcatalina.base=/XX/myapp/tomcat -Dcatalina.home=/XX/myapp/tomcat -Djava.io.tmpdir=/XX/myapp/tomcat/temp org.apache.catalina.startup.Bootstrap start
Swap usage when checked for each process, its Java that uses 90% of Swap
Your Java process is made not only from heap memory, watch this for a good example.
Now, you say that you have 28GB of RAM, out of which you allocate 20GB for heap only. Not only do you reserve virtual memory, but you also commit it, via AlwaysPreTouch (I now doubt you even understand what this does). So your OS, maps 20GB of RAM to your process (simplified explanation).
Even if you see that only 50% is occupied, the garbage collector that you use - does not release memory back to the OS, so the entire 20GC are always occupied and can not be re-used by some other process. As such, it is pointless to measure or monitor the heap.
Your process fails with Native memory allocation (mmap) failed to map..., as said this is unrelated to the heap. It fails in native memory, this is != heap. I also do not know the specifics of your application, but -XX:+DisableExplicitGC might not be a good option; instead you might enable the concurrent invocation (if your GC supports that) via -XX:+ExplicitGCInvokesConcurrent.
You also seem to be using CMS garbage collector - which is deprecated.
Are there any tools that are able to get Metaspace dump from a Java8 hotspot vm ?
It seems you encounter a class loading leak.
Use
jmap -clstats PID to dump class loader statistics;
jcmd PID GC.class_stats to print the detailed information about memory usage of each loaded class. The latter requires -XX:+UnlockDiagnosticVMOptions.
The heap dump will also help, because each class in the Metaspace has a corresponding java.lang.Class instance in the heap.
If you wanted to dig into what your metaspace allocations are, a more in depth option would be to use Native Memory Tracking. You would want to use detail level native memory tracking, which can be enabled by passing -XX:NativeMemoryTracking=detail to the JVM. Then you can run
jcmd <pid> VM.native_memory baseline
To establish a baseline. Then after letting the JVM run until the problem should have reoccurred, you can run
jcmd <pid> VM.native_memory detail.diff
Then the Class allocations in the NMT diff will provide the metaspace allocations. The orcale docs have more information on NMT.
I have 16GB RAM and 64bit windows operating system.I want to run an web application I got heap space exception if i change VM arguments to -Xms3512m -Xmx3512m -XX:MaxPermSize=128m -XX:-UseGCOverheadLimit -XX:ReservedCodeCacheSize=32m I got exception as
Error occurred during initialization of VM
Could not reserve enough space for object heap
but I have another system with same configuration but that system accept this VM Arguments. please give me solution
Increase the heap size with: XX:MaxHeapSize=??m
Heap allocation done at the JVM initialization. It look for contiguous memory space of size -Xmx. If it could not find the continuous space of Xmx size then JVM failed during initialization Please add the argument -verbose:init and check the console output to identify which stage it failed on initialization.
I have a Java service that currently runs with a 14GB heap. I am keen to try out the -XX:+UseLargePages option to see how this might affect the performance of the system. I have configured the OS as described by Oracle using appropriate shared memory and page values (these can also be calculated with an online tool).
Once the OS is configured, I can see that it allocates the expected amount of memory as huge-pages. However, starting the VM with the -XX:+UseLargePages option set always results in one of the following errors:
When -Xms / -Xmx is almost equal to the huge page allocation:
Failed to reserve shared memory (errno = 28). // 'No space left on device'
When -Xms / -Xmx is less than the huge page allocation:
Failed to reserve shared memory (errno = 12). // 'Out of memory'
I did try introducing some leeway - so on a 32GB system I allocated 24GB of shared memory and hugepages to use with a JVM configured with a 20GB heap, of which only 14GB is currently utilized. I also verified that the user executing the JVM did have group rights consistent with /proc/sys/vm/hugetlb_shm_group.
Can anyone give me some pointers on where I might be going wrong and what I could try next?
Allocations/utilization:
-Xms / -Xmx - 20GB
Utilized heap - 14GB
/proc/sys/kernel/shmmax - 25769803776 (24GB)
/proc/sys/vm/nr_hugepages - 12288
Environment:
System memory - 32GB
System page size - 2048KB
debian 2.6.26-2-amd64
Sun JVM 1.6.0_20-b02
Solution
Thanks to #jfgagne for providing an answer that lead to a solution. In addition to the /proc/sys/kernel/shmall setting (specified as 4KB pages), I had to add entries to /etc/security/limits.conf as described on Thomas' blog. However, as my application is started using jsvc I also had to duplicate the settings for the root user (note that the limits are specified in KB):
root soft memlock 25165824
root hard memlock 25165824
pellegrino soft memlock 25165824
pellegrino hard memlock 25165824
It's also worth mentioning that settings could be tested quickly by starting the JVM with the -version argument:
java -XX:+UseLargePages -Xmx20g -version
When you use huge pages with Java, there is not only the heap using huge pages, but there is also the PermGen: do not forget to allocate space for it. It seems this is why you have a different errno message when you set Xmx near the amount of huge pages.
There is also the shmall kernel parameter that needs to be set which you did not mention, maybe it is what is blocking you. In your case, you should set it to 6291456.
The last thing to say: when using huge pages, the Xms parameter is not used anymore: Java reserves all Xmx in shared memory using huge pages.