Growing resident memory usage (RSS) of Java Proces

Question

Our recent observation on our production system, tells us the resident memory usage of our Java container grows up. Regarding to this problem, we have made some investigations to understand, why java process consumes much more memory than Heap + Thread Stacks + Shared Objects + Code Cache + etc, using some native tools like pmap. As a result of this, we found some 64M memory blocks (in pairs) allocated by native process (probably with malloc/mmap) :

0000000000400000      4K r-x--  /usr/java/jdk1.7.0_17/bin/java
0000000000600000      4K rw---  /usr/java/jdk1.7.0_17/bin/java
0000000001d39000   4108K rw---    [ anon ]
0000000710000000  96000K rw---    [ anon ]
0000000715dc0000  39104K -----    [ anon ]
00000007183f0000 127040K rw---    [ anon ]
0000000720000000 3670016K rw---    [ anon ]
00007fe930000000  62876K rw---    [ anon ]
00007fe933d67000   2660K -----    [ anon ]
00007fe934000000  20232K rw---    [ anon ]
00007fe9353c2000  45304K -----    [ anon ]
00007fe938000000  65512K rw---    [ anon ]
00007fe93bffa000     24K -----    [ anon ]
00007fe940000000  65504K rw---    [ anon ]
00007fe943ff8000     32K -----    [ anon ]
00007fe948000000  61852K rw---    [ anon ]
00007fe94bc67000   3684K -----    [ anon ]
00007fe950000000  64428K rw---    [ anon ]
00007fe953eeb000   1108K -----    [ anon ]
00007fe958000000  42748K rw---    [ anon ]
00007fe95a9bf000  22788K -----    [ anon ]
00007fe960000000   8080K rw---    [ anon ]
00007fe9607e4000  57456K -----    [ anon ]
00007fe968000000  65536K rw---    [ anon ]
00007fe970000000  22388K rw---    [ anon ]
00007fe9715dd000  43148K -----    [ anon ]
00007fe978000000  60972K rw---    [ anon ]
00007fe97bb8b000   4564K -----    [ anon ]
00007fe980000000  65528K rw---    [ anon ]
00007fe983ffe000      8K -----    [ anon ]
00007fe988000000  14080K rw---    [ anon ]
00007fe988dc0000  51456K -----    [ anon ]
00007fe98c000000  12076K rw---    [ anon ]
00007fe98cbcb000  53460K -----    [ anon ]

I interpret the line with 0000000720000000 3670016K refers to the heap space, of which size we define using JVM parameter "-Xmx". Right after that, the pairs begin, of which sum is 64M exactly. We are using CentOS release 5.10 (Final) 64-bit arch and JDK 1.7.0_17 .

The question is, what are those blocks? Which subsystem does allocate these?

Update: We do not use JIT and/or JNI native code invocations.

Answer 1

I ran in to the same problem. This is a known problem with glibc >= 2.10

The cure is to set this env variable export MALLOC_ARENA_MAX=4

IBM article about setting MALLOC_ARENA_MAX https://www.ibm.com/developerworks/community/blogs/kevgrig/entry/linux_glibc_2_10_rhel_6_malloc_may_show_excessive_virtual_memory_usage?lang=en

Google for MALLOC_ARENA_MAX or search for it on SO to find a lot of references.

You might want to tune also other malloc options to optimize for low fragmentation of allocated memory:

# tune glibc memory allocation, optimize for low fragmentation
# limit the number of arenas
export MALLOC_ARENA_MAX=2
# disable dynamic mmap threshold, see M_MMAP_THRESHOLD in "man mallopt"
export MALLOC_MMAP_THRESHOLD_=131072
export MALLOC_TRIM_THRESHOLD_=131072
export MALLOC_TOP_PAD_=131072
export MALLOC_MMAP_MAX_=65536

Answer 2

It's also possible that there is a native memory leak. A common problem is native memory leaks caused by not closing a ZipInputStream/GZIPInputStream.

A typical way that a ZipInputStream is opened is by a call to Class.getResource/ClassLoader.getResource and calling openConnection().getInputStream() on the java.net.URL instance or by calling Class.getResourceAsStream/ClassLoader.getResourceAsStream. One must ensure that these streams always get closed.

You can use jemalloc to debug native memory leaks by enabling malloc sampling profiling by specifying the settings in MALLOC_CONF environment variable. Detailed instructions are available in this blog post: http://www.evanjones.ca/java-native-leak-bug.html . This blog post also has information about using jemalloc to debug a native memory leak in java applications.

The same blog also contains information about another native memory leak related to ByteBuffers.