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JAVA使用堆外内存导致swap飙高 #29

Open nereuschen opened 9 years ago

nereuschen commented 9 years ago

近期遇到一个堆外内存导致swap飙高的问题，这类问题比较罕见，因此将整个排查过程记录下来了

现象描述

最近1周线上服务器时不时出现swap报警（swap超过内存10%时触发报警，内存是4G，因此swap超过400M会触发报警），每次都是童鞋们通过重启tomcat解决的； 但导致的根本原因是什么呢？必须找到根本原因才行，总是这么重启就有点low了

问题排查

于是找了1台占用了swap但还未触发报警的服务器进行了排查 以下是当时通过top命令观察到的结果

23:03:22 swap占用了354M的内存 top-swap

23:55:42 swap占用了398M的内存 top-swap-2

原因分析

到底是什么原因导致swap飙高呢？肯定是tomcat，因为每次重启tomcat就解决了;但根本原因是？

谁占用了swap

通过以下脚本 swap.sh

#!/bin/bash
# Get current swap usage for all running processes
# Erik Ljungstrom 27/05/2011
do_swap () {
SUM=0
OVERALL=0
for DIR in `find /proc/ -maxdepth 1 -type d | egrep "^/proc/[0-9]"` ; do
PID=`echo $DIR | cut -d / -f 3`
PROGNAME=`ps -p $PID -o comm --no-headers`
for SWAP in `grep Swap $DIR/smaps 2>/dev/null| awk '{ print $2 }'`
do
let SUM=$SUM+$SWAP
done
echo "PID=$PID - Swap used: $SUM - ($PROGNAME )"
let OVERALL=$OVERALL+$SUM
SUM=0

done
echo "Overall swap used: $OVERALL"
}
do_swap  |awk -F[\ \(] '{print $5,$1,$8}' | sort -n | tail -3

可以看出PID=19911这个进程使用了324M的swap

swap-sh

通过grep进程号19911可以看出确实是tomcat占用swap最多 grep-pid

进程19911占用总的物理内存是3.1G，java占用的堆内内存大小为2.78G，剩下的320M是堆外内存占用的

Max memory = [-Xmx] + [-XX:MaxPermSize] + number_of_threads * [-Xss]

2779M=2048M+268M+463*1M

sudo -u tomcat ./jinfo -flag MaxPermSize 19911
-XX:MaxPermSize=268435456
java -XX:+PrintFlagsFinal -version | grep ThreadStackSize
     intx CompilerThreadStackSize                   = 0               {pd product}
     intx ThreadStackSize                           = 1024            {pd product}
     intx VMThreadStackSize                         = 1024            {pd product}
java version "1.7.0_45"
Java(TM) SE Runtime Environment (build 1.7.0_45-b18)
Java HotSpot(TM) 64-Bit Server VM (build 24.45-b08, mixed mode)
java -XX:+PrintFlagsFinal -version | grep -i permsize
    uintx AdaptivePermSizeWeight                    = 20              {product}
    uintx MaxPermSize                               = 85983232        {pd product}
    uintx PermSize                                  = 21757952        {pd product}
java version "1.7.0_45"
Java(TM) SE Runtime Environment (build 1.7.0_45-b18)
Java HotSpot(TM) 64-Bit Server VM (build 24.45-b08, mixed mode)

哪行代码占用了堆外内存

堆内内存溢出可以直接通过MAT分析堆信息就可以定位到具体的代码，但是对于堆外内存就必须通过BTrace来解决

google-perftools 定位类名和方法名

如何安装和使用google-perftools见这里 由于要启动google-perftools需要重启tomcat，所以重启tomcat后，PID从19911变成了9176

重启tomcat后，会自动生成heap文件，文件名的命名规范是gperf_pid.xxx.heap，所以我们只需要关注gperf_9176.*即可

[xxxx@xxxx   /home/xxx/logs]$ ll *.heap
…...
-rw-r--r-- 1 tomcat tomcat    5048 May  6 10:46 gperf_9171.0001.heap
-rw-r--r-- 1 tomcat tomcat    5036 May  6 10:46 gperf_9173.0001.heap
-rw-r--r-- 1 tomcat tomcat    5055 May  6 10:46 gperf_9174.0001.heap
-rw-r--r-- 1 tomcat tomcat    5352 May  6 10:46 gperf_9175.0001.heap
-rw-r--r-- 1 tomcat tomcat 1048563 May  6 10:46 gperf_9176.0001.heap
-rw-r--r-- 1 tomcat tomcat 1048564 May  6 10:46 gperf_9176.0002.heap
-rw-r--r-- 1 tomcat tomcat 1048563 May  6 10:47 gperf_9176.0003.heap
-rw-r--r-- 1 tomcat tomcat 1048565 May  6 10:47 gperf_9176.0004.heap
-rw-r--r-- 1 tomcat tomcat 1048574 May  6 10:49 gperf_9176.0005.heap
-rw-r--r-- 1 tomcat tomcat 1048574 May  6 10:50 gperf_9176.0006.heap
-rw-r--r-- 1 tomcat tomcat 1048568 May  6 10:51 gperf_9176.0007.heap
-rw-r--r-- 1 tomcat tomcat 1048572 May  6 10:53 gperf_9176.0008.heap
-rw-r--r-- 1 tomcat tomcat 1048564 May  6 10:55 gperf_9176.0009.heap
-rw-r--r-- 1 tomcat tomcat 1048560 May  6 10:58 gperf_9176.0010.heap
-rw-r--r-- 1 tomcat tomcat 1048563 May  6 11:00 gperf_9176.0011.heap
-rw-r--r-- 1 tomcat tomcat 1048564 May  6 11:03 gperf_9176.0012.heap
…...

分析heap文件

/home/google-perftools/bin/pprof  --text  /home/java  /home/logs/gperf_9176.0010.heap
Using local file /home/java.
Using local file /home/logs/gperf_9176.0010.heap.
Total: 186.4 MB
91.2 48.9% 48.9% 91.2 48.9% updatewindow
52.5 28.2% 77.1% 52.5 28.2% os::malloc
38.0 20.4% 97.4% 38.0 20.4% inflateInit2_
3.0 1.6% 99.0% 3.0 1.6% init
0.8 0.4% 99.5% 0.8 0.4% ObjectSynchronizer::omAlloc
0.4 0.2% 99.7% 0.4 0.2% readCEN
0.3 0.2% 99.9% 38.3 20.5% Java_java_util_zip_Inflater_init
0.1 0.1% 100.0% 0.1 0.1% _dl_allocate_tls
0.0 0.0% 100.0% 0.0 0.0% _dl_new_object
0.0 0.0% 100.0% 1.1 0.6% Thread::Thread
0.0 0.0% 100.0% 0.0 0.0% CollectedHeap::CollectedHeap
0.0 0.0% 100.0% 0.0 0.0% Events::init
0.0 0.0% 100.0% 0.4 0.2% ZIP_Put_In_Cache0
0.0 0.0% 100.0% 0.0 0.0% read_alias_file
0.0 0.0% 100.0% 0.0 0.0% _nl_intern_locale_data

可以看出是java.util.zip.Inflater的init()占用了比较多的内存

通过BTrace定位代码调用方

编写代码BtracerInflater.java对init方法进行拦截

import static com.sun.btrace.BTraceUtils.*;
import com.sun.btrace.annotations.*;

import java.nio.ByteBuffer;
import java.lang.Thread;

@BTrace public class BtracerInflater{
   @OnMethod(
      clazz="java.util.zip.Inflater",
      method="/.*/"
   )
   public static void traceCacheBlock(){
      println("Who call java.util.zip.Inflater's methods :");
     jstack();
   }
}

运行BTrace

[xxxx@l-xxx.xx.xx /home/xxx/btrace-bin/bin]$ sudo -u tomcat ./btrace -cp ../build 9176 BtracerInflater.java|more
Who call java.util.zip.Inflater's methods :
java.util.zip.Inflater.<init>(Inflater.java:102)
java.util.zip.GZIPInputStream.<init>(GZIPInputStream.java:76)
java.util.zip.GZIPInputStream.<init>(GZIPInputStream.java:90)
com.xxx.OrderDiffUtil.ungzip(OrderDiffUtil.java:54)
com.xxx.OrderDiffUtil.parse(OrderDiffUtil.java:32)
com.xxx.FaxOrderEventListener.takeSectionChangedInfo(FaxOrderEventListener.java:87)
com.xxx.FaxOrderEventListener.onMessage(FaxOrderEventListener.java:46)
.......

可以看出是OrderDiffUtil的ungzip()调用了java.util.zip.Inflater的init() 看看OrderDiffUtil.ungzip()

    private static String ungzip(String encodeJson) {
        ByteArrayOutputStream out = new ByteArrayOutputStream(encodeJson.length() * 5);
        ByteArrayInputStream in = null;
        try {
            in = new ByteArrayInputStream(Base64.decode(encodeJson));
        } catch (UnsupportedEncodingException e) {
            return "{}";
        }
        try {
            GZIPInputStream gunzip = new GZIPInputStream(in);
            byte buffer[] = new byte[1024];
            int len = 0;
            while ((len = gunzip.read(buffer)) != -1) {
                out.write(buffer, 0, len);
            }
        } catch (IOException e) {
            return "{}";
        }
        try {
            return out.toString("ISO-8859-1");
        } catch (UnsupportedEncodingException e) {
        }
        return "{}";
    }

可见gunzip未被close 所以根本原因是未调用GZIPInputStream的close()关闭流导致堆外内存占用

总结

http://m.blog.csdn.net/blog/whuoyunshen88/19508075 http://itindex.net/detail/11709-perftools-内存-hbase http://outofmemory.cn/code-snippet/1713/Btrace-usage-introduction