【JVM】记录一次线上SWAP偏高告警的故障分析过程

近期遇到一个堆外内存致使swap飙高的问题，这类问题比较罕见，所以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，所以swap超过400M会触发报警），每次都是童鞋们经过重启tomcat解决的；
但致使的根本缘由是什么呢？必须找到根本缘由才行，老是这么重启就有点low了

问题排查

因而找了1台占用了swap但还未触发报警的服务器进行了排查
如下是当时经过top命令观察到的结果

23:03:22 swap占用了354M的内存

23:55:42 swap占用了398M的内存

缘由分析

究竟是什么缘由致使swap飙高呢？确定是tomcat，由于每次重启tomcat就解决了;但根本缘由是？

谁占用了swap

经过如下脚本 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

 

能够看出PID=19911这个进程使用了324M的swap

经过grep进程号19911能够看出确实是tomcat占用swap最多

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

堆内内存溢出能够直接经过MAT分析堆信息就能够定位到具体的代码，可是对于堆外内存就必须经过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
因为要启动google-perftools须要重启tomcat，因此重启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，因此咱们只须要关注gperf_9176.*便可

[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

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

经过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)
.......

能够看出是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

因此根本缘由是未调用GZIPInputStream的close()关闭流致使堆外内存占用