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SpringBoot-线上服务卡死卡顿分析-http请求进不去服务-调整tomcat-undertow线程数

 

线程监控工具查看 stack.log文件
查内存镜像和阻塞情况：java调优相关：来源：https://gitee.com/jiangjiesheng/java-optimization-and-debug-for-prod-env	jps -l 查看当前系统运行了哪些Java进程【给出进程号和包名】 jstat 查看jvm统计信息（好像没啥实际的作用） jmap 手动导出内存镜像文件用于内存溢出分析（结合jps -l 或ps -ef | grep 查到进程号）  jmap -dump:format=b,file=java_pid9544_by_jmap.hprof 9544， 也可以通过参数自动导出 -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=./export/ 	          分析工具：MemoryAnalyzer.exe（MAT工具）     	jstack 实战死循环与死锁 ，由阻塞方法引起的死锁，看起来不动了【实用】   jstack -F 进程号 > jstack.deadlock.10892.txt # -F参数可以强制导出   或者 jstack -l  进程号 | grep deadlocks 进程号，直接展示结果。 	  报告中搜索 deadlock 关键词，如果没有死锁 No deadlocks found。  如果报告中有 Thread 1783: (state = BLOCKED)，这个怎么定位？结合服务的log日志中线程号来定位？   不处理的危害可能导致java占用内存越来越大，这个时候就需要去脚本限制内存大小了   jstack 8 > stack.log查SQL情况：mysql -hmysql -umaster -ppZdxysqJX4bK4VrB -Aedu:use seats   SELECT trx_mysql_thread_id,trx_query FROM INFORMATION_SCHEMA.INNODB_TRX 
where trx_mysql_thread_id in (select id from information_schema.processlist where command != 'Sleep' ) 
and (trx_query like "%course%" or trx_query like "%edu%" or trx_query like "%exam%" or trx_query like "%inte%")\G如何排查java程序导致的cpu和内存过高异常   https://blog.csdn.net/qq_40322236/article/details/127223538打印gc日志：-Dlogin.cache.switch=true -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps 
-XX:+DisableExplicitGC -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=./
undertow设置：-DinvokeSeconds=60 -Dserver.undertow.io-threads=16 -Dserver.undertow.worker-threads=500 或server:  undertow:    io-threads: 16    worker-threads: 500实测：无效，断点看相关的初始化还是按默认的计算规则走的
tomcat设置：-Dserver.tomcat.max-threads=500 -Dserver.tomcat.max-connections=20000-Dserver.tomcat.accept-count=2000 -Dserver.tomcat.min-spare-threads=20
下次卡的时候 再看线程另外看undertow的  java.lang.Thread.State: TIMED_WAITING (parking)
处理1通过代码初始化线程数，debug初始化有效package cn.jiangjiesheng.edu.config;
import org.springframework.beans.factory.annotation.Value;import org.springframework.boot.web.embedded.undertow.UndertowServletWebServerFactory;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;
@Configurationpublic class UndertowConfig {    @Value(value = "${server.undertow.io-threads:16}")    private Integer ioThreads;    @Value(value = "${server.undertow.worker-threads:500}")    private Integer workerThreads;
    @Bean    public UndertowServletWebServerFactory embeddedServletContainerFactory() {        UndertowServletWebServerFactory factory = new UndertowServletWebServerFactory();        factory.setIoThreads(ioThreads);        factory.setWorkerThreads(workerThreads);        return factory;    }}
处理2：加锁方式，调试不同人员的学习 会 触发 同一个课程id的数据同步，
所以同一课程处理处理过程中要排除掉进来的其他请求【可能也有问题，极低概率下正好错过了】
concurrentTaskBySingleKeyExecutor.doTask("syncEduTrainImplementRecordDetailService
#insertOrUpdateCourse", implementId + "#courseId" + courseId, new Runnable() {

网络资料：https://www.zhihu.com/tardis/bd/art/401186598?source_id=1001 
【关键，但是参数设置，不生效，要用代码初始化，根据断点看Undertow的初始化】
debug关键代码：private Undertow(Builder builder) {        ...        this.ioThreads = builder.ioThreads;        this.workerThreads = builder.workerThreads;        ...	}
public synchronized void start() {        UndertowLogger.ROOT_LOGGER.infof("starting server: %s", Version.getFullVersionString());        xnio = Xnio.getInstance(Undertow.class.getClassLoader());        channels = new ArrayList<>();        try {            if (internalWorker) {                worker = xnio.createWorker(OptionMap.builder()                        .set(Options.WORKER_IO_THREADS, ioThreads)                        .set(Options.CONNECTION_HIGH_WATER, 1000000)                        .set(Options.CONNECTION_LOW_WATER, 1000000)                        .set(Options.WORKER_TASK_CORE_THREADS, workerThreads)                        .set(Options.WORKER_TASK_MAX_THREADS, workerThreads)                        .set(Options.TCP_NODELAY, true)                        .set(Options.CORK, true)                        .addAll(workerOptions)                        .getMap());            }		....}
public static final class Builder {
        private int ioThreads;        private int workerThreads;        private Builder() {            ioThreads = Math.max(Runtime.getRuntime().availableProcessors(), 2);            workerThreads = ioThreads * 8;            long maxMemory = Runtime.getRuntime().maxMemory();            //smaller than 64mb of ram we use 512b buffers            if (maxMemory < 64 * 1024 * 1024) {                //use 512b buffers                directBuffers = false;                bufferSize = 512;            } else if (maxMemory < 128 * 1024 * 1024) {                //use 1k buffers                directBuffers = true;                bufferSize = 1024;            } else {                //use 16k buffers for best performance                //as 16k is generally the max amount of data that can be sent in a single write() call                directBuffers = true;                bufferSize = 1024 * 16 - 20; //the 20 is to allow some space for protocol headers, see UNDERTOW-1209            }        }

        public Builder setIoThreads(final int ioThreads) {            this.ioThreads = ioThreads;            return this;        }
        public Builder setWorkerThreads(final int workerThreads) {            this.workerThreads = workerThreads;            return this;        }    }
更多网络资料：https://blog.csdn.net/weixin_43958014/article/details/129684017 
https://www.lxiaoyu.com/p/161092 
https://www.cnblogs.com/koal/p/12347982.html 
https://blog.csdn.net/tiandixuanwuliang/article/details/102733441https://www.ibm.com/support/pages/ibm-thread-and-monitor-dump-analyzer-java-tmda 
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所属分类：Java
本文标签： Spring Boot Spring
本文链接： https://code.jiangjiesheng.cn/article/32
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SpringBoot-线上服务卡死卡顿分析-http请求进不去服务-调整tomcat-undertow线程数

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