⭐⭐⭐ Spring Boot 项目实战	⭐⭐⭐ Spring Cloud 项目实战
《Dubbo 实现原理与源码解析 —— 精品合集》	《Netty 实现原理与源码解析 —— 精品合集》
《Spring 实现原理与源码解析 —— 精品合集》	《MyBatis 实现原理与源码解析 —— 精品合集》
《Spring MVC 实现原理与源码解析 —— 精品合集》	《数据库实体设计合集》
《Spring Boot 实现原理与源码解析 —— 精品合集》	《Java 面试题 + Java 学习指南》

摘要: 原创出处 juejin.cn/post/7259320326898876477 「小蚂蚁技术」欢迎转载，保留摘要，谢谢！

🙂🙂🙂关注微信公众号：【芋道源码】有福利：

RocketMQ / MyCAT / Sharding-JDBC 所有源码分析文章列表

RocketMQ / MyCAT / Sharding-JDBC 中文注释源码 GitHub 地址

您对于源码的疑问每条留言都将得到认真回复。甚至不知道如何读源码也可以请教噢。

新的源码解析文章实时收到通知。每周更新一篇左右。

认真的源码交流微信群。

1背景

Helios 系统要处理的数据量比较大，尤其是查询所有服务一天的评分数据时要返回每日 1440 分钟的所有应用的评分，总计有几十万个数据点，接口有时延迟会达到数秒。

本文记录如何利用 Arthas ，将接口从几百几千 ms，优化到几十 ms。

从链路上看，线上获取一整天的数据时大概 300 多 ms，而查询数据库只有 11ms，说明大部分时间都是程序组装数据时消耗的，于是动起了优化代码的念头。

2优化过程

代码业务可以不用去理解，最主要的是看利用trace优化的过程

3初始未优化版本

代码

private HeliosGetScoreResponse queryScores(HeliosGetScoreRequest request) {
    HeliosGetScoreResponse response = new HeliosGetScoreResponse();

    List<HeliosScore> heliosScores = heliosService.queryScoresTimeBetween(request.getStartTime(), request.getEndTime(), request.getFilterByAppId());
    if (CollectionUtils.isEmpty(heliosScores)) {
        return response;
    }

    Set<String> dateSet = new HashSet<>();

    Map<String, List<HeliosScore>> groupByAppIdHeliosScores = heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
    for (List<HeliosScore> value : groupByAppIdHeliosScores.values()) {
        value.sort(Comparator.comparing(HeliosScore::getTimeFrom));
        HeliosGetScoreResponse.Score score = new HeliosGetScoreResponse.Score();
        score.setNamespace(value.get(0).getNamespace());
        score.setAppId(value.get(0).getAppId());
        for (HeliosScore heliosScore : value) {
            List<HeliosScore> splitHeliosScores = heliosScore.split();
            for (HeliosScore splitHeliosScore : splitHeliosScores) {
                if (splitHeliosScore.getTimeFrom().compareTo(request.getStartTime()) < 0) {
                    continue;
                }
                if (splitHeliosScore.getTimeFrom().compareTo(request.getEndTime()) > 0) {
                    break;
                }
                dateSet.add(DateUtils.yyyyMMddHHmm.formatDate(splitHeliosScore.getTimeFrom()));
                if (splitHeliosScore.getScores() == null) {
                    splitHeliosScore.setScores("100");
                    log.error("查询时发现数据缺失: {}", heliosScore);
                }
                score.add(Math.max(0, Integer.parseInt(splitHeliosScore.getScores())), null);
            }
        }
        response.getValues().add(score);
    }

    response.setDates(new ArrayList<>(dateSet).stream().sorted().collect(Collectors.toList()));
    return response;
}

Arthas Trace

---ts=2021-08-17 16:28:00;thread_name=http-nio-8080-exec-10;id=81;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@20864cd1
    `---[4046.398447ms] xxxService.controller.HeliosController:queryScores()
        +---[0.022259ms] xxxService.model.helios.HeliosGetScoreResponse:<init>() #147
        +---[0.007132ms] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #149
        +---[0.006985ms] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #149
        +---[0.008704ms] xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId() #149
        +---[19.284658ms] xxxService.service.HeliosService:queryScoresTimeBetween() #149
        +---[0.017468ms] org.apache.commons.collections.CollectionUtils:isEmpty() #150
        +---[0.008054ms] java.util.HashSet:<init>() #154
        +---[0.027591ms] java.util.List:stream() #156
        +---[0.044229ms] java.util.stream.Collectors:groupingBy() #156
        +---[0.155582ms] java.util.stream.Stream:collect() #156
        +---[0.018318ms] java.util.Map:values() #157
        +---[0.019199ms] java.util.Collection:iterator() #157
        +---[min=3.51E-4ms,max=0.014266ms,total=0.125003ms,count=123] java.util.Iterator:hasNext() #157
        +---[min=5.11E-4ms,max=0.010188ms,total=0.145693ms,count=122] java.util.Iterator:next() #157
        +---[min=4.89E-4ms,max=0.045356ms,total=0.321978ms,count=122] java.util.Comparator:comparing() #158
        +---[min=0.003637ms,max=0.033049ms,total=0.928795ms,count=122] java.util.List:sort() #158
        +---[min=5.94E-4ms,max=0.010442ms,total=0.1485ms,count=122] xxxService.model.helios.HeliosGetScoreResponse$Score:<init>() #159
        +---[min=4.5E-4ms,max=0.010857ms,total=0.12773ms,count=122] java.util.List:get() #160
        +---[min=5.01E-4ms,max=0.007849ms,total=0.123696ms,count=122] xxxService.helios.entity.HeliosScore:getNamespace() #160
        +---[min=6.5E-4ms,max=0.007324ms,total=0.135906ms,count=122] xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace() #160
        +---[min=3.72E-4ms,max=0.010288ms,total=0.086703ms,count=122] java.util.List:get() #161
        +---[min=5.1E-4ms,max=0.00627ms,total=0.103871ms,count=122] xxxService.helios.entity.HeliosScore:getAppId() #161
        +---[min=5.97E-4ms,max=0.006531ms,total=0.126184ms,count=122] xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId() #161
        +---[min=4.45E-4ms,max=0.020198ms,total=0.138299ms,count=122] java.util.List:iterator() #162
        +---[min=3.42E-4ms,max=0.014615ms,total=0.256056ms,count=366] java.util.Iterator:hasNext() #162
        +---[min=3.59E-4ms,max=0.014974ms,total=0.174396ms,count=244] java.util.Iterator:next() #162
        +---[min=0.071035ms,max=0.148132ms,total=19.444179ms,count=244] xxxService.helios.entity.HeliosScore:split() #163
        +---[min=4.06E-4ms,max=0.022364ms,total=0.210152ms,count=244] java.util.List:iterator() #164
        +---[min=3.07E-4ms,max=0.199649ms,total=143.267893ms,count=351604] java.util.Iterator:hasNext() #164
        +---[min=3.25E-4ms,max=24.863976ms,total=177.15363ms,count=351360] java.util.Iterator:next() #164
        +---[min=3.93E-4ms,max=0.096771ms,total=176.843018ms,count=351360] xxxService.helios.entity.HeliosScore:getTimeFrom() #165
        +---[min=4.07E-4ms,max=18.772715ms,total=205.632183ms,count=351360] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #165
        +---[min=3.33E-4ms,max=0.045589ms,total=149.24486ms,count=351360] java.util.Date:compareTo() #165
        +---[min=3.93E-4ms,max=0.032972ms,total=86.466793ms,count=175680] xxxService.helios.entity.HeliosScore:getTimeFrom() #168
        +---[min=4.12E-4ms,max=0.061003ms,total=94.294061ms,count=175680] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #168
        +---[min=3.37E-4ms,max=0.038792ms,total=74.505056ms,count=175680] java.util.Date:compareTo() #168
        +---[min=3.97E-4ms,max=0.036548ms,total=87.693935ms,count=175680] xxxService.helios.entity.HeliosScore:getTimeFrom() #171
     1  +---[min=0.001952ms,max=0.068413ms,total=391.739063ms,count=175680] xxxService.utils.DateUtils$yyyyMMddHHmm:formatDate() #171
        +---[min=4.07E-4ms,max=0.037904ms,total=108.107714ms,count=175680] java.util.Set:add() #171
        +---[min=3.95E-4ms,max=0.031555ms,total=88.173857ms,count=175680] xxxService.helios.entity.HeliosScore:getScores() #172
        +---[min=3.88E-4ms,max=0.033584ms,total=84.689466ms,count=175680] xxxService.helios.entity.HeliosScore:getScores() #176
        +---[min=3.11E-4ms,max=0.038121ms,total=69.708752ms,count=175680] java.lang.Math:max() #176
        +---[min=4.66E-4ms,max=0.03391ms,total=104.476576ms,count=175680] xxxService.model.helios.HeliosGetScoreResponse$Score:add() #176
        +---[min=6.17E-4ms,max=0.01503ms,total=0.159826ms,count=122] xxxService.model.helios.HeliosGetScoreResponse:getValues() #179
        +---[min=6.44E-4ms,max=0.03742ms,total=0.21068ms,count=122] java.util.List:add() #179
        +---[0.108961ms] java.util.ArrayList:<init>() #182
        +---[0.017455ms] java.util.ArrayList:stream() #182
        +---[0.011099ms] java.util.stream.Stream:sorted() #182
        +---[0.013699ms] java.util.stream.Collectors:toList() #182
        +---[0.38178ms] java.util.stream.Stream:collect() #182
        `---[0.004627ms] xxxService.model.helios.HeliosGetScoreResponse:setDates() #182

分析

Arthas 显示总共花了 4 秒，但实际上在链路上看大概是 350~450ms 左右。其他多出来的时间是 Arthas 每一次执行统计的消耗，因为方法里的循环比较多。这也告诉我们，不要用 trace 去看循环很多的方法。会对性能有非常严重的影响。

可以看出整个函数有 3 个循环，第一层循环的数量为 appId 的数量约为 140，第二层是查出来的数据条数，一天的数据已经归并了所以这里应该是 1，第三层是时间区间的分钟数，一天的话就是 1440 个。

Trace 中可以看到消耗最多的是封装的一个 SimpleDateFormat.formatDate()。

4第一次优化

优化方向

遍历每个时间点的思路改变，把合并过的大对象拆分成一个个小对象直接遍历，改成先合并起来，通过时间点逻辑上遍历。这样会减少创建几十万个对象。

将时间点集合 Set<String> dateSet 改为 Set<Date>，这样减少反复 formatDate() 的开销。

优化字符串转数字的过程，减少 Integer.parseInt方法调用，改为用 Map<String, Integer> 提前创建出 0~100 的字符串数字字典。（后来经过 JMH 测试，还是 Integer.parseInt 最快）

代码

private HeliosGetScoreResponse queryScores(HeliosGetScoreRequest request) {
   HeliosGetScoreResponse response = new HeliosGetScoreResponse();
   List<HeliosScore> heliosScoresRecord = heliosService.queryScoresTimeBetween(request.getStartTime(), request.getEndTime(), request.getFilterByAppId());
   if (CollectionUtils.isEmpty(heliosScoresRecord)) {
       return response;
   }
   
   Set<Date> dateSet = new HashSet<>();
   
   List<HeliosScore> heliosScores = HeliosDataMergeJob.mergeData(heliosScoresRecord);
   
   Map<String, List<HeliosScore>> groupByAppIdHeliosScores = heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
   
   for (List<HeliosScore> scores : groupByAppIdHeliosScores.values()) {
       HeliosScore heliosScore = scores.get(0);
       HeliosGetScoreResponse.Score score = new HeliosGetScoreResponse.Score();
       score.setNamespace(heliosScore.getNamespace());
       score.setAppId(heliosScore.getAppId());
       score.setScores(new ArrayList<>());
       response.getValues().add(score);
   
       List<Integer> scoreIntList = HeliosHelper.splitScores(heliosScore);
   
       // 以 requestTime 为准
       Calendar indexDate = DateUtils.roundDownMinute(request.getStartTime().getTime());
       int index = 0;
       // 如果 timeFrom < requestTime，则增加 timeFrom 到 requestTime
       while (indexDate.getTime().compareTo(heliosScore.getTimeFrom()) > 0) {
           heliosScore.getTimeFrom().setTime(heliosScore.getTimeFrom().getTime() + 60_000);
           index++;
       }
   
       while (indexDate.getTime().compareTo(request.getEndTime()) <= 0 && indexDate.getTime().compareTo(heliosScore.getTimeTo()) <= 0  && index < scoreIntList.size()) {
           Integer scoreInt = scoreIntList.get(index++);
           score.getScores().add(scoreInt);
           dateSet.add(indexDate.getTime());
           indexDate.add(Calendar.MINUTE, 1);
       }
   }
   
       response.setDates(new ArrayList<>(dateSet).stream().sorted().map(DateUtils.yyyyMMddHHmm::formatDate).collect(Collectors.toList()));
       return response;
}

Arthas Trace

---ts=2021-08-17 14:44:11;thread_name=http-nio-8080-exec-10;id=ab;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@16ea0f22
    `---[6997.005629ms] xxxService.controller.HeliosController:queryScores()
        +---[0.020032ms] xxxService.model.helios.HeliosGetScoreResponse:<init>() #149
        +---[0.007451ms] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #151
        +---[min=0.001054ms,max=7.458198ms,total=213.19538ms,count=170754] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #57
        +---[0.007267ms] xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId() #57
        +---[15.255919ms] xxxService.service.HeliosService:queryScoresTimeBetween() #57
        +---[0.020045ms] org.apache.commons.collections.CollectionUtils:isEmpty() #152
        +---[0.015161ms] java.util.HashSet:<init>() #156
        +---[20.06713ms] xxxService.helios.jobs.HeliosDataMergeJob:mergeData() #158
        +---[0.043042ms] java.util.List:stream() #160
        +---[0.028232ms] java.util.stream.Collectors:groupingBy() #57
        +---[min=0.087087ms,max=1.931641ms,total=2.018728ms,count=2] java.util.stream.Stream:collect() #57
        +---[0.0151ms] java.util.Map:values() #162
        +---[0.019611ms] java.util.Collection:iterator() #57
        +---[min=7.55E-4ms,max=0.015165ms,total=0.201221ms,count=121] java.util.Iterator:hasNext() #57
        +---[min=0.001178ms,max=0.02477ms,total=0.220931ms,count=120] java.util.Iterator:next() #57
        +---[min=8.14E-4ms,max=0.01101ms,total=0.155044ms,count=120] java.util.List:get() #163
        +---[min=0.001049ms,max=0.009425ms,total=0.231297ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:<init>() #164
        +---[min=0.001167ms,max=0.009721ms,total=0.194502ms,count=120] xxxService.helios.entity.HeliosScore:getNamespace() #165
        +---[min=0.001222ms,max=0.020409ms,total=0.264791ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace() #57
        +---[min=0.001097ms,max=0.006475ms,total=0.169987ms,count=120] xxxService.helios.entity.HeliosScore:getAppId() #166
        +---[min=0.00121ms,max=0.007106ms,total=0.207877ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId() #57
        +---[min=8.63E-4ms,max=0.008981ms,total=0.176195ms,count=120] java.util.ArrayList:<init>() #167
        +---[min=0.001225ms,max=0.021948ms,total=0.340375ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setScores() #57
        +---[min=0.00112ms,max=0.008984ms,total=0.196212ms,count=120] xxxService.model.helios.HeliosGetScoreResponse:getValues() #168
        +---[min=7.64E-4ms,max=0.027237ms,total=154.660479ms,count=170753] java.util.List:add() #57
        +---[min=0.028779ms,max=0.237608ms,total=20.049731ms,count=120] xxxService.helios.HeliosHelper:splitScores() #170
        +---[min=0.001178ms,max=0.008102ms,total=0.199087ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #173
        +---[min=6.89E-4ms,max=0.048069ms,total=140.74298ms,count=170040] java.util.Date:getTime() #57
        +---[min=0.004686ms,max=0.03805ms,total=0.775394ms,count=120] xxxService.utils.DateUtils:roundDownMinute() #57
        +---[min=7.84E-4ms,max=7.562581ms,total=162.855553ms,count=170040] java.util.Calendar:getTime() #176
      2 +---[min=9.94E-4ms,max=0.029962ms,total=385.371864ms,count=339960] xxxService.helios.entity.HeliosScore:getTimeFrom() #57
      1 +---[min=7.76E-4ms,max=7.936578ms,total=483.361269ms,count=511428] java.util.Date:compareTo() #57
        +---[min=9.95E-4ms,max=0.077109ms,total=192.749805ms,count=169920] xxxService.helios.entity.HeliosScore:getTimeFrom() #177
        +---[min=6.94E-4ms,max=7.358942ms,total=151.184751ms,count=169920] java.util.Date:setTime() #57
        +---[min=7.67E-4ms,max=0.029244ms,total=152.500401ms,count=170753] java.util.Calendar:getTime() #181
        +---[min=7.65E-4ms,max=0.016336ms,total=151.879643ms,count=170635] java.util.Calendar:getTime() #182
        +---[min=0.001011ms,max=0.028133ms,total=196.192946ms,count=170635] xxxService.helios.entity.HeliosScore:getTimeTo() #57
        +---[min=6.93E-4ms,max=0.836104ms,total=141.443001ms,count=170635] java.util.List:size() #57
        +---[min=7.63E-4ms,max=7.940119ms,total=162.285955ms,count=170633] java.util.List:get() #183
      3 +---[min=0.001068ms,max=0.973964ms,total=209.721ms,count=170633] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #184
        +---[min=7.71E-4ms,max=0.028856ms,total=154.918574ms,count=170633] java.util.Calendar:getTime() #185
        +---[min=8.07E-4ms,max=8.030316ms,total=186.971072ms,count=170633] java.util.Set:add() #57
        +---[min=7.82E-4ms,max=0.034732ms,total=156.2645ms,count=170633] java.util.Calendar:add() #186
        +---[0.050615ms] java.util.ArrayList:<init>() #190
        +---[0.019114ms] java.util.ArrayList:stream() #57
        +---[0.029096ms] java.util.stream.Stream:sorted() #57
        +---[0.018823ms] java.util.stream.Stream:map() #57
        +---[0.009092ms] java.util.stream.Collectors:toList() #57
        `---[0.006768ms] xxxService.model.helios.HeliosGetScoreResponse:setDates() #57

分析

这一步实际上执行时间优化了 50ms 左右。

从 Trace 中看耗时时间最长的是 Date 的 compareTo，也就是代码中的 if (splitHeliosScore.getTimeFrom().compareTo(request.getStartTime()) < 0)

而比较意外的是从对象中 get 属性居然也是有开销的。

5第二次优化

优化方向

结合上一次 Arthas Trace 的结果，在以下几个方向进行优化：

将 Date 对象的换成 long 型时间戳进行比较
将 Date 对象反复 getTime、setTime，改为 long 型时间戳 += 60_000 实现，得到结果后只 setTime 一次。
每次填充数据都往 Set<String> dateSet 放入数据，改为通过标识判断只放入一次。
存放分数的 ArrayList 在第一次循环之后，可以确认大小，之后循环创建 ArrayList 时直接填入固定的大小，减少内存创建。

代码

private HeliosGetScoreResponse queryScores(HeliosGetScoreRequest request) {
    HeliosGetScoreResponse response = new HeliosGetScoreResponse();

    List<HeliosScore> heliosScoresRecord = heliosService.queryScoresTimeBetween(request.getStartTime(), request.getEndTime(), request.getFilterByAppId());
    if (CollectionUtils.isEmpty(heliosScoresRecord)) {
        return response;
    }

    Set<Date> dateSet = new HashSet<>();
    boolean isDateSetInitial = false;
    int scoreSize = 16;

    List<HeliosScore> heliosScores = HeliosDataMergeJob.mergeData(heliosScoresRecord);

    Map<String, List<HeliosScore>> groupByAppIdHeliosScores = heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));

    for (List<HeliosScore> scores : groupByAppIdHeliosScores.values()) {
        HeliosScore heliosScore = scores.get(0);
        HeliosGetScoreResponse.Score score = new HeliosGetScoreResponse.Score();
        score.setNamespace(heliosScore.getNamespace());
        score.setAppId(heliosScore.getAppId());
        score.setScores(new ArrayList<>(scoreSize));
        response.getValues().add(score);

        List<Integer> scoreIntList = HeliosHelper.splitScores(heliosScore);

        // 以 requestTime 为准
        long indexDateMills = request.getStartTime().getTime();
        int index = 0;
        // 如果 timeFrom < requestTime，则增加 timeFrom 到 requestTime
        long heliosScoreTimeFromMills = heliosScore.getTimeFrom().getTime();
        while (indexDateMills > heliosScoreTimeFromMills) {
            heliosScoreTimeFromMills += 60_000;
            index++;
        }
        heliosScore.getTimeFrom().setTime(heliosScoreTimeFromMills);

        long requestEndTimeMills = request.getEndTime().getTime();
        long heliosScoreTimeToMills = heliosScore.getTimeTo().getTime();
        // 循环条件为 (当前时间 <= 请求最大时间) && (当前时间 <= 数据最大时间) && (index < 数据条数)
        while (indexDateMills <= requestEndTimeMills && indexDateMills <= heliosScoreTimeToMills && index < scoreIntList.size()) {
            score.getScores().add(scoreIntList.get(index++));
            if (!isDateSetInitial) {
                dateSet.add(new Date(indexDateMills));
            }
            indexDateMills += 60_000;
        }
        // 性能优化，减少重复放入的次数
        isDateSetInitial = true;
        // 性能优化，初始化足够的 size 减少扩容次数。x1.1 为了万一数据数量不一致，留出一点 buffer。
        scoreSize = (int) (score.getScores().size() * 1.1);
    }

    response.setDates(new ArrayList<>(dateSet).stream().sorted().map(DateUtils.yyyyMMddHHmm::formatDate).collect(Collectors.toList()));
    return response;
}

Arthas Trace

---ts=2021-08-17 15:20:41;thread_name=http-nio-8080-exec-7;id=aa;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@14be750c
    `---[1411.395123ms] xxxService.controller.HeliosController:queryScores()
        +---[0.016102ms] xxxService.model.helios.HeliosGetScoreResponse:<init>() #149
        +---[0.019084ms] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #151
        +---[0.007879ms] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #57
        +---[0.006808ms] xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId() #57
        +---[27.494178ms] xxxService.service.HeliosService:queryScoresTimeBetween() #57
        +---[0.02087ms] org.apache.commons.collections.CollectionUtils:isEmpty() #152
        +---[0.007694ms] java.util.HashSet:<init>() #156
        +---[19.990512ms] xxxService.helios.jobs.HeliosDataMergeJob:mergeData() #160
        +---[0.044161ms] java.util.List:stream() #162
        +---[0.025737ms] java.util.stream.Collectors:groupingBy() #57
        +---[min=0.079651ms,max=2.007048ms,total=2.086699ms,count=2] java.util.stream.Stream:collect() #57
        +---[0.018405ms] java.util.Map:values() #164
        +---[0.021408ms] java.util.Collection:iterator() #57
        +---[min=7.4E-4ms,max=0.015625ms,total=0.177657ms,count=121] java.util.Iterator:hasNext() #57
        +---[min=0.001193ms,max=0.026712ms,total=0.258491ms,count=120] java.util.Iterator:next() #57
        +---[min=7.69E-4ms,max=0.011855ms,total=0.158671ms,count=120] java.util.List:get() #165
        +---[min=0.001045ms,max=0.019788ms,total=0.232004ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:<init>() #166
        +---[min=0.001072ms,max=0.007958ms,total=0.193652ms,count=120] xxxService.helios.entity.HeliosScore:getNamespace() #167
        +---[min=0.001164ms,max=0.007796ms,total=0.201584ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace() #57
        +---[min=0.001048ms,max=0.007456ms,total=0.178323ms,count=120] xxxService.helios.entity.HeliosScore:getAppId() #168
        +---[min=0.001137ms,max=0.010225ms,total=0.201887ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId() #57
        +---[min=0.001627ms,max=0.010431ms,total=0.291395ms,count=120] java.util.ArrayList:<init>() #169
        +---[min=0.00116ms,max=0.0088ms,total=0.20171ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setScores() #57
        +---[min=0.001076ms,max=0.010293ms,total=0.199407ms,count=120] xxxService.model.helios.HeliosGetScoreResponse:getValues() #170
        +---[min=7.54E-4ms,max=0.086952ms,total=150.86682ms,count=170753] java.util.List:add() #57
        +---[min=0.020428ms,max=0.269554ms,total=19.477128ms,count=120] xxxService.helios.HeliosHelper:splitScores() #172
        +---[min=0.001092ms,max=0.005258ms,total=0.202045ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #175
        +---[min=7.09E-4ms,max=0.021027ms,total=0.630747ms,count=480] java.util.Date:getTime() #57
        +---[min=0.00106ms,max=0.015055ms,total=0.188439ms,count=120] xxxService.helios.entity.HeliosScore:getTimeFrom() #178
        +---[min=0.001025ms,max=0.009712ms,total=0.171506ms,count=120] xxxService.helios.entity.HeliosScore:getTimeFrom() #183
        +---[min=7.4E-4ms,max=0.092253ms,total=0.251068ms,count=120] java.util.Date:setTime() #57
        +---[min=0.001086ms,max=0.006234ms,total=0.184256ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #185
        +---[min=0.001036ms,max=0.012332ms,total=0.176491ms,count=120] xxxService.helios.entity.HeliosScore:getTimeTo() #186
      3 +---[min=6.73E-4ms,max=0.066785ms,total=135.009239ms,count=170635] java.util.List:size() #188
      1 +---[min=0.001085ms,max=0.089243ms,total=208.003309ms,count=170633] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #189
      2 +---[min=7.31E-4ms,max=0.070823ms,total=145.488732ms,count=170633] java.util.List:get() #57
        +---[min=0.001177ms,max=0.143546ms,total=2.319379ms,count=1440] java.util.Date:<init>() #191
        +---[min=0.001346ms,max=0.064411ms,total=2.839878ms,count=1440] java.util.Set:add() #57
        +---[min=0.001096ms,max=0.009059ms,total=0.190336ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #198
        +---[min=6.92E-4ms,max=0.016223ms,total=0.141751ms,count=120] java.util.List:size() #57
        +---[0.069753ms] java.util.ArrayList:<init>() #201
        +---[0.021066ms] java.util.ArrayList:stream() #57
        +---[0.029498ms] java.util.stream.Stream:sorted() #57
        +---[0.014089ms] java.util.stream.Stream:map() #57
        +---[0.013053ms] java.util.stream.Collectors:toList() #57
        `---[0.009818ms] xxxService.model.helios.HeliosGetScoreResponse:setDates() #57

分析

这一步将执行时间又优化了 80ms 左右。现在还剩是 160ms 了。

从 Trace 中看耗时时间最长的是三个方法：

getScores 直接 get 了属性啥也没干，但是积少成多
list.size()
list.get(index)

也就是说虽然这几个函数里也没干什么东西，但是函数调用、指针寻址本身也是有开销的。

6第三次优化

优化方向

减少 list 属性的调用
一次次 list.add 方法改成 subList 一次性放入

也就是说循环中不做任何耗时操作，不做任何指针/引用。

代码

private HeliosGetScoreResponse queryScores(HeliosGetScoreRequest request) {
   HeliosGetScoreResponse response = new HeliosGetScoreResponse();
   List<HeliosScore> heliosScoresRecord = heliosService.queryScoresTimeBetween(request.getStartTime(), request.getEndTime(), request.getFilterByAppId());
   if (CollectionUtils.isEmpty(heliosScoresRecord)) {
       return response;
   }
   
   Set<Date> dateSet = new HashSet<>();
   boolean isDateSetInitial = false;
   int scoreSize = 16;
   
   List<HeliosScore> heliosScores = HeliosDataMergeJob.mergeData(heliosScoresRecord);
   
   Map<String, List<HeliosScore>> groupByAppIdHeliosScores = heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
   
   for (List<HeliosScore> scores : groupByAppIdHeliosScores.values()) {
       HeliosScore heliosScore = scores.get(0);
       HeliosGetScoreResponse.Score score = new HeliosGetScoreResponse.Score();
       score.setNamespace(heliosScore.getNamespace());
       score.setAppId(heliosScore.getAppId());
       score.setScores(new ArrayList<>(scoreSize));
       response.getValues().add(score);
   
       List<Integer> scoreIntList = HeliosHelper.splitScores(heliosScore);
   
       // 以 requestTime 为准
       long indexDateMills = request.getStartTime().getTime();
       int index = 0;
       // 如果 timeFrom < requestTime，则增加 timeFrom 到 requestTime
       long heliosScoreTimeFromMills = heliosScore.getTimeFrom().getTime();
       while (indexDateMills > heliosScoreTimeFromMills) {
           heliosScoreTimeFromMills += 60_000;
           index++;
       }
       heliosScore.getTimeFrom().setTime(heliosScoreTimeFromMills);
   
       long requestEndTimeMills = request.getEndTime().getTime();
       long heliosScoreTimeToMills = heliosScore.getTimeTo().getTime();
   
       // 循环条件为 (当前时间 <= 请求最大时间) && (当前时间 <= 数据最大时间) && (index < 数据条数)
       int scoreIntListSize = scoreIntList.size();
       int indexStart = index;
       while (indexDateMills <= requestEndTimeMills && indexDateMills <= heliosScoreTimeToMills && index++ < scoreIntListSize) {
           if (!isDateSetInitial) {
               dateSet.add(new Date(indexDateMills));
           }
           indexDateMills += 60_000;
       }
       score.getScores().addAll(scoreIntList.subList(indexStart, index - 1));
       // 性能优化，减少重复放入的次数
       isDateSetInitial = true;
       // 性能优化，初始化足够的 size 减少扩容次数。x1.1 为了万一数据数量不一致，留出一点 buffer。
       scoreSize = (int) (score.getScores().size() * 1.1);
   }
   
   response.setDates(new ArrayList<>(dateSet).stream().sorted().map(DateUtils.yyyyMMddHHmm::formatDate).collect(Collectors.toList()));
   return response;
}

Arthas Trace

---ts=2021-08-17 15:33:40;thread_name=http-nio-8080-exec-11;id=f1;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@d1c5cf2
    `---[138.624811ms] xxxService.controller.HeliosController:queryScores()
        +---[0.021852ms] xxxService.model.helios.HeliosGetScoreResponse:<init>() #149
        +---[0.00746ms] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #151
        +---[0.005838ms] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #57
        +---[0.006341ms] xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId() #57
    2   +---[15.227453ms] xxxService.service.HeliosService:queryScoresTimeBetween() #57
        +---[0.02168ms] org.apache.commons.collections.CollectionUtils:isEmpty() #152
        +---[0.008923ms] java.util.HashSet:<init>() #156
    1   +---[22.703926ms] xxxService.helios.jobs.HeliosDataMergeJob:mergeData() #160
        +---[0.047118ms] java.util.List:stream() #162
        +---[0.043183ms] java.util.stream.Collectors:groupingBy() #57
        +---[min=0.095654ms,max=2.183288ms,total=2.278942ms,count=2] java.util.stream.Stream:collect() #57
        +---[0.022906ms] java.util.Map:values() #164
        +---[0.025777ms] java.util.Collection:iterator() #57
        +---[min=9.28E-4ms,max=0.017187ms,total=0.261862ms,count=121] java.util.Iterator:hasNext() #57
        +---[min=9.88E-4ms,max=0.018901ms,total=0.280889ms,count=120] java.util.Iterator:next() #57
        +---[min=9.65E-4ms,max=0.014741ms,total=0.262695ms,count=120] java.util.List:get() #165
        +---[min=0.001215ms,max=0.013928ms,total=0.347762ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:<init>() #166
        +---[min=0.001253ms,max=0.010855ms,total=0.328842ms,count=120] xxxService.helios.entity.HeliosScore:getNamespace() #167
        +---[min=0.001316ms,max=0.014714ms,total=0.372553ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace() #57
        +---[min=0.001211ms,max=0.010511ms,total=0.322723ms,count=120] xxxService.helios.entity.HeliosScore:getAppId() #168
        +---[min=0.00132ms,max=0.010201ms,total=0.334627ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId() #57
        +---[min=0.00116ms,max=0.014504ms,total=0.386879ms,count=120] java.util.ArrayList:<init>() #169
        +---[min=0.00131ms,max=0.014072ms,total=0.344922ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setScores() #57
        +---[min=0.001261ms,max=0.017312ms,total=0.356444ms,count=120] xxxService.model.helios.HeliosGetScoreResponse:getValues() #170
        +---[min=9.73E-4ms,max=0.016531ms,total=0.275794ms,count=120] java.util.List:add() #57
     3  +---[min=0.023208ms,max=19.808819ms,total=47.196601ms,count=120] xxxService.helios.HeliosHelper:splitScores() #172
        +---[min=0.001289ms,max=0.009578ms,total=0.36878ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #175
        +---[min=8.85E-4ms,max=0.016405ms,total=0.994157ms,count=480] java.util.Date:getTime() #57
        +---[min=0.001238ms,max=0.016801ms,total=0.34399ms,count=120] xxxService.helios.entity.HeliosScore:getTimeFrom() #178
        +---[min=0.001217ms,max=0.008931ms,total=0.316197ms,count=120] xxxService.helios.entity.HeliosScore:getTimeFrom() #183
        +---[min=9.14E-4ms,max=0.015929ms,total=0.277078ms,count=120] java.util.Date:setTime() #57
        +---[min=0.001238ms,max=0.01061ms,total=0.3375ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #185
        +---[min=0.001225ms,max=0.018059ms,total=0.315198ms,count=120] xxxService.helios.entity.HeliosScore:getTimeTo() #186
        +---[min=8.79E-4ms,max=0.022669ms,total=0.272356ms,count=120] java.util.List:size() #189
        +---[min=0.002001ms,max=0.056977ms,total=4.32853ms,count=1440] java.util.Date:<init>() #193
        +---[min=0.002174ms,max=0.040594ms,total=4.594415ms,count=1440] java.util.Set:add() #57
        +---[min=0.001302ms,max=0.012925ms,total=0.353165ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #197
        +---[min=0.001004ms,max=0.033424ms,total=0.338294ms,count=120] java.util.List:subList() #57
        +---[min=0.004871ms,max=0.051046ms,total=2.945263ms,count=120] java.util.List:addAll() #57
        +---[min=0.001291ms,max=0.009831ms,total=0.314292ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #201
        +---[min=8.84E-4ms,max=0.018168ms,total=0.249321ms,count=120] java.util.List:size() #57
        +---[0.054305ms] java.util.ArrayList:<init>() #204
        +---[0.024481ms] java.util.ArrayList:stream() #57
        +---[0.028717ms] java.util.stream.Stream:sorted() #57
        +---[0.013725ms] java.util.stream.Stream:map() #57
        +---[0.0128ms] java.util.stream.Collectors:toList() #57
        `---[0.007166ms] xxxService.model.helios.HeliosGetScoreResponse:setDates() #57

分析

这一步又优化了 100ms 左右，现在还剩 60ms。

现在从 trace 上看耗时操作只有三个了：

查数据库
合并数据
拆分得分字符串 “100,100,100“ 为 int 数组 [100,100,100]

7第四次优化

优化方向

查数据库发现由于 SQL 判断不准确，每次会多查出来一条数据，在后边循环的时候会多循环一倍

合并数据时发现可以针对单条数据的情况直接过滤，减少开销。

代码

改了 SQL 并验证，减少查询出来的数据量
单条数据时不再处理合并逻辑

Arthas Trace

---ts=2021-08-17 16:03:24;thread_name=http-nio-8080-exec-13;id=f1;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@69e2fe3b
    `---[38.171379ms] xxxService.controller.HeliosController:queryScores()
        +---[0.009463ms] xxxService.model.helios.HeliosGetScoreResponse:<init>() #149
        +---[0.00348ms] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #151
        +---[0.003233ms] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #57
        +---[0.003395ms] xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId() #57
     1  +---[10.157226ms] xxxService.service.HeliosService:queryScoresTimeBetween() #57
        +---[0.009989ms] org.apache.commons.collections.CollectionUtils:isEmpty() #152
        +---[0.003394ms] java.util.HashSet:<init>() #156
        +---[0.083535ms] xxxService.helios.jobs.HeliosDataMergeJob:mergeData() #160
        +---[0.017819ms] java.util.List:stream() #162
        +---[0.011787ms] java.util.stream.Collectors:groupingBy() #57
        +---[min=0.047561ms,max=2.02786ms,total=2.075421ms,count=2] java.util.stream.Stream:collect() #57
        +---[0.015525ms] java.util.Map:values() #164
        +---[0.021965ms] java.util.Collection:iterator() #57
        +---[min=7.25E-4ms,max=0.009733ms,total=0.115783ms,count=121] java.util.Iterator:hasNext() #57
        +---[min=8.43E-4ms,max=0.011422ms,total=0.142771ms,count=120] java.util.Iterator:next() #57
        +---[min=7.81E-4ms,max=0.010883ms,total=0.128809ms,count=120] java.util.List:get() #165
        +---[min=0.001023ms,max=0.004301ms,total=0.150165ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:<init>() #166
        +---[min=0.001066ms,max=0.004648ms,total=0.154698ms,count=120] xxxService.helios.entity.HeliosScore:getNamespace() #167
        +---[min=0.001137ms,max=0.005607ms,total=0.170279ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace() #57
        +---[min=0.001023ms,max=0.004292ms,total=0.151767ms,count=120] xxxService.helios.entity.HeliosScore:getAppId() #168
        +---[min=0.001105ms,max=0.004701ms,total=0.164955ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId() #57
        +---[min=0.001359ms,max=0.007931ms,total=0.233665ms,count=120] java.util.ArrayList:<init>() #169
        +---[min=0.001117ms,max=0.00785ms,total=0.168539ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:setScores() #57
        +---[min=0.001073ms,max=0.004488ms,total=0.156654ms,count=120] xxxService.model.helios.HeliosGetScoreResponse:getValues() #170
        +---[min=7.98E-4ms,max=0.00977ms,total=0.125818ms,count=120] java.util.List:add() #57
        +---[min=0.022304ms,max=0.12093ms,total=8.88628ms,count=120] xxxService.helios.HeliosHelper:splitScores() #172
        +---[min=0.001092ms,max=0.004967ms,total=0.161288ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getStartTime() #175
        +---[min=7.02E-4ms,max=0.012136ms,total=0.467786ms,count=480] java.util.Date:getTime() #57
        +---[min=0.001022ms,max=0.004944ms,total=0.151353ms,count=120] xxxService.helios.entity.HeliosScore:getTimeFrom() #178
        +---[min=0.001018ms,max=0.004731ms,total=0.148025ms,count=120] xxxService.helios.entity.HeliosScore:getTimeFrom() #183
        +---[min=7.3E-4ms,max=0.009359ms,total=0.120588ms,count=120] java.util.Date:setTime() #57
        +---[min=0.00107ms,max=0.008948ms,total=0.162848ms,count=120] xxxService.model.helios.HeliosGetScoreRequest:getEndTime() #185
        +---[min=0.001034ms,max=0.014003ms,total=0.158614ms,count=120] xxxService.helios.entity.HeliosScore:getTimeTo() #186
        +---[min=6.99E-4ms,max=0.009995ms,total=0.11179ms,count=120] java.util.List:size() #189
        +---[min=6.95E-4ms,max=0.005468ms,total=1.116308ms,count=1440] java.util.Date:<init>() #193
        +---[min=7.79E-4ms,max=0.029909ms,total=1.407528ms,count=1440] java.util.Set:add() #57
        +---[min=0.001097ms,max=0.008616ms,total=0.160597ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #197
        +---[min=8.23E-4ms,max=0.0294ms,total=0.153353ms,count=120] java.util.List:subList() #57
        +---[min=0.005771ms,max=0.04465ms,total=1.992151ms,count=120] java.util.List:addAll() #57
        +---[min=0.001098ms,max=0.007013ms,total=0.169555ms,count=120] xxxService.model.helios.HeliosGetScoreResponse$Score:getScores() #201
        +---[min=7.04E-4ms,max=0.01315ms,total=0.120998ms,count=120] java.util.List:size() #57
        +---[0.197732ms] java.util.ArrayList:<init>() #204
        +---[0.018589ms] java.util.ArrayList:stream() #57
        +---[0.025192ms] java.util.stream.Stream:sorted() #57
        +---[0.012544ms] java.util.stream.Stream:map() #57
        +---[0.012188ms] java.util.stream.Collectors:toList() #57
        `---[0.0067ms] xxxService.model.helios.HeliosGetScoreResponse:setDates() #57

分析

可以看到现在最大耗时的地方终于是数据库查询了。现在查询一整天的数据，也只需要 25~40ms 左右。

8结果

链路上看程序代码还是要处理个十几 ms，主要是字符串转 int[] 时的开销，这一步可以再想办法继续优化。结论

从这次优化我们可以得到一些结论：

1、尽量少创建对象

2、SimpleDateFormat的开销很大

3、Date.compare 的开销不低

4、哪怕最简单的操作如 list.size() list.add次数多了开销也很可观

5、对于性能分析和优化一定要有合适工具，才能得出有用的结论并针对性优化。一开始我以为减少对象创建就万事大吉，但实际上性能消耗的大头并不在这里。还是得借助 Arthas 的 Trace 才能真正针对性地优化

芋道源码 —— 纯源码解析博客

接口性能优化十倍，来了解一下 Arthas 的强大！

1背景

2优化过程

3初始未优化版本

代码

Arthas Trace

分析

4第一次优化

优化方向

代码

Arthas Trace

分析

5第二次优化

优化方向

代码

Arthas Trace

分析

6第三次优化

优化方向

代码

Arthas Trace

分析

7第四次优化

优化方向

代码

Arthas Trace

分析

8结果