Java Metrics系统性能监控工具

Metrics是一个Java库，可以对系统进行监控，统计一些系统的性能指标。

比如一个系统后台服务，我们可能需要了解一下下面的一些情况：
1、每秒钟的请求数是多少（TPS）？
2、平均每个请求处理的时间？
3、请求处理的最长耗时？
4、等待处理的请求队列长度？
5、又或者一个缓存服务：缓存的命中率？平均查询缓存的时间？

基本上每一个服务、应用都需要做一个监控系统，这需要尽量以少量的代码，实现统计某类数据的功能。

Metric Registries

MetricRegistry类是Metrics的核心，它是存放应用中所有metrics的容器，也是我们使用 Metrics 库的起点。

MetricRegistry registry = new MetricRegistry(); 

Metrics 数据展示

Metrics 提供了 Report 接口，用于展示 metrics 获取到的统计数据。metrics-core中主要实现了四种 reporter： JMX ，console， SLF4J， 和 CSV。 在本文的例子中，我们使用 ConsoleReporter 。

Metrics的五种类型

Gauges

最简单的度量指标，只有一个简单的返回值，例如，我们想衡量一个待处理队列中任务的个数，代码如下：

package com.zyh.maven.metricsdemo;

import com.codahale.metrics.ConsoleReporter; import com.codahale.metrics.Gauge; import com.codahale.metrics.MetricRegistry; import java.util.LinkedList; import java.util.Queue; import java.util.concurrent.TimeUnit; public class GaugeTest { public static Queue<String> q = new LinkedList<String>(); public static void main(String[] args) throws InterruptedException { MetricRegistry metricRegistry = new MetricRegistry(); ConsoleReporter reporter = ConsoleReporter.forRegistry(metricRegistry).build(); reporter.start(1, TimeUnit.SECONDS); metricRegistry.register(MetricRegistry.name(GaugeTest.class, "queue", "size"), new Gauge<Integer>(){ @Override public Integer getValue() { return q.size(); } }); while (true) { Thread.sleep(1000); q.add("张永辉"); } } } 

运行结果

18-2-5 14:36:28 ================================================================ -- Gauges ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.GaugeTest.queue.size value = 1 18-2-5 14:36:29 ================================================================ -- Gauges ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.GaugeTest.queue.size value = 1 18-2-5 14:36:30 ================================================================ -- Gauges ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.GaugeTest.queue.size value = 2 18-2-5 14:36:31 ================================================================ -- Gauges ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.GaugeTest.queue.size value = 3 

Counters

Counter 就是计数器，Counter 只是用 Gauge 封装了 AtomicLong ，我们可以使用如下的方法获得队列大小，代码如下：

package com.zyh.maven.metricsdemo; import com.codahale.metrics.ConsoleReporter; import com.codahale.metrics.Counter; import com.codahale.metrics.MetricRegistry; import java.util.Queue; import java.util.Random; import java.util.concurrent.LinkedBlockingDeque; import java.util.concurrent.TimeUnit; public class CounterTest { public static Queue<String> q = new LinkedBlockingDeque<String>(); public static Counter pendingJobs; public static Random random = new Random(); public static void addJob(String job) { pendingJobs.inc(); q.offer(job); } public static String takeJob() { pendingJobs.dec(); return q.poll(); } public static void main(String[] args) throws InterruptedException { MetricRegistry registry = new MetricRegistry(); ConsoleReporter reporter = ConsoleReporter.forRegistry(registry).build(); reporter.start(1, TimeUnit.SECONDS); pendingJobs = registry.counter(MetricRegistry.name(Queue.class, "pending-jobs", "size")); int num = 1; while(true) { Thread.sleep(200); if(random.nextDouble() > 0.7) { String job = takeJob(); System.out.println("take job :" + job); }else{ String job = "Job-" + num; addJob(job); System.out.println("add Job :" + job); } num++; } } } 

运行结果

take job :Job-14
add Job :Job-26 add Job :Job-27 add Job :Job-28 add Job :Job-29 18-2-5 14:39:58 ================================================================ -- Counters -------------------------------------------------------------------- java.util.Queue.pending-jobs.size count = 11 take job :Job-16 add Job :Job-31 add Job :Job-32 take job :Job-17 take job :Job-18 18-2-5 14:39:59 ================================================================ -- Counters -------------------------------------------------------------------- java.util.Queue.pending-jobs.size count = 10 

Meters

Meter度量一系列事件发生的速率(rate)，例如TPS。Meters会统计最近1分钟，5分钟，15分钟，还有全部时间的速率。

package com.zyh.maven.metricsdemo;

import com.codahale.metrics.ConsoleReporter; import com.codahale.metrics.Meter; import com.codahale.metrics.MetricRegistry; import java.util.Random; import java.util.concurrent.TimeUnit; public class MeterTest { public static Random random = new Random(); public static void request(Meter meter) { System.out.println("request"); meter.mark(); } public static void request(Meter meter, int n) { while(n > 0) { request(meter); n--; } } public static void main(String[] args) throws InterruptedException { MetricRegistry registry = new MetricRegistry(); ConsoleReporter reporter = ConsoleReporter.forRegistry(registry).build(); reporter.start(1, TimeUnit.SECONDS); Meter meterTps = registry.meter(MetricRegistry.name(MeterTest.class, "request", "tps")); while(true) { request(meterTps, random.nextInt(5)); Thread.sleep(1000); } } } 

运行结果

18-2-5 14:42:44 ================================================================ -- Meters ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.MeterTest.request.tps count = 16 mean rate = 2.67 events/second 1-minute rate = 3.20 events/second 5-minute rate = 3.20 events/second 15-minute rate = 3.20 events/second request request request request 18-2-5 14:42:45 ================================================================ -- Meters ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.MeterTest.request.tps count = 20 mean rate = 2.86 events/second 1-minute rate = 3.20 events/second 5-minute rate = 3.20 events/second 15-minute rate = 3.20 events/second 

Histograms

Histogram统计数据的分布情况。比如最小值，最大值，中间值，还有中位数，75百分位，90百分位，95百分位，98百分位，99百分位，和 99.9百分位的值(percentiles)。

package com.zyh.maven.metricsdemo;

import com.codahale.metrics.ConsoleReporter; import com.codahale.metrics.ExponentiallyDecayingReservoir; import com.codahale.metrics.Histogram; import com.codahale.metrics.MetricRegistry; import java.util.Random; import java.util.concurrent.TimeUnit; public class HistogramsTest { public static Random random = new Random(); public static void main(String[] args) throws InterruptedException { MetricRegistry registry = new MetricRegistry(); ConsoleReporter reporter = ConsoleReporter.forRegistry(registry).build(); reporter.start(1, TimeUnit.SECONDS); Histogram histogram = new Histogram(new ExponentiallyDecayingReservoir()); registry.register(MetricRegistry.name(HistogramsTest.class, "request", "histogram"), histogram); while (true) { Thread.sleep(1000); histogram.update(random.nextInt(100000)); } } } 

运行结果

18-2-5 14:45:45 ================================================================ -- Histograms ------------------------------------------------------------------ com.zyh.maven.metricsdemo.HistogramsTest.request.histogram count = 8 min = 8676 max = 94954 mean = 36405.28 stddev = 27543.74 median = 28243.00 75% <= 58814.00 95% <= 94954.00 98% <= 94954.00 99% <= 94954.00 99.9% <= 94954.00 18-2-5 14:45:46 ================================================================ -- Histograms ------------------------------------------------------------------ com.zyh.maven.metricsdemo.HistogramsTest.request.histogram count = 9 min = 8676 max = 94954 mean = 39131.65 stddev = 26922.72 median = 28243.00 75% <= 58814.00 95% <= 94954.00 98% <= 94954.00 99% <= 94954.00 99.9% <= 94954.00 

Timers

Timer其实是 Histogram 和 Meter 的结合， histogram 某部分代码/调用的耗时， meter统计TPS。

package com.zyh.maven.metricsdemo;

import com.codahale.metrics.ConsoleReporter; import com.codahale.metrics.MetricRegistry; import com.codahale.metrics.Timer; import java.util.Random; import java.util.concurrent.TimeUnit; public class TimerTest { public static Random random = new Random(); public static void main(String[] args) throws InterruptedException { MetricRegistry registry = new MetricRegistry(); ConsoleReporter reporter = ConsoleReporter.forRegistry(registry).build(); reporter.start(1, TimeUnit.SECONDS); Timer timer = registry.timer(MetricRegistry.name(TimerTest.class, "get-latency")); Timer.Context ctx; while (true) { ctx = timer.time(); Thread.sleep(random.nextInt(1000)); ctx.stop(); } } } 

运行结果

18-2-5 14:48:30 ================================================================ -- Timers ---------------------------------------------------------------------- com.zyh.maven.metricsdemo.TimerTest.get-latency count = 30 mean rate = 2.15 calls/second 1-minute rate = 2.02 calls/second 5-minute rate = 2.00 calls/second 15-minute rate = 2.00 calls/second min = 22.82 milliseconds max = 987.23 milliseconds mean = 439.66 milliseconds stddev = 263.14 milliseconds median = 421.99 milliseconds 75% <= 582.73 milliseconds 95% <= 926.66 milliseconds 98% <= 987.23 milliseconds 99% <= 987.23 milliseconds 99.9% <= 987.23 milliseconds 

上面写了几个demo尝试用了一下Metrics，在这里记录一下！

作者：雨林木风博客
链接：https://www.jianshu.com/p/e5bba03fd64f
来源：简书
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