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 q = new LinkedList();

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(){

@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 q = new LinkedBlockingDeque();

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！