Java Metrics系统性能监控工具

客官°小女子只卖身不卖艺 2024-04-01 11:50 15阅读 0赞

#### 文章目录 ####

*  前言
 *  Metric Registries :
 *  Metrics 数据展示 :
 *  Metrics的五种类型 :
 *   *  Gauges
     *  Counters
     *  Meters
     *  Histograms
     *  Timers
 *  总结

## 前言 ##

> **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。 在的例子中，我们使用 ConsoleReporter 。**

## Metrics的五种类型 : ##

### Gauges ###

> 比较简单的度量指标，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("lfwhvip");
            }
        }
    }

**运行结果 :**

22-11-3 14:36:28 ================================================================
    
    -- Gauges ----------------------------------------------------------------------
    com.zyh.maven.metricsdemo.GaugeTest.queue.size
                 value = 1
    
    
    22-11-3 14:36:29 ================================================================
    
    -- Gauges ----------------------------------------------------------------------
    com.zyh.maven.metricsdemo.GaugeTest.queue.size
                 value = 1

### 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
    22-11-3 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
    22-11-3 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**

22-11-7 16:18:38 ===============================================================
    
    -- Meters ----------------------------------------------------------------------
    com.example.jkytest.modules.MeterTest.request.tps
                 count = 8
             mean rate = 1.60 events/second
         1-minute rate = 1.60 events/second
         5-minute rate = 1.60 events/second
        15-minute rate = 1.60 events/second
    
    
    request
    request
    request
    request
    22-11-7 16:18:39 ===============================================================
    
    -- Meters ----------------------------------------------------------------------
    com.example.jkytest.modules.MeterTest.request.tps
                 count = 12
             mean rate = 2.00 events/second
         1-minute rate = 1.60 events/second
         5-minute rate = 1.60 events/second
        15-minute rate = 1.60 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.example.jkytest.modules;
    
    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**

-- Histograms ------------------------------------------------------------------
    com.example.jkytest.modules.HistogramsTest.request.histogram
                 count = 1
                   min = 33246
                   max = 33246
                  mean = 33246.00
                stddev = 0.00
                median = 33246.00
                  75% <= 33246.00
                  95% <= 33246.00
                  98% <= 33246.00
                  99% <= 33246.00
                99.9% <= 33246.00
    
    
    22-11-7 16:26:34 ===============================================================
    
    -- Histograms ------------------------------------------------------------------
    com.example.jkytest.modules.HistogramsTest.request.histogram
                 count = 2
                   min = 33246
                   max = 68864
                  mean = 51188.56
                stddev = 17808.50
                median = 68864.00
                  75% <= 68864.00
                  95% <= 68864.00
                  98% <= 68864.00
                  99% <= 68864.00
                99.9% <= 68864.00

### 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.example.jkytest.modules;
    
    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**

-- Timers ----------------------------------------------------------------------
    com.example.jkytest.modules.TimerTest.get-latency
                 count = 1
             mean rate = 1.00 calls/second
         1-minute rate = 0.00 calls/second
         5-minute rate = 0.00 calls/second
        15-minute rate = 0.00 calls/second
                   min = 560.21 milliseconds
                   max = 560.21 milliseconds
                  mean = 560.21 milliseconds
                stddev = 0.00 milliseconds
                median = 560.21 milliseconds
                  75% <= 560.21 milliseconds
                  95% <= 560.21 milliseconds
                  98% <= 560.21 milliseconds
                  99% <= 560.21 milliseconds
                99.9% <= 560.21 milliseconds

--------------------

## 总结 ##

> 如果此篇文章有帮助到您, 希望打大佬们能`关注`、`点赞`、`收藏`、`评论`支持一波，非常感谢大家！  
> 如果有不对的地方请指正!!!

[参考1][1]  
[参考2][2]  
[参考3][3]

[1]: https://www.cnblogs.com/sidesky/p/13177242.html
[2]: https://www.modb.pro/db/209666
[3]: https://zuozewei.blog.csdn.net/article/details/117959427?spm=1001.2101.3001.6650.1&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7ECTRLIST%7ERate-1-117959427-blog-123670985.pc_relevant_3mothn_strategy_and_data_recovery&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7ECTRLIST%7ERate-1-117959427-blog-123670985.pc_relevant_3mothn_strategy_and_data_recovery&utm_relevant_index=2