<dependency> <groupId>com.codahale.metricsgroupId> <artifactId>metrics-coreartifactId> <version>3.0.1version> dependency>core包主要提供如下核心功能：
- Metrics Registries類似一個metrics容器，維護一個Map，可以是一個服務一個實例。
- 支持五種metric類型：Gauges、Counters、Meters、Histograms和Timers。
- 可以將metrics值通過JMX、Console，CSV文件和SLF4J loggers發佈出來。
五種Metrics類型：
1. Gauges
Gauges是一個最簡單的計量，一般用來統計瞬時狀態的數據信息，比如系統中處於pending狀態的job。測試代碼
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Gauge;
import com.codahale.metrics.JmxReporter;
import com.codahale.metrics.MetricRegistry;
import java.util.Queue;
import java.util.concurrent.LinkedBlockingDeque;
import java.util.concurrent.TimeUnit;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 14:47
* 測試Gauges，實時統計pending狀態的job個數
*/
public class TestGauges {
/**
* 實例化一個registry，最核心的一個模塊，相當於一個應用程序的metrics系統的容器，維護一個Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
private static Queue<String> queue = new LinkedBlockingDeque<String>();
/**
* 在控制檯上打印輸出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
//實例化一個Gauge
Gauge<Integer> gauge = new Gauge<Integer>() {
@Override
public Integer getValue() {
return queue.size();
}
};
//註冊到容器中
metrics.register(MetricRegistry.name(TestGauges.class, "pending-job", "size"), gauge);
//測試JMX
JmxReporter jmxReporter = JmxReporter.forRegistry(metrics).build();
jmxReporter.start();
//模擬數據
for (int i=0; i<20; i++){
queue.add("a");
Thread.sleep(1000);
}
}
}
/*
console output:
14-2-17 15:29:35 ===============================================================
-- Gauges ----------------------------------------------------------------------
com.netease.test.metrics.TestGauges.pending-job.size
value = 4
14-2-17 15:29:38 ===============================================================
-- Gauges ----------------------------------------------------------------------
com.netease.test.metrics.TestGauges.pending-job.size
value = 6
14-2-17 15:29:41 ===============================================================
-- Gauges ----------------------------------------------------------------------
com.netease.test.metrics.TestGauges.pending-job.size
value = 9
*/- JMX Gauges—提供給第三方庫只通過JMX將指標暴露出來。
- Ratio Gauges—簡單地通過創建一個gauge計算兩個數的比值。
- Cached Gauges—對某些計量指標提供緩存
Derivative Gauges—提供Gauge的值是基於其他Gauge值的接口。
2. Counter
Counter是Gauge的一個特例，維護一個計數器，可以通過inc()和dec()方法對計數器做修改。使用步驟與Gauge基本類似，在MetricRegistry中提供了靜態方法可以直接實例化一個Counter。
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Counter;
import com.codahale.metrics.MetricRegistry;
import java.util.LinkedList;
import java.util.Queue;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.*;
/**
* User: hzwangxx
* Date: 14-2-14
* Time: 14:02
* 測試Counter
*/
public class TestCounter {
/**
* 實例化一個registry，最核心的一個模塊，相當於一個應用程序的metrics系統的容器，維護一個Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制檯上打印輸出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 實例化一個counter,同樣可以通過如下方式進行實例化再註冊進去
* pendingJobs = new Counter();
* metrics.register(MetricRegistry.name(TestCounter.class, "pending-jobs"), pendingJobs);
*/
private static Counter pendingJobs = metrics.counter(name(TestCounter.class, "pedding-jobs"));
// private static Counter pendingJobs = metrics.counter(MetricRegistry.name(TestCounter.class, "pedding-jobs"));
private static Queue<String> queue = new LinkedList<String>();
public static void add(String str) {
pendingJobs.inc();
queue.offer(str);
}
public String take() {
pendingJobs.dec();
return queue.poll();
}
public static void main(String[]args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
while(true){
add("1");
Thread.sleep(1000);
}
}
}
/*
console output：
14-2-17 17:52:34 ===============================================================
-- Counters --------------------------------------------------------------------
com.netease.test.metrics.TestCounter.pedding-jobs
count = 4
14-2-17 17:52:37 ===============================================================
-- Counters --------------------------------------------------------------------
com.netease.test.metrics.TestCounter.pedding-jobs
count = 6
14-2-17 17:52:40 ===============================================================
-- Counters --------------------------------------------------------------------
com.netease.test.metrics.TestCounter.pedding-jobs
count = 9
*/3. Meters
Meters用來度量某個時間段的平均處理次數（request per second），每1、5、15分鐘的TPS。比如一個service的請求數，通過metrics.meter()實例化一個Meter之後，然後通過meter.mark()方法就能將本次請求記錄下來。統計結果有總的請求數，平均每秒的請求數，以及最近的1、5、15分鐘的平均TPS。
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Meter;
import com.codahale.metrics.MetricRegistry;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.*;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 18:34
* 測試Meters
*/
public class TestMeters {
/**
* 實例化一個registry，最核心的一個模塊，相當於一個應用程序的metrics系統的容器，維護一個Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制檯上打印輸出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 實例化一個Meter
*/
private static final Meter requests = metrics.meter(name(TestMeters.class, "request"));
public static void handleRequest() {
requests.mark();
}
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
while(true){
handleRequest();
Thread.sleep(100);
}
}
}
/*
14-2-17 18:43:08 ===============================================================
-- Meters ----------------------------------------------------------------------
com.netease.test.metrics.TestMeters.request
count = 30
mean rate = 9.95 events/second
1-minute rate = 0.00 events/second
5-minute rate = 0.00 events/second
15-minute rate = 0.00 events/second
14-2-17 18:43:11 ===============================================================
-- Meters ----------------------------------------------------------------------
com.netease.test.metrics.TestMeters.request
count = 60
mean rate = 9.99 events/second
1-minute rate = 10.00 events/second
5-minute rate = 10.00 events/second
15-minute rate = 10.00 events/second
14-2-17 18:43:14 ===============================================================
-- Meters ----------------------------------------------------------------------
com.netease.test.metrics.TestMeters.request
count = 90
mean rate = 9.99 events/second
1-minute rate = 10.00 events/second
5-minute rate = 10.00 events/second
15-minute rate = 10.00 events/second
*/4. Histograms
Histograms主要使用來統計數據的分佈情況，最大值、最小值、平均值、中位數，百分比（75%、90%、95%、98%、99%和99.9%）。例如，需要統計某個頁面的請求響應時間分佈情況，可以使用該種類型的Metrics進行統計。具體的樣例代碼如下：
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Histogram;
import com.codahale.metrics.MetricRegistry;
import java.util.Random;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.name;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 18:34
* 測試Histograms
*/
public class TestHistograms {
/**
* 實例化一個registry，最核心的一個模塊，相當於一個應用程序的metrics系統的容器，維護一個Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制檯上打印輸出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 實例化一個Histograms
*/
private static final Histogram randomNums = metrics.histogram(name(TestHistograms.class, "random"));
public static void handleRequest(double random) {
randomNums.update((int) (random*100));
}
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
Random rand = new Random();
while(true){
handleRequest(rand.nextDouble());
Thread.sleep(100);
}
}
}
/*
14-2-17 19:39:11 ===============================================================
-- Histograms ------------------------------------------------------------------
com.netease.test.metrics.TestHistograms.random
count = 30
min = 1
max = 97
mean = 45.93
stddev = 29.12
median = 39.50
75% <= 71.00
95% <= 95.90
98% <= 97.00
99% <= 97.00
99.9% <= 97.00
14-2-17 19:39:14 ===============================================================
-- Histograms ------------------------------------------------------------------
com.netease.test.metrics.TestHistograms.random
count = 60
min = 0
max = 97
mean = 41.17
stddev = 28.60
median = 34.50
75% <= 69.75
95% <= 92.90
98% <= 96.56
99% <= 97.00
99.9% <= 97.00
14-2-17 19:39:17 ===============================================================
-- Histograms ------------------------------------------------------------------
com.netease.test.metrics.TestHistograms.random
count = 90
min = 0
max = 97
mean = 44.67
stddev = 28.47
median = 43.00
75% <= 71.00
95% <= 91.90
98% <= 96.18
99% <= 97.00
99.9% <= 97.00
*/5. Timers
Timers主要是用來統計某一塊代碼段的執行時間以及其分佈情況，具體是基於Histograms和Meters來實現的。樣例代碼如下：
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.MetricRegistry;
import com.codahale.metrics.Timer;
import java.util.Random;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.name;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 18:34
* 測試Timers
*/
public class TestTimers {
/**
* 實例化一個registry，最核心的一個模塊，相當於一個應用程序的metrics系統的容器，維護一個Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制檯上打印輸出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 實例化一個Meter
*/
// private static final Timer requests = metrics.timer(name(TestTimers.class, "request"));
private static final Timer requests = metrics.timer(name(TestTimers.class, "request"));
public static void handleRequest(int sleep) {
Timer.Context context = requests.time();
try {
//some operator
Thread.sleep(sleep);
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
context.stop();
}
}
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
Random random = new Random();
while(true){
handleRequest(random.nextInt(1000));
}
}
}
/*
14-2-18 9:31:54 ================================================================
-- Timers ----------------------------------------------------------------------
com.netease.test.metrics.TestTimers.request
count = 4
mean rate = 1.33 calls/second
1-minute rate = 0.00 calls/second
5-minute rate = 0.00 calls/second
15-minute rate = 0.00 calls/second
min = 483.07 milliseconds
max = 901.92 milliseconds
mean = 612.64 milliseconds
stddev = 196.32 milliseconds
median = 532.79 milliseconds
75% <= 818.31 milliseconds
95% <= 901.92 milliseconds
98% <= 901.92 milliseconds
99% <= 901.92 milliseconds
99.9% <= 901.92 milliseconds
14-2-18 9:31:57 ================================================================
-- Timers ----------------------------------------------------------------------
com.netease.test.metrics.TestTimers.request
count = 8
mean rate = 1.33 calls/second
1-minute rate = 1.40 calls/second
5-minute rate = 1.40 calls/second
15-minute rate = 1.40 calls/second
min = 41.07 milliseconds
max = 968.19 milliseconds
mean = 639.50 milliseconds
stddev = 306.12 milliseconds
median = 692.77 milliseconds
75% <= 885.96 milliseconds
95% <= 968.19 milliseconds
98% <= 968.19 milliseconds
99% <= 968.19 milliseconds
99.9% <= 968.19 milliseconds
14-2-18 9:32:00 ================================================================
-- Timers ----------------------------------------------------------------------
com.netease.test.metrics.TestTimers.request
count = 15
mean rate = 1.67 calls/second
1-minute rate = 1.40 calls/second
5-minute rate = 1.40 calls/second
15-minute rate = 1.40 calls/second
min = 41.07 milliseconds
max = 968.19 milliseconds
mean = 591.35 milliseconds
stddev = 302.96 milliseconds
median = 650.56 milliseconds
75% <= 838.07 milliseconds
95% <= 968.19 milliseconds
98% <= 968.19 milliseconds
99% <= 968.19 milliseconds
99.9% <= 968.19 milliseconds
*/6 Health Checks
Metrics提供了一個獨立的模塊：Health Checks，用於對Application、其子模塊或者關聯模塊的運行是否正常做檢測。該模塊是獨立metrics-core模塊的，使用時則導入metrics-healthchecks包。
<dependency> <groupId>com.codahale.metricsgroupId> <artifactId>metrics-healthchecksartifactId> <version>3.0.1version> dependency>使用起來和與上述幾種類型的Metrics有點類似，但是需要重新實例化一個Metrics容器HealthCheckRegistry，待檢測模塊繼承抽象類HealthCheck並實現check()方法即可，然後將該模塊註冊到HealthCheckRegistry中，判斷的時候通過isHealthy()接口即可。如下示例代碼:
package com.netease.test.metrics;
import com.codahale.metrics.health.HealthCheck;
import com.codahale.metrics.health.HealthCheckRegistry;
import java.util.Map;
import java.util.Random;
/**
* User: hzwangxx
* Date: 14-2-18
* Time: 9:57
*/
public class DatabaseHealthCheck extends HealthCheck{
private final Database database;
public DatabaseHealthCheck(Database database) {
this.database = database;
}
@Override
protected Result check() throws Exception {
if (database.ping()) {
return Result.healthy();
}
return Result.unhealthy("Can't ping database.");
}
/**
* 模擬Database對象
*/
static class Database {
/**
* 模擬database的ping方法
* @return 隨機返回boolean值
*/
public boolean ping() {
Random random = new Random();
return random.nextBoolean();
}
}
public static void main(String[] args) {
// MetricRegistry metrics = new MetricRegistry();
// ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
HealthCheckRegistry registry = new HealthCheckRegistry();
registry.register("database1", new DatabaseHealthCheck(new Database()));
registry.register("database2", new DatabaseHealthCheck(new Database()));
while (true) {
for (Map.Entry<String, Result> entry : registry.runHealthChecks().entrySet()) {
if (entry.getValue().isHealthy()) {
System.out.println(entry.getKey() + ": OK");
} else {
System.err.println(entry.getKey() + ": FAIL, error message: " + entry.getValue().getMessage());
final Throwable e = entry.getValue().getError();
if (e != null) {
e.printStackTrace();
}
}
}
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
}
}
}
}
/*
console output:
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: OK
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: OK
database1: FAIL, error message: Can't ping database.
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: FAIL, error message: Can't ping database.
database1: OK
database2: OK
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: OK
database1: OK
database2: OK
database1: FAIL, error message: Can't ping database.
database2: OK
database1: OK
database2: OK
database1: OK
database2: OK
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: FAIL, error message: Can't ping database.
*/其他支持
metrics提供了對Ehcache、Apache HttpClient、JDBI、Jersey、Jetty、Log4J、Logback、JVM等的集成，可以方便地將Metrics輸出到Ganglia、Graphite中，供用戶圖形化展示。