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Fix JavaDoc warnings
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README.md

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### Summary
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Summaries and Histograms can both be used to monitor latencies (or other things like request sizes).
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Summaries and Histograms can both be used to monitor distributions, like latencies or request sizes.
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An overview of when to use Summaries and when to use Histograms can be found on [https://prometheus.io/docs/practices/histograms](https://prometheus.io/docs/practices/histograms).
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simpleclient/src/main/java/io/prometheus/client/SimpleCollector.java

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* <p>
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* This class handles common initialization and label logic for the standard metrics.
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* You should never subclass this class.
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* <p>
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*
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* <h2>Initialization</h2>
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* After calling build() on a subclass, {@link Builder#name(String) name},
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* {@link SimpleCollector.Builder#help(String) help},

simpleclient/src/main/java/io/prometheus/client/Summary.java

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import java.util.concurrent.TimeUnit;
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/**
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* {@link Summary} metrics and {@link Histogram} metrics can both be used to monitor latencies (or other things like request sizes).
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* {@link Summary} metrics and {@link Histogram} metrics can both be used to monitor distributions like latencies or request sizes.
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* <p>
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* An overview of when to use Summaries and when to use Histograms can be found on <a href="https://prometheus.io/docs/practices/histograms">https://prometheus.io/docs/practices/histograms</a>.
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* <p>
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* The {@link Summary} class provides different utility methods for observing values, like {@link #observe(double)},
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* {@link #startTimer()} and {@link Timer#observeDuration()}, {@link #time(Callable)}, etc.
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* <p>
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* By default, {@link Summary} metrics provide the <tt>count</tt> and the <tt>sum</tt>. For example, if you measure
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* latencies of a REST service, the <tt>count</tt> will tell you how often the REST service was called,
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* and the <tt>sum</tt> will tell you the total aggregated response time.
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* You can calculate the average response time using a Prometheus query dividing <tt>sum / count</tt>.
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* By default, {@link Summary} metrics provide the {@code count} and the {@code sum}. For example, if you measure
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* latencies of a REST service, the {@code count} will tell you how often the REST service was called,
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* and the {@code sum} will tell you the total aggregated response time.
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* You can calculate the average response time using a Prometheus query dividing {@code sum / count}.
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* <p>
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* In addition to <tt>count</tt> and <tt>sum</tt>, you can configure a Summary to provide quantiles:
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* In addition to {@code count} and {@code sum}, you can configure a Summary to provide quantiles:
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*
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* <pre>
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* Summary requestLatency = Summary.build()
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*
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* <ul>
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* <li>You can set an allowed error of 0, but then the {@link Summary} will keep all observations in memory.</li>
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* <li>You can track the minimum value with <tt>.quantile(0.0, 0.0)</tt>.
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* <li>You can track the minimum value with {@code .quantile(0.0, 0.0)}.
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* This special case will not use additional memory even though the allowed error is 0.</li>
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* <li>You can track the maximum value with <tt>.quantile(1.0, 0.0)</tt>.
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* <li>You can track the maximum value with {@code .quantile(1.0, 0.0)}.
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* This special case will not use additional memory even though the allowed error is 0.</li>
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* </ul>
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*

simpleclient_jetty/src/main/java/io/prometheus/client/jetty/JettyStatisticsCollector.java

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/**
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* Collect metrics from jetty's org.eclipse.jetty.server.handler.StatisticsHandler.
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* <p>
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* <pre>{@code
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* <pre>
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* Server server = new Server(8080);
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*
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* ServletContextHandler context = new ServletContextHandler();
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* server.setHandler(handlers);
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*
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* server.start();
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* }</pre>
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* </pre>
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*/
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public class JettyStatisticsCollector extends Collector {
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private final StatisticsHandler statisticsHandler;

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