/**
    * Licensed to the Apache Software Foundation (ASF) under one
    * or more contributor license agreements.  See the NOTICE file
    * distributed with this work for additional information
    * regarding copyright ownership.  The ASF licenses this file
    * to you under the Apache License, Version 2.0 (the
    * "License"); you may not use this file except in compliance
    * with the License.  You may obtain a copy of the License at
    *
   *     http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  package org.apache.hadoop.metrics2.lib;
  
  import static org.apache.hadoop.hbase.metrics.Interns.info;
  
  import java.io.IOException;
  import java.util.Map;
  import java.util.concurrent.TimeUnit;
  
  import org.apache.commons.lang.StringUtils;
  import org.apache.hadoop.hbase.classification.InterfaceAudience;
  import org.apache.hadoop.metrics2.MetricHistogram;
  import org.apache.hadoop.metrics2.MetricsExecutor;
  import org.apache.hadoop.metrics2.MetricsInfo;
  import org.apache.hadoop.metrics2.MetricsRecordBuilder;
  import org.apache.hadoop.metrics2.util.MetricQuantile;
  import org.apache.hadoop.metrics2.util.MetricSampleQuantiles;
  
  import com.google.common.annotations.VisibleForTesting;
  
  /**
   * Watches a stream of long values, maintaining online estimates of specific quantiles with provably
   * low error bounds. This is particularly useful for accurate high-percentile (e.g. 95th, 99th)
   * latency metrics.
   */
  @InterfaceAudience.Private
  public class MetricMutableQuantiles extends MutableMetric implements MetricHistogram {
  
    static final MetricQuantile[] quantiles = {new MetricQuantile(0.50, 0.050),
        new MetricQuantile(0.75, 0.025), new MetricQuantile(0.90, 0.010),
        new MetricQuantile(0.95, 0.005), new MetricQuantile(0.99, 0.001)};
  
    private final MetricsInfo numInfo;
    private final MetricsInfo[] quantileInfos;
    private final int interval;
  
    private MetricSampleQuantiles estimator;
    private long previousCount = 0;
    private MetricsExecutor executor;
  
  
    @VisibleForTesting
    protected Map<MetricQuantile, Long> previousSnapshot = null;
  
    /**
     * Instantiates a new {@link MetricMutableQuantiles} for a metric that rolls itself over on the
     * specified time interval.
     *
     * @param name        of the metric
     * @param description long-form textual description of the metric
     * @param sampleName  type of items in the stream (e.g., "Ops")
     * @param valueName   type of the values
     * @param interval    rollover interval (in seconds) of the estimator
     */
    public MetricMutableQuantiles(String name, String description, String sampleName,
                                  String valueName, int interval) {
      String ucName = StringUtils.capitalize(name);
      String usName = StringUtils.capitalize(sampleName);
      String uvName = StringUtils.capitalize(valueName);
      String desc = StringUtils.uncapitalize(description);
      String lsName = StringUtils.uncapitalize(sampleName);
      String lvName = StringUtils.uncapitalize(valueName);
  
      numInfo = info(ucName + "Num" + usName, String.format(
          "Number of %s for %s with %ds interval", lsName, desc, interval));
      // Construct the MetricsInfos for the quantiles, converting to percentiles
      quantileInfos = new MetricsInfo[quantiles.length];
      String nameTemplate = "%s%dthPercentile%dsInterval%s";
      String descTemplate = "%d percentile %s with %d second interval for %s";
      for (int i = 0; i < quantiles.length; i++) {
        int percentile = (int) (100 * quantiles[i].quantile);
        quantileInfos[i] = info(String.format(nameTemplate, ucName, percentile, interval, uvName),
            String.format(descTemplate, percentile, lvName, interval, desc));
      }
  
      estimator = new MetricSampleQuantiles(quantiles);
      executor = new MetricsExecutorImpl();
      this.interval = interval;
      executor.getExecutor().scheduleAtFixedRate(new RolloverSample(this),
          interval,
          interval,
          TimeUnit.SECONDS);
   }
 
   @Override
   public synchronized void snapshot(MetricsRecordBuilder builder, boolean all) {
     if (all || changed()) {
       builder.addGauge(numInfo, previousCount);
       for (int i = 0; i < quantiles.length; i++) {
         long newValue = 0;
         // If snapshot is null, we failed to update since the window was empty
         if (previousSnapshot != null) {
           newValue = previousSnapshot.get(quantiles[i]);
         }
         builder.addGauge(quantileInfos[i], newValue);
       }
       if (changed()) {
         clearChanged();
       }
     }
   }
 
   public synchronized void add(long value) {
     estimator.insert(value);
   }
 
   public int getInterval() {
     return interval;
   }
 
   /** Runnable used to periodically roll over the internal {@link org.apache.hadoop.metrics2.util.MetricSampleQuantiles} every interval. */
   private static class RolloverSample implements Runnable {
 
     MetricMutableQuantiles parent;
 
     public RolloverSample(MetricMutableQuantiles parent) {
       this.parent = parent;
     }
 
     @Override
     public void run() {
       synchronized (parent) {
         try {
           parent.previousCount = parent.estimator.getCount();
           parent.previousSnapshot = parent.estimator.snapshot();
         } catch (IOException e) {
           // Couldn't get a new snapshot because the window was empty
           parent.previousCount = 0;
           parent.previousSnapshot = null;
         }
         parent.estimator.clear();
       }
       parent.setChanged();
     }
 
   }
 }