code: /*
   * 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.skywalking.oap.server.core.analysis.metrics;
  
  import org.apache.skywalking.oap.server.core.analysis.metrics.annotation.Arg;
  import org.apache.skywalking.oap.server.core.analysis.metrics.annotation.Entrance;
  import org.apache.skywalking.oap.server.core.analysis.metrics.annotation.MetricsFunction;
  import org.apache.skywalking.oap.server.core.analysis.metrics.annotation.SourceFrom;
  import org.apache.skywalking.oap.server.core.storage.annotation.BanyanDB;
  import org.apache.skywalking.oap.server.core.storage.annotation.Column;
  import org.apache.skywalking.oap.server.core.storage.annotation.ElasticSearch;
  import java.util.Comparator;
  import java.util.List;
  import java.util.stream.IntStream;
  import lombok.Getter;
  import lombok.Setter;
  
  /**
   * Percentile is a better implementation than deprecated PxxMetrics in older releases.
   * This could calculate the multiple P50/75/90/95/99 values once for all.
   *
   * @since 7.0.0
   */
  @MetricsFunction(functionName = "percentile")
  public abstract class PercentileMetrics extends Metrics implements MultiIntValuesHolder {
      protected static final String DATASET = "dataset";
      protected static final String VALUE = "datatable_value";
      protected static final String PRECISION = "precision";
  
      private static final int[] RANKS = {
          50,
          75,
          90,
          95,
          99
      };
  
      @Getter
      @Setter
      @Column(name = VALUE, dataType = Column.ValueDataType.LABELED_VALUE, storageOnly = true)
      @ElasticSearch.Column(legacyName = "value")
      @BanyanDB.MeasureField
      private DataTable percentileValues;
      @Getter
      @Setter
      @Column(name = PRECISION, storageOnly = true)
      @BanyanDB.MeasureField
      private int precision;
      @Getter
      @Setter
      @Column(name = DATASET, storageOnly = true)
      @BanyanDB.MeasureField
      private DataTable dataset;
  
      private boolean isCalculated;
  
      public PercentileMetrics() {
          percentileValues = new DataTable(RANKS.length);
          dataset = new DataTable(30);
      }
  
      @Entrance
      public final void combine(@SourceFrom int value, @Arg int precision) {
          this.isCalculated = false;
          this.precision = precision;
  
          String index = String.valueOf(value / precision);
          dataset.valueAccumulation(index, 1L);
      }
  
      @Override
      public boolean combine(Metrics metrics) {
          this.isCalculated = false;
  
          PercentileMetrics percentileMetrics = (PercentileMetrics) metrics;
          this.dataset.append(percentileMetrics.dataset);
          return true;
      }
  
      @Override
      public final void calculate() {
          if (!isCalculated) {
              long total = dataset.sumOfValues();
  
              int[] roofs = new int[RANKS.length];
              for (int i = 0; i < RANKS.length; i++) {
                  roofs[i] = Math.round(total * RANKS[i] * 1.0f / 100);
              }
  
              int count = 0;
              final List<String> sortedKeys = dataset.sortedKeys(Comparator.comparingInt(Integer::parseInt));
  
              int loopIndex = 0;
              for (String key : sortedKeys) {
                  final Long value = dataset.get(key);
  
                  count += value;
                  for (int rankIdx = loopIndex; rankIdx < roofs.length; rankIdx++) {
                      int roof = roofs[rankIdx];
  
                      if (count >= roof) {
                          percentileValues.put(String.valueOf(rankIdx), Long.parseLong(key) * precision);
                          loopIndex++;
                      } else {
                          break;
                      }
                  }
              }
          }
      }
  
      @Override
      public int[] getValues() {
          return percentileValues.sortedValues(Comparator.comparingInt(Integer::parseInt))
                                 .stream()
                                 .flatMapToInt(l -> IntStream.of(l.intValue()))
                                 .toArray();
      }
  }
  