content: /*
   * 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.cassandra.metrics;
  
  import java.util.Collections;
  import java.util.List;
  import java.util.stream.Collectors;
  
  import org.slf4j.Logger;
  import org.slf4j.LoggerFactory;
  
  import com.clearspring.analytics.stream.StreamSummary;
  
  import static java.util.concurrent.TimeUnit.MILLISECONDS;
  
  /**
   * Find the most frequent sample. A sample adds to the sum of its key ie
   * <p>add("x", 10); and add("x", 20); will result in "x" = 30</p> This uses StreamSummary to only store the
   * approximate cardinality (capacity) of keys. If the number of distinct keys exceed the capacity, the error of the
   * sample may increase depending on distribution of keys among the total set.
   *
   * Note: {@link Sampler#samplerExecutor} is single threaded but we still need to synchronize as we have access
   * from both internal and the external JMX context that can cause races.
   * 
   * @param <T>
   */
  public abstract class FrequencySampler<T> extends Sampler<T>
  {
      private static final Logger logger = LoggerFactory.getLogger(FrequencySampler.class);
  
      private StreamSummary<T> summary;
  
      /**
       * Start to record samples
       *
       * @param capacity Number of sample items to keep in memory, the lower this is
       *                 the less accurate results are. For best results use value
       *                 close to cardinality, but understand the memory trade offs.
       */
      public synchronized void beginSampling(int capacity, long durationMillis)
      {
          if (isActive())
              throw new RuntimeException("Sampling already in progress");
          updateEndTime(clock.now() + MILLISECONDS.toNanos(durationMillis));
          summary = new StreamSummary<>(capacity);
      }
  
      /**
       * Call to stop collecting samples, and gather the results
       * @param count Number of most frequent items to return
       */
      public synchronized List<Sample<T>> finishSampling(int count)
      {
          List<Sample<T>> results = Collections.emptyList();
          if (isEnabled())
          {
              disable();
              results = summary.topK(count)
                               .stream()
                               .map(c -> new Sample<>(c.getItem(), c.getCount(), c.getError()))
                               .collect(Collectors.toList());
          }
          return results;
      }
  
      protected synchronized void insert(final T item, final long value)
      {
          if (value > 0 && isActive())
          {
              try
              {
                  summary.offer(item, (int) Math.min(value, Integer.MAX_VALUE));
              }
              catch (Exception e)
              {
                  logger.trace("Failure to offer sample", e);
              }
          }
      }
  }
  