/*
 * Copyright 2020, OpenTelemetry Authors
 *
 * Licensed 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 io.opentelemetry.sdk.metrics.aggregator;

import java.util.concurrent.TimeUnit;
import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.Level;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.OutputTimeUnit;
import org.openjdk.jmh.annotations.Scope;
import org.openjdk.jmh.annotations.Setup;
import org.openjdk.jmh.annotations.State;
import org.openjdk.jmh.annotations.Threads;
import org.openjdk.jmh.annotations.Warmup;

@State(Scope.Benchmark)
public class DoubleMinMaxSumCountBenchmark {

  private Aggregator aggregator;

  @Setup(Level.Trial)
  public final void setup() {
    aggregator = DoubleMinMaxSumCount.getFactory().getAggregator();
  }

  @Benchmark
  @Fork(1)
  @Warmup(iterations = 5, time = 1)
  @Measurement(iterations = 10, time = 1)
  @OutputTimeUnit(TimeUnit.MILLISECONDS)
  @Threads(value = 10)
  public void aggregate_10Threads() {
    aggregator.recordDouble(100.0056);
  }

  @Benchmark
  @Fork(1)
  @Warmup(iterations = 5, time = 1)
  @Measurement(iterations = 10, time = 1)
  @OutputTimeUnit(TimeUnit.MILLISECONDS)
  @Threads(value = 5)
  public void aggregate_5Threads() {
    aggregator.recordDouble(100.0056);
  }

  @Benchmark
  @Fork(1)
  @Warmup(iterations = 5, time = 1)
  @Measurement(iterations = 10, time = 1)
  @OutputTimeUnit(TimeUnit.MILLISECONDS)
  @Threads(value = 1)
  public void aggregate_1Threads() {
    aggregator.recordDouble(100.0056);
  }
}