content: package io.airlift.stats;
  
  import com.google.common.collect.ImmutableList;
  import io.airlift.slice.Slice;
  import org.openjdk.jmh.annotations.Benchmark;
  import org.openjdk.jmh.annotations.Fork;
  import org.openjdk.jmh.annotations.Measurement;
  import org.openjdk.jmh.annotations.OperationsPerInvocation;
  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.Warmup;
  import org.openjdk.jmh.profile.GCProfiler;
  import org.openjdk.jmh.runner.Runner;
  import org.openjdk.jmh.runner.RunnerException;
  import org.openjdk.jmh.runner.options.Options;
  import org.openjdk.jmh.runner.options.OptionsBuilder;
  import org.openjdk.jmh.runner.options.VerboseMode;
  
  import java.util.List;
  import java.util.concurrent.ThreadLocalRandom;
  import java.util.concurrent.TimeUnit;
  
  @OutputTimeUnit(TimeUnit.SECONDS)
  @Fork(3)
  @Warmup(iterations = 10)
  @Measurement(iterations = 10)
  public class BenchmarkQuantileDigest
  {
      private static final int NUMBER_OF_ENTRIES = 10_000;
  
      @State(Scope.Thread)
      public static class Data
      {
          private long[] values1;
          private long[] values2;
  
          @Setup
          public void setup()
          {
              values1 = makeValues(NUMBER_OF_ENTRIES);
              values2 = makeValues(NUMBER_OF_ENTRIES);
          }
  
          private long[] makeValues(int size)
          {
              long[] values = new long[size];
              for (int i = 0; i < size; i++) {
                  // generate values from a large domain but not many distinct values
                  long value = Math.abs((long) (ThreadLocalRandom.current().nextGaussian() * 1_000_000_000));
                  values[i] = (value / 1_000_000) * 1_000_000;
              }
  
              return values;
          }
      }
  
      @State(Scope.Thread)
      public static class Digest
      {
          private QuantileDigest digest1;
          private QuantileDigest digest2;
          private Slice serializedDigest;
  
          @Setup
          public void setup(Data data)
          {
              digest1 = makeDigest(data.values1);
              digest2 = makeDigest(data.values2);
              serializedDigest = digest1.serialize();
          }
  
          private QuantileDigest makeDigest(long[] values)
          {
              QuantileDigest result = new QuantileDigest(0.01);
              for (long value : values) {
                  result.add(value);
              }
              return result;
          }
      }
  
      @Benchmark
      @OperationsPerInvocation(NUMBER_OF_ENTRIES)
      public QuantileDigest benchmarkInserts(Data data)
      {
          QuantileDigest digest = new QuantileDigest(0.01);
  
          for (long value : data.values1) {
              digest.add(value);
          }
  
          return digest;
      }
  
      @Benchmark
      public QuantileDigest benchmarkCopy(Digest data)
      {
          return new QuantileDigest(data.digest1);
      }
  
      @Benchmark
      public QuantileDigest benchmarkMerge(Digest data)
      {
          QuantileDigest merged = new QuantileDigest(data.digest1);
          merged.merge(data.digest2);
          return merged;
      }
  
      @Benchmark
      public QuantileDigest benchmarkDeserialize(Digest data)
      {
          return new QuantileDigest(data.serializedDigest);
      }
  
      @Benchmark
      public Slice benchmarkSerialize(Digest data)
      {
          return data.digest1.serialize();
      }
  
      @Benchmark
      public List<QuantileDigest.Bucket> benchmarkHistogram(Digest data)
      {
          return data.digest1.getHistogram(
                  ImmutableList.of(0L, 100_000_000L, 200_000_000L, 300_000_000L, 400_000_000L, 500_000_000L, 600_000_000L, 700_000_000L, 800_000_000L, 900_000_000L, 1_000_000_000L));
      }
  
      public static void main(String[] args)
              throws RunnerException
      {
          Options options = new OptionsBuilder()
                  .verbosity(VerboseMode.NORMAL)
                  .include(".*" + BenchmarkQuantileDigest.class.getSimpleName() + ".*")
                  .addProfiler(GCProfiler.class)
                  .build();
  
          new Runner(options).run();
      }
  }
  