assertEquals(Float.parseFloat(expected), DocumentUtil.getValue(doc, "key1", Float.class).floatValue());
        assertEquals(Double.parseDouble(expected), DocumentUtil.getValue(doc, "key1", Double.class).doubleValue());

        assertNull(DocumentUtil.getValue(doc, "key2", String.class));
    }

    public void test_strings() {
        Map<String, Object> doc = new HashMap<>();

            if (!(value instanceof Integer)) {
                return (T) Integer.valueOf(value.toString());
            }
        } else if (clazz.isAssignableFrom(Double.class)) {
            if (!(value instanceof Double)) {
                return (T) Double.valueOf(value.toString());
            }
        } else if (clazz.isAssignableFrom(Float.class)) {
            if (!(value instanceof Float)) {

   * requestCount}, or {@code 1.0} when {@code requestCount == 0}. Note that {@code hitRate +
   * missRate =~ 1.0}.
   */
  public double hitRate() {
    long requestCount = requestCount();
    return (requestCount == 0) ? 1.0 : (double) hitCount / requestCount;
  }

  /**
   * Returns the number of times {@link Cache} lookup methods have returned an uncached (newly

   * requestCount}, or {@code 1.0} when {@code requestCount == 0}. Note that {@code hitRate +
   * missRate =~ 1.0}.
   */
  public double hitRate() {
    long requestCount = requestCount();
    return (requestCount == 0) ? 1.0 : (double) hitCount / requestCount;
  }

  /**
   * Returns the number of times {@link Cache} lookup methods have returned an uncached (newly

 * <p>Note: the Apache benchmarks are not open sourced to avoid the extra dependency.
 *
 * @author Louis Wasserman
 */
public class ApacheBenchmark {
  private enum Impl {
    GUAVA {
      @Override
      public double factorialDouble(int n) {
        return DoubleMath.factorial(n);
      }

      @Override
      public int gcdInt(int a, int b) {
        return IntMath.gcd(a, b);
      }

      @Override

035D..035F    ; valid                                  # 4.0  COMBINING DOUBLE BREVE..COMBINING DOUBLE MACRON BELOW
0360..0361    ; valid                                  # 1.1  COMBINING DOUBLE TILDE..COMBINING DOUBLE INVERTED BREVE
0362          ; valid                                  # 3.0  COMBINING DOUBLE RIGHTWARDS ARROW BELOW

    out.writeShort((short) 50000);
    out.writeInt(0xCAFEBABE);
    out.writeLong(0xDEADBEEFCAFEBABEL);
    out.writeUTF("Herby Derby");
    out.writeFloat(Float.intBitsToFloat(0xCAFEBABE));
    out.writeDouble(Double.longBitsToDouble(0xDEADBEEFCAFEBABEL));

    byte[] data = baos.toByteArray();

    /* Setup input streams */
    DataInput in = new DataInputStream(new ByteArrayInputStream(data));

    out.writeShort((short) 50000);
    out.writeInt(0xCAFEBABE);
    out.writeLong(0xDEADBEEFCAFEBABEL);
    out.writeUTF("Herby Derby");
    out.writeFloat(Float.intBitsToFloat(0xCAFEBABE));
    out.writeDouble(Double.longBitsToDouble(0xDEADBEEFCAFEBABEL));

    byte[] data = baos.toByteArray();

    /* Setup input streams */
    DataInput in = new DataInputStream(new ByteArrayInputStream(data));

    public void setAvailable_PercentileRanks(double[] values) {
        setAvailable_PercentileRanks(values, null);
    }

    public void setAvailable_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setAvailable_PercentileRanks("available", values, opLambda);
    }

    public void setAvailable_PercentileRanks(String name, double[] values,

      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES, 2);
      double populationCovariance = accumulator.populationCovariance();
      double populationCovarianceByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.populationCovariance();
      if (values.hasAnyNonFinite()) {