// Test case 2: Single padding
        final byte[] data2 = "abcd".getBytes();
        assertEquals("YWJjZA==", Base64Util.encode(data2));

        // Test case 3: Double padding
        final byte[] data3 = "abcde".getBytes();
        assertEquals("YWJjZGU=", Base64Util.encode(data3));

        // Test case 4: No padding
        final byte[] data4 = "abcdef".getBytes();

        if (read(tmp, 0, 4) < 0) {
            throw new SmbException("EOF");
        }
        return Encdec.dec_floatbe(tmp, 0);
    }

    @Override
    public final double readDouble() throws SmbException {
        if (read(tmp, 0, 8) < 0) {
            throw new SmbException("EOF");
        }
        return Encdec.dec_doublebe(tmp, 0);
    }

    @Override

     *
     * @param data the data to analyze
     * @param algorithm the compression algorithm
     * @return estimated compression ratio (0.0 to 1.0, where 0.5 means 50% size reduction)
     */
    double estimateCompressionRatio(byte[] data, int algorithm);

    /**
     * Gets the minimum data size threshold for compression.
     * Data smaller than this threshold should not be compressed.
     *

# | BIGINT        | java.lang.Long       | long?         |
# | REAL          | java.math.BigDecimal | decimal?      |
# | FLOAT         | java.math.BigDecimal | decimal?      |
# | DOUBLE        | java.math.BigDecimal | decimal?      |
# | DATE          | java.util.Date       | DateTime?     |
# | TIME          | java.sql.Time        | DateTime?     |
# | TIMESTAMP     | java.sql.Timestamp   | DateTime?     |

        assertEquals("array", Constants.MAPPING_TYPE_ARRAY);
        assertEquals("string", Constants.MAPPING_TYPE_STRING);
        assertEquals("long", Constants.MAPPING_TYPE_LONG);
        assertEquals("double", Constants.MAPPING_TYPE_DOUBLE);
        assertEquals("date", Constants.MAPPING_TYPE_DATE);
    }

    /**
     * Testable implementation of AbstractFessFileTransformer for unit testing.
     */

    assertThat(stats.hitRate()).isEqualTo(11.0 / requestCount);
    int missCount = 23;
    assertThat(stats.missCount()).isEqualTo(missCount);
    assertThat(stats.missRate()).isEqualTo(((double) missCount) / requestCount);
    assertThat(stats.loadSuccessCount()).isEqualTo(13);
    assertThat(stats.loadExceptionCount()).isEqualTo(17);
    assertThat(stats.loadCount()).isEqualTo(13 + 17);

    }
    final class Splitr extends MapWithIndexSpliterator<Spliterator.OfDouble, R, Splitr>
        implements DoubleConsumer {
      double holder;

      Splitr(Spliterator.OfDouble splitr, long index) {
        super(splitr, index);
      }

      @Override
      public void accept(double t) {
        this.holder = t;
      }

      @Override
      public boolean tryAdvance(Consumer<? super R> action) {

   * saving space.
   */
  @VisibleForTesting static final double MAX_LOAD_FACTOR = 1.2;

  /**
   * Maximum allowed false positive probability of detecting a hash flooding attack given random
   * input.
   */
  @VisibleForTesting static final double HASH_FLOODING_FPP = 0.001;

  /**
   * Maximum allowed length of a hash table bucket before falling back to a j.u.HashMap based

    }

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

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

      countRemaps(r.nextLong(), map);
    }
    for (int shard = 2; shard <= MAX_SHARDS; shard++) {
      // Rough: don't exceed 1.2x the expected number of remaps by more than 20
      assertThat((double) map.get(shard)).isAtMost(1.2 * ITERS / shard + 20);
    }
  }

  private void countRemaps(long h, AtomicLongMap<Integer> map) {
    int last = 0;
    for (int shards = 2; shards <= MAX_SHARDS; shards++) {