- Fixed bug which caused the status of Indexed Jobs to only be updated when there are newly completed indexes. The completed indexes are now updated if the .status.completedIndexes has values outside of the [0, .spec.completions> range ([#115460](https://github.com/kubernetes/kubernetes/pull/115460), [@danielvegamyhre](https://github....

- Fixed bug which caused the status of Indexed Jobs to only be updated when there are newly completed indexes. The completed indexes are now updated if the .status.completedIndexes has values outside of the [0, .spec.completions> range ([#115462](https://github.com/kubernetes/kubernetes/pull/115462), [@danielvegamyhre](https://github....

        return badWords;
    }

    /**
     * Indexes a single suggest item.
     * @param item The suggest item to index.
     * @return The SuggestIndexResponse.
     */
    public SuggestIndexResponse index(final SuggestItem item) {
        ensureOperations();
        return indexingOps.index(index, item, badWords);
    }

    /**
     * Indexes multiple suggest items.

     * @throws IllegalArgumentException if {@code indexes} is empty
     */
    public ScaleAndIndexes indexes(int... indexes) {
      return new ScaleAndIndexes(scale, indexes.clone());
    }

    /**
     * Specifies multiple quantile indexes to be calculated, each index being the k in the kth
     * q-quantile.
     *
     * @param indexes the quantile indexes, each of which must be in the inclusive range [0, q] for

        suggester.indexer().deleteBadWord("[");
        suggester.indexer().deleteBadWord("ｴﾝｼﾞﾝ");
        assertEquals(0, suggester.settings().badword().get(false).length);
    }

    @Test
    public void test_popularWords() throws Exception {
        SuggestItem[] items = getPopularWordsItemSet2();
        suggester.indexer().index(items);
        suggester.refresh();

      return Quantiles.scale(scale).index(index).computeInPlace(dataset);
    }

    @Override
    Map<Integer, Double> multipleQuantiles(
        Collection<Integer> indexes, int scale, double[] dataset) {
      return Quantiles.scale(scale).indexes(indexes).computeInPlace(dataset);
    }
  },
  ;

  /**
   * Calculates a single quantile. Equivalent to {@code

        SuggestIndexer indexer = suggester.indexer();

        assertNotNull(indexer.setIndexName("test-index"));
        assertNotNull(indexer.setSupportedFields(new String[] { "field1", "field2" }));
        assertNotNull(indexer.setTagFieldNames(new String[] { "tag1", "tag2" }));
        assertNotNull(indexer.setRoleFieldName("role"));
        assertNotNull(indexer.setReadingConverter(null));

    ImmutableSet<Integer> indexes = ImmutableSet.of(50, 90, 99);
    Map<Integer, Double> referenceQuantiles =
        REFERENCE_ALGORITHM.multipleQuantiles(indexes, 100, dataset.clone());
    assertThat(referenceQuantiles.keySet()).isEqualTo(indexes);
    for (QuantilesAlgorithm algorithm : NON_REFERENCE_ALGORITHMS) {
      Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());

    // array of indexes to be calculated is modified between the calls to indexes and compute: since
    // the contract is that it is snapshotted, this shouldn't make any difference to the result.
    int[] indexes = {0, 10, 5, 1, 8, 10};
    ScaleAndIndexes intermediate = Quantiles.scale(10).indexes(indexes);
    indexes[0] = 3;
    assertThat(intermediate.compute(SIXTEEN_SQUARES_DOUBLES))

    // array of indexes to be calculated is modified between the calls to indexes and compute: since
    // the contract is that it is snapshotted, this shouldn't make any difference to the result.
    int[] indexes = {0, 10, 5, 1, 8, 10};
    ScaleAndIndexes intermediate = Quantiles.scale(10).indexes(indexes);
    indexes[0] = 3;
    assertThat(intermediate.compute(SIXTEEN_SQUARES_DOUBLES))