}

  private static double expectedLargeDatasetPercentile(int index) {
    // We have q=100, k=index, and N=9951. Therefore k*(N-1)/q is 99.5*index. If index is even, that
    // is an integer 199*index/2. If index is odd, that is halfway between floor(199*index/2) and
    // ceil(199*index/2).
    if (index % 2 == 0) {
      int position = IntMath.divide(199 * index, 2, UNNECESSARY);
      return PSEUDORANDOM_DATASET_SORTED.get(position);

  }

  private static double expectedLargeDatasetPercentile(int index) {
    // We have q=100, k=index, and N=9951. Therefore k*(N-1)/q is 99.5*index. If index is even, that
    // is an integer 199*index/2. If index is odd, that is halfway between floor(199*index/2) and
    // ceil(199*index/2).
    if (index % 2 == 0) {
      int position = IntMath.divide(199 * index, 2, UNNECESSARY);
      return PSEUDORANDOM_DATASET_SORTED.get(position);

        final String index1 = "test-multi-index-001";
        final String index2 = "test-multi-index-002";
        final String aliasName = "test-multi-alias";

        // Create first index with alias
        client.admin().indices().prepareCreate(index1).addAlias(new Alias(aliasName)).execute().actionGet();

        // Create second index and add to same alias

    @ParametricNullness final K key;
    int index;

    EntryForKey(int index) {
      // The cast is safe because we call forEntry only for indexes that contain entries.
      this.key = uncheckedCastNullableTToT(keys[index]);
      this.index = index;
    }

    void updateIndex() {
      if (index == ABSENT || index > size || !Objects.equals(keys[index], key)) {
        index = findEntryByKey(key);
      }
    }

import org.codelibs.fess.util.ComponentUtil;
import org.opensearch.common.lucene.search.function.CombineFunction;
import org.opensearch.index.query.BoolQueryBuilder;
import org.opensearch.index.query.QueryBuilders;
import org.opensearch.index.query.functionscore.FunctionScoreQueryBuilder;
import org.opensearch.index.query.functionscore.ScoreFunctionBuilders;
import org.opensearch.search.sort.SortBuilders;

import jakarta.annotation.PostConstruct;

    });
```

## Advanced Usage

### Index from Existing Documents

```java
import org.codelibs.fess.suggest.index.contents.document.ESSourceReader;

// Index suggestions from existing Elasticsearch documents
DocumentReader reader = new ESSourceReader(
    client,
    suggester.settings(),
    "content-index",        // source index
    "document"             // document type
);

          S extends MapWithIndexSpliterator<F, R, S>>
      implements Spliterator<R> {
    final F fromSpliterator;
    long index;

    MapWithIndexSpliterator(F fromSpliterator, long index) {
      this.fromSpliterator = fromSpliterator;
      this.index = index;
    }

    abstract S createSplit(F from, long i);

    @Override
    public @Nullable S trySplit() {

    /**
     * Specifies a single quantile index to be calculated, i.e. the k in the kth q-quantile.
     *
     * @param index the quantile index, which must be in the inclusive range [0, q] for q-quantiles
     */
    public ScaleAndIndex index(int index) {
      return new ScaleAndIndex(scale, index);
    }

    /**
     * Specifies multiple quantile indexes to be calculated, each index being the k in the kth
     * q-quantile.

    final F fromSpliterator;
    long index;

    MapWithIndexSpliterator(F fromSpliterator, long index) {
      this.fromSpliterator = fromSpliterator;
      this.index = index;
    }

    abstract S createSplit(F from, long i);

    @Override
    public @Nullable S trySplit() {
      Spliterator<?> splitOrNull = fromSpliterator.trySplit();
      if (splitOrNull == null) {
        return null;

import org.codelibs.fess.suggest.entity.ElevateWord;
import org.codelibs.fess.suggest.entity.SuggestItem;
import org.codelibs.fess.suggest.index.SuggestIndexResponse;
import org.codelibs.fess.suggest.index.contents.document.ESSourceReader;
import org.codelibs.fess.suggest.index.contents.querylog.QueryLog;
import org.codelibs.fess.suggest.index.contents.querylog.QueryLogReader;
import org.codelibs.fess.suggest.request.popularwords.PopularWordsResponse;