}
        return list;
    }

    /**
     * Filter out whitelisted projects with a big twist:
     * Assume we have all projects {@code a, b, c} while active are {@code a, c} and relation among all projects
     * is {@code a -> b -> c}. This method handles well the case for transitive list. But, for non-transitive we need

            result.from(0);
            result.size(0);
            result.topDocs(
                new TopDocsAndMaxScore(
                    new TopDocs(new TotalHits(1000, TotalHits.Relation.GREATER_THAN_OR_EQUAL_TO), new ScoreDoc[0]),
                    Float.NaN
                ),
                new DocValueFormat[] { DocValueFormat.RAW }
            );

 */
package org.codelibs.fess.rank.fusion;

import java.util.HashMap;
import java.util.Locale;
import java.util.Map;

import org.apache.lucene.search.TotalHits.Relation;
import org.codelibs.fess.entity.FacetInfo;
import org.codelibs.fess.entity.GeoInfo;
import org.codelibs.fess.entity.HighlightInfo;
import org.codelibs.fess.entity.SearchRequestParams;

 * a traditional {@code HashMap} implementation which stores keys and count values as map entries,
 * {@code ObjectCountHashMap} minimizes object allocation and reduces memory footprint.
 *
 * <p>In the absence of element deletions, this will iterate over elements in insertion order.
 */
@GwtCompatible
@NullMarked
class ObjectCountHashMap<K extends @Nullable Object> {

  /** Creates an empty {@code ObjectCountHashMap} instance. */

versioning is designed to keep multiple versions of an object in one bucket. For example, you could store `spark.csv` (version `ede336f2`) and `spark.csv` (version `fae684da`) in a single bucket. Versioning protects you from unintended overwrites, deletions, protect objects with retention policies.

To control data retention and storage usage, use object versioning with [object lifecycle management](https://github.com/minio/minio/blob/master/docs/bucket/lifecycle/README.md).  If you have an object...

        // Test with empty string
        searchRenderData.setAllRecordCountRelation("");
        assertEquals("", searchRenderData.getAllRecordCountRelation());

        // Test with relation types
        searchRenderData.setAllRecordCountRelation("eq");
        assertEquals("eq", searchRenderData.getAllRecordCountRelation());

        searchRenderData.setAllRecordCountRelation("gte");

      if (count == 0 && !isLinkedHash) {
        contents = new ObjectCountLinkedHashMap<E>(contents);
        isLinkedHash = true;
        // to preserve insertion order through deletions, we have to switch to an actual linked
        // implementation at least for now, but this should be a super rare case
      } else if (buildInvoked) {
        contents = new ObjectCountHashMap<E>(contents);

   *   <li>The {@link Predicate} returned by this method catches {@link ClassCastException} and
   *       {@link NullPointerException}.
   *   <li>Code that chains multiple predicates together (especially negations) may be more readable
   *       using this method. For example, {@code not(in(target))} is generally more readable than
   *       {@code not(target::contains)}.

   *       Double.NEGATIVE_INFINITY} are fuzzily equal only to themselves.
   * </ul>
   *
   * <p>This is reflexive and symmetric, but not transitive, so it is not an
   * equivalence relation and not suitable for use in {@link Object#equals}
   * implementations.
   *
   * @throws IllegalArgumentException if {@code tolerance} is {@code < 0} or NaN
   * @since 13.0
   */

         */
        protected int pageNumber;
        /**
         * The total number of records found.
         */
        protected long recordCount;
        /**
         * The relation of the record count (e.g., "eq" for exact, "gte" for greater than or equal to).
         */
        protected String recordCountRelation;
        /**
         * The total number of pages in the search results.