import org.opensearch.index.query.RangeQueryBuilder;
import org.opensearch.index.query.RegexpQueryBuilder;
import org.opensearch.index.query.SpanTermQueryBuilder;
import org.opensearch.index.query.TermQueryBuilder;
import org.opensearch.index.query.TermsQueryBuilder;
import org.opensearch.index.query.WildcardQueryBuilder;
import org.opensearch.index.query.functionscore.FunctionScoreQueryBuilder;

import org.opensearch.index.query.RangeQueryBuilder;
import org.opensearch.index.query.RegexpQueryBuilder;
import org.opensearch.index.query.SpanTermQueryBuilder;
import org.opensearch.index.query.TermQueryBuilder;
import org.opensearch.index.query.TermsQueryBuilder;
import org.opensearch.index.query.WildcardQueryBuilder;
import org.opensearch.index.query.functionscore.FunctionScoreQueryBuilder;

				goto fallback
			}
		}
		return -1

	fallback:
		// Switch to bytealg.Index, if available, or a brute force search when
		// IndexByte returns too many false positives.
		if haveFastIndex {
			if j := bytealg.Index(s[i-last:], b[:n]); j >= 0 {
				return i + j - last
			}
		} else {
			// If bytealg.Index is not available a brute force search is
			// ~1.5-3x faster than Rabin-Karp since n is small.

  var index = 0
  val result = mutableListOf<Mapping>()

  while (index < mappings.size) {
    val mapping = mappings[index]
    val type = canonicalizeType(mapping.type)
    val mappedTo = mapping.mappedTo

    var unionWith: Mapping = mapping
    index++

    while (index < mappings.size) {
      val next = mappings[index]

      int hash = map.hash(key);
      int index = hash & (table.length() - 1);
      ReferenceEntry<Object, Object> first = table.get(index);
      entry = map.newEntry(key, hash, first);
      ValueReference<Object, Object> valueRef = map.newValueReference(entry, value, 1);
      entry.setValueReference(valueRef);
      segment.recordWrite(entry, 1, map.ticker.read());
      table.set(index, entry);
      originalMap.put(key, value);

      int hash = map.hash(key);
      int index = hash & (table.length() - 1);
      ReferenceEntry<Object, Object> first = table.get(index);
      entry = map.newEntry(key, hash, first);
      ValueReference<Object, Object> valueRef = map.newValueReference(entry, value, 1);
      entry.setValueReference(valueRef);
      segment.recordWrite(entry, 1, map.ticker.read());
      table.set(index, entry);
      originalMap.put(key, value);

            logger.info("Skipped to create new suggest index.");
            return 0;
        }

        final SuggestHelper suggestHelper = ComponentUtil.getSuggestHelper();

        logger.info("Creating new suggest index.");
        suggestHelper.suggester().createNextIndex();

        logger.info("Storing all bad words.");

  /**
   * Returns the {@code int} value present at the given index.
   *
   * @throws IndexOutOfBoundsException if {@code index} is negative, or greater than or equal to
   *     {@link #length}
   */
  public int get(int index) {
    Preconditions.checkElementIndex(index, length());
    return array[start + index];
  }

  /**
   * Returns the smallest index for which {@link #get} returns {@code target}, or {@code -1} if no

1. Go to kibana home [http://localhost:5601/](http://localhost:5601/).
1. Click **Management**.
1. Click **Index Patterns**.
1. Click **Create index pattern** button
1. Input "fess\_log\*" to the textbox of **index pattern**.
1. Click **Next step**.
1. Set "requestedAt" to the **Time Filter field name**.
1. Click **Create index pattern**.
1. Click **Saved Objects**.
1. Click **Import** and select "fess\_log.ndjson" to import example settings.

            if (index < size) buffer[index++] = (byte) (block & 0xff);
        }
        return buffer;
    }