if (!hasRelevant) {
                return RelevanceEvaluationResult.noRelevantResults();
            }

            final List<Integer> indexes = extractJsonIntArray(response, "relevant_indexes");
            final List<String> docIds = indexes.stream()
                    .filter(i -> i > 0 && i <= searchResults.size())
                    .map(i -> getStringValue(searchResults.get(i - 1), "doc_id"))

                final String id = crawlingInfoHelper.generateId(dataMap);

                if (logger.isDebugEnabled()) {
                    logger.debug("Searching indexed document: {}", id);
                }
                final Map<String, Object> document = indexingHelper.getDocument(searchEngineClient, id,

// on host. The data contained in dimension `dim_index` on device
// can correspond to the data contained in another dimension in on-host
// representation. The dimensions are indexed using the standard TensorFlow
// major-to-minor order (slowest varying dimension first),
// not the XLA's minor-to-major order.
// On-device dimensions can be padded. TFE_TensorDebugInfoOnDeviceDim returns

				continue
			}
			foundSet.Add(endpoint.Hostname())
		}
	}
	return foundSet.ToSlice()
}

// hostsSorted will return all hosts found.
// The LOCAL host will be nil, but the indexes of all hosts should
// remain consistent across the cluster.
func (l EndpointServerPools) hostsSorted() []*xnet.Host {
	peers, localPeer := l.peers()
	sort.Strings(peers)
	hosts := make([]*xnet.Host, len(peers))

      sort(
          insertionOrder,
          new Comparator<V>() {
            @Override
            public int compare(V left, V right) {
              // The indexes are small enough for the subtraction trick to be safe.
              return indexOfEntryWithValue(left) - indexOfEntryWithValue(right);
            }

            int indexOfEntryWithValue(V value) {

     *
     * @param index the name of the OpenSearch index
     * @param type the type of the document (deprecated in newer versions of OpenSearch)
     * @param item the SuggestItem containing the data to be indexed
     * @return a string representing the bulk line for OpenSearch indexing
     * @throws SuggesterException if an I/O error occurs during the creation of the bulk line
     */

 *       hunt through classes like {@link Arrays} and {@link Longs} for them.
 *   <li>Supports a copy-free {@link #subArray} view, so methods that accept this type don't need to
 *       add overloads that accept start and end indexes.
 *   <li>Can be streamed without "breaking the chain": {@code foo.getBarLongs().stream()...}.
 *   <li>Access to all collection-based utilities via {@link #asList} (though at the cost of
 *       allocating garbage).
 * </ul>

type comparable interface{ comparable }

// iota is a predeclared identifier representing the untyped integer ordinal
// number of the current const specification in a (usually parenthesized)
// const declaration. It is zero-indexed.
const iota = 0 // Untyped int.

// nil is a predeclared identifier representing the zero value for a
// pointer, channel, func, interface, map, or slice type.

   * 'a'/'A' returns 0 and 'z'/'Z' returns 25. Non-alpha characters return a value of 26 or greater.
   */
  private static int getAlphaIndex(char c) {
    // Fold upper-case ASCII to lower-case and make zero-indexed and unsigned (by casting to char).
    return (char) ((c | CASE_MASK) - 'a');
  }

     * and performs bulk indexing operations with proper error handling.
     *
     * @param searchEngineClient the search engine client to use for indexing
     * @param docList the list of documents to be indexed
     * @throws SearchEngineClientException if the bulk indexing operation fails
     */
    public void sendDocuments(final SearchEngineClient searchEngineClient, final DocList docList) {
        if (docList.isEmpty()) {