}

    @Override
    public List<Integer> subList(int fromIndex, int toIndex) {
      return parent.subArray(fromIndex, toIndex).asList();
    }

    // The default List spliterator is not efficiently splittable
    @Override
    public Spliterator<Integer> spliterator() {
      return parent.spliterator();
    }

    @Override
    public boolean equals(@Nullable Object object) {

    /**
     * Exports all crawling information parameters to CSV format.
     * The CSV output includes: SessionId, SessionCreatedTime, Key, Value, CreatedTime.
     * Uses cursor-based selection to handle large datasets efficiently.
     *
     * @param writer the Writer to output CSV data to
     */
    public void exportCsv(final Writer writer) {
        final CsvConfig cfg = new CsvConfig(',', '"', '"');

To improve this, we’re working on automation tools 🤖 to manage translations more efficiently. Once ready, documentation will be machine-translated and still reviewed by at least two native speakers ✅ before publishing. This will allow us to keep translations up-to-date while reducing the review burden on maintainers.

   * <p><b>Warning:</b> Be extremely careful what you do with the {@code asSet} view of a large
   * range set (such as {@code ImmutableRangeSet.of(Range.greaterThan(0))}). Certain operations on
   * such a set can be performed efficiently, but others (such as {@link Set#hashCode} or {@link
   * Collections#frequency}) can cause major performance problems.
   *
   * <p>The returned set's {@link Object#toString} method returns a shorthand form of the set's

In the end, the ultimate objective is to be able to **serve your API clients** in a way that is **secure**, to **avoid disruptions**, and to use the **compute resources** (for example remote servers/virtual machines) as efficiently as possible. 🚀

                }).orElse(queryResponseList);
            }
        }
        return documentItems;
    }

    /**
     * Performs a scroll search for processing large result sets efficiently.
     *
     * This method uses OpenSearch scroll API to iterate through large numbers of
     * documents without loading them all into memory at once.
     *
     * @param params The search request parameters

   * en]}.
   *
   * <p><b>{@code Stream} equivalent:</b> {@code stream.collect(Collectors.joining(", ", "[", "]"))}
   * or (less efficiently) {@code stream.collect(Collectors.toList()).toString()}.
   */
  @Override
  public String toString() {
    return Iterables.toString(getDelegate());
  }

  /**

   * en]}.
   *
   * <p><b>{@code Stream} equivalent:</b> {@code stream.collect(Collectors.joining(", ", "[", "]"))}
   * or (less efficiently) {@code stream.collect(Collectors.toList()).toString()}.
   */
  @Override
  public String toString() {
    return Iterables.toString(getDelegate());
  }

  /**

                assertEquals(firstResult, result, "All thread results should be consistent");
            }
        }

        @Test
        @DisplayName("Should handle concurrent verify operations efficiently")
        void testConcurrentVerifyPerformance() throws InterruptedException {
            int threadCount = 50;
            int operationsPerThread = 100;

        // a cyclic edge: it's possible for two threads to simultaneous find
        // "safe" edges which together form a cycle. Preventing this race
        // condition efficiently without _introducing_ deadlock is probably
        // tricky. For now, just accept the race condition---missing a warning
        // now and then is still better than having no deadlock detection.