}
        return response.getStatus().getStatus();
    }

    /**
     * Calculates the memory size of a document data map.
     * This is useful for monitoring memory usage during indexing operations.
     *
     * @param dataMap the document data as a map of field names to values
     * @return the estimated memory size in bytes
     */
    public long calculateDocumentSize(final Map<String, Object> dataMap) {

   *
   * {@snippet :
   * Stream.of("foo", "quux", "banana", "elephant").collect(least(2, comparingInt(String::length)))
   * // returns {"foo", "quux"}
   * }
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log
   * k)), as opposed to e.g. {@code Stream.sorted(comparator).limit(k)}, which currently takes O(n
   * log n) time and O(n) space.
   *

   * having a hash table of size eight. Providing a large enough estimate at construction time
   * avoids the need for expensive resizing operations later, but setting this value unnecessarily
   * high wastes memory.
   *
   * @throws IllegalArgumentException if {@code initialCapacity} is negative
   * @throws IllegalStateException if an initial capacity was already set
   */
  @CanIgnoreReturnValue

 * highest valued code point that requires escaping. For example a replacement map containing the
 * single character '{@code \}{@code u1000}' will require approximately 16K of memory. If you need
 * to create multiple escaper instances that have the same character replacement mapping consider
 * using {@link ArrayBasedEscaperMap}.
 *
 * @author David Beaumont
 * @since 15.0
 */
@GwtCompatible

  // We could make this a Map<E, EndpointPair<N>>. It would make incidentNodes(edge) slightly
  // faster, but also make Networks consume 5 to 20+% (increasing with average degree) more memory.
  final MapIteratorCache<E, N> edgeToReferenceNode; // referenceNode == source if directed

  /** Constructs a graph with the properties specified in {@code builder}. */

- Added memory tracking to scheduler performance tests to help detect memory leaks and monitored memory usage patterns while running `scheduler_perf`. ([#132910](https://github.com/kubernetes/kubernetes/pull/132910), [@utam0k](https://github.com/utam0k)) [SIG Scheduling and Testing]

   * interned, and so does not prevent these instances from being garbage-collected. This most
   * likely does not perform as well as {@link #newStrongInterner}, but is the best alternative when
   * the memory usage of that implementation is unacceptable.
   */
  @GwtIncompatible // java.lang.ref.WeakReference
  public static <E> Interner<E> newWeakInterner() {
    return newBuilder().weak().build();
  }

 *    Otherwise it would compress values in a way that servers could not decompress.
 *  * If `server_max_window_bits` is less than 15, OkHttp will waste memory on an oversized buffer.
 *
 * See [RFC 7692, 7.1][rfc_7692] for details on negotiation process.
 *
 * [rfc_7692]: https://tools.ietf.org/html/rfc7692#section-7.1
 */

   *       and virtual memory, this is not a problem - because it is mapped read-only, the kernel
   *       can always page it to disk "for free". However, on systems where killing processes
   *       happens all the time in normal conditions (i.e., android) the OS must make a tradeoff

* Fix gce.getDiskByNameUnknownZone logic. ([#24452](https://github.com/kubernetes/kubernetes/pull/24452), [@a-robinson](https://github.com/a-robinson))
* kubelet: add RSS memory to the summary API ([#24015](https://github.com/kubernetes/kubernetes/pull/24015), [@yujuhong](https://github.com/yujuhong))