* required to be a {@link BufferedOutputStream} in order to allow implementations to simply
   * delegate to {@link #openStream()} when the stream returned by that method does not benefit from
   * additional buffering (for example, a {@code ByteArrayOutputStream}). This method returns a new,
   * independent stream each time it is called.
   *
   * <p>The caller is responsible for ensuring that the returned stream is closed.
   *

   * required to be a {@link BufferedWriter} in order to allow implementations to simply delegate to
   * {@link #openStream()} when the stream returned by that method does not benefit from additional
   * buffering. This method returns a new, independent writer each time it is called.
   *
   * <p>The caller is responsible for ensuring that the returned writer is closed.
   *

		}
	}
}

// TestWriterReadFromCounts tests that using io.Copy to copy into a
// bufio.Writer does not prematurely flush the buffer. For example, when
// buffering writes to a network socket, excessive network writes should be
// avoided.
func TestWriterReadFromCounts(t *testing.T) {
	var w0 writeCountingDiscard
	b0 := NewWriterSize(&w0, 1234)

- Text logging in Kubernetes components now uses [textlogger](https://pkg.go.dev/k8s.io/klog/v2@v2.120.0/textlogger). The same split streams of info and error log entries with buffering of info entries is now also supported for text output (off by default, alpha feature). Previously, this was only supported for JSON. Performance is better also without split streams. ([#114672](https://github.com/kubernetes/kubernetes/pull/114672),...

import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * Implementation of {@link Multisets#unmodifiableSortedMultiset(SortedMultiset)}, split out into
 * its own file so it can be GWT emulated (to deal with the differing elementSet() types in GWT and
 * non-GWT).
 *
 * @author Louis Wasserman
 */
@GwtCompatible(emulated = true)
@ElementTypesAreNonnullByDefault

    }

    @Override
    public void offerAll(final String sessionId, final List<OpenSearchUrlQueue> urlQueueList) {
        if (logger.isDebugEnabled()) {
            logger.debug("Offering URL: Session ID: {}, UrlQueue: {}", sessionId, urlQueueList);
        }
        final List<UrlQueue<String>> targetList = new ArrayList<>(urlQueueList.size());
        for (final UrlQueue<String> urlQueue : urlQueueList) {

 * Ordering#leastOf(Iterable, int)}, which provides the same implementation with an interface
 * tailored to that use case.
 *
 * <p>This uses the same efficient implementation as {@link Ordering#leastOf(Iterable, int)},
 * offering expected O(n + k log k) performance (worst case O(n log k)) for n calls to {@link
 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same

   * Returns {@code true} if {@code object} is an {@code Optional} instance, and either the
   * contained references are {@linkplain Object#equals equal} to each other or both are absent.
   * Note that {@code Optional} instances of differing parameterized types can be equal.
   *
   * <p><b>Comparison to {@code java.util.Optional}:</b> no differences.
   */
  @Override
  public abstract boolean equals(@CheckForNull Object object);

  /**

        to datasets that end in synchronous transformations. This enables data
        generation to be overlapped with data consumption. This may cause a
        small increase in memory usage due to buffering. To enable this
        behavior, set `inject_prefetch=True` in
        `tf.data.experimental.OptimizationOptions`.
    *   Added a new value to `tf.data.Options.autotune.autotune_algorithm`: