if (windowSize != DEFAULT_INITIAL_WINDOW_SIZE) {
        writer.windowUpdate(0, (windowSize - DEFAULT_INITIAL_WINDOW_SIZE).toLong())
      }
    }
    // Thread doesn't use client Dispatcher, since it is scoped potentially across clients via
    // ConnectionPool.
    taskRunner.newQueue().execute(name = connectionName, block = readerRunnable)
  }

  private var cache: Cache? = null

  @BeforeEach
  fun setUp() {
    platform.assumeNotOpenJSSE()
    listener.forbidLock(get(client.connectionPool))
    listener.forbidLock(client.dispatcher)
  }

  @AfterEach
  fun tearDown() {
    if (socksProxy != null) {
      socksProxy!!.shutdown()
    }
    if (cache != null) {
      cache!!.delete()
    }
  }

  @Test

    compressed file (like a JAR or APK), so compressing its internal data was redundant.

 *  Fix: Call `ProxySelector.connectFailed()` when a connection's initial TCP handshake fails.

 *  Fix: Change the signature of `Dispatcher` to accept a nullable `ExecutorService`. Changing this
    parameter to be non-null was an unintended signature change in OkHttp 4.0.

=== ":material-language-kotlin: Kotlin"
    ```kotlin

 * #enqueue enqueueing} and then {@linkplain #dispatch dispatching} events.
 *
 * <p>The API of this class is designed to make it easy to achieve the following properties
 *
 * <ul>
 *   <li>Multiple events for the same listener are never dispatched concurrently.
 *   <li>Events for the different listeners are dispatched concurrently.
 *   <li>All events for a given listener dispatch on the provided executor.

    register a dataset with the tf.data service, and another process to consume
    data from the dataset.
*   Adds support for dispatcher fault tolerance. To enable fault tolerance,
    configure a `work_dir` when running your dispatcher server and set
    `dispatcher_fault_tolerance=True`. The dispatcher will store its state to
    `work_dir`, so that on restart it can continue from its previous state after
    restart.

So we have a dedicated thread for every socket that just reads frames and dispatches them.

The reader thread must never run application-layer code. Otherwise one slow stream can hold up the entire connection.

import java.io.IOException
import java.util.concurrent.TimeUnit
import kotlin.test.assertFailsWith
import kotlin.time.Duration.Companion.seconds
import kotlinx.coroutines.CancellationException
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.TimeoutCancellationException
import kotlinx.coroutines.coroutineScope
import kotlinx.coroutines.job
import kotlinx.coroutines.supervisorScope
import kotlinx.coroutines.test.runTest

- Watch requests that are delegated to aggregated API servers no longer reserve concurrency units (seats) in the API Priority and Fairness dispatcher for their entire duration. ([#105511](https://github.com/kubernetes/kubernetes/pull/105511), [@benluddy](https://github.com/benluddy))

   *         <li>and {@link AbstractInvocationHandler#equals} returns true for the {@link
   *             InvocationHandler} of {@code argument}
   *       </ul>
   *   <li>other method calls are dispatched to {@link #handleInvocation}.
   * </ul>
   */
  @Override
  public final @Nullable Object invoke(
      Object proxy, Method method, @Nullable Object @Nullable [] args) throws Throwable {
    if (args == null) {