*
   * @param from the URL to read from
   * @param to the output stream
   * @throws IOException if an I/O error occurs
   */
  public static void copy(URL from, OutputStream to) throws IOException {
    asByteSource(from).copyTo(to);
  }

  /**
   * Returns a {@code URL} pointing to {@code resourceName} if the resource is found using the

    }
  }

  abstract val path: Any

  /**
   * Reads the public suffix list treating the operation as uninterruptible. We always want to read
   * the list otherwise we'll be left in a bad state. If the thread was interrupted prior to this
   * operation, it will be re-interrupted after the list is read.
   */
  private fun readTheListUninterruptibly() {
    var interrupted = false
    try {
      while (true) {
        try {

          try (InputStreamReader reader = new InputStreamReader(byteSource.openStream(), cs)) {
            int nRead = 0;
            while (remaining > 0 && (nRead = reader.read(buffer, bufIndex, remaining)) != -1) {
              bufIndex += nRead;
              remaining -= nRead;
            }
            if (nRead == -1) {
              // we reached EOF
              return new String(buffer, 0, bufIndex);
            }

    val source = relay.newSource()
    val sourceBuffer = Buffer()
    assertThat(source!!.read(sourceBuffer, 5)).isEqualTo(5)
    assertThat(sourceBuffer.readUtf8()).isEqualTo("abcde")
    assertThat(source.read(sourceBuffer, 1024)).isEqualTo(8)
    assertThat(sourceBuffer.readUtf8()).isEqualTo("fghijklm")
    assertThat(source.read(sourceBuffer, 1024)).isEqualTo(-1)
    assertThat(sourceBuffer.size).isEqualTo(0)
    source.close()

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 org.apache.logging.log4j.Logger;

/**
 * A thread that reads from an input stream line by line and maintains a buffer of recent lines.
 * This class provides functionality to read input stream data asynchronously,
 * optionally process each line with a callback function, and maintain a circular buffer
 * of recent lines for retrieval.
 */
public class InputStreamThread extends Thread {
    /** Logger instance for this class */

     * simple approach would be for each caller CAS it from null to a Set populated with its
     * exception. But there's another race: If the first thread fails with an exception and a second
     * thread immediately fails with the same exception:
     *
     * Thread1: calls setException(), which returns true, context switch before it can CAS
     * seenExceptionsField to its exception
     *

    assertEquals(0, ticker.read());
    assertEquals(10, ticker.read());
    assertEquals(20, ticker.read());
  }

  public void testAutoIncrementStep_millis() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(1, MILLISECONDS);
    assertEquals(0, ticker.read());
    assertEquals(1000000, ticker.read());
    assertEquals(2000000, ticker.read());
  }

   * As such, this field must be cleared before every map mutation.
   *
   * Note about volatile: volatile doesn't make it safe to read from a mutable graph in one thread
   * while writing to it in another. All it does is help with _reading_ from multiple threads
   * concurrently. For more information, see AbstractNetworkTest.concurrentIteration.
   */

    void testConcurrentLogging() throws InterruptedException {
        int threadCount = 10;
        int eventsPerThread = 100;
        Thread[] threads = new Thread[threadCount];

        for (int i = 0; i < threadCount; i++) {
            final int threadId = i;
            threads[i] = new Thread(() -> {
                for (int j = 0; j < eventsPerThread; j++) {