* than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope

    thread.start();
    thread.awaitWaiting();
    Thread.class.getMethod("suspend").invoke(thread);
    // Sleep for enough time to add 1500 milliseconds of overwait to the get() call.
    long toWaitMillis = 3500 - NANOSECONDS.toMillis(System.nanoTime() - thread.startTime);
    Thread.sleep(toWaitMillis);
    thread.setPriority(Thread.MAX_PRIORITY);
    Thread.class.getMethod("resume").invoke(thread);
    thread.join();

            reader.addSort(SortBuilders.scoreSort());
            return reader;
        }, docPerReq, () -> {
            systemHelper.calibrateCpuLoad();
            ThreadUtil.sleep(interval);
        }).then(response -> {
            refresh();
            success.accept(true);
        }).error(t -> error.accept(t));
    }

    /**
     * Purges old suggest data from documents.

     * and applies it by sleeping the current thread.
     */
    public void delayByRules() {
        final long delay = getDelay();
        if (delay > 0) {
            ThreadUtil.sleep(delay);
        }
    }

    /**
     * Calculates the delay in milliseconds based on current time and configured rules.
     * The method checks each rule to see if it applies to the current time and day.
     *

        // After first call isPrimary should be false
        assertFalse(d.getIsPrimary(), "isPrimary should be cleared after first call");
        // Second call keeps the same state
        SmbComTransactionResponse r2 = (SmbComTransactionResponse) d.nextElement();
        assertSame(d, r2, "Subsequent calls still return same instance");

         * than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope

      DerHeader(
        tagClass = DerHeader.TAG_CLASS_UNIVERSAL,
        tag = DerHeader.TAG_END_OF_CONTENTS,
        constructed = false,
        length = -1L,
      )
  }

  /** A source that keeps track of how many bytes it's consumed. */
  private class CountingSource(
    source: Source,
  ) : ForwardingSource(source) {
    var bytesRead = 0L

    override fun read(
      sink: Buffer,

    thread.start();
    thread.awaitWaiting();
    Thread.class.getMethod("suspend").invoke(thread);
    // Sleep for enough time to add 1500 milliseconds of overwait to the get() call.
    long toWaitMillis = 3500 - NANOSECONDS.toMillis(System.nanoTime() - thread.startTime);
    Thread.sleep(toWaitMillis);
    thread.setPriority(Thread.MAX_PRIORITY);
    Thread.class.getMethod("resume").invoke(thread);
    thread.join();

            task.start();
            task.join(timeout);
            if (!done.get()) {
                for (int i = 0; i < 100 && !done.get(); i++) {
                    task.interrupt();
                    ThreadUtil.sleep(100L);
                }
                throw new ExtractException("PDFBox process cannot finish in " + timeout + " sec.");
            }
            if (!exceptionSet.isEmpty()) {

   * Performs maintenance on this pool, evicting the connection that has been idle the longest if
   * either it has exceeded the keep alive limit or the idle connections limit.
   *
   * Returns the duration in nanoseconds to sleep until the next scheduled call to this method.
   * Returns -1 if no further cleanups are required.
   */
  fun closeConnections(now: Long): Long {
    // Find the longest-idle connections in 2 categories:
    //