* non-static, and is initialized/removed frequently - this causes churn in the Thread specific
   * hashmaps. Using a static ThreadLocal to avoid that overhead would mean that different
   * ExecutionSequencer objects interfere with each other, which would be undesirable, in addition
   * to increasing the memory footprint of every thread that interacted with it. In order to release

### Multi destination replication

The replication design for multiple sites works in a similar manner as described above for two site scenario. However there are some
important exceptions.

  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for
  //   similar purposes.
  // * We want to behave reasonably for timeouts of 0

  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for
  //   similar purposes.
  // * We want to behave reasonably for timeouts of 0

    /**
     * The smallest message that will be compressed. We use 1024 because smaller messages already
     * fit comfortably within a single ethernet packet (1500 bytes) even with framing overhead.
     *
     * For tests this must be big enough to realize real compression on test messages like
     * 'aaaaaaaaaa...'. Our tests check if compression was applied just by looking at the size if
     * the inbound buffer.

	if r.ContentLength <= 0 {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrMissingContentLength), r.URL)
		return
	}

	// The max. XML contains 100000 object names (each at most 1024 bytes long) + XML overhead
	const maxBodySize = 2 * 100000 * 1024

	if r.ContentLength > maxBodySize {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrEntityTooLarge), r.URL)
		return
	}

	paths = make([]string, len(elem))
	for i, e := range elem {
		paths[i] = pathJoin(prefix, e)
	}
	return paths
}

// string concat alternative to s1 + s2 with low overhead.
func concat(ss ...string) string {
	length := len(ss)
	if length == 0 {
		return ""
	}
	// create & allocate the memory in advance.
	n := 0
	for i := range length {
		n += len(ss[i])
	}

 * is satisfied. The limit is not strict: the cache may temporarily exceed it while waiting for
 * files to be deleted. The limit does not include filesystem overhead or the cache journal so
 * space-sensitive applications should set a conservative limit.
 *
 * Clients call [edit] to create or update the values of an entry. An entry may have only one editor

     */
    int getListCount();

    /**
     *
     * Property {@code jcifs.smb.client.listSize} (int, default 65435)
     *
     * @return maximum data size for list/info requests (known overhead is subtracted)
     */
    int getListSize();

    /**
     *
     *
     * Property {@code jcifs.smb.client.attrExpirationPeriod} (int, 5000)
     *
     * @return timeout of file attribute cache

   *       userspace buffer (byte[] or ByteBuffer), then copies them from that buffer into the
   *       destination channel.
   * </ol>
   *
   * This value is intended to be large enough to make the overhead of system calls negligible,
   * without being so large that it causes problems for systems with atypical memory management if
   * approaches 2 or 3 are used.
   */
  private static final int ZERO_COPY_CHUNK_SIZE = 512 * 1024;