assertEquals(0, negotiationWithEmptyBuffers.getResponseRaw().length);
    }

    @Test
    @DisplayName("Test with large buffers")
    void testWithLargeBuffers() {
        // Test with large byte arrays
        byte[] largeRequestBuffer = new byte[1024];
        byte[] largeResponseBuffer = new byte[2048];

        // Fill with some test data

   *       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;

        // Adaptive strategy based on message type and size

        if (isLargeTransfer(message)) {
            // For large transfers, prefer high-bandwidth channels
            ChannelInfo maxBandwidthChannel = null;
            int maxBandwidth = 0;
            for (ChannelInfo channel : channels) {

        ByteArrayInputStream bais = new ByteArrayInputStream(data);
        SessionRetargetResponsePacket packet = new SessionRetargetResponsePacket();

        // Create a buffer large enough to hold the read bytes
        byte[] buffer = new byte[6];
        int bytesRead = packet.readTrailerWireFormat(bais, buffer, 0);

        // Verify that 6 bytes were read, which is the expected length.

The result of calling it is something that can be encoded with the Python standard <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.

It doesn't return a large `str` containing the data in JSON format (as a string). It returns a Python standard data structure (e.g. a `dict`) with values and sub-values that are all compatible with JSON.

/// note

	// Total number of completed operations
	ReplicatedCount int64 `json:"replicationCount"`
	// Replication latency information
	Latency ReplicationLatency `json:"replicationLatency"`
	// transfer rate for large uploads
	XferRateLrg *XferStats `json:"largeTransferRate" msg:"lt"`
	// transfer rate for small uploads
	XferRateSml *XferStats `json:"smallTransferRate" msg:"st"`
	// Endpoint is the replication target endpoint

        RescorerBuilder<?> result = ltrQueryRescorer.evaluate(params);
        assertNotNull(result);
        assertEquals(10, ((QueryRescorerBuilder) result).windowSize().intValue());

        // Test with large window size
        ComponentUtil.setFessConfig(new FessConfig.SimpleImpl() {
            @Override
            public String getLtrModelName() {
                return testModelName;
            }

### 5. (optional) Any other info / logs

MinIO is a high performance distributed object storage server, designed for large-scale private cloud infrastructure. MinIO is designed in a cloud-native manner to scale sustainably in multi-tenant environments. Orchestration platforms like Kubernetes provide perfect cloud-native environment to deploy and scale MinIO.

        // Assert
        assertFalse(result);
        verify(signingDigest, times(1)).verify(emptyData, offset, length, extraPad, message);
    }

    @Test
    @DisplayName("Test sign method with large data array")
    void testSignWithLargeData() {
        // Arrange
        byte[] largeData = new byte[65536]; // 64KB
        for (int i = 0; i < largeData.length; i++) {
            largeData[i] = (byte) (i % 256);