while (true) {
          val socket = serverSocket!!.accept()
          connectionCount.incrementAndGet()
          service(socket)
        }
      } catch (e: SocketException) {
        logger.info("$threadName done accepting connections: ${e.message}")
      } catch (e: IOException) {
        logger.log(Level.WARNING, "$threadName failed unexpectedly", e)
      } finally {
        for (socket in openSockets) {

		{"ad", "", ObjectInfo{}, BucketNameInvalid{Bucket: "ad"}, false},
		// Test cases with valid but non-existing bucket names (Test number 5-6).
		{"abcdefgh", "abc", ObjectInfo{}, BucketNotFound{Bucket: "abcdefgh"}, false},
		{"ijklmnop", "efg", ObjectInfo{}, BucketNotFound{Bucket: "ijklmnop"}, false},
		// Test cases with valid but non-existing bucket names and invalid object name (Test number 7-8).

	// 2: Also block, but with streaming.
	h2 := StreamHandler{
		Handle: func(ctx context.Context, payload []byte, request <-chan []byte, resp chan<- []byte) *RemoteErr {
			gotCall <- struct{}{}
			select {
			case <-ctx.Done():
				gotCall <- struct{}{}
			case <-cleanReqs:
				panic("should not be called")
			}
			return nil
		},
		OutCapacity: 1,
		InCapacity:  1,
	}

	// atomics, keep at top:
	types          uint64
	numSubscribers int32
	maxSubscribers int32

	// not atomics:
	subs []*Sub[T]
	sync.RWMutex
}

// Publish message to the subscribers.
// Note that publish is always non-blocking send so that we don't block on slow receivers.
// Hence receivers should use buffered channel so as not to miss the published events.
func (ps *PubSub[T, M]) Publish(item T) {
	ps.RLock()
	defer ps.RUnlock()

				return nil, nil, fmt.Errorf("could not unmarshal ClientConfig: %w", err)
			}
			meta, err := model.ParseMetadata(clientConfig.GetNode().GetMetadata())
			if err != nil {
				return nil, nil, fmt.Errorf("could not parse node metadata: %w", err)
			}
			if s.Namespace != "" && meta.Namespace != s.Namespace {
				continue
			}
			cds, lds, eds, rds, ecds := getSyncStatus(&clientConfig)
			cp := multixds.CpInfo(dr)

  TF_DeleteAbstractOp(add_op);

  TF_AbstractFunction* func =
      TF_FinalizeFunction(graph_ctx, add_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  // Note: TF_OutputList does not own the underlying AbstractTensors, those
  // need to be deleted explicitly.
  TF_DeleteAbstractTensor(TF_OutputListGet(add_outputs, 0));

  // Build eager context.

    if (state != State.NOT_DONE && (numListeners != 0 || numThreads != 0)) {
      throw new SkipThisScenarioException();
    }
  }

  // This exclusion doesn't exclude the TOMBSTONE objects we set. So 'done' NEW futures will look
  // larger than they are.
  @SuppressWarnings("FutureReturnValueIgnored")
  @Footprint(exclude = {Runnable.class, Executor.class, Thread.class, Exception.class})
  public Object measureSize() {

                    dns_forest.buffer[_i] = (short)_src.dec_ndr_short();
                }
            }
            if (domain_guid.node == null) {
                if (_domain_guid_nodes < 0 || _domain_guid_nodes > 0xFFFF) throw new NdrException( NdrException.INVALID_CONFORMANCE );
                domain_guid.node = new byte[_domain_guid_nodes];
            }
            _src = _src.derive(_domain_guid_nodei);

	if err != nil {
		// Failed to create newbucket, abort.
		t.Fatalf("%s : %s", instanceType, err.Error())
	}

	// Take 4 disks down, one more we loose quorum on 16 disk node.
	for _, disk := range disks[:4] {
		os.RemoveAll(disk)
	}

	testCases := []struct {
		bucketName    string
		objName       string
		inputData     []byte

Follow these steps to run the Spark Pi example:

- Login as user **‘spark’**.
- When the job runs, the library can now use **MinIO** during intermediate processing.
- Navigate to a node with the Spark client and access the spark2-client directory:

```
cd /usr/hdp/current/spark2-client
su spark
```

- Run the Apache Spark Pi job in yarn-client mode, using code from **org.apache.spark**: