// can easily eat into the internode bandwidth. This function would be mostly
	// TX saturating, however there are situations where a RX might also saturate.
	// To avoid these problems we must split the work at scale. With 1000 node
	// setup becoming a reality we must try to shard the work properly such as
	// pick 10 nodes that precisely can send those 100 requests the first node

  // +optional
  optional .k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

  // nodeTopology defines which nodes have access to the storage
  // for which capacity was reported. If not set, the storage is
  // not accessible from any node in the cluster. If empty, the
  // storage is accessible from all nodes. This field is
  // immutable.
  //
  // +optional

// For PVCs that are bound, then it checks that the corresponding PV's node affinity is
// satisfied by the given node.
//
// For PVCs that are unbound, it tries to find available PVs that can satisfy the PVC requirements
// and that the PV node affinity is satisfied by the given node.
//
// If storage capacity tracking is enabled, then enough space has to be available
// for the node and volumes that still need to be created.
//

	"":           "ResourceSlice provides information about available resources on individual nodes.",
	"metadata":   "Standard object metadata",
	"nodeName":   "NodeName identifies the node which provides the resources if they are local to a node.\n\nA field selector can be used to list only ResourceSlice objects with a certain node name.",

import org.gradle.api.tasks.diagnostics.internal.ProjectDetails.ProjectNameAndPath;
import org.gradle.api.tasks.diagnostics.internal.graph.nodes.RenderableDependency;
import org.gradle.api.tasks.diagnostics.internal.graph.nodes.RenderableModuleResult;
import org.gradle.api.tasks.diagnostics.internal.insight.DependencyInsightReporter;
import org.gradle.internal.Actions;
import org.gradle.util.GradleVersion;

			if matchExpr.Key == v1.LabelHostname && matchExpr.Operator == v1.NodeSelectorOpIn {
				if nodes == nil {
					nodes = sets.New(matchExpr.Values...)
				} else {
					nodes = nodes.Intersection(sets.New(matchExpr.Values...))
				}
			}
		}
		result = result.Union(nodes)
	}

	return sets.List(result)
}

// GetPodVolumeNames returns names of volumes that are used in a pod,

 * <p>This type is intended to contain values that are calculated as nodes in the work graph, but which may also be calculated
 * on demand. An instance of this type can be used as a node in the work graph.
 * </p>
 *
 * <p>Note that when used as a work node, any failure to calculate the value is collected and not rethrown. This means that the node is considered to have succeeded and any dependent

  TF_RETURN_IF_ERROR(s.ToGraph(graph.get()));
  FunctionLibraryDefinition flib_def(graph->op_registry(), fdef_lib);

  // Assign all nodes to the CPU device.
  static const char* kCpuDevice = "/job:localhost/replica:0/task:0/cpu:0";
  for (Node* n : graph->nodes()) {
    if (n->requested_device().empty()) {
      n->set_assigned_device_name(kCpuDevice);
    } else {
      n->set_assigned_device_name(n->requested_device());

	sc := clienttest.NewWriter[*corev1.Service](t, s.client)
	pod1 := generatePod("127.0.0.1", "pod1", testNS, "sa1", "node1", map[string]string{"app": "a"}, nil)
	pc.CreateOrUpdateStatus(pod1)
	fx.WaitOrFail(t, "xds")

	pod2 := generatePod("127.0.0.2", "pod2", testNS, "sa2", "node1", map[string]string{"app": "a"}, nil)
	pc.CreateOrUpdateStatus(pod2)
	fx.WaitOrFail(t, "xds")

Kubernetes manages stateless Spark and Hive containers elastically on the compute nodes. Spark has native scheduler integration with Kubernetes. Hive, for legacy reasons, uses YARN scheduler on top of Kubernetes.