for (int i = 0; i < nodeList.size(); i++) {
                    final Node node = nodeList.get(i);
                    strList.add(node.getTextContent());
                }
                return strList.toArray(n -> new String[n]);
            case NODE:
                final Node node = (Node) xObj.value();
                return new String[] { node.getTextContent() };
            default:

    /**
     * @return the rpath
     */
    public final String getRpath () {
        return this.rpath;
    }


    /**
     * @return the node
     */
    public final String getNode () {
        return this.node;
    }


    /**
     * @return the specialName
     */
    public final String getSpecialName () {
        return this.specialName;
    }

  @CanIgnoreReturnValue
  boolean addNode(N node);

  /**
   * Adds {@code edge} connecting {@code nodeU} to {@code nodeV}.
   *
   * <p>If the graph is directed, {@code edge} will be directed in this graph; otherwise, it will be
   * undirected.
   *
   * <p><b>{@code edge} must be unique to this graph</b>, just as a {@code Map} key must be. It must
   * also be non-null.
   *

  bearer_token: <secret>
  metrics_path: /minio/v2/metrics/bucket
  scheme: http
  static_configs:
  - targets: ['localhost:9000']
```

##### Node centric (optional)

```yaml
- job_name: minio-job-node
  bearer_token: <secret>
  metrics_path: /minio/v2/metrics/node
  scheme: http
  static_configs:
  - targets: ['localhost:9000']
```

##### Resource centric (optional)

```yaml

  // implementation will use to handle pods of this class. The possible values
  // are specific to the node & CRI configuration.  It is assumed that all
  // handlers are available on every node, and handlers of the same name are
  // equivalent on every node.
  // For example, a handler called "runc" might specify that the runc OCI
  // runtime (using native Linux containers) will be used to run the containers

    private void processTreeNodes(MetadataGraphVertex parentVertex, MetadataTreeNode node, int depth, int pomOrder)
            throws MetadataResolutionException {
        if (node == null) {
            return;
        }

        MetadataGraphVertex vertex = new MetadataGraphVertex(node.md, versionedVertices, scopedVertices);
        if (!vertices.contains(vertex)) {
            vertices.add(vertex);

}

func main() {
	var node, args string

	flag.StringVar(&node, "local-node-name", "", "the name of the local node")
	flag.StringVar(&args, "args", "", "arguments passed to MinIO server")

	flag.Parse()

	localDisks, err := filterLocalDisks(node, args)
	if err != nil {
		log.Fatal(err)
	}

	if len(localDisks) == 0 {
		log.Fatal("Fix --local-node-name or/and --args to select local disks.")
	}

### Node Binaries

filename | sha256 hash
-------- | -----------
[kubernetes-node-linux-amd64.tar.gz](https://dl.k8s.io/v1.5.8/kubernetes-node-linux-amd64.tar.gz) | `4d73ccd2ecac0f2e161f88e4d77004298d10a009f9b5fa0203fa7bff70a82e30`

MinIO in distributed mode lets you pool multiple drives (even on different machines) into a single object storage server. As drives are distributed across several nodes, distributed MinIO can withstand multiple node failures and yet ensure full data protection.

## Why distributed MinIO?

  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding