memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")
	memUsedMD      = NewGaugeMD(memUsed, "Used memory on the node")
	memUsedPercMD  = NewGaugeMD(memUsedPerc, "Used memory percentage on the node")
	memFreeMD      = NewGaugeMD(memFree, "Free memory on the node")
	memBuffersMD   = NewGaugeMD(memBuffers, "Buffers memory on the node")
	memCacheMD     = NewGaugeMD(memCache, "Cache memory on the node")

 * from the {@code pathScope} and the injected field type. If the type
 * is {@link org.apache.maven.api.Node Node} and {@code pathScope == ""},
 * then the dependencies will be <i>collected</i>.
 * If the type is {@link org.apache.maven.api.Node Node} or
 * {@code List<}{@link org.apache.maven.api.Node Node}{@code >},
 * and {@code pathScope != ""}, the dependencies will be <i>flattened</i>.

                .get(stream -> stream.map(String::trim).filter(StringUtil::isNotEmpty).toArray(n -> new String[n]));
        nodeManager = new NodeManager(hosts, node -> request(new CurlRequest(Method.GET, node.getUrl("/"))));
        nodeManager.setHeartbeatInterval(fessConfig.getFesenHeartbeatInterval());
    }

    /**
     * Creates a GET request for the specified path.

        return flags;
    }

    /**
     * Gets the new node address.
     *
     * @return the new node address
     */
    public String getNewNodeAddress() {
        return newNodeAddress;
    }

    /**
     * Sets the new node address.
     *
     * @param newNodeAddress the new node address
     */
    public void setNewNodeAddress(String newNodeAddress) {

                    for (int i = 0; i < nodeList.getLength(); i++) {
                        final Node node = nodeList.item(i);
                        final NamedNodeMap attributes = node.getAttributes();
                        if (attributes != null) {
                            final Node classAttr = attributes.getNamedItem("class");
                            if (classAttr != null) {

Node metrics can be viewed in the Grafana dashboard using [json file here](https://raw.githubusercontent.com/minio/minio/master/docs/metrics/prometheus/grafana/node/minio-node.json)

![Grafana](https://raw.githubusercontent.com/minio/minio/master/docs/metrics/prometheus/grafana/node/grafana-node.png)

sets, which is *16* 64 = 1024* drives in total.

- *If total number of nodes are of odd number then GCD algorithm provides affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards...

`<Address for MinIO Node>/minio/v2/metrics/node`.

The additional bucket specific metrics which include additional go metrics or process metrics are exposed at
`<Address for MinIO Node>/minio/v2/metrics/bucket`.

The additional resource specific metrics which include additional go metrics or process metrics are exposed at
`<Address for MinIO Node>/minio/v2/metrics/resource`.

    assertThat(graph).isNotEqualTo(g2);
  }

  // Node/edge sets are the same, but node/edge connections differ due to edge type.
  @Test
  public void equivalent_directedVsUndirected() {
    graph.putEdge(N1, N2);

    MutableGraph<Integer> g2 = createGraph(oppositeType(edgeType));
    g2.putEdge(N1, N2);

    assertThat(graph).isNotEqualTo(g2);
  }

  // Node/edge sets and node/edge connections are the same, but directedness differs.

    assertThat(graph).isNotEqualTo(g2);
  }

  // Node/edge sets are the same, but node/edge connections differ due to edge type.
  @Test
  public void equivalent_directedVsUndirected() {
    graph.putEdge(N1, N2);

    MutableGraph<Integer> g2 = createGraph(oppositeType(edgeType));
    g2.putEdge(N1, N2);

    assertThat(graph).isNotEqualTo(g2);
  }

  // Node/edge sets and node/edge connections are the same, but directedness differs.