NetworkX to GraphLab Connected Component Conversion

Question

What is the GraphLab equivalent to the following NetworkX code?
for nodeset in nx.connected_components(G):

In GraphLab, I would like to obtain a set of Vertex IDs for each connected component.

Answer 1

The component IDs returned by graphlab.graph_analytics.connected_components are in the form of an SFrame, so the easiest way to get the IDs for a given component is by filtering the SFrame:

# Make a graph with two components.
import graphlab
G = graphlab.SGraph().add_edges(
    [graphlab.Edge(i, i+1) for i in range(3)])
G = G.add_edges([graphlab.Edge(i, i+1) for i in range(4, 6)])

# Get the connected components.
cc = graphlab.connected_components.create(G)

# Find the vertices for a given component (0, in this example).
nodes = cc.component_id.filter_by(0, 'component_id')
print nodes

+------+--------------+
| __id | component_id |
+------+--------------+
|  5   |      0       |
|  6   |      0       |
|  4   |      0       |
+------+--------------+
[3 rows x 2 columns]

Answer 2

Here is the first cut at porting from NetworkX to GraphLab. However, iterating appears to be very slow.
temp1 = cc['component_id']
temp1.remove_column('__id')
id_set = set()
id_set = temp1['component_id']
for item in id_set:
nodeset = cc_out[cc_out['component_id'] == item]['__id']