Caches the vertices and edges associated with this graph at the previously-specified target storage levels, which default to MEMORY_ONLY. This is used to pin a graph in memory enabling multiple queries to reuse the same construction process.

Mark this Graph for checkpointing. It will be saved to a file inside the checkpoint directory set with SparkContext.setCheckpointDir() and all references to its parent RDDs will be removed. It is strongly recommended that this Graph is persisted in memory, otherwise saving it on a file will require recomputation.

An RDD containing the edges and their associated attributes. The entries in the RDD contain just the source id and target id along with the edge data.

Gets the name of the files to which this Graph was checkpointed. (The vertices RDD and edges RDD are checkpointed separately.)

Merges multiple edges between two vertices into a single edge. For correct results, the graph must have been partitioned using partitionBy.

Return whether this Graph has been checkpointed or not. This returns true iff both the vertices RDD and edges RDD have been checkpointed.

Transforms each edge attribute using the map function, passing it a whole partition at a time. The map function is given an iterator over edges within a logical partition as well as the partition's ID, and it should return a new iterator over the new values of each edge. The new iterator's elements must correspond one-to-one with the old iterator's elements. If adjacent vertex values are desired, use mapTriplets.

Transforms each edge attribute a partition at a time using the map function, passing it the adjacent vertex attributes as well. The map function is given an iterator over edge triplets within a logical partition and should yield a new iterator over the new values of each edge in the order in which they are provided. If adjacent vertex values are not required, consider using mapEdges instead.

Transforms each vertex attribute in the graph using the map function.

Restricts the graph to only the vertices and edges that are also in other, but keeps the attributes from this graph.

Joins the vertices with entries in the table RDD and merges the results using mapFunc. The input table should contain at most one entry for each vertex. If no entry in other is provided for a particular vertex in the graph, the map function receives None.

Repartitions the edges in the graph according to partitionStrategy.

Repartitions the edges in the graph according to partitionStrategy.

Caches the vertices and edges associated with this graph at the specified storage level, ignoring any target storage levels previously set.

Reverses all edges in the graph. If this graph contains an edge from a to b then the returned graph contains an edge from b to a.

Restricts the graph to only the vertices and edges satisfying the predicates. The resulting subgraph satisfies

V' = {v : for all v in V where vpred(v)}
E' = {(u,v): for all (u,v) in E where epred((u,v)) && vpred(u) && vpred(v)}

An RDD containing the edge triplets, which are edges along with the vertex data associated with the adjacent vertices. The caller should use edges if the vertex data are not needed, i.e. if only the edge data and adjacent vertex ids are needed.

Uncaches both vertices and edges of this graph. This is useful in iterative algorithms that build a new graph in each iteration.

Uncaches only the vertices of this graph, leaving the edges alone. This is useful in iterative algorithms that modify the vertex attributes but reuse the edges. This method can be used to uncache the vertex attributes of previous iterations once they are no longer needed, improving GC performance.

An RDD containing the vertices and their associated attributes.

Aggregates values from the neighboring edges and vertices of each vertex. The user-supplied sendMsg function is invoked on each edge of the graph, generating 0 or more messages to be sent to either vertex in the edge. The mergeMsg function is then used to combine all messages destined to the same vertex.

Transforms each edge attribute in the graph using the map function. The map function is not passed the vertex value for the vertices adjacent to the edge. If vertex values are desired, use mapTriplets.

Transforms each edge attribute using the map function, passing it the adjacent vertex attributes as well. If adjacent vertex values are not required, consider using mapEdges instead.

Transforms each edge attribute using the map function, passing it the adjacent vertex attributes as well. If adjacent vertex values are not required, consider using mapEdges instead.