degree.annotate.directed. VertexInDegree 
Annotate vertices of a directed graph with the indegree.
DataSet<Vertex<K, LongValue>> inDegree = graph
.run(new VertexInDegree()
.setIncludeZeroDegreeVertices(true));
Optional configuration:
setIncludeZeroDegreeVertices: by default only the edge set is processed for the computation of degree; when this flag is set an additional join is performed against the vertex set in order to output vertices with an indegree of zero
setParallelism: override the operator parallelism

degree.annotate.directed. VertexOutDegree 
Annotate vertices of a directed graph with the outdegree.
DataSet<Vertex<K, LongValue>> outDegree = graph
.run(new VertexOutDegree()
.setIncludeZeroDegreeVertices(true));
Optional configuration:
setIncludeZeroDegreeVertices: by default only the edge set is processed for the computation of degree; when this flag is set an additional join is performed against the vertex set in order to output vertices with an outdegree of zero
setParallelism: override the operator parallelism

degree.annotate.directed. VertexDegrees 
Annotate vertices of a directed graph with the degree, outdegree, and indegree.
DataSet<Vertex<K, Tuple2<LongValue, LongValue>>> degrees = graph
.run(new VertexDegrees()
.setIncludeZeroDegreeVertices(true));
Optional configuration:
setIncludeZeroDegreeVertices: by default only the edge set is processed for the computation of degree; when this flag is set an additional join is performed against the vertex set in order to output vertices with out and indegree of zero
setParallelism: override the operator parallelism

degree.annotate.directed. EdgeSourceDegrees 
Annotate edges of a directed graph with the degree, outdegree, and indegree of the source ID.
DataSet<Edge<K, Tuple2<EV, Degrees>>> sourceDegrees = graph
.run(new EdgeSourceDegrees());
Optional configuration:

degree.annotate.directed. EdgeTargetDegrees 
Annotate edges of a directed graph with the degree, outdegree, and indegree of the target ID.
DataSet<Edge<K, Tuple2<EV, Degrees>>> targetDegrees = graph
.run(new EdgeTargetDegrees();
Optional configuration:

degree.annotate.directed. EdgeDegreesPair 
Annotate edges of a directed graph with the degree, outdegree, and indegree of both the source and target vertices.
DataSet<Edge<K, Tuple2<EV, Degrees>>> degrees = graph
.run(new EdgeDegreesPair());
Optional configuration:

degree.annotate.undirected. VertexDegree 
Annotate vertices of an undirected graph with the degree.
DataSet<Vertex<K, LongValue>> degree = graph
.run(new VertexDegree()
.setIncludeZeroDegreeVertices(true)
.setReduceOnTargetId(true));
Optional configuration:
setIncludeZeroDegreeVertices: by default only the edge set is processed for the computation of degree; when this flag is set an additional join is performed against the vertex set in order to output vertices with a degree of zero
setParallelism: override the operator parallelism
setReduceOnTargetId: the degree can be counted from either the edge source or target IDs. By default the source IDs are counted. Reducing on target IDs may optimize the algorithm if the input edge list is sorted by target ID.

degree.annotate.undirected. EdgeSourceDegree 
Annotate edges of an undirected graph with degree of the source ID.
DataSet<Edge<K, Tuple2<EV, LongValue>>> sourceDegree = graph
.run(new EdgeSourceDegree()
.setReduceOnTargetId(true));
Optional configuration:
setParallelism: override the operator parallelism
setReduceOnTargetId: the degree can be counted from either the edge source or target IDs. By default the source IDs are counted. Reducing on target IDs may optimize the algorithm if the input edge list is sorted by target ID.

degree.annotate.undirected. EdgeTargetDegree 
Annotate edges of an undirected graph with degree of the target ID.
DataSet<Edge<K, Tuple2<EV, LongValue>>> targetDegree = graph
.run(new EdgeTargetDegree()
.setReduceOnSourceId(true));
Optional configuration:
setParallelism: override the operator parallelism
setReduceOnSourceId: the degree can be counted from either the edge source or target IDs. By default the target IDs are counted. Reducing on source IDs may optimize the algorithm if the input edge list is sorted by source ID.

degree.annotate.undirected. EdgeDegreePair 
Annotate edges of an undirected graph with the degree of both the source and target vertices.
DataSet<Edge<K, Tuple3<EV, LongValue, LongValue>>> pairDegree = graph
.run(new EdgeDegreePair()
.setReduceOnTargetId(true));
Optional configuration:
setParallelism: override the operator parallelism
setReduceOnTargetId: the degree can be counted from either the edge source or target IDs. By default the source IDs are counted. Reducing on target IDs may optimize the algorithm if the input edge list is sorted by target ID.

degree.filter.undirected. MaximumDegree 
Filter an undirected graph by maximum degree.
Graph<K, VV, EV> filteredGraph = graph
.run(new MaximumDegree(5000)
.setBroadcastHighDegreeVertices(true)
.setReduceOnTargetId(true));
Optional configuration:
setBroadcastHighDegreeVertices: join highdegree vertices using a broadcasthash to reduce data shuffling when removing a relatively small number of highdegree vertices.
setParallelism: override the operator parallelism
setReduceOnTargetId: the degree can be counted from either the edge source or target IDs. By default the source IDs are counted. Reducing on target IDs may optimize the algorithm if the input edge list is sorted by target ID.

simple.directed. Simplify 
Remove selfloops and duplicate edges from a directed graph.
graph.run(new Simplify());
Optional configuration:

simple.undirected. Simplify 
Add symmetric edges and remove selfloops and duplicate edges from an undirected graph.
graph.run(new Simplify());
Optional configuration:

translate. TranslateGraphIds 
Translate vertex and edge IDs using the given TranslateFunction .
graph.run(new TranslateGraphIds(new LongValueToStringValue()));
Required configuration:
Optional configuration:

translate. TranslateVertexValues 
Translate vertex values using the given TranslateFunction .
graph.run(new TranslateVertexValues(new LongValueAddOffset(vertexCount)));
Required configuration:
Optional configuration:

translate. TranslateEdgeValues 
Translate edge values using the given TranslateFunction .
graph.run(new TranslateEdgeValues(new Nullify()));
Required configuration:
Optional configuration:
