Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/430#discussion_r25415172
--- Diff: docs/gelly_guide.md ---
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+---
+title: "Gelly: Flink Graph API"
+---
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements. See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership. The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied. See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+* This will be replaced by the TOC
+{:toc}
+
+<a href="#top"></a>
+
+Introduction
+------------
+
+Gelly is a Java Graph API for Flink. It contains a set of methods and
utilities which aim to simplify the development of graph analysis applications
in Flink. In Gelly, graphs can be transformed and modified using high-level
functions similar to the ones provided by the batch processing API. Gelly
provides methods to create, transform and modify graphs, as well as a library
of graph algorithms.
+
+Using Gelly
+-----------
+
+Gelly is currently part of the *staging* Maven project. All relevant
classes are located in the *org.apache.flink.graph* package.
+
+Add the following dependency to your `pom.xml` to use Gelly.
+
+~~~xml
+<dependency>
+ <groupId>org.apache.flink</groupId>
+ <artifactId>flink-gelly</artifactId>
+ <version>{{site.FLINK_VERSION_SHORT}}</version>
+</dependency>
+~~~
+
+The remaining sections provide a description of available methods and
present several examples of how to use Gelly and how to mix it with the Flink
Java API. After reading this guide, you might also want to check the {% gh_link
/flink-staging/flink-gelly/src/main/java/org/apache/flink/graph/example/ "Gelly
examples" %}.
+
+Graph Representation
+-----------
+
+In Gelly, a `Graph` is represented by a `DataSet` of vertices and a
`DataSet` of edges.
+
+The `Graph` nodes are represented by the `Vertex` type. A `Vertex` is
defined by a unique ID and a value. `Vertex` IDs should implement the
`Comparable` interface. Vertices without value can be represented by setting
the value type to `NullValue`.
+
+{% highlight java %}
+// create a new vertex with a Long ID and a String value
+Vertex<Long, String> v = new Vertex<Long, String>(1L, "foo");
+
+// create a new vertex with a Long ID and no value
+Vertex<Long, NullValue> v = new Vertex<Long, NullValue>(1L,
NullValue.getInstance());
+{% endhighlight %}
+
+The graph edges are represented by the `Edge` type. An `Edge` is defined
by a source ID (the ID of the source `Vertex`), a target ID (the ID of the
target `Vertex`) and an optional value. The source and target IDs should be of
the same type as the `Vertex` IDs. Edges with no value have a `NullValue` value
type.
+
+{% highlight java %}
+Edge<Long, Double> e = new Edge<Long, Double>(1L, 2L, 0.5);
+
+// reverse the source and target of this edge
+Edge<Long, Double> reversed = e.reverse();
+
+Double weight = e.getValue(); // weight = 0.5
+{% endhighlight %}
+
+[Back to top](#top)
+
+Graph Creation
+-----------
+
+You can create a `Graph` in the following ways:
+
+* from a `DataSet` of edges and an optional `DataSet` of vertices:
+
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+
+DataSet<Vertex<String, Long>> vertices = ...
+
+DataSet<Edge<String, Double>> edges = ...
+
+Graph<String, Long, Double> graph = Graph.fromDataSet(vertices, edges,
env);
+{% endhighlight %}
+
+* from a `DataSet` of `Tuple3` and an optional `DataSet` of `Tuple2`. In
this case, Gelly will convert each `Tuple3` to an `Edge`, where the first field
will be the source ID, the second field will be the target ID and the third
field will be the edge value. Equivalently, each `Tuple2` will be converted to
a `Vertex`, where the first field will be the vertex ID and the second field
will be the vertex value:
+
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+
+DataSet<Tuple2<String, Long>> vertexTuples =
env.readCsvFile("path/to/vertex/input");
+
+DataSet<Tuple3<String, String, Double>> edgeTuples =
env.readCsvFile("path/to/edge/input");
+
+Graph<String, Long, Double> graph = Graph.fromTupleDataSet(vertexTuples,
edgeTuples, env);
+{% endhighlight %}
+
+* from a `Collection` of edges and an optional `Collection` of vertices:
+
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+
+List<Vertex<Long, Long>> vertexList = new ArrayList...
+
+List<Edge<Long, String>> edgeList = new ArrayList...
+
+Graph<Long, Long, String> graph = Graph.fromCollection(vertexList,
edgeList, env);
+{% endhighlight %}
+
+If no vertex input is provided during Graph creation, Gelly will
automatically produce the `Vertex` `DataSet` from the edge input. In this case,
the created vertices will have no values. Alternatively, you can provide a
`MapFunction` as an argument to the creation method, in order to initialize the
`Vertex` values:
+
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+
+// initialize the vertex value to be equal to the vertex ID
+Graph<Long, Long, String> graph = Graph.fromCollection(edges,
+ new MapFunction<Long, Long>() {
+ public Long map(Long value) {
+ return value;
+ }
+ }, env);
+{% endhighlight %}
+
+[Back to top](#top)
+
+Graph Properties
+------------
+
+Gelly includes the following methods for retrieving various Graph
properties and metrics:
+
+{% highlight java %}
+// get the Vertex DataSet
+DataSet<Vertex<K, VV>> getVertices()
+
+// get the Edge DataSet
+DataSet<Edge<K, EV>> getEdges()
+
+// get the IDs of the vertices as a DataSet
+DataSet<K> getVertexIds()
+
+// get the source-target pairs of the edge IDs as a DataSet
+DataSet<Tuple2<K, K>> getEdgeIds()
+
+// get a DataSet of <vertex ID, in-degree> pairs for all vertices
+DataSet<Tuple2<K, Long>> inDegrees()
+
+// get a DataSet of <vertex ID, out-degree> pairs for all vertices
+DataSet<Tuple2<K, Long>> outDegrees()
+
+// get a DataSet of <vertex ID, degree> pairs for all vertices, where
degree is the sum of in- and out- degrees
+DataSet<Tuple2<K, Long>> getDegrees()
+
+// get the number of vertices
+DataSet<Integer> numberOfVertices()
+
+// get the number of edges
+DataSet<Integer> numberOfEdges()
+
+{% endhighlight %}
+
+[Back to top](#top)
+
+Graph Transformations
+-----------------
+
+* <strong>Map</strong>: Gelly provides specialized methods for applying a
map transformation on the vertex values or edge values. `mapVertices` and
`mapEdges` return a new `Graph`, where the IDs of the vertices (or edges)
remain unchanged, while the values are transformed according to the provided
user-defined map function. The map functions also allow changing the type of
the vertex or edge values.
+
+{% highlight java %}
+ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
+Graph<Long, Long, Long> graph = Graph.fromDataSet(vertices, edges, env);
+
+// increment each vertex value by one
+Graph<Long, Long, Long> updatedGraph = graph.mapVertices(
+ new MapFunction<Vertex<Long, Long>, Long>() {
+ public Long map(Vertex<Long, Long>
value) {
+ return value.getValue() + 1;
+ }
+ });
+{% endhighlight %}
+
+* <strong>Filter</strong>: A filter transformation applies a user-defined
filter function on the vertices or edges of the `Graph`. `filterOnEdges` will
create a sub-graph of the original graph, keeping only the edges that satisfy
the provided predicate. Note that the vertex dataset will not be modified.
Respectively, `filterOnVertices` applies a filter on the vertices of the graph.
Edges whose source and/or target do not satisfy the vertex predicate are
removed from the resulting edge dataset. The `subgraph` method can be used to
apply a filter function to the vertices and the edges at the same time.
+
+{% highlight java %}
+Graph<Long, Long, Long> graph = ...
+
+graph.subgraph(
+ new FilterFunction<Vertex<Long, Long>>() {
+ public boolean filter(Vertex<Long, Long>
vertex) {
+ // keep only vertices with positive
values
+ return (vertex.getValue() > 0);
+ }
+ },
+ new FilterFunction<Edge<Long, Long>>() {
+ public boolean filter(Edge<Long, Long> edge) {
+ // keep only edges with negative values
+ return (edge.getValue() < 0);
+ }
+ })
+{% endhighlight %}
+
+<p class="text-center">
+ <img alt="Filter Transformations" width="80%"
src="img/gelly-filter.png"/>
+</p>
+
+* <strong>Join</strong>: Gelly provides specialized methods for joining
the vertex and edge datasets with other input datasets. `joinWithVertices`
joins the vertices with a `Tuple2` input data set. The join is performed using
the vertex ID and the first field of the `Tuple2` input as the join keys. The
method returns a new `Graph` where the vertex values have been updated
according to the provided a user-defined map function.
--- End diff --
"...updated according to a provided user-defined map function"
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