some cleanuups, global property var for flink dependency, added clust…

…er exec to readme, flink action for build

.github/workflows/maven.yml

@@ -0,0 +1,9 @@
+steps:
+  - uses: actions/checkout@v4
+  - name: Set up JDK 8 for x64 and run maven
+    uses: actions/setup-java@v4
+    with:
+      java-version: '8'
+      distribution: 'oracle'
+      architecture: x64
+  - run: mvn -B build --file pom.xml

README.md

@@ -1,5 +1,5 @@
 [![Apache License, Version 2.0, January 2004](https://img.shields.io/github/license/apache/maven.svg?label=License)](https://www.apache.org/licenses/LICENSE-2.0)
-
+[![Apache Flink](https://img.shields.io/badge/Apache%20Flink-E6526F?style=for-the-badge&logo=Apache%20Flink&logoColor=white)](https://flink.apache.org)
 # Graph Stream Zoomer
 ![GraphStreamZoomer_Logo](logo/GraphStreamZoomerLogo_small.png)
 
@@ -18,64 +18,6 @@ aggregate functions and a window size. Through the closed operator concept, the
 graph stream consisting of summarized vertices and edges. The system is based on Apache Flink® and its 
 Table API, SQL API and DataStream API, thus providing a distributed execution of the summarization.
 
-### Windowing
-*Graph Stream Zoomer* groups the graph using a windowing approach. The user can specify the size of the 
-window by a `WindowConfig`. Currently, there are just tumbling windows supported, but sliding windows are 
-planned for the near future.
-
-Example window definition for a 10 seconds tumbling window:
-
-`groupingBuilder.setWindowSize(10, WindowConfig.TimeUnit.SECONDS);`
-
-### Grouping Keys
-Vertices as well as edges will be grouped by common characteristics, which we call grouping keys. These 
-characteristics can be zero, one or multiple of the following:
-* Label - groups all vertices/edges sharing the same type label
-* Property value (by name) - groups all vertices/edges that contain a property with the specified name and 
-  an equal value. All vertices/edges _without_ a property of this name are grouped as one group. The super 
-  vertex or super edge (the resulting group representative) contains the property and (1) the respective 
-  value or (2) null, for the group that do not have this property
-* Time - groups all vertices/edges with a timestamp in the same window -> see _Windowing_ above
-* User-defined grouping key - tbd.
-
-### Aggregate functions
-Vertices and edges are grouped according to the selected grouping keys. The content of all vertices/edges 
-that are grouped together can be used to calculate aggregates that will be part of the super vertex / 
-super edge (the resulting group representative).
-* Count - just counts the number of elements that were merged to a group and stores them in a new property 
-  with name `count`
-* MinProperty - calculates the minimum value of a given property and stores it to a new property called 
-  `min_{name}`. Just works with numerical property values.
-* MaxProperty - calculates the maximum value of a given property and stores it to a new property called
-  `max_{name}`. Just works with numerical property values.
-* AvgProperty - calculates the average value of a given property and stores it to a new property called
-  `avg_{name}`. Just works with numerical property values.
-* User-defined aggregate function - tbd.
-
-## Graph Stream Data Model
-The graph stream data model of *Graph Stream Zoomer* is defined as follows.
-
-`DataStream<StreamTriple>` -> the Flink representation of a graph stream
-
-`StreamTriple`
-* `StreamVertex`
-* `StreamEdge`
-* `StreamVertex`
-
-`StreamVertex`
-* `id (String)` 
-* `label (String)` 
-* `properties (Properties)` 
-* `event_time (Timestamp)`
-
-`StreamEdge`
-* `id (String)`
-* `label (String)`
-* `properties (Properties)`
-* `source_id (String)`
-* `target_id (String)`
-* `event_time (Timestamp)`
-
 ## Usage
 
 ### As an own project
@@ -124,7 +66,77 @@ env.execute();
 * LocalExample -> loads a tiny stream from a collection
 * TwitterExample -> loads a live twitter message stream (credentials required)
 * CitiBikeExample -> uses citibike rental data to create a graph stream
-* SocketExample -> loads a graph stream from a socket connection
+* RandomGeneratorExample -> loads a random generated graph stream with configurable frequency
+
+## Execution on Apache Flink Cluster
+
+The power of the zoomer relies on the distributed processing coming with Apache Flink. To execute the 
+zoomer on an Apache Flink cluster, you have to follow three easy steps:
+
+1. set the Flink dependencies in the `pom.xml` to scope `provided` by changing the property from `<flink.scope>compile</flink.scope>` to `<flink.scope>provided</flink.scope>`
+2. run `mvn clean package` to build the project and create the file `target/graph-stream-grouping-0.1-SNAPSHOT.jar`
+3. on the running flink cluster, deploy your job (e.g. the `RandomGeneratorExample`) via 
+`bin/flink run -c edu.dbsleipzig.stream.grouping.application.RandomGeneratorExample target/graph-stream-grouping-0.1-SNAPSHOT.jar 10 1000` (10s tumbling window with 1000 elements/sec random input)
+
+## Details
+
+### Windowing
+*Graph Stream Zoomer* groups the graph using a windowing approach. The user can specify the size of the
+window by a `WindowConfig`. Currently, there are just tumbling windows supported, but sliding windows are
+planned for the near future.
+
+Example window definition for a 10 seconds tumbling window:
+
+`groupingBuilder.setWindowSize(10, WindowConfig.TimeUnit.SECONDS);`
+
+### Grouping Keys
+Vertices as well as edges will be grouped by common characteristics, which we call grouping keys. These
+characteristics can be zero, one or multiple of the following:
+* Label - groups all vertices/edges sharing the same type label
+* Property value (by name) - groups all vertices/edges that contain a property with the specified name and
+  an equal value. All vertices/edges _without_ a property of this name are grouped as one group. The super
+  vertex or super edge (the resulting group representative) contains the property and (1) the respective
+  value or (2) null, for the group that do not have this property
+* Time - groups all vertices/edges with a timestamp in the same window -> see _Windowing_ above
+* User-defined grouping key - tbd.
+
+### Aggregate functions
+Vertices and edges are grouped according to the selected grouping keys. The content of all vertices/edges
+that are grouped together can be used to calculate aggregates that will be part of the super vertex /
+super edge (the resulting group representative).
+* Count - just counts the number of elements that were merged to a group and stores them in a new property
+  with name `count`
+* MinProperty - calculates the minimum value of a given property and stores it to a new property called
+  `min_{name}`. Just works with numerical property values.
+* MaxProperty - calculates the maximum value of a given property and stores it to a new property called
+  `max_{name}`. Just works with numerical property values.
+* AvgProperty - calculates the average value of a given property and stores it to a new property called
+  `avg_{name}`. Just works with numerical property values.
+* User-defined aggregate function - tbd.
+
+## Graph Stream Data Model
+The graph stream data model of *Graph Stream Zoomer* is defined as follows.
+
+`DataStream<StreamTriple>` -> the Flink representation of a graph stream
+
+`StreamTriple`
+* `StreamVertex`
+* `StreamEdge`
+* `StreamVertex`
+
+`StreamVertex`
+* `id (String)`
+* `label (String)`
+* `properties (Properties)`
+* `event_time (Timestamp)`
+
+`StreamEdge`
+* `id (String)`
+* `label (String)`
+* `properties (Properties)`
+* `source_id (String)`
+* `target_id (String)`
+* `event_time (Timestamp)`
 
 ## Credits
 This project has its base in two master thesis. It contains main ideas and code fragments from E. Saalmann