Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

update algorithm #1049

Merged
merged 1 commit into from
Jan 18, 2022
Merged

update algorithm #1049

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
89 changes: 49 additions & 40 deletions docs-2.0/nebula-algorithm.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,18 @@

[Nebula Algorithm](https://github.com/vesoft-inc/nebula-algorithm) (Algorithm) is a Spark application based on [GraphX](https://spark.apache.org/graphx/). It uses a complete algorithm tool to perform graph computing on the data in the Nebula Graph database by submitting a Spark task. You can also programmatically use the algorithm under the lib repository to perform graph computing on DataFrame.

## Version compatibility

The correspondence between the Nebula Algorithm release and the Nebula Graph core release is as follows.

|Algorithm client|Nebula Graph|
|:---|:---|
|3.0-SNAPSHOT | nightly |
|{{algorithm.release}}| 2.6.0、2.6.1 |
| 2.6.0 | 2.6.0、2.6.1 |
| 2.5.0 | 2.5.0、2.5.1 |
| 2.1.0 | 2.0.0、2.0.1 |

## Prerequisites

Before using the Nebula Algorithm, users need to confirm the following information:
Expand All @@ -22,6 +34,27 @@ Before using the Nebula Algorithm, users need to confirm the following informati

- Graph computing outputs vertex datasets, and the algorithm results are stored in DataFrames as the properties of vertices. You can do further operations such as statistics and filtering according to your business requirements.

- When writing the algorithm results into the Nebula Graph, make sure that the Tag in the corresponding graph space has properties corresponding to the algorithm result name. The corresponding properties of each algorithm are as follows.

| Algorithm | Properties name |Properties type|
|:------------------------:|:-----------------------:|:-----------:|
| pagerank | pagerank |double/string|
| louvain | louvain | int/string |
| kcore | kcore | int/string |
| labelpropagation | lpa | int/string |
| connectedcomponent | cc | int/string |
|stronglyconnectedcomponent| scc | int/string |
| betweenness | betweenness |double/string|
| shortestpath | shortestpath | string |
| degreestatic |degree,inDegree,outDegree| int/string |
| trianglecount | trianglecount | int/string |
| clusteringcoefficient | clustercoefficient |double/string|
| closeness | closeness |double/string|
| hanp | hanp | int/string |
| bfs | bfs | string |
| jaccard | jaccard | string |
| node2vec | node2vec | string |

## Supported algorithms

The graph computing algorithms supported by Nebula Algorithm are as follows.
Expand All @@ -32,14 +65,19 @@ The graph computing algorithms supported by Nebula Algorithm are as follows.
| Louvain | Community discovery | Community mining, hierarchical clustering|
| KCore | K core | Community discovery, financial risk control|
| LabelPropagation | Label propagation | Information spreading, advertising, and community discovery|
| Hanp |Label propagation advanced |Community discovery, recommendation system |
| ConnectedComponent | Connected component | Community discovery, island discovery|
| StronglyConnectedComponent |Strongly connected component | Community discovery |
| ShortestPath |The shortest path | Path planning, network planning |
| TriangleCount |Triangle counting | Network structure analysis|
| GraphTriangleCount | Graph triangle counting | Network structure and tightness analysis|
| GraphTriangleCount | Graph triangle counting | Network structure and tightness analysis|
| BetweennessCentrality | Intermediate centrality | Key node mining, node influence computing |
| Closeness | Closeness centrality |Key node mining, node influence computing|
| DegreeStatic |Degree of statistical | Graph structure analysis|
| ClusteringCoefficient | Recommendation system, telecom fraud analysis|
| ClusteringCoefficient |Aggregation coefficient| Recommendation system, telecom fraud analysis|
| Jaccard | Jaccard similarity | Similarity computing, recommendation system|
| BFS | Breadth-First Search| Sequence traversal, shortest path planning|
| Node2Vec | - | Graph classification |

## Implementation methods

Expand Down Expand Up @@ -75,11 +113,11 @@ For detailed implementation methods, see [Scala file](https://github.com/vesoft-
$ mvn clean package -Dgpg.skip -Dmaven.javadoc.skip=true -Dmaven.test.skip=true
```

After the compilation, a similar file `nebula-algorithm-{{algorithm.release}}.jar` is generated in the directory `nebula-algorithm/target`.
After the compilation, a similar file `nebula-algorithm-3.x-SNAPSHOT.jar` is generated in the directory `nebula-algorithm/target`.

### Download maven from the remote repository

[Download address](https://repo1.maven.org/maven2/com/vesoft/nebula-algorithm/{{algorithm.release}}/)
[Download address](https://repo1.maven.org/maven2/com/vesoft/nebula-algorithm/)

## How to use

Expand Down Expand Up @@ -208,15 +246,16 @@ The `lib` repository provides 10 common graph algorithms.
algorithm: {
# The algorithm to execute. Optional values are pagerank, louvain, connectedcomponent,
# labelpropagation, shortestpaths, degreestatic, kcore,
# stronglyconnectedcomponent, trianglecount, betweenness,
# The algorithm to execute. Optional values are as follow:
# pagerank, louvain, connectedcomponent, labelpropagation, shortestpaths,
# degreestatic, kcore, stronglyconnectedcomponent, trianglecount ,
# betweenness, graphtriangleCount.
executeAlgo: pagerank
# PageRank
pagerank: {
maxIter: 10
resetProb: 0.15 # The default value is 0.15
resetProb: 0.15
}
# Louvain
Expand All @@ -226,38 +265,8 @@ The `lib` repository provides 10 common graph algorithms.
tol: 0.5
}
# ConnectedComponent/StronglyConnectedComponent
connectedcomponent: {
maxIter: 20
}
# LabelPropagation
labelpropagation: {
maxIter: 20
}
# ShortestPath
shortestpaths: {
# several vertices to compute the shortest path to all vertices.
landmarks: "1"
}
# DegreeStatic
degreestatic: {}
# KCore
kcore:{
maxIter:10
degree:1
}
# ...
# TriangleCount
trianglecount:{}
# BetweennessCentrality
betweenness:{
maxIter:5
}
}
}
```
Expand All @@ -271,5 +280,5 @@ The `lib` repository provides 10 common graph algorithms.
Example:

```bash
${SPARK_HOME}/bin/spark-submit --master "local" --class com.vesoft.nebula.algorithm.Main /root/nebula-algorithm/target/nebula-algorithm-{{algorithm.release}}.jar -p /root/nebula-algorithm/src/main/resources/application.conf
${SPARK_HOME}/bin/spark-submit --master "local" --class com.vesoft.nebula.algorithm.Main /root/nebula-algorithm/target/nebula-algorithm-3.0-SNAPSHOT.jar -p /root/nebula-algorithm/src/main/resources/application.conf
```
4 changes: 2 additions & 2 deletions mkdocs.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -69,8 +69,8 @@ extra:
release: 2.6.0
branch: v2.6.0
algorithm:
release: 2.5.1
branch: master
release: 2.6.2
branch: v2.6
sparkconnector:
release: 2.6.1
branch: v2.6
Expand Down