Welcome to Nebula Algorithm

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nebula-algorithm is a Spark Application based on GraphX with the following Algorithm provided for now:

You could submit the entire spark application or invoke algorithms in lib library to apply graph algorithms for DataFrame.

Get Nebula Algorithm

1. Build Nebula Algorithm

   $ git clone https://github.com/vesoft-inc/nebula-algorithm.git
   $ cd nebula-algorithm
   $ mvn clean package -Dgpg.skip -Dmaven.javadoc.skip=true -Dmaven.test.skip=true

   After the above buiding process, the target file nebula-algorithm-3.0-SNAPSHOT.jar will be placed under nebula-algorithm/target.

2. Download from Maven repo

   Alternatively, it could be downloaded from the following Maven repo:

   https://repo1.maven.org/maven2/com/vesoft/nebula-algorithm/

Use Nebula Algorithm

• Option 1: Submit nebula-algorithm package

  • Configuration

  Refer to the configuration example.

  • Submit Spark Application

  ${SPARK_HOME}/bin/spark-submit --master <mode> --class com.vesoft.nebula.algorithm.Main nebula-algorithm-3.0—SNAPSHOT.jar -p application.conf

• Option2: Call nebula-algorithm interface

  Now there are 10+ algorithms provided in lib from nebula-algorithm, which could be invoked in a programming fashion as below:

  • Add dependencies in pom.xml.

    <dependency>
     <groupId>com.vesoft</groupId>
     <artifactId>nebula-algorithm</artifactId>
     <version>3.0.0</version>
    </dependency>

  • Instantiate algorithm's config, below is an example for PageRank.

    
    import com.vesoft.nebula.algorithm.config.{Configs, PRConfig, SparkConfig}
    import org.apache.spark.sql.{DataFrame, SparkSession}

  val spark = SparkSession.builder().master("local").getOrCreate() val data = spark.read.option("header", true).csv("src/test/resources/edge.csv") val prConfig = new PRConfig(5, 1.0) val prResult = PageRankAlgo.apply(spark, data, prConfig, false)

  
  
  If your vertex ids are Strings, please set the algo config with encodeId = true. see [examples](https://github.com/vesoft-inc/nebula-algorithm/tree/master/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala)
  
  For examples of other algorithms, see [examples](https://github.com/vesoft-inc/nebula-algorithm/tree/master/example/src/main/scala/com/vesoft/nebula/algorithm)
  > Note: The first column of DataFrame in the application represents the source vertices, the second represents the target vertices and the third represents edges' weight.

Sink to NebulaGraph

If you want to write the algorithm execution result into NebulaGraph(sink: nebula), make sure there is corresponding property name in your tag defination.

Version Compatibility Matrix

Contribute

Nebula Algorithm is open source, you are more than welcomed to contribute in the following ways:

• Discuss in the community via the forum or raise issues here.
• Compose or improve our documents.
• Pull Request to help improve the code itself here.