快速入门

本快速入门指南展示了如何开始使用 GraphFrames。完成本指南后，请继续阅读用户指南以了解更多关于 GraphFrames 支持的众多查询和算法。

以下示例展示了如何创建一个GraphFrame、查询它以及运行PageRank算法。

Python 应用程序接口

# Create a Vertex DataFrame with unique ID column "id"
v = spark.createDataFrame([
    ("a", "Alice", 34),
    ("b", "Bob", 36),
    ("c", "Charlie", 30),
], ["id", "name", "age"])

# Create an Edge DataFrame with "src" and "dst" columns
e = spark.createDataFrame([
    ("a", "b", "friend"),
    ("b", "c", "follow"),
    ("c", "b", "follow"),
], ["src", "dst", "relationship"])
# Create a GraphFrame
from graphframes import *

g = GraphFrame(v, e)

# Query: Get in-degree of each vertex.
g.inDegrees.show()

# Query: Count the number of "follow" connections in the graph.
g.edges.filter("relationship = 'follow'").count()

# Run PageRank algorithm, and show results.
results = g.pageRank(resetProbability=0.01, maxIter=20)
results.vertices.select("id", "pagerank").show()

Scala API

// import graphframes package

import org.graphframes._

// Create a Vertex DataFrame with unique ID column "id"
val v = spark.createDataFrame(List(
  ("a", "Alice", 34),
  ("b", "Bob", 36),
  ("c", "Charlie", 30)
)).toDF("id", "name", "age")

// Create an Edge DataFrame with "src" and "dst" columns
val e = spark.createDataFrame(List(
  ("a", "b", "friend"),
  ("b", "c", "follow"),
  ("c", "b", "follow")
)).toDF("src", "dst", "relationship")
// Create a GraphFrame

import org.graphframes.GraphFrame

val g = GraphFrame(v, e)

// Query: Get in-degree of each vertex.
g.inDegrees.show()

// Query: Count the number of "follow" connections in the graph.
g.edges.filter("relationship = 'follow'").count()

// Run PageRank algorithm, and show results.
val results = g.pageRank.resetProbability(0.01).maxIter(20).run()
results.vertices.select("id", "pagerank").show()

图算法

历史上，Apache Spark 曾内置一个名为 GraphX 的图处理工具，该工具基于 RDD（Spark 2.x 之前的处理方式）。GraphX 提供了一系列图算法，如 PageRank、LabelPropagation 等。在 Spark 4.0.x 中，GraphX 已被弃用，不推荐使用。相反，GraphFrames 使用 Spark 的 Dataset / Dataframe 来表示图。GraphFrames 也提供了一系列标准图算法，并且这一集合正在不断增长。对于在 GraphX 中实现但目前在 GraphFrames 中尚未原生支持的算法，该库还提供了一个转换方法（参见 用户指南）。下表展示了当前支持的算法：