2.1 节点的度、入度和出度操作 graph.degrees graph.inDegrees graph.outDegrees 2.2 过滤节点和边形成新的图 #抽取原图中有顶点编号小于5000的点发出的边组成的图 g1=graph.filterEdges(func.expr('int(src)')<5000) #抽取原图中顶点编号小于5000的所有的点组成的图 g2=graph.filterVertices(func.expr('int(...
graph.degrees.show() graph.inDegrees.show() graph.outDegrees.show() 1. 2. 3. 4. 5. 6. 7. 8. 3)依据点、边、出入度的子图筛选 graph.vertices().filter("age > 30").show() graph.edges.filter("type == friends").show() graph.inDegrees.filter("inDegree >= 2").show() 1. 2. ...
为了创建图数据结构并进行分析,可以简化流程,直接读取相关文件并进行处理。 # 计算每个节点的入度和出度in_degrees = graph.inDegrees out_degrees = graph.outDegrees# 打印节点的入度和出度in_degrees.show() out_degrees.show() 查找具有最大入度和出度的节点: # 找到具有最大入度的节点max_in_degree = in_...
.inDegrees.collectres5: Array[(org.apache.spark.graphx.VertexId, Int)] = Array((4,2), (3,1), (5,1), (2,2))// 出度scala> graph.outDegrees.collectres6: Array[(org.apache.spark.graphx.VertexId, Int)] = Array((1,2), (3,3), (2,1))// 点边关系scala> graph.triplets.col...
graph-tool提供了基于数组的接口,比如get_vertices(), get_edges(), get_out_edges(), get_in_edges(), get_all_edges(), get_out_neighbors(), get_in_neighbors(), get_all_neighbors(), get_out_degrees(), get_in_degrees() and get_total_degrees() ...
degrees既包括inDegrees和outDegrees之和。 2,图的视图 edges和vertices必须包括属性,如果没有,一般给每个顶点和边填充一个1作为属性。 可以从triplets中同时获取边的属性,以及与之关联的顶点属性。 3,图的缓存和分区 如果图要多次被使用,应当使用persist缓存进行。如果确认图不再用到,推荐使用unpersist清理缓存以减轻...
# Calculate the inDeg (flights into the airport) and outDeg (flights leaving the airport)inDeg=tripGraph.inDegrees outDeg=tripGraph.outDegrees# Calculate the degreeRatio (inDeg/outDeg)degreeRatio=inDeg.join(outDeg,inDeg.id==outDeg.id).drop(outDeg.id).selectExpr("id","double(inDegree)...
LongValue>>inDegrees()// get a DataSet of <vertex ID, out-degree> pairs for all verticesDataSet<Tuple2<K,LongValue>>outDegrees()// get a DataSet of <vertex ID, degree> pairs for all vertices, where degree is the sum of in- and out- degreesDataSet<Tuple2<K,LongValue>>getDegrees(...
However, this information is useless if it has been unnaturally skewed by bots. Fortunately, graph analytics can provide an excellent means for identifying and filtering out bots. In a real-world use case, the Oracle team used Oracle Marketing Cloud to evaluate social media advertising and tractio...
(sc, "data/social_network.txt");// 计算节点的度VertexRDD<Object> degrees = graph.degrees();// 找出度最大的节点Tuple2<Object, Object> maxDegree = degrees.max(new DegreeComparator());// 输出结果System.out.println("节点 " + maxDegree._1() + " 的度最大,为 " + maxDegree._2());...