边聚类系数算法是指在无向图G中，计算每一条边周围的稠密度。本文为您介绍PAI-Studio提供的边聚类系数组件。

PAI-Studio支持通过可视化或PAI命令方式，配置边聚类系数组件的参数。

可视化方式

页签 参数 描述
IO/字段设置 起始节点 边表的起点所在列。
结束节点 边表的终点所在列。
执行调优 进程数量 作业并行执行的节点数。数字越大并行度越高，但是框架通讯开销会增大。
进程内存 单个作业可使用的最大内存量。系统默认为每个作业分配4096 MB内存，实际使用内存超过该值，会抛出OutOfMemory异常。
数据切分大小 数据切分的大小，默认为64。

PAI命令方式

PAI -name EdgeDensity
    -project algo_public
    -DinputEdgeTableName=EdgeDensity_func_test_edge
    -DfromVertexCol=flow_out_id
    -DtoVertexCol=flow_in_id
    -DoutputTableName=EdgeDensity_func_test_result;
参数 是否必选 描述 默认值
inputEdgeTableName 是 输入边表名。 无
inputEdgeTablePartitions 否 输入边表的分区。 全表读入
fromVertexCol 是 输入边表的起点所在列。 无
toVertexCol 是 输入边表的终点所在列。 无
outputTableName 是 输出表名。 无
outputTablePartitions 否 输出表的分区。 无
lifecycle 否 输出表的生命周期。 无
workerNum 否 作业并行执行的节点数。数字越大并行度越高，但是框架通讯开销会增大。 未设置
workerMem 否 单个作业可使用的最大内存量。系统默认为每个作业分配4096 MB内存，实际使用内存超过该值，会抛出OutOfMemory异常。 4096
splitSize 否 数据切分大小。 64

使用示例

  1. 生成训练数据。
    drop table if exists EdgeDensity_func_test_edge;
create table EdgeDensity_func_test_edge as
select * from
(
  select '1' as flow_out_id,'2' as flow_in_id from dual
  union all
  select '1' as flow_out_id,'3' as flow_in_id from dual
  union all
  select '1' as flow_out_id,'5' as flow_in_id from dual
  union all
  select '1' as flow_out_id,'7' as flow_in_id from dual
  union all
  select '2' as flow_out_id,'5' as flow_in_id from dual
  union all
  select '2' as flow_out_id,'4' as flow_in_id from dual
  union all
  select '2' as flow_out_id,'3' as flow_in_id from dual
  union all
  select '3' as flow_out_id,'5' as flow_in_id from dual
  union all
  select '3' as flow_out_id,'4' as flow_in_id from dual
  union all
  select '4' as flow_out_id,'5' as flow_in_id from dual
  union all
  select '4' as flow_out_id,'8' as flow_in_id from dual
  union all
  select '5' as flow_out_id,'6' as flow_in_id from dual
  union all
  select '5' as flow_out_id,'7' as flow_in_id from dual
  union all
  select '5' as flow_out_id,'8' as flow_in_id from dual
  union all
  select '7' as flow_out_id,'6' as flow_in_id from dual
  union all
  select '6' as flow_out_id,'8' as flow_in_id from dual
)tmp;
drop table if exists EdgeDensity_func_test_result;
create table EdgeDensity_func_test_result
(
  node1 string,
  node2 string,
  node1_edge_cnt bigint,
  node2_edge_cnt bigint,
  triangle_cnt bigint,
  density double
);
    对应的图结构如下图所示。 边聚类系数图结构
  2. 查看训练结果。
    1,2,4,4,2,0.5
2,3,4,4,3,0.75
2,5,4,7,3,0.75
3,1,4,4,2,0.5
3,4,4,4,2,0.5
4,2,4,4,2,0.5
4,5,4,7,3,0.75
5,1,7,4,3,0.75
5,3,7,4,3,0.75
5,6,7,3,2,0.66667
5,8,7,3,2,0.66667
6,7,3,3,1,0.33333
7,1,3,4,1,0.33333
7,5,3,7,2,0.66667
8,4,3,4,1,0.33333
8,6,3,3,1,0.33333