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Platform For AI:Counting Triangle

Last Updated:Mar 20, 2024

The Counting Triangle component is used to count the number of triangles in an undirected graph. This component can provide the vertices of all triangles.

Configure the component

Method 1: Configure the component on the pipeline page

You can add the Counting Triangle component on the pipeline page of Machine Learning Designer in the Platform for AI (PAI) console. The following table describes the parameters.

Tab

Parameter

Description

Fields Setting

Start Vertex

The start vertex column in the edge table.

End Vertex

The end vertex column in the edge table.

Parameters Setting

Largest Vertex Degree

If the vertex degree is larger than the value of this parameter, sampling is required. Default value: 500.

Tuning

Workers

The number of vertices for parallel job execution. The degree of parallelism and framework communication costs increase with the value of this parameter.

Memory Size per Worker (MB)

The maximum size of memory that a single job can use. Unit: MB. Default value: 4096.

If the size of used memory exceeds the value of this parameter, the OutOfMemory error is reported.

Data Split Size (MB)

The data split size. Unit: MB. Default value: 64.

Method 2: Configure the component by using PAI commands

You can configure the Counting Triangle component by using PAI commands. You can use the SQL Script component to run PAI commands. For more information, see Scenario 4: Execute PAI commands within the SQL script component in the "SQL Script" topic.

PAI -name TriangleCount
    -project algo_public
    -DinputEdgeTableName=TriangleCount_func_test_edge
    -DfromVertexCol=flow_out_id
    -DtoVertexCol=flow_in_id
    -DoutputTableName=TriangleCount_func_test_result;

Parameter

Required

Default value

Description

inputEdgeTableName

Yes

No default value

The name of the input edge table.

inputEdgeTablePartitions

No

Full table

The partitions in the input edge table.

fromVertexCol

Yes

No default value

The start vertex column in the input edge table.

toVertexCol

Yes

No default value

The end vertex column in the input edge table.

outputTableName

Yes

No default value

The name of the output table.

outputTablePartitions

No

No default value

The partitions in the output table.

lifecycle

No

No default value

The lifecycle of the output table.

maxEdgeCnt

No

500

If the vertex degree is greater than the value of this parameter, sampling is required.

workerNum

No

No default value

The number of vertices for parallel job execution. The degree of parallelism and framework communication costs increase with the value of this parameter.

workerMem

No

4096

The maximum size of memory that a single job can use. Unit: MB. Default value: 4096.

If the size of used memory exceeds the value of this parameter, the OutOfMemory error is reported.

splitSize

No

64

The data split size. Unit: MB.

Example

  1. Add the SQL Script component as a node to the canvas and execute the following SQL statements to generate training data.

    drop table if exists TriangleCount_func_test_edge;
    create table TriangleCount_func_test_edge as
    select * from
    (
      select '1' as flow_out_id,'2' as flow_in_id
      union all
      select '1' as flow_out_id,'3' as flow_in_id
      union all
      select '1' as flow_out_id,'4' as flow_in_id
      union all
      select '1' as flow_out_id,'5' as flow_in_id
      union all
      select '1' as flow_out_id,'6' as flow_in_id
      union all
      select '2' as flow_out_id,'3' as flow_in_id
      union all
      select '3' as flow_out_id,'4' as flow_in_id
      union all
      select '4' as flow_out_id,'5' as flow_in_id
      union all
      select '5' as flow_out_id,'6' as flow_in_id
      union all
      select '5' as flow_out_id,'7' as flow_in_id
      union all
      select '6' as flow_out_id,'7' as flow_in_id
    )tmp;
    drop table if exists TriangleCount_func_test_result;
    create table TriangleCount_func_test_result
    (
      node1 string,
      node2 string,
      node3 string
    );

    Data structure

    image

  2. Add the SQL Script component as a node to the canvas and run the following PAI commands to train the model.

    drop table if exists ${o1};
    PAI -name TriangleCount
        -project algo_public
        -DinputEdgeTableName=TriangleCount_func_test_edge
        -DfromVertexCol=flow_out_id
        -DtoVertexCol=flow_in_id
        -DoutputTableName=${o1};
  3. Right-click the SQL Script component and choose View Data > SQL Script Output to view the training results.

    | node1 | node2 | node3 |
    | ----- | ----- | ----- |
    | 1     | 2     | 3     |
    | 1     | 3     | 4     |
    | 1     | 4     | 5     |
    | 1     | 5     | 6     |
    | 5     | 6     | 7     |