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Platform For AI:GMM prediction

Last Updated:Mar 11, 2026

Generate cluster predictions using a trained Gaussian Mixture Model (GMM).

Limits

Supported computing engines: MaxCompute, Flink, or DLC.

Configure component in Designer

Configure parameters in Designer.

Tab

Parameter

Description

Fields setting

Vector column name

Name of the vector column containing input data.

Reserved columns

Columns preserved in prediction output.

Parameters setting

Prediction result column name

Name of the column storing cluster assignments.

Prediction detail column name

Name of the column storing probability distributions across clusters.

Number of threads for the component

Number of threads used for prediction. Default: 1.

Execution tuning

Number of workers

Number of parallel workers. Used with Memory per worker (MB). Value ranges from 1 to 9999. See Estimate resource usage.

Memory per worker (MB)

Memory allocated to each worker. Ranges from 1024 MB to 65536 MB. See Estimate resource usage.

Estimate resource usage

Estimate resource requirements using the following guidelines.

  • Memory per node

    Allocate approximately 30 times the model size in memory per node.

    Example: For a 1 GB model, allocate 30 GB per node.

  • Number of nodes

    Adding nodes initially improves performance, but communication overhead eventually degrades speed. Stop adding nodes when performance decreases.