Briefly, this error occurs when Elasticsearch’s machine learning feature fails to load a model definition due to issues like incorrect model ID, insufficient memory, or corrupted model definition. To resolve this, ensure the model ID is correct and the model definition is not corrupted. If the issue persists, check if there’s enough memory allocated for machine learning jobs. Increasing the memory limit or reducing the size of the model may also help. Lastly, restarting the Elasticsearch node can sometimes resolve such issues.
This guide will help you check for common problems that cause the log ” [” + modelId + “] failed to load model definition ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.
Log Context
Log “[” + modelId + “] failed to load model definition” classname is ModelLoadingService.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
handleLoadSuccess(modelId; consumer; trainedModelConfig; inferenceDefinition);
}; failure -> {
// We failed to get the definition; remove the initial estimation.
trainedModelCircuitBreaker.addWithoutBreaking(-trainedModelConfig.getModelSize());
logger.warn(() -> "[" + modelId + "] failed to load model definition"; failure);
handleLoadFailure(modelId; failure);
}));
}; failure -> {
logger.warn(() -> "[" + modelId + "] failed to load model configuration"; failure);
handleLoadFailure(modelId; failure);
