Briefly, this error occurs when Elasticsearch is unable to tokenize the input data for a search operation. This could be due to incorrect configuration of the analyzer or the input data not being compatible with the defined analyzer. To resolve this issue, you can check the analyzer configuration and ensure it’s correctly set up. Also, validate your input data to ensure it’s in the correct format. If the error persists, consider changing the analyzer or adjusting the input data to match the requirements of the current analyzer.
This guide will help you check for common problems that cause the log ” no valid tokenization to build result ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.
Log Context
Log “no valid tokenization to build result” class name is NerProcessor.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
} @Override
public InferenceResults processResult(TokenizationResult tokenization; PyTorchInferenceResult pyTorchResult) {
if (tokenization.isEmpty()) {
throw new ElasticsearchStatusException("no valid tokenization to build result"; RestStatus.INTERNAL_SERVER_ERROR);
}
// TODO - process all results in the batch // TODO It might be best to do the soft max after averaging scores for
// sub-tokens. If we had a word that is "elastic" which is tokenized to
[ratemypost]
