No known trained model with model_id – How to solve this Elasticsearch error

Opster Team

July-20, Version: 1.7-8.0

Before you begin reading this guide, we recommend you try running the Elasticsearch Check-Up which can resolve issues that cause many errors.

This guide will help you check for common problems that cause the log ” No known trained model with model_id ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.

Advanced users might want to skip right to the common problems section in each concept or try running the Check-Up to analyze Elasticsearch configuration and help resolve this error.

Log Context

Log “No known trained model with model_id [{}]”classname  is ExceptionsHelper.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :

public static ResourceAlreadyExistsException dataFrameAnalyticsAlreadyExists(String id) {
 return new ResourceAlreadyExistsException("A data frame analytics with id [{}] already exists"; id);
 } 
 public static ResourceNotFoundException missingTrainedModel(String modelId) {
 return new ResourceNotFoundException("No known trained model with model_id [{}]"; modelId);
 } 
 public static ElasticsearchException serverError(String msg) {
 return new ElasticsearchException(msg);
 }

 

Try AutoOps to detect and fix issues in your cluster:

Overview

A plugin is used to enhance the core functionalities of Elasticsearch. Elasticsearch provides some core plugins as a part of their release installation. In addition to those core plugins, it is possible to write your own custom plugins as well. There are several community plugins available on GitHub for various use cases.

Examples

Get all of the instructions for the plugin:

sudo bin/elasticsearch-plugin -h

Installing the S3 plugin for storing Elasticsearch snapshots on S3:

sudo bin/elasticsearch-plugin install repository-s3

Removing a plugin:

sudo bin/elasticsearch-plugin remove repository-s3

Installing a plugin using the file’s path:

sudo bin/elasticsearch-plugin install file:///path/to/plugin.zip

Notes and good things to know

  • Plugins are installed and removed using the elasticsearch-plugin script, which ships as a part of the Elasticsearch installation and can be found inside the bin/ directory of the Elasticsearch installation path.
  • A plugin has to be installed on every node of the cluster and each of the nodes has to be restarted to make the plugin visible.
  • You can also download the plugin manually and then install it using the elasticsearch-plugin install command, providing the file name/path of the plugin’s source file.
  • When a plugin is removed, you will need to restart every Elasticsearch node in order to complete the removal process.

Common issues

  • Managing permission issues during and after plugin installation is the most common problem. If Elasticsearch was installed using the DEB or RPM packages then the plugin has to be installed using the root user. Otherwise you can install the plugin as the user that owns all of the Elasticsearch files.
  • In the case of DEB or RPM package installation, it is important to check the permissions of the plugins directory after you install it. You can update the permission if it has been modified using the following command:
chown -R elasticsearch:elasticsearch path_to_plugin_directory 
  • If your Elasticsearch nodes are running in a private subnet without internet access, you cannot install a plugin directly. In this case, you can simply download the plugins and copy the files inside the plugins directory of the Elasticsearch installation path on every node. The node has to be restarted in this case as well.

Log Context

Log “No known trained model with model_id [{}]”classname  is ExceptionsHelper.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :

public static ResourceAlreadyExistsException dataFrameAnalyticsAlreadyExists(String id) {
 return new ResourceAlreadyExistsException("A data frame analytics with id [{}] already exists"; id);
 } 
 public static ResourceNotFoundException missingTrainedModel(String modelId) {
 return new ResourceNotFoundException("No known trained model with model_id [{}]"; modelId);
 } 
 public static ElasticsearchException serverError(String msg) {
 return new ElasticsearchException(msg);
 }

 

Try AutoOps to detect and fix issues in your cluster:

Analyze Your Cluster

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