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How to add support for more languages in Elastic Search Engines

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To add support for more languages in Elasticsearch, you need to install the relevant language analyzers and plugins. Elasticsearch provides built-in support for a variety of languages, but additional languages may require additional configuration. Here are the general steps to follow:

    1. Install Elasticsearch: Download and install Elasticsearch on your system. You can find the installation packages and instructions on the official Elasticsearch website.
    1. Install the relevant language plugin: Elasticsearch provides language-specific analyzers and tokenizers through plugins. Search for a plugin that supports the language you want to add. For example, if you want to add support for the French language, you can use the `analysis-icu` plugin, which includes French language support.

   To install a plugin, you can use the Elasticsearch plugin installation script. Run the following command, replacing `<plugin-name>` with the name of the plugin you want to install:


   bin/elasticsearch-plugin install <plugin-name>


   Note that you may need to restart Elasticsearch after installing the plugin for it to take effect.

    1. Configure the language analyzer: Once the plugin is installed, you need to configure the language analyzer for your Elasticsearch index. An analyzer defines how text is processed and tokenized during indexing and searching.

   You can define the analyzer settings when creating or updating your index. Here’s an example of creating an index with a French language analyzer:


PUT /my_index


“settings”: {

“analysis”: {

“analyzer”: {

“french_analyzer”: {

“tokenizer”: “standard”,

“filter”: [








“filter”: {

“french_stemmer”: {

“type”: “stemmer”,

“name”: “french”





“mappings”: {

“properties”: {

“my_field”: {

“type”: “text”,

“analyzer”: “french_analyzer”






In this example, the `french_analyzer` is defined with a tokenizer and a set of filters specific to the French language. The `my_field` property is mapped to use this analyzer.

    1. Reindex your data: If you have existing data in your Elasticsearch index, you may need to reindex it to apply the new language analyzer. You can use the Elasticsearch Reindex API or other tools like Logstash or Elasticsearch’s Ingest Node to accomplish this task.

   Reindexing involves creating a new index with the updated settings and mappings, and then copying the data from the old index to the new one using the appropriate analyzer.

    1. Test the language support: Once your index is configured with the language analyzer, you can test the language support by indexing and searching documents containing text in the desired language. Make sure to use the appropriate analyzer when querying the data.

By following these steps, you can add support for additional languages in Elasticsearch and take advantage of language-specific analyzers for indexing and searching text. Nexbrick provides Elasticsearch consulting services for your enterprises search requirements.

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