Hunspell Token Filter

Basic support for hunspell stemming. Hunspell dictionaries will be picked up from a dedicated hunspell directory on the filesystem (defaults to <path.conf>/hunspell). Each dictionary is expected to have its own directory named after its associated locale (language). This dictionary directory is expected to hold a single *.aff and one or more *.dic files (all of which will automatically be picked up). For example, assuming the default hunspell location is used, the following directory layout will define the en_US dictionary:

- conf
    |-- hunspell
    |    |-- en_US
    |    |    |-- en_US.dic
    |    |    |-- en_US.aff

The location of the hunspell directory can be configured using the indices.analysis.hunspell.dictionary.location settings in elasticsearch.yml.

Each dictionary can be configured with one setting:

This setting can be configured globally in elasticsearch.yml using

or for specific dictionaries:

It is also possible to add settings.yml file under the dictionary directory which holds these settings (this will override any other settings defined in the elasticsearch.yml).

One can use the hunspell stem filter by configuring it the analysis settings:

{
    "analysis" : {
        "analyzer" : {
            "en" : {
                "tokenizer" : "standard",
                "filter" : [ "lowercase", "en_US" ]
            }
        },
        "filter" : {
            "en_US" : {
                "type" : "hunspell",
                "locale" : "en_US",
                "dedup" : true
            }
        }
    }
}

The hunspell token filter accepts four options:

By default, the configured (indices.analysis.hunspell.dictionary.location) or default Hunspell directory (config/hunspell/) is checked for dictionaries when the node starts up, and any dictionaries are automatically loaded.

Dictionary loading can be deferred until they are actually used by setting indices.analysis.hunspell.dictionary.lazy to `true`in the config file.

Hunspell is a spell checker and morphological analyzer designed for languages with rich morphology and complex word compounding and character encoding.