I have an index with the following mapping:
{
"my_index": {
"mappings": {
"properties": {
"teacher_id": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"school_id": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"name": {
"type": "text"
},
"height": {
"type": "text"
},
"family_name": {
"type": "text"
},
"studentID": {
"type": "keyword"
},
"performance_text": {
"type": "text",
"fields": {
"highlight": {
"type": "text",
"store": true,
"term_vector": "with_positions_offsets"
},
"stemmed": {
"type": "text",
"analyzer": "snowball",
"fielddata": true
}
}
},
"_class": {
"type": "keyword",
"index": false,
"doc_values": false
}
}
}
}
}
The performance_text field contains large texts. The search will always be on the performance_text field. I want the elastic search to be able to first anaylize the language of the text and then perform stemming dependent on the language of the text. Therefore, I need a multilingual analyzer with stemming. The current snowball analyzer is not able to stem non-english words. How can I update my index mapping to be able to achieve this?