How to match "prefix" and not whole string in elasticsearch? - elasticsearch

Question

I have indexed documents, each with a field: "CodeName" that has values like the following:
document 1 has CodeName: "AAA01"
document 2 has CodeName: "AAA02"
document 3 has CodeName: "AAA03"
document 4 has CodeName: "BBB02"
When I try to use a match query on field:
query: {
"match": {
"CodeName": "AAA"
}
}
I expect to get results for "AAA01" and "AAA02", but instead, I am getting an empty array. When I pass in "AAA01" (I type in the whole thing), I get a result. How do I make it such that it matches more generically? I tried using "prefix" instead of "match" and am getting the same problem.
The mapping for "CodeName" is a "type": "string".

Answer 1

I expect to get results for "AAA01" and "AAA02"
This is not what Elastic Search expects. ES breaks your string into tokens using a tokenizer that you specify. If you didn't specify any tokenizer/analyzer, the default standard tokenizer splits words on spaces and hyphens etc. In your case, the tokens are stored as "AAA01", "AAA02" and so on. There is no such term as "AAA", and hence you don't get any results back.
To fix this, you can use match_phrase_prefix query or set the type of match query to be phrase_prefix . Try this code:
"query": {
"match_phrase_prefix": {
"CodeName": "AAA"
}
}
OR
"query": {
"match": {
"CodeName": {
"query": "AAA",
"type": "phrase_prefix"
}
}
}
Here is the documentation: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-match-query.html. Also pay attention to the max_expansions parameter, as this query can be slow sometimes depending upon your data.
Note that for this technique, you should go with default mapping. You don't not to use nGram.

Answer 2

As far as I know first of all you sould index your data using a tokenizer of type nGram.
You can check detailes in documentation
COMMENT RELATED:
I'm familiar with symfony-way of using elasticsearch and we are using it like this:
indexes:
search:
client: default
settings:
index:
analysis:
custom_index_analyzer:
type: custom
tokenizer: nGram
filter: [lowercase, kstem]
tokenizer:
nGram:
type: nGram
min_gram: 2
max_gram: 20
types:
skill:
mappings:
skill.name:
search_analyzer: custom_index_analyzer
index_analyzer: custom_index_analyzer
type: string
boost: 1