ElasticSearch: how to search for %like% values in a field - elasticsearch

Question

I have a search query (in Postman/Chrome) that returns a list of companies, but I need to filter them out for a specific pattern. What filter do I use and how to do it?
I need to filter query result for company_id LIKE %50%
Her is what I run:
{
"fields": [
"company_id"
],
"query": {
"bool": {
"must": [
{"term": {"app.raw": "AAA"}},
{"wildcard": {"cat.raw": "RS"}}
],
"must_not": [],
"should": []
}
},
"from": 0,
"size": 5,
"sort": [],
"facets": {}
}
I get back something like:
"hits": [
{
...
"fields": {
"company_id": [
"745"
]
}
},
{
...
"fields": {
"company_id": [
"5056"
]
}
},
{
...
"fields": {
"company_id": [
"7765"
]
}
},
{
...
"fields": {
"company_id": [
"5044"
]
}
},
{
...
"fields": {
"company_id": [
"501"
]
}

Answer 1

First of all I am not fully sure what issue you are facing. You are not getting correct/expected result? You need to include the mapping you have used because the query will depend on it.
Wildcard searches are heavy. If you want to do partial matching search (equivalent of %like%)You can use ngram token filter in your analyzer and do term search. It will take care of matching partial string.
You can define an analyzer like
{
"settings":{
"analysis":{
"analyzer":{
"Like":{
"type":"custom",
"tokenizer":"keyword",
"filter":[ "lowercase", "ngram" ]
}
},
"filter":{
"ngram":{
"type":"ngram",
"min_gram":2,
"max_gram":15
}
}
}
}
}
And define in your mapping for cat.raw the analyzer "Like" defined above.
If you have used the ngram in your analyzer then You can change the query part to something simple term query like
"query": {
"bool": {
"must": [
{"term": {"app.raw": "AAA"}},
{"term": {"cat.raw": "RS"}}
],
"must_not": [],
"should": []
}
}
EDIT: updated answer based on comment
Ok now it is clear what you want to do.
One way is to define company_id As string in your mapping and use prefix query
"query": {
"bool": {
"must": [
{"term": {"app.raw": "AAA"}},
{"term": {"cat.raw": "RS"}},
{"prefix":{"company_id": "50"}}
],
"must_not": [],
"should": []
}
}
Another alternative could be to use edgengram in your analyzer for company_id and use term filter/query.
Note: for search in "cat.raw" it is still better to use the term query with analyzer having ngram instead of the wildcard query.