Another approach is multi_match with wildcard field names: https://www.elastic.co/guide/en/elasticsearch/guide/current/multi-match-query.html#_using_wildcards_in_field_names
Something like this, I think:
"query": {
"nested": {
"path": "author",
"query": {
"multi_match": {
"query": "doe",
"fields": [
"author.*"
]
}
}
}
}
UPDATE: full sample provided
PUT /books
{
"mappings": {
"paper": {
"properties": {
"author": {
"type": "nested",
"properties": {
"name": {
"type": "string"
},
"alias": {
"type": "string"
}
}
}
}
}
}
}
POST /books/paper/_bulk
{"index":{"_id":1}}
{"author":[{"name":"john doe","alias":"doe"},{"name":"mark twain","alias":"twain"}]}
{"index":{"_id":2}}
{"author":[{"name":"mark doe","alias":"john"}]}
{"index":{"_id":3}}
{"author":[{"name":"whatever","alias":"whatever"}]}
GET /books/paper/_search
{
"query": {
"nested": {
"path": "author",
"query": {
"multi_match": {
"query": "john",
"fields": [
"author.*"
]
}
}
}
}
}
Result is:
"hits": {
"total": 2,
"max_score": 0.5906161,
"hits": [
{
"_index": "books",
"_type": "paper",
"_id": "2",
"_score": 0.5906161,
"_source": {
"author": [
{
"name": "mark doe",
"alias": "john"
}
]
}
},
{
"_index": "books",
"_type": "paper",
"_id": "1",
"_score": 0.5882852,
"_source": {
"author": [
{
"name": "john doe",
"alias": "doe"
},
{
"name": "mark twain",
"alias": "twain"
}
]
}
}
]
}