Elastic Search - select DISTINCT value from aggregation result? - elasticsearch

Question

In Elastic Search I have an index named Menu. In Menu have an array of Shop. Something like this.
{
"menu_id": 1,
"name": 1,
"shops": [
{
"name": "A",
"shop_id: "A",
},
{
"name": "B",
"shop_id: "B",
}
]
}
{
"menu_id": 2,
"name": 2,
"shops": [
{
"name": "C",
"shop_id: "C",
}
]
}
{
"menu_id": 3,
"name": 3,
"shops": [
{
"name": "A",
"shop_id: "A",
}
]
}
{
"menu_id": 4,
"name": 4,
"shops": [
{
"name": "A",
"shop_id: "A",
},
{
"name": "C",
"shop_id: "C",
}
]
}
With my query I want to search Shop that have id "A" or "C". I want my result being like this.
{
"name": "A",
"shop_id: "A",
},
{
"name": "C",
"shop_id: "C",
}
I tried with this query.
{
"_source": "shops",
"query": {
"bool": {
"should": [
{
"match": {
"shops.id": "A"
}
},
{
"match": {
"shops.id": "C"
}
}
]
}
},
"aggs": {
"all_shops": {
"terms": {
"field": "shops.id.keyword",
"min_doc_count": 1
},
"aggs": {
"real_shop": {
"top_hits": {
"_source": [
"shops"
],
"size": 1
}
}
}
}
}
}
And this query.
{
"_source": "shops",
"query": {
"bool": {
"should": [
{
"match": {
"shops.id": "A"
}
},
{
"match": {
"shops.id": "C"
}
}
]
}
},
"aggs": {
"messages": {
"filters": {
"filters": [
{
"match": {
"shops.id": "A"
}
},
{
"match": {
"shops.id": "C"
}
}
]
},
"aggs": {
"real_shop": {
"top_hits": {
"_source": [
"shops"
],
"size": 1
}
}
}
}
}
}
I still got many "A", "B" and many "C".
How can I get just once "A" and once "C".
I cannot search it with Index Shop Because I want to use Information from Menu to search it.
Final Query is "Search shop with shop's name or menu's name with shop ids".

Answer 1

You need to make shops to be of the nested type, to query on each nested field object. You can use inner_hits to return documents that matched exactly with the query. Modify your index mapping as shown below
{
"mappings": {
"properties": {
"shops": {
"type": "nested"
}
}
}
}
Search Query:
{
"query": {
"nested": {
"path": "shops",
"query": {
"terms": {
"shops.shop_id.keyword": [
"A",
"C"
]
}
},
"inner_hits": {}
}
}
}
Search Result:
"hits": [
{
"_index": "66675093",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"menu_id": 1,
"name": 1,
"shops": [
{
"name": "A",
"shop_id": "A"
},
{
"name": "B",
"shop_id": "B"
}
]
},
"inner_hits": {
"shops": {
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "66675093",
"_type": "_doc",
"_id": "1",
"_nested": {
"field": "shops",
"offset": 0
},
"_score": 1.0,
"_source": {
"name": "A", // note this
"shop_id": "A"
}
}
]
}
}
}
},
{
"_index": "66675093",
"_type": "_doc",
"_id": "2",
"_score": 1.0,
"_source": {
"menu_id": 1,
"name": 1,
"shops": [
{
"name": "C",
"shop_id": "C"
}
]
},
"inner_hits": {
"shops": {
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "66675093",
"_type": "_doc",
"_id": "2",
"_nested": {
"field": "shops",
"offset": 0
},
"_score": 1.0,
"_source": {
"name": "C",
"shop_id": "C" // note this
}
}
]
}
}
}
}
]
UPDATE 1:
You can use filter aggregation along with nested aggregation, to achieve your use case. Try out this below query
{
"size": 0,
"aggs": {
"NAME": {
"nested": {
"path": "shops"
},
"aggs": {
"NAME": {
"filter": {
"terms": {
"shops.shop_id.keyword": ["A","C"]
}
},
"aggs": {
"NAME": {
"terms": {
"field": "shops.shop_id.keyword"
},
"aggs": {
"top_sales_hits": {
"top_hits": {
"size": 1
}
}
}
}
}
}
}
}
}
}
Search Result will be
"aggregations": {
"NAME": {
"doc_count": 6,
"NAME": {
"doc_count": 5,
"NAME": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "A",
"doc_count": 3,
"top_sales_hits": {
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "66675093",
"_type": "_doc",
"_id": "1",
"_nested": {
"field": "shops",
"offset": 0
},
"_score": 1.0,
"_source": {
"name": "A", // note this
"shop_id": "A"
}
}
]
}
}
},
{
"key": "C",
"doc_count": 2,
"top_sales_hits": {
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "66675093",
"_type": "_doc",
"_id": "2",
"_nested": {
"field": "shops",
"offset": 0
},
"_score": 1.0,
"_source": {
"name": "C", // note this
"shop_id": "C"
}
}
]
}
}
}
]
}
}
}
}