How to build simple terms query for nested object? - elasticsearch

Question

I have index like this:
PUT job_offers
{
"mappings": {
"properties": {
"location": {
"properties": {
"slug": {
"type": "keyword"
},
"name": {
"type": "text"
}
},
"type": "nested"
},
"experience": {
"properties": {
"slug": {
"type": "keyword"
},
"name": {
"type": "text"
}
},
"type": "nested"
}
}
}
}
I insert this object:
POST job_offers/_doc
{
"title": "Junior Ruby on Rails Developer",
"location": [
{
"slug": "new-york",
"name": "New York"
},
{
"slug": "atlanta",
"name": "Atlanta"
},
{
"slug": "remote",
"name": "Remote"
}
],
"experience": [
{
"slug": "junior",
"name": "Junior"
}
]
}
This query returns 0 documents.
GET job_offers/_search
{
"query": {
"terms": {
"location.slug": [
"remote",
"new-york"
]
}
}
}
Can you explain me why? I thought it should return documents where location.slug is remote or new-york.

Answer 1

Nested- Query have a different syntax
GET job_offers/_search
{
"query": {
"nested": {
"path": "location",
"query": {
"terms": {
"location.slug": ["remote","new-york"]
}
}
}
}
}
Result:
"hits" : [
{
"_index" : "job_offers",
"_type" : "_doc",
"_id" : "wWjoXnEBs0rCGpYsvUf4",
"_score" : 1.0,
"_source" : {
"title" : "Junior Ruby on Rails Developer",
"location" : [
{
"slug" : "new-york",
"name" : "New York"
},
{
"slug" : "atlanta",
"name" : "Atlanta"
},
{
"slug" : "remote",
"name" : "Remote"
}
],
"experience" : [
{
"slug" : "junior",
"name" : "Junior"
}
]
}
}
]
It will return entire document where location.slug matches "remote" or "new-york". If you want to get matched nested document , you need to use inner_hits
GET job_offers/_search
{
"query": {
"nested": {
"path": "location",
"query": {
"terms": {
"location.slug": ["remote","new-york"]
}
},
"inner_hits": {} --> note
}
}
}
Result:
"hits" : [
{
"_index" : "job_offers",
"_type" : "_doc",
"_id" : "wWjoXnEBs0rCGpYsvUf4",
"_score" : 1.0,
"_source" : {
"title" : "Junior Ruby on Rails Developer",
"location" : [
{
"slug" : "new-york",
"name" : "New York"
},
{
"slug" : "atlanta",
"name" : "Atlanta"
},
{
"slug" : "remote",
"name" : "Remote"
}
],
"experience" : [
{
"slug" : "junior",
"name" : "Junior"
}
]
},
"inner_hits" : { --> will give matched nested object
"location" : {
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "job_offers",
"_type" : "_doc",
"_id" : "wWjoXnEBs0rCGpYsvUf4",
"_nested" : {
"field" : "location",
"offset" : 0
},
"_score" : 1.0,
"_source" : {
"slug" : "new-york",
"name" : "New York"
}
},
{
"_index" : "job_offers",
"_type" : "_doc",
"_id" : "wWjoXnEBs0rCGpYsvUf4",
"_nested" : {
"field" : "location",
"offset" : 2
},
"_score" : 1.0,
"_source" : {
"slug" : "remote",
"name" : "Remote"
}
}
]
}
}
}
}
]
Also I see that you are using two fields for same data with different types. if data is same in both fields(name and slug) and only data type is different, you can use fields for that
It is often useful to index the same field in different ways for
different purposes. This is the purpose of multi-fields. For instance,
a string field could be mapped as a text field for full-text search,
and as a keyword field for sorting or aggregations:
In that case your mapping will become below
PUT job_offers
{
"mappings": {
"properties": {
"location": {
"properties": {
"name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
},
"type": "nested"
},
"experience": {
"properties": {
"name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
},
"type": "nested"
}
}
}
}