The nested type is a specialised version of the object data type
that allows arrays of objects to be indexed in a way that they can be queried
independently of each other.
When ingesting key-value pairs with a large, arbitrary set of keys, you might consider modeling each key-value pair as its own nested document with key and value fields. Instead, consider using the flattened data type, which maps an entire object as a single field and allows for simple searches over its contents.
Nested documents and queries are typically expensive, so using the flattened data type for this use case is a better option.
Elasticsearch has no concept of inner objects. Therefore, it flattens object hierarchies into a simple list of field names and values. For instance, consider the following document:
response = client.index(
index: 'my-index-000001',
id: 1,
body: {
group: 'fans',
user: [
{
first: 'John',
last: 'Smith'
},
{
first: 'Alice',
last: 'White'
}
]
}
)
puts response
res, err := es.Index(
"my-index-000001",
strings.NewReader(`{
"group": "fans",
"user": [
{
"first": "John",
"last": "Smith"
},
{
"first": "Alice",
"last": "White"
}
]
}`),
es.Index.WithDocumentID("1"),
es.Index.WithPretty(),
)
fmt.Println(res, err)
PUT my-index-000001/_doc/1
{
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
The previous document would be transformed internally into a document that looks more like this:
{
"group" : "fans",
"user.first" : [ "alice", "john" ],
"user.last" : [ "smith", "white" ]
}
The user.first and user.last fields are flattened into multi-value fields,
and the association between alice and white is lost. This document would
incorrectly match a query for alice AND smith:
response = client.search(
index: 'my-index-000001',
body: {
query: {
bool: {
must: [
{
match: {
"user.first": 'Alice'
}
},
{
match: {
"user.last": 'Smith'
}
}
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithIndex("my-index-000001"),
es.Search.WithBody(strings.NewReader(`{
"query": {
"bool": {
"must": [
{
"match": {
"user.first": "Alice"
}
},
{
"match": {
"user.last": "Smith"
}
}
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
GET my-index-000001/_search
{
"query": {
"bool": {
"must": [
{ "match": { "user.first": "Alice" }},
{ "match": { "user.last": "Smith" }}
]
}
}
}
If you need to index arrays of objects and to maintain the independence of
each object in the array, use the nested data type instead of the
object data type.
Internally, nested objects index each object in
the array as a separate hidden document, meaning that each nested object can be
queried independently of the others with the nested query:
response = client.indices.create(
index: 'my-index-000001',
body: {
mappings: {
properties: {
user: {
type: 'nested'
}
}
}
}
)
puts response
response = client.indices.create(
index: 'my-index-000001',
id: 1,
body: {
group: 'fans',
user: [
{
first: 'John',
last: 'Smith'
},
{
first: 'Alice',
last: 'White'
}
]
}
)
puts response
response = client.indices.create(
index: 'my-index-000001',
body: {
query: {
nested: {
path: 'user',
query: {
bool: {
must: [
{
match: {
"user.first": 'Alice'
}
},
{
match: {
"user.last": 'Smith'
}
}
]
}
}
}
}
}
)
puts response
response = client.indices.create(
index: 'my-index-000001',
body: {
query: {
nested: {
path: 'user',
query: {
bool: {
must: [
{
match: {
"user.first": 'Alice'
}
},
{
match: {
"user.last": 'White'
}
}
]
}
},
inner_hits: {
highlight: {
fields: {
"user.first": {
}
}
}
}
}
}
}
)
puts response
{
res, err := es.Indices.Create(
"my-index-000001",
es.Indices.Create.WithBody(strings.NewReader(`{
"mappings": {
"properties": {
"user": {
"type": "nested"
}
}
}
}`)),
)
fmt.Println(res, err)
}
{
res, err := es.Index(
"my-index-000001",
strings.NewReader(`{
"group": "fans",
"user": [
{
"first": "John",
"last": "Smith"
},
{
"first": "Alice",
"last": "White"
}
]
}`),
es.Index.WithDocumentID("1"),
es.Index.WithPretty(),
)
fmt.Println(res, err)
}
{
res, err := es.Search(
es.Search.WithIndex("my-index-000001"),
es.Search.WithBody(strings.NewReader(`{
"query": {
"nested": {
"path": "user",
"query": {
"bool": {
"must": [
{
"match": {
"user.first": "Alice"
}
},
{
"match": {
"user.last": "Smith"
}
}
]
}
}
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
}
{
res, err := es.Search(
es.Search.WithIndex("my-index-000001"),
es.Search.WithBody(strings.NewReader(`{
"query": {
"nested": {
"path": "user",
"query": {
"bool": {
"must": [
{
"match": {
"user.first": "Alice"
}
},
{
"match": {
"user.last": "White"
}
}
]
}
},
"inner_hits": {
"highlight": {
"fields": {
"user.first": {}
}
}
}
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
}
PUT my-index-000001
{
"mappings": {
"properties": {
"user": {
"type": "nested"
}
}
}
}
PUT my-index-000001/_doc/1
{
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
GET my-index-000001/_search
{
"query": {
"nested": {
"path": "user",
"query": {
"bool": {
"must": [
{ "match": { "user.first": "Alice" }},
{ "match": { "user.last": "Smith" }}
]
}
}
}
}
}
GET my-index-000001/_search
{
"query": {
"nested": {
"path": "user",
"query": {
"bool": {
"must": [
{ "match": { "user.first": "Alice" }},
{ "match": { "user.last": "White" }}
]
}
},
"inner_hits": {
"highlight": {
"fields": {
"user.first": {}
}
}
}
}
}
}
Nested documents can be:
-
queried with the
nestedquery. -
analyzed with the
nestedandreverse_nestedaggregations. - sorted with nested sorting.
- retrieved and highlighted with nested inner hits.
Because nested documents are indexed as separate documents, they can only be
accessed within the scope of the nested query, the
nested/reverse_nested aggregations, or nested inner hits.
For instance, if a string field within a nested document has
index_options set to offsets to allow use of the postings
during the highlighting, these offsets will not be available during the main highlighting
phase. Instead, highlighting needs to be performed via
nested inner hits. The same consideration applies when loading
fields during a search through docvalue_fields or stored_fields.
The following parameters are accepted by nested fields:
-
dynamic -
(Optional, string)
Whether or not new
propertiesshould be added dynamically to an existing nested object. Acceptstrue(default),falseandstrict. -
properties -
(Optional, object)
The fields within the nested object, which can be of any
data type, including
nested. New properties may be added to an existing nested object. -
include_in_parent -
(Optional, Boolean)
If
true, all fields in the nested object are also added to the parent document as standard (flat) fields. Defaults tofalse. -
include_in_root -
(Optional, Boolean)
If
true, all fields in the nested object are also added to the root document as standard (flat) fields. Defaults tofalse.
Limits on nested mappings and objects
As described earlier, each nested object is indexed as a separate Lucene document.
Continuing with the previous example, if we indexed a single document containing 100 user objects,
then 101 Lucene documents would be created: one for the parent document, and one for each
nested object. Because of the expense associated with nested mappings, Elasticsearch puts
settings in place to guard against performance problems:
-
index.mapping.nested_fields.limit -
The maximum number of distinct
nestedmappings in an index. Thenestedtype should only be used in special cases, when arrays of objects need to be queried independently of each other. To safeguard against poorly designed mappings, this setting limits the number of uniquenestedtypes per index. Default is50.
In the previous example, the user mapping would count as only 1 towards this limit.
-
index.mapping.nested_objects.limit -
The maximum number of nested JSON objects that a single document can contain across all
nestedtypes. This limit helps to prevent out of memory errors when a document contains too many nested objects. Default is10000.
To illustrate how this setting works, consider adding another nested type called comments
to the previous example mapping. For each document, the combined number of user and comment
objects it contains must be below the limit.
See Settings to prevent mapping explosion regarding additional settings for preventing mappings explosion.