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analyzer
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- ILM: Manage the index lifecycle
- Tutorial: Customize built-in policies
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- Index management in Kibana
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- Definitions
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- Release notes
- Elasticsearch version 8.18.0
- Elasticsearch version 8.17.0
- Elasticsearch version 8.16.1
- Elasticsearch version 8.16.0
- Elasticsearch version 8.15.5
- Elasticsearch version 8.15.4
- Elasticsearch version 8.15.3
- Elasticsearch version 8.15.2
- Elasticsearch version 8.15.1
- Elasticsearch version 8.15.0
- Elasticsearch version 8.14.3
- Elasticsearch version 8.14.2
- Elasticsearch version 8.14.1
- Elasticsearch version 8.14.0
- Elasticsearch version 8.13.4
- Elasticsearch version 8.13.3
- Elasticsearch version 8.13.2
- Elasticsearch version 8.13.1
- Elasticsearch version 8.13.0
- Elasticsearch version 8.12.2
- Elasticsearch version 8.12.1
- Elasticsearch version 8.12.0
- Elasticsearch version 8.11.4
- Elasticsearch version 8.11.3
- Elasticsearch version 8.11.2
- Elasticsearch version 8.11.1
- Elasticsearch version 8.11.0
- Elasticsearch version 8.10.4
- Elasticsearch version 8.10.3
- Elasticsearch version 8.10.2
- Elasticsearch version 8.10.1
- Elasticsearch version 8.10.0
- Elasticsearch version 8.9.2
- Elasticsearch version 8.9.1
- Elasticsearch version 8.9.0
- Elasticsearch version 8.8.2
- Elasticsearch version 8.8.1
- Elasticsearch version 8.8.0
- Elasticsearch version 8.7.1
- Elasticsearch version 8.7.0
- Elasticsearch version 8.6.2
- Elasticsearch version 8.6.1
- Elasticsearch version 8.6.0
- Elasticsearch version 8.5.3
- Elasticsearch version 8.5.2
- Elasticsearch version 8.5.1
- Elasticsearch version 8.5.0
- Elasticsearch version 8.4.3
- Elasticsearch version 8.4.2
- Elasticsearch version 8.4.1
- Elasticsearch version 8.4.0
- Elasticsearch version 8.3.3
- Elasticsearch version 8.3.2
- Elasticsearch version 8.3.1
- Elasticsearch version 8.3.0
- Elasticsearch version 8.2.3
- Elasticsearch version 8.2.2
- Elasticsearch version 8.2.1
- Elasticsearch version 8.2.0
- Elasticsearch version 8.1.3
- Elasticsearch version 8.1.2
- Elasticsearch version 8.1.1
- Elasticsearch version 8.1.0
- Elasticsearch version 8.0.1
- Elasticsearch version 8.0.0
- Elasticsearch version 8.0.0-rc2
- Elasticsearch version 8.0.0-rc1
- Elasticsearch version 8.0.0-beta1
- Elasticsearch version 8.0.0-alpha2
- Elasticsearch version 8.0.0-alpha1
- Dependencies and versions
Retrieve selected fields from a search
editRetrieve selected fields from a search
editBy default, each hit in the search response includes the document
_source
, which is the entire JSON object that was
provided when indexing the document. There are two recommended methods to
retrieve selected fields from a search query:
-
Use the
fields
option to extract the values of fields present in the index mapping -
Use the
_source
option if you need to access the original data that was passed at index time
You can use both of these methods, though the fields
option is preferred
because it consults both the document data and index mappings. In some
instances, you might want to use other methods of
retrieving data.
The fields
option
editTo retrieve specific fields in the search response, use the fields
parameter.
Because it consults the index mappings, the fields
parameter provides several
advantages over referencing the _source
directly. Specifically, the fields
parameter:
- Returns each value in a standardized way that matches its mapping type
- Accepts multi-fields and field aliases
- Formats dates and spatial data types
- Retrieves runtime field values
- Returns fields calculated by a script at index time
- Returns fields from related indices using lookup runtime fields
Other mapping options are also respected, including
ignore_above
, ignore_malformed
, and
null_value
.
The fields
option returns values in the way that matches how Elasticsearch indexes
them. For standard fields, this means that the fields
option looks in
_source
to find the values, then parses and formats them using the mappings.
Selected fields that can’t be found in _source
are skipped.
Retrieve specific fields
editThe following search request uses the fields
parameter to retrieve values
for the user.id
field, all fields starting with http.response.
, and the
@timestamp
field.
Using object notation, you can pass a format
argument to
customize the format of returned date or geospatial values.
resp = client.search( index="my-index-000001", query={ "match": { "user.id": "kimchy" } }, fields=[ "user.id", "http.response.*", { "field": "@timestamp", "format": "epoch_millis" } ], source=False, ) print(resp)
response = client.search( index: 'my-index-000001', body: { query: { match: { 'user.id' => 'kimchy' } }, fields: [ 'user.id', 'http.response.*', { field: '@timestamp', format: 'epoch_millis' } ], _source: false } ) puts response
const response = await client.search({ index: "my-index-000001", query: { match: { "user.id": "kimchy", }, }, fields: [ "user.id", "http.response.*", { field: "@timestamp", format: "epoch_millis", }, ], _source: false, }); console.log(response);
POST my-index-000001/_search { "query": { "match": { "user.id": "kimchy" } }, "fields": [ "user.id", "http.response.*", { "field": "@timestamp", "format": "epoch_millis" } ], "_source": false }
Both full field names and wildcard patterns are accepted. |
|
Use the |
By default, document metadata fields like _id
or _index
are not
returned when the requested fields
option uses wildcard patterns like *
.
However, when explicitly requested using the field name, the _id
, _routing
,
_ignored
, _index
and _version
metadata fields can be retrieved.
Response always returns an array
editThe fields
response always returns an array of values for each field,
even when there is a single value in the _source
. This is because Elasticsearch has
no dedicated array type, and any field could contain multiple values. The
fields
parameter also does not guarantee that array values are returned in
a specific order. See the mapping documentation on arrays for more
background.
The response includes values as a flat list in the fields
section for each
hit. Because the fields
parameter doesn’t fetch entire objects, only leaf
fields are returned.
{ "hits" : { "total" : { "value" : 1, "relation" : "eq" }, "max_score" : 1.0, "hits" : [ { "_index" : "my-index-000001", "_id" : "0", "_score" : 1.0, "fields" : { "user.id" : [ "kimchy" ], "@timestamp" : [ "4098435132000" ], "http.response.bytes": [ 1070000 ], "http.response.status_code": [ 200 ] } } ] } }
Retrieve nested fields
editDetails
The fields
response for nested
fields is slightly different from that
of regular object fields. While leaf values inside regular object
fields are
returned as a flat list, values inside nested
fields are grouped to maintain the
independence of each object inside the original nested array.
For each entry inside a nested field array, values are again returned as a flat list
unless there are other nested
fields inside the parent nested object, in which case
the same procedure is repeated again for the deeper nested fields.
Given the following mapping where user
is a nested field, after indexing
the following document and retrieving all fields under the user
field:
resp = client.indices.create( index="my-index-000001", mappings={ "properties": { "group": { "type": "keyword" }, "user": { "type": "nested", "properties": { "first": { "type": "keyword" }, "last": { "type": "keyword" } } } } }, ) print(resp) resp1 = client.index( index="my-index-000001", id="1", refresh=True, document={ "group": "fans", "user": [ { "first": "John", "last": "Smith" }, { "first": "Alice", "last": "White" } ] }, ) print(resp1) resp2 = client.search( index="my-index-000001", fields=[ "*" ], source=False, ) print(resp2)
response = client.indices.create( index: 'my-index-000001', body: { mappings: { properties: { group: { type: 'keyword' }, user: { type: 'nested', properties: { first: { type: 'keyword' }, last: { type: 'keyword' } } } } } } ) puts response response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { group: 'fans', user: [ { first: 'John', last: 'Smith' }, { first: 'Alice', last: 'White' } ] } ) puts response response = client.search( index: 'my-index-000001', body: { fields: [ '*' ], _source: false } ) puts response
const response = await client.indices.create({ index: "my-index-000001", mappings: { properties: { group: { type: "keyword", }, user: { type: "nested", properties: { first: { type: "keyword", }, last: { type: "keyword", }, }, }, }, }, }); console.log(response); const response1 = await client.index({ index: "my-index-000001", id: 1, refresh: "true", document: { group: "fans", user: [ { first: "John", last: "Smith", }, { first: "Alice", last: "White", }, ], }, }); console.log(response1); const response2 = await client.search({ index: "my-index-000001", fields: ["*"], _source: false, }); console.log(response2);
PUT my-index-000001 { "mappings": { "properties": { "group" : { "type" : "keyword" }, "user": { "type": "nested", "properties": { "first" : { "type" : "keyword" }, "last" : { "type" : "keyword" } } } } } } PUT my-index-000001/_doc/1?refresh=true { "group" : "fans", "user" : [ { "first" : "John", "last" : "Smith" }, { "first" : "Alice", "last" : "White" } ] } POST my-index-000001/_search { "fields": ["*"], "_source": false }
The response will group first
and last
name instead of
returning them as a flat list.
{ "took": 2, "timed_out": false, "_shards": { "total": 1, "successful": 1, "skipped": 0, "failed": 0 }, "hits": { "total": { "value": 1, "relation": "eq" }, "max_score": 1.0, "hits": [{ "_index": "my-index-000001", "_id": "1", "_score": 1.0, "fields": { "group" : ["fans"], "user": [{ "first": ["John"], "last": ["Smith"] }, { "first": ["Alice"], "last": ["White"] } ] } }] } }
Nested fields will be grouped by their nested paths, no matter the pattern used
to retrieve them. For example, if you query only for the user.first
field from
the previous example:
resp = client.search( index="my-index-000001", fields=[ "user.first" ], source=False, ) print(resp)
response = client.search( index: 'my-index-000001', body: { fields: [ 'user.first' ], _source: false } ) puts response
const response = await client.search({ index: "my-index-000001", fields: ["user.first"], _source: false, }); console.log(response);
POST my-index-000001/_search { "fields": ["user.first"], "_source": false }
The response returns only the user’s first name, but still maintains the
structure of the nested user
array:
{ "took": 2, "timed_out": false, "_shards": { "total": 1, "successful": 1, "skipped": 0, "failed": 0 }, "hits": { "total": { "value": 1, "relation": "eq" }, "max_score": 1.0, "hits": [{ "_index": "my-index-000001", "_id": "1", "_score": 1.0, "fields": { "user": [{ "first": ["John"] }, { "first": ["Alice"] } ] } }] } }
However, when the fields
pattern targets the nested user
field directly, no
values will be returned because the pattern doesn’t match any leaf fields.
Retrieve unmapped fields
editDetails
By default, the fields
parameter returns only values of mapped fields.
However, Elasticsearch allows storing fields in _source
that are unmapped, such as
setting dynamic field mapping to false
or by using
an object field with enabled: false
. These options disable parsing and
indexing of the object content.
To retrieve unmapped fields in an object from _source
, use the
include_unmapped
option in the fields
section:
resp = client.indices.create( index="my-index-000001", mappings={ "enabled": False }, ) print(resp) resp1 = client.index( index="my-index-000001", id="1", refresh=True, document={ "user_id": "kimchy", "session_data": { "object": { "some_field": "some_value" } } }, ) print(resp1) resp2 = client.search( index="my-index-000001", fields=[ "user_id", { "field": "session_data.object.*", "include_unmapped": True } ], source=False, ) print(resp2)
response = client.indices.create( index: 'my-index-000001', body: { mappings: { enabled: false } } ) puts response response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { user_id: 'kimchy', session_data: { object: { some_field: 'some_value' } } } ) puts response response = client.search( index: 'my-index-000001', body: { fields: [ 'user_id', { field: 'session_data.object.*', include_unmapped: true } ], _source: false } ) puts response
const response = await client.indices.create({ index: "my-index-000001", mappings: { enabled: false, }, }); console.log(response); const response1 = await client.index({ index: "my-index-000001", id: 1, refresh: "true", document: { user_id: "kimchy", session_data: { object: { some_field: "some_value", }, }, }, }); console.log(response1); const response2 = await client.search({ index: "my-index-000001", fields: [ "user_id", { field: "session_data.object.*", include_unmapped: true, }, ], _source: false, }); console.log(response2);
PUT my-index-000001 { "mappings": { "enabled": false } } PUT my-index-000001/_doc/1?refresh=true { "user_id": "kimchy", "session_data": { "object": { "some_field": "some_value" } } } POST my-index-000001/_search { "fields": [ "user_id", { "field": "session_data.object.*", "include_unmapped" : true } ], "_source": false }
The response will contain field results under the session_data.object.*
path,
even if the fields are unmapped. The user_id
field is also unmapped, but it
won’t be included in the response because include_unmapped
isn’t set to
true
for that field pattern.
{ "took" : 2, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 1, "relation" : "eq" }, "max_score" : 1.0, "hits" : [ { "_index" : "my-index-000001", "_id" : "1", "_score" : 1.0, "fields" : { "session_data.object.some_field": [ "some_value" ] } } ] } }
Ignored field values
editDetails
The fields
section of the response only returns values that were valid when indexed.
If your search request asks for values from a field that ignored certain values
because they were malformed or too large these values are returned
separately in an ignored_field_values
section.
In this example we index a document that has a value which is ignored and not added to the index so is shown separately in search results:
resp = client.indices.create( index="my-index-000001", mappings={ "properties": { "my-small": { "type": "keyword", "ignore_above": 2 }, "my-large": { "type": "keyword" } } }, ) print(resp) resp1 = client.index( index="my-index-000001", id="1", refresh=True, document={ "my-small": [ "ok", "bad" ], "my-large": "ok content" }, ) print(resp1) resp2 = client.search( index="my-index-000001", fields=[ "my-*" ], source=False, ) print(resp2)
response = client.indices.create( index: 'my-index-000001', body: { mappings: { properties: { "my-small": { type: 'keyword', ignore_above: 2 }, "my-large": { type: 'keyword' } } } } ) puts response response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { "my-small": [ 'ok', 'bad' ], "my-large": 'ok content' } ) puts response response = client.search( index: 'my-index-000001', body: { fields: [ 'my-*' ], _source: false } ) puts response
const response = await client.indices.create({ index: "my-index-000001", mappings: { properties: { "my-small": { type: "keyword", ignore_above: 2, }, "my-large": { type: "keyword", }, }, }, }); console.log(response); const response1 = await client.index({ index: "my-index-000001", id: 1, refresh: "true", document: { "my-small": ["ok", "bad"], "my-large": "ok content", }, }); console.log(response1); const response2 = await client.search({ index: "my-index-000001", fields: ["my-*"], _source: false, }); console.log(response2);
PUT my-index-000001 { "mappings": { "properties": { "my-small" : { "type" : "keyword", "ignore_above": 2 }, "my-large" : { "type" : "keyword" } } } } PUT my-index-000001/_doc/1?refresh=true { "my-small": ["ok", "bad"], "my-large": "ok content" } POST my-index-000001/_search { "fields": ["my-*"], "_source": false }
This field has a size restriction |
|
This document field has a value that exceeds the size restriction so is ignored and not indexed |
The response will contain ignored field values under the ignored_field_values
path.
These values are retrieved from the document’s original JSON source and are raw so will
not be formatted or treated in any way, unlike the successfully indexed fields which are
returned in the fields
section.
{ "took" : 2, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 1, "relation" : "eq" }, "max_score" : 1.0, "hits" : [ { "_index" : "my-index-000001", "_id" : "1", "_score" : 1.0, "_ignored" : [ "my-small"], "fields" : { "my-large": [ "ok content" ], "my-small": [ "ok" ] }, "ignored_field_values" : { "my-small": [ "bad" ] } } ] } }
The _source
option
editYou can use the _source
parameter to select what fields of the source are
returned. This is called source filtering.
The following search API request sets the _source
request body parameter to
false
. The document source is not included in the response.
resp = client.search( source=False, query={ "match": { "user.id": "kimchy" } }, ) print(resp)
response = client.search( body: { _source: false, query: { match: { 'user.id' => 'kimchy' } } } ) puts response
const response = await client.search({ _source: false, query: { match: { "user.id": "kimchy", }, }, }); console.log(response);
GET /_search { "_source": false, "query": { "match": { "user.id": "kimchy" } } }
To return only a subset of source fields, specify a wildcard (*
) pattern in
the _source
parameter. The following search API request returns the source for
only the obj
field and its properties.
resp = client.search( source="obj.*", query={ "match": { "user.id": "kimchy" } }, ) print(resp)
response = client.search( body: { _source: 'obj.*', query: { match: { 'user.id' => 'kimchy' } } } ) puts response
const response = await client.search({ _source: "obj.*", query: { match: { "user.id": "kimchy", }, }, }); console.log(response);
GET /_search { "_source": "obj.*", "query": { "match": { "user.id": "kimchy" } } }
You can also specify an array of wildcard patterns in the _source
field. The
following search API request returns the source for only the obj1
and
obj2
fields and their properties.
resp = client.search( source=[ "obj1.*", "obj2.*" ], query={ "match": { "user.id": "kimchy" } }, ) print(resp)
response = client.search( body: { _source: [ 'obj1.*', 'obj2.*' ], query: { match: { 'user.id' => 'kimchy' } } } ) puts response
const response = await client.search({ _source: ["obj1.*", "obj2.*"], query: { match: { "user.id": "kimchy", }, }, }); console.log(response);
GET /_search { "_source": [ "obj1.*", "obj2.*" ], "query": { "match": { "user.id": "kimchy" } } }
For finer control, you can specify an object containing arrays of includes
and
excludes
patterns in the _source
parameter.
If the includes
property is specified, only source fields that match one of
its patterns are returned. You can exclude fields from this subset using the
excludes
property.
If the includes
property is not specified, the entire document source is
returned, excluding any fields that match a pattern in the excludes
property.
The following search API request returns the source for only the obj1
and
obj2
fields and their properties, excluding any child description
fields.
resp = client.search( source={ "includes": [ "obj1.*", "obj2.*" ], "excludes": [ "*.description" ] }, query={ "term": { "user.id": "kimchy" } }, ) print(resp)
response = client.search( body: { _source: { includes: [ 'obj1.*', 'obj2.*' ], excludes: [ '*.description' ] }, query: { term: { 'user.id' => 'kimchy' } } } ) puts response
const response = await client.search({ _source: { includes: ["obj1.*", "obj2.*"], excludes: ["*.description"], }, query: { term: { "user.id": "kimchy", }, }, }); console.log(response);
GET /_search { "_source": { "includes": [ "obj1.*", "obj2.*" ], "excludes": [ "*.description" ] }, "query": { "term": { "user.id": "kimchy" } } }
Other methods of retrieving data
editA document’s _source
is stored as a single field in Lucene. This structure
means that the whole _source
object must be loaded and parsed even if you’re
only requesting part of it. To avoid this limitation, you can try other options
for loading fields:
-
Use the
docvalue_fields
parameter to get values for selected fields. This can be a good choice when returning a fairly small number of fields that support doc values, such as keywords and dates. -
Use the
stored_fields
parameter to get the values for specific stored fields (fields that use thestore
mapping option).
Elasticsearch always attempts to load values from _source
. This behavior has the same
implications of source filtering where Elasticsearch needs to load and parse the entire
_source
to retrieve just one field.
Doc value fields
editYou can use the docvalue_fields
parameter to return
doc values for one or more fields in the search response.
Doc values store the same values as the _source
but in an on-disk,
column-based structure that’s optimized for sorting and aggregations. Since each
field is stored separately, Elasticsearch only reads the field values that were requested
and can avoid loading the whole document _source
.
Doc values are stored for supported fields by default. However, doc values are
not supported for text
or
text_annotated
fields.
The following search request uses the docvalue_fields
parameter to retrieve
doc values for the user.id
field, all fields starting with http.response.
, and the
@timestamp
field:
resp = client.search( index="my-index-000001", query={ "match": { "user.id": "kimchy" } }, docvalue_fields=[ "user.id", "http.response.*", { "field": "date", "format": "epoch_millis" } ], ) print(resp)
response = client.search( index: 'my-index-000001', body: { query: { match: { 'user.id' => 'kimchy' } }, docvalue_fields: [ 'user.id', 'http.response.*', { field: 'date', format: 'epoch_millis' } ] } ) puts response
const response = await client.search({ index: "my-index-000001", query: { match: { "user.id": "kimchy", }, }, docvalue_fields: [ "user.id", "http.response.*", { field: "date", format: "epoch_millis", }, ], }); console.log(response);
GET my-index-000001/_search { "query": { "match": { "user.id": "kimchy" } }, "docvalue_fields": [ "user.id", "http.response.*", { "field": "date", "format": "epoch_millis" } ] }
Both full field names and wildcard patterns are accepted. |
|
Using object notation, you can pass a |
You cannot use the docvalue_fields
parameter to retrieve doc values for
nested objects. If you specify a nested object, the search returns an empty
array ([ ]
) for the field. To access nested fields, use the
inner_hits
parameter’s docvalue_fields
property.
Stored fields
editIt’s also possible to store an individual field’s values by using the
store
mapping option. You can use the
stored_fields
parameter to include these stored values in the search response.
The stored_fields
parameter is for fields that are explicitly marked as
stored in the mapping, which is off by default and generally not recommended.
Use source filtering instead to select
subsets of the original source document to be returned.
Allows to selectively load specific stored fields for each document represented by a search hit.
resp = client.search( stored_fields=[ "user", "postDate" ], query={ "term": { "user": "kimchy" } }, ) print(resp)
response = client.search( body: { stored_fields: [ 'user', 'postDate' ], query: { term: { user: 'kimchy' } } } ) puts response
const response = await client.search({ stored_fields: ["user", "postDate"], query: { term: { user: "kimchy", }, }, }); console.log(response);
GET /_search { "stored_fields" : ["user", "postDate"], "query" : { "term" : { "user" : "kimchy" } } }
*
can be used to load all stored fields from the document.
An empty array will cause only the _id
and _type
for each hit to be
returned, for example:
resp = client.search( stored_fields=[], query={ "term": { "user": "kimchy" } }, ) print(resp)
response = client.search( body: { stored_fields: [], query: { term: { user: 'kimchy' } } } ) puts response
const response = await client.search({ stored_fields: [], query: { term: { user: "kimchy", }, }, }); console.log(response);
GET /_search { "stored_fields" : [], "query" : { "term" : { "user" : "kimchy" } } }
If the requested fields are not stored (store
mapping set to false
), they will be ignored.
Stored field values fetched from the document itself are always returned as an array. On the contrary, metadata fields like _routing
are never returned as an array.
Also only leaf fields can be returned via the stored_fields
option. If an object field is specified, it will be ignored.
On its own, stored_fields
cannot be used to load fields in nested
objects — if a field contains a nested object in its path, then no data will
be returned for that stored field. To access nested fields, stored_fields
must be used within an inner_hits
block.
Disable stored fields
editTo disable the stored fields (and metadata fields) entirely use: _none_
:
resp = client.search( stored_fields="_none_", query={ "term": { "user": "kimchy" } }, ) print(resp)
response = client.search( body: { stored_fields: '_none_', query: { term: { user: 'kimchy' } } } ) puts response
const response = await client.search({ stored_fields: "_none_", query: { term: { user: "kimchy", }, }, }); console.log(response);
GET /_search { "stored_fields": "_none_", "query" : { "term" : { "user" : "kimchy" } } }
Script fields
editYou can use the script_fields
parameter to retrieve a script
evaluation (based on different fields) for each hit. For example:
resp = client.search( query={ "match_all": {} }, script_fields={ "test1": { "script": { "lang": "painless", "source": "doc['price'].value * 2" } }, "test2": { "script": { "lang": "painless", "source": "doc['price'].value * params.factor", "params": { "factor": 2 } } } }, ) print(resp)
response = client.search( body: { query: { match_all: {} }, script_fields: { "test1": { script: { lang: 'painless', source: "doc['price'].value * 2" } }, "test2": { script: { lang: 'painless', source: "doc['price'].value * params.factor", params: { factor: 2 } } } } } ) puts response
const response = await client.search({ query: { match_all: {}, }, script_fields: { test1: { script: { lang: "painless", source: "doc['price'].value * 2", }, }, test2: { script: { lang: "painless", source: "doc['price'].value * params.factor", params: { factor: 2, }, }, }, }, }); console.log(response);
GET /_search { "query": { "match_all": {} }, "script_fields": { "test1": { "script": { "lang": "painless", "source": "doc['price'].value * 2" } }, "test2": { "script": { "lang": "painless", "source": "doc['price'].value * params.factor", "params": { "factor": 2.0 } } } } }
Script fields can work on fields that are not stored (price
in
the above case), and allow to return custom values to be returned (the
evaluated value of the script).
Script fields can also access the actual _source
document and
extract specific elements to be returned from it by using params['_source']
.
Here is an example:
resp = client.search( query={ "match_all": {} }, script_fields={ "test1": { "script": "params['_source']['message']" } }, ) print(resp)
response = client.search( body: { query: { match_all: {} }, script_fields: { "test1": { script: "params['_source']['message']" } } } ) puts response
const response = await client.search({ query: { match_all: {}, }, script_fields: { test1: { script: "params['_source']['message']", }, }, }); console.log(response);
GET /_search { "query": { "match_all": {} }, "script_fields": { "test1": { "script": "params['_source']['message']" } } }
Note the _source
keyword here to navigate the json-like model.
It’s important to understand the difference between
doc['my_field'].value
and params['_source']['my_field']
. The first,
using the doc keyword, will cause the terms for that field to be loaded to
memory (cached), which will result in faster execution, but more memory
consumption. Also, the doc[...]
notation only allows for simple valued
fields (you can’t return a json object from it) and makes sense only for
non-analyzed or single term based fields. However, using doc
is
still the recommended way to access values from the document, if at all
possible, because _source
must be loaded and parsed every time it’s used.
Using _source
is very slow.
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