Sort search results
editSort search results
editAllows you to add one or more sorts on specific fields. Each sort can be
reversed as well. The sort is defined on a per field level, with special
field name for _score
to sort by score, and _doc
to sort by index order.
Assuming the following index mapping:
res, err := es.Indices.Create( "my-index-000001", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "post_date": { "type": "date" }, "user": { "type": "keyword" }, "name": { "type": "keyword" }, "age": { "type": "integer" } } } }`)), ) fmt.Println(res, err)
PUT /my-index-000001 { "mappings": { "properties": { "post_date": { "type": "date" }, "user": { "type": "keyword" }, "name": { "type": "keyword" }, "age": { "type": "integer" } } } }
GET /my-index-000001/_search { "sort" : [ { "post_date" : {"order" : "asc", "format": "strict_date_optional_time_nanos"}}, "user", { "name" : "desc" }, { "age" : "desc" }, "_score" ], "query" : { "term" : { "user" : "kimchy" } } }
_doc
has no real use-case besides being the most efficient sort order.
So if you don’t care about the order in which documents are returned, then you
should sort by _doc
. This especially helps when scrolling.
Sort Values
editThe search response includes sort
values for each document. Use the format
parameter to specify a date format for the sort
values of date
and date_nanos
fields. The following
search returns sort
values for the post_date
field in the
strict_date_optional_time_nanos
format.
GET /my-index-000001/_search { "sort" : [ { "post_date" : {"format": "strict_date_optional_time_nanos"}} ], "query" : { "term" : { "user" : "kimchy" } } }
Sort Order
editThe order
option can have the following values:
|
Sort in ascending order |
|
Sort in descending order |
The order defaults to desc
when sorting on the _score
, and defaults
to asc
when sorting on anything else.
Sort mode option
editElasticsearch supports sorting by array or multi-valued fields. The mode
option
controls what array value is picked for sorting the document it belongs
to. The mode
option can have the following values:
|
Pick the lowest value. |
|
Pick the highest value. |
|
Use the sum of all values as sort value. Only applicable for number based array fields. |
|
Use the average of all values as sort value. Only applicable for number based array fields. |
|
Use the median of all values as sort value. Only applicable for number based array fields. |
The default sort mode in the ascending sort order is min
— the lowest value
is picked. The default sort mode in the descending order is max
— the highest value is picked.
Sort mode example usage
editIn the example below the field price has multiple prices per document. In this case the result hits will be sorted by price ascending based on the average price per document.
{ res, err := es.Index( "my-index-000001", strings.NewReader(`{ "product": "chocolate", "price": [ 20, 4 ] }`), es.Index.WithDocumentID("1"), es.Index.WithRefresh("true"), es.Index.WithPretty(), ) fmt.Println(res, err) } { res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "term": { "product": "chocolate" } }, "sort": [ { "price": { "order": "asc", "mode": "avg" } } ] }`)), es.Search.WithPretty(), ) fmt.Println(res, err) }
PUT /my-index-000001/_doc/1?refresh { "product": "chocolate", "price": [20, 4] } POST /_search { "query" : { "term" : { "product" : "chocolate" } }, "sort" : [ {"price" : {"order" : "asc", "mode" : "avg"}} ] }
Sorting numeric fields
editFor numeric fields it is also possible to cast the values from one type
to another using the numeric_type
option.
This option accepts the following values: ["double", "long", "date", "date_nanos"
]
and can be useful for searches across multiple data streams or indices where the sort field is mapped differently.
Consider for instance these two indices:
response = client.indices.create( index: 'index_double', body: { mappings: { properties: { field: { type: 'double' } } } } ) puts response
res, err := es.Indices.Create( "index_double", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "field": { "type": "double" } } } }`)), ) fmt.Println(res, err)
PUT /index_double { "mappings": { "properties": { "field": { "type": "double" } } } }
response = client.indices.create( index: 'index_long', body: { mappings: { properties: { field: { type: 'long' } } } } ) puts response
res, err := es.Indices.Create( "index_long", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "field": { "type": "long" } } } }`)), ) fmt.Println(res, err)
PUT /index_long { "mappings": { "properties": { "field": { "type": "long" } } } }
Since field
is mapped as a double
in the first index and as a long
in the second index, it is not possible to use this field to sort requests
that query both indices by default. However you can force the type to one
or the other with the numeric_type
option in order to force a specific
type for all indices:
$params = [ 'index' => 'index_long,index_double', 'body' => [ 'sort' => [ [ 'field' => [ 'numeric_type' => 'double', ], ], ], ], ]; $response = $client->search($params);
resp = client.search( index=["index_long", "index_double"], body={"sort": [{"field": {"numeric_type": "double"}}]}, ) print(resp)
response = client.search( index: 'index_long,index_double', body: { sort: [ { field: { numeric_type: 'double' } } ] } ) puts response
res, err := es.Search( es.Search.WithIndex("index_long,index_double"), es.Search.WithBody(strings.NewReader(`{ "sort": [ { "field": { "numeric_type": "double" } } ] }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
const response = await client.search({ index: 'index_long,index_double', body: { sort: [ { field: { numeric_type: 'double' } } ] } }) console.log(response)
POST /index_long,index_double/_search { "sort" : [ { "field" : { "numeric_type" : "double" } } ] }
In the example above, values for the index_long
index are casted to
a double in order to be compatible with the values produced by the
index_double
index.
It is also possible to transform a floating point field into a long
but note that in this case floating points are replaced by the largest
value that is less than or equal (greater than or equal if the value
is negative) to the argument and is equal to a mathematical integer.
This option can also be used to convert a date
field that uses millisecond
resolution to a date_nanos
field with nanosecond resolution.
Consider for instance these two indices:
res, err := es.Indices.Create( "index_double", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "field": { "type": "date" } } } }`)), ) fmt.Println(res, err)
PUT /index_double { "mappings": { "properties": { "field": { "type": "date" } } } }
res, err := es.Indices.Create( "index_long", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "field": { "type": "date_nanos" } } } }`)), ) fmt.Println(res, err)
PUT /index_long { "mappings": { "properties": { "field": { "type": "date_nanos" } } } }
Values in these indices are stored with different resolutions so sorting on these
fields will always sort the date
before the date_nanos
(ascending order).
With the numeric_type
type option it is possible to set a single resolution for
the sort, setting to date
will convert the date_nanos
to the millisecond resolution
while date_nanos
will convert the values in the date
field to the nanoseconds resolution:
$params = [ 'index' => 'index_long,index_double', 'body' => [ 'sort' => [ [ 'field' => [ 'numeric_type' => 'date_nanos', ], ], ], ], ]; $response = $client->search($params);
resp = client.search( index=["index_long", "index_double"], body={"sort": [{"field": {"numeric_type": "date_nanos"}}]}, ) print(resp)
res, err := es.Search( es.Search.WithIndex("index_long,index_double"), es.Search.WithBody(strings.NewReader(`{ "sort": [ { "field": { "numeric_type": "date_nanos" } } ] }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
const response = await client.search({ index: 'index_long,index_double', body: { sort: [ { field: { numeric_type: 'date_nanos' } } ] } }) console.log(response)
POST /index_long,index_double/_search { "sort" : [ { "field" : { "numeric_type" : "date_nanos" } } ] }
To avoid overflow, the conversion to date_nanos
cannot be applied on dates before
1970 and after 2262 as nanoseconds are represented as longs.
Sorting within nested objects.
editElasticsearch also supports sorting by
fields that are inside one or more nested objects. The sorting by nested
field support has a nested
sort option with the following properties:
-
path
- Defines on which nested object to sort. The actual sort field must be a direct field inside this nested object. When sorting by nested field, this field is mandatory.
-
filter
-
A filter that the inner objects inside the nested path
should match with in order for its field values to be taken into account
by sorting. Common case is to repeat the query / filter inside the
nested filter or query. By default no
filter
is active. -
max_children
- The maximum number of children to consider per root document when picking the sort value. Defaults to unlimited.
-
nested
-
Same as top-level
nested
but applies to another nested path within the current nested object.
Elasticsearch will throw an error if a nested field is defined in a sort without
a nested
context.
Nested sorting examples
editIn the below example offer
is a field of type nested
.
The nested path
needs to be specified; otherwise, Elasticsearch doesn’t know on what nested level sort values need to be captured.
$params = [ 'body' => [ 'query' => [ 'term' => [ 'product' => 'chocolate', ], ], 'sort' => [ [ 'offer.price' => [ 'mode' => 'avg', 'order' => 'asc', 'nested' => [ 'path' => 'offer', 'filter' => [ 'term' => [ 'offer.color' => 'blue', ], ], ], ], ], ], ], ]; $response = $client->search($params);
resp = client.search( body={ "query": {"term": {"product": "chocolate"}}, "sort": [ { "offer.price": { "mode": "avg", "order": "asc", "nested": { "path": "offer", "filter": {"term": {"offer.color": "blue"}}, }, } } ], }, ) print(resp)
response = client.search( body: { query: { term: { product: 'chocolate' } }, sort: [ { "offer.price": { mode: 'avg', order: 'asc', nested: { path: 'offer', filter: { term: { "offer.color": 'blue' } } } } } ] } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "term": { "product": "chocolate" } }, "sort": [ { "offer.price": { "mode": "avg", "order": "asc", "nested": { "path": "offer", "filter": { "term": { "offer.color": "blue" } } } } } ] }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
const response = await client.search({ body: { query: { term: { product: 'chocolate' } }, sort: [ { 'offer.price': { mode: 'avg', order: 'asc', nested: { path: 'offer', filter: { term: { 'offer.color': 'blue' } } } } } ] } }) console.log(response)
POST /_search { "query" : { "term" : { "product" : "chocolate" } }, "sort" : [ { "offer.price" : { "mode" : "avg", "order" : "asc", "nested": { "path": "offer", "filter": { "term" : { "offer.color" : "blue" } } } } } ] }
In the below example parent
and child
fields are of type nested
.
The nested.path
needs to be specified at each level; otherwise, Elasticsearch doesn’t know on what nested level sort values need to be captured.
$params = [ 'body' => [ 'query' => [ 'nested' => [ 'path' => 'parent', 'query' => [ 'bool' => [ 'must' => [ 'range' => [ 'parent.age' => [ 'gte' => 21, ], ], ], 'filter' => [ 'nested' => [ 'path' => 'parent.child', 'query' => [ 'match' => [ 'parent.child.name' => 'matt', ], ], ], ], ], ], ], ], 'sort' => [ [ 'parent.child.age' => [ 'mode' => 'min', 'order' => 'asc', 'nested' => [ 'path' => 'parent', 'filter' => [ 'range' => [ 'parent.age' => [ 'gte' => 21, ], ], ], 'nested' => [ 'path' => 'parent.child', 'filter' => [ 'match' => [ 'parent.child.name' => 'matt', ], ], ], ], ], ], ], ], ]; $response = $client->search($params);
resp = client.search( body={ "query": { "nested": { "path": "parent", "query": { "bool": { "must": {"range": {"parent.age": {"gte": 21}}}, "filter": { "nested": { "path": "parent.child", "query": { "match": {"parent.child.name": "matt"} }, } }, } }, } }, "sort": [ { "parent.child.age": { "mode": "min", "order": "asc", "nested": { "path": "parent", "filter": {"range": {"parent.age": {"gte": 21}}}, "nested": { "path": "parent.child", "filter": { "match": {"parent.child.name": "matt"} }, }, }, } } ], }, ) print(resp)
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "nested": { "path": "parent", "query": { "bool": { "must": { "range": { "parent.age": { "gte": 21 } } }, "filter": { "nested": { "path": "parent.child", "query": { "match": { "parent.child.name": "matt" } } } } } } } }, "sort": [ { "parent.child.age": { "mode": "min", "order": "asc", "nested": { "path": "parent", "filter": { "range": { "parent.age": { "gte": 21 } } }, "nested": { "path": "parent.child", "filter": { "match": { "parent.child.name": "matt" } } } } } } ] }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
const response = await client.search({ body: { query: { nested: { path: 'parent', query: { bool: { must: { range: { 'parent.age': { gte: 21 } } }, filter: { nested: { path: 'parent.child', query: { match: { 'parent.child.name': 'matt' } } } } } } } }, sort: [ { 'parent.child.age': { mode: 'min', order: 'asc', nested: { path: 'parent', filter: { range: { 'parent.age': { gte: 21 } } }, nested: { path: 'parent.child', filter: { match: { 'parent.child.name': 'matt' } } } } } } ] } }) console.log(response)
POST /_search { "query": { "nested": { "path": "parent", "query": { "bool": { "must": {"range": {"parent.age": {"gte": 21}}}, "filter": { "nested": { "path": "parent.child", "query": {"match": {"parent.child.name": "matt"}} } } } } } }, "sort" : [ { "parent.child.age" : { "mode" : "min", "order" : "asc", "nested": { "path": "parent", "filter": { "range": {"parent.age": {"gte": 21}} }, "nested": { "path": "parent.child", "filter": { "match": {"parent.child.name": "matt"} } } } } } ] }
Nested sorting is also supported when sorting by scripts and sorting by geo distance.
Missing Values
editThe missing
parameter specifies how docs which are missing
the sort field should be treated: The missing
value can be
set to _last
, _first
, or a custom value (that
will be used for missing docs as the sort value).
The default is _last
.
For example:
response = client.search( body: { sort: [ { price: { missing: '_last' } } ], query: { term: { product: 'chocolate' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "price": { "missing": "_last" } } ], "query": { "term": { "product": "chocolate" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort" : [ { "price" : {"missing" : "_last"} } ], "query" : { "term" : { "product" : "chocolate" } } }
If a nested inner object doesn’t match with
the nested.filter
then a missing value is used.
Ignoring Unmapped Fields
editBy default, the search request will fail if there is no mapping
associated with a field. The unmapped_type
option allows you to ignore
fields that have no mapping and not sort by them. The value of this
parameter is used to determine what sort values to emit. Here is an
example of how it can be used:
response = client.search( body: { sort: [ { price: { unmapped_type: 'long' } } ], query: { term: { product: 'chocolate' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "price": { "unmapped_type": "long" } } ], "query": { "term": { "product": "chocolate" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort" : [ { "price" : {"unmapped_type" : "long"} } ], "query" : { "term" : { "product" : "chocolate" } } }
If any of the indices that are queried doesn’t have a mapping for price
then Elasticsearch will handle it as if there was a mapping of type
long
, with all documents in this index having no value for this field.
Geo Distance Sorting
editAllow to sort by _geo_distance
. Here is an example, assuming pin.location
is a field of type geo_point
:
response = client.search( body: { sort: [ { _geo_distance: { "pin.location": [ -70, 40 ], order: 'asc', unit: 'km', mode: 'min', distance_type: 'arc', ignore_unmapped: true } } ], query: { term: { user: 'kimchy' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "_geo_distance": { "pin.location": [ -70, 40 ], "order": "asc", "unit": "km", "mode": "min", "distance_type": "arc", "ignore_unmapped": true } } ], "query": { "term": { "user": "kimchy" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort" : [ { "_geo_distance" : { "pin.location" : [-70, 40], "order" : "asc", "unit" : "km", "mode" : "min", "distance_type" : "arc", "ignore_unmapped": true } } ], "query" : { "term" : { "user" : "kimchy" } } }
-
distance_type
-
How to compute the distance. Can either be
arc
(default), orplane
(faster, but inaccurate on long distances and close to the poles). -
mode
-
What to do in case a field has several geo points. By default, the shortest
distance is taken into account when sorting in ascending order and the
longest distance when sorting in descending order. Supported values are
min
,max
,median
andavg
. -
unit
-
The unit to use when computing sort values. The default is
m
(meters). -
ignore_unmapped
-
Indicates if the unmapped field should be treated as a missing value. Setting it to
true
is equivalent to specifying anunmapped_type
in the field sort. The default isfalse
(unmapped field cause the search to fail).
geo distance sorting does not support configurable missing values: the
distance will always be considered equal to Infinity
when a document does not
have values for the field that is used for distance computation.
The following formats are supported in providing the coordinates:
Lat Lon as Properties
editresponse = client.search( body: { sort: [ { _geo_distance: { "pin.location": { lat: 40, lon: -70 }, order: 'asc', unit: 'km' } } ], query: { term: { user: 'kimchy' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "_geo_distance": { "pin.location": { "lat": 40, "lon": -70 }, "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort" : [ { "_geo_distance" : { "pin.location" : { "lat" : 40, "lon" : -70 }, "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } }
Lat Lon as WKT String
editFormat in Well-Known Text.
response = client.search( body: { sort: [ { _geo_distance: { "pin.location": 'POINT (-70 40)', order: 'asc', unit: 'km' } } ], query: { term: { user: 'kimchy' } } } ) puts response
GET /_search { "sort": [ { "_geo_distance": { "pin.location": "POINT (-70 40)", "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }
Geohash
editresponse = client.search( body: { sort: [ { _geo_distance: { "pin.location": 'drm3btev3e86', order: 'asc', unit: 'km' } } ], query: { term: { user: 'kimchy' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "_geo_distance": { "pin.location": "drm3btev3e86", "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort": [ { "_geo_distance": { "pin.location": "drm3btev3e86", "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }
Lat Lon as Array
editFormat in [lon, lat]
, note, the order of lon/lat here in order to
conform with GeoJSON.
response = client.search( body: { sort: [ { _geo_distance: { "pin.location": [ -70, 40 ], order: 'asc', unit: 'km' } } ], query: { term: { user: 'kimchy' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "_geo_distance": { "pin.location": [ -70, 40 ], "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort": [ { "_geo_distance": { "pin.location": [ -70, 40 ], "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }
Multiple reference points
editMultiple geo points can be passed as an array containing any geo_point
format, for example
response = client.search( body: { sort: [ { _geo_distance: { "pin.location": [ [ -70, 40 ], [ -71, 42 ] ], order: 'asc', unit: 'km' } } ], query: { term: { user: 'kimchy' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "sort": [ { "_geo_distance": { "pin.location": [ [ -70, 40 ], [ -71, 42 ] ], "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "sort": [ { "_geo_distance": { "pin.location": [ [ -70, 40 ], [ -71, 42 ] ], "order": "asc", "unit": "km" } } ], "query": { "term": { "user": "kimchy" } } }
and so forth.
The final distance for a document will then be min
/max
/avg
(defined via mode
) distance of all points contained in the document to all points given in the sort request.
Script Based Sorting
editAllow to sort based on custom scripts, here is an example:
response = client.search( body: { query: { term: { user: 'kimchy' } }, sort: { _script: { type: 'number', script: { lang: 'painless', source: "doc['field_name'].value * params.factor", params: { factor: 1.1 } }, order: 'asc' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "term": { "user": "kimchy" } }, "sort": { "_script": { "type": "number", "script": { "lang": "painless", "source": "doc['field_name'].value * params.factor", "params": { "factor": 1.1 } }, "order": "asc" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "query": { "term": { "user": "kimchy" } }, "sort": { "_script": { "type": "number", "script": { "lang": "painless", "source": "doc['field_name'].value * params.factor", "params": { "factor": 1.1 } }, "order": "asc" } } }
Track Scores
editWhen sorting on a field, scores are not computed. By setting
track_scores
to true, scores will still be computed and tracked.
response = client.search( body: { track_scores: true, sort: [ { post_date: { order: 'desc' } }, { name: 'desc' }, { age: 'desc' } ], query: { term: { user: 'kimchy' } } } ) puts response
res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "track_scores": true, "sort": [ { "post_date": { "order": "desc" } }, { "name": "desc" }, { "age": "desc" } ], "query": { "term": { "user": "kimchy" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)
GET /_search { "track_scores": true, "sort" : [ { "post_date" : {"order" : "desc"} }, { "name" : "desc" }, { "age" : "desc" } ], "query" : { "term" : { "user" : "kimchy" } } }
Memory Considerations
editWhen sorting, the relevant sorted field values are loaded into memory.
This means that per shard, there should be enough memory to contain
them. For string based types, the field sorted on should not be analyzed
/ tokenized. For numeric types, if possible, it is recommended to
explicitly set the type to narrower types (like short
, integer
and
float
).