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Sort
editSort
editAllows to add one or more sort 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.
{ "sort" : [ { "post_date" : {"order" : "asc"}}, "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 sort values for each document returned are also returned as part of the response.
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. |
Sort mode example usage
editIn the example below the field price has multiple prices per document. In this case the result hits will be sort by price ascending based on the average price per document.
curl -XPOST 'localhost:9200/_search' -d '{ "query" : { ... }, "sort" : [ {"price" : {"order" : "asc", "mode" : "avg"}} ] }'
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 the following parameters on top of the already existing sort options:
-
nested_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.
-
nested_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
nested_filter
is active.
Nested sorting example
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.
curl -XPOST 'localhost:9200/_search' -d '{ "query" : { ... }, "sort" : [ { "offer.price" : { "mode" : "avg", "order" : "asc", "nested_path" : "offer", "nested_filter" : { "term" : { "offer.color" : "blue" } } } } ] }'
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 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). For example:
{ "sort" : [ { "price" : {"missing" : "_last"} }, ], "query" : { "term" : { "user" : "kimchy" } } }
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 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:
{ "sort" : [ { "price" : {"unmapped_type" : "long"} }, ], "query" : { "term" : { "user" : "kimchy" } } }
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:
{ "sort" : [ { "_geo_distance" : { "pin.location" : [-70, 40], "order" : "asc", "unit" : "km", "mode" : "min", "distance_type" : "sloppy_arc" } } ], "query" : { "term" : { "user" : "kimchy" } } }
-
distance_type
-
How to compute the distance. Can either be
sloppy_arc
(default),arc
(slightly more precise but significantly slower) orplane
(faster, but inaccurate on long distances and close to the poles).
Note: the geo distance sorting supports sort_mode
options: min
,
max
and avg
.
The following formats are supported in providing the coordinates:
Lat Lon as Properties
edit{ "sort" : [ { "_geo_distance" : { "pin.location" : { "lat" : 40, "lon" : -70 }, "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } }
Lat Lon as String
editFormat in lat,lon
.
{ "sort" : [ { "_geo_distance" : { "pin.location" : "40,-70", "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } }
Geohash
edit{ "sort" : [ { "_geo_distance" : { "pin.location" : "drm3btev3e86", "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
"pin.location" : [[-70, 40], [-71, 42]] "pin.location" : [{"lat": 40, "lon": -70}, {"lat": 42, "lon": -71}]
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:
{ "query" : { .... }, "sort" : { "_script" : { "type" : "number", "script" : { "inline": "doc['field_name'].value * 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.
{ "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
).