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opensearch-docs-cn/_query-dsl/geo-and-xy/xy.md

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---
layout: default
title: xy
parent: Geographic and xy queries
grand_parent: Query DSL
nav_order: 50
redirect_from:
- /opensearch/query-dsl/geo-and-xy/xy/
- /query-dsl/query-dsl/geo-and-xy/xy/
---
# xy query
To search for documents that contain [xy point]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/xy-point) and [xy shape]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/xy-shape) fields, use an xy query.
## Spatial relations
When you provide an xy shape to the xy query, the xy fields are matched using the following spatial relations to the provided shape.
Relation | Description | Supporting xy Field Type
:--- | :--- | :---
`INTERSECTS` | (Default) Matches documents whose xy point or xy shape intersects the shape provided in the query. | `xy_point`, `xy_shape`
`DISJOINT` | Matches documents whose xy shape does not intersect with the shape provided in the query. | `xy_shape`
`WITHIN` | Matches documents whose xy shape is completely within the shape provided in the query. | `xy_shape`
`CONTAINS` | Matches documents whose xy shape completely contains the shape provided in the query. | `xy_shape`
The following examples illustrate searching for documents that contain xy shapes. To learn how to search for documents that contain xy points, see the [Querying xy points](#querying-xy-points) section.
## Defining the shape in an xy query
You can define the shape in an xy query either by providing a new shape definition at query time or by referencing the name of a shape pre-indexed in another index.
### Using a new shape definition
To provide a new shape to an xy query, define it in the `xy_shape` field.
The following example illustrates searching for documents with xy shapes that match an xy shape defined at query time.
First, create an index and map the `geometry` field as an `xy_shape`:
```json
PUT testindex
{
"mappings": {
"properties": {
"geometry": {
"type": "xy_shape"
}
}
}
}
```
Index a document with a point and a document with a polygon:
```json
PUT testindex/_doc/1
{
"geometry": {
"type": "point",
"coordinates": [0.5, 3.0]
}
}
PUT testindex/_doc/2
{
"geometry" : {
"type" : "polygon",
"coordinates" : [
[[2.5, 6.0],
[0.5, 4.5],
[1.5, 2.0],
[3.5, 3.5],
[2.5, 6.0]]
]
}
}
```
Define an [`envelope`]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/xy-shape#envelope)—a bounding rectangle in the `[[minX, maxY], [maxX, minY]]` format. Search for documents with xy points or shapes that intersect that envelope:
```json
GET testindex/_search
{
"query": {
"xy_shape": {
"geometry": {
"shape": {
"type": "envelope",
"coordinates": [ [ 0.0, 6.0], [ 4.0, 2.0] ]
},
"relation": "WITHIN"
}
}
}
}
```
The following image depicts the example. Both the point and the polygon are within the bounding envelope.
<img src="{{site.url}}{{site.baseurl}}/images/xy_query.png" alt="xy shape query" width="250">
The response contains both documents:
```json
{
"took" : 363,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.0,
"hits" : [
{
"_index" : "testindex",
"_id" : "1",
"_score" : 0.0,
"_source" : {
"geometry" : {
"type" : "point",
"coordinates" : [
0.5,
3.0
]
}
}
},
{
"_index" : "testindex",
"_id" : "2",
"_score" : 0.0,
"_source" : {
"geometry" : {
"type" : "polygon",
"coordinates" : [
[
[
2.5,
6.0
],
[
0.5,
4.5
],
[
1.5,
2.0
],
[
3.5,
3.5
],
[
2.5,
6.0
]
]
]
}
}
}
]
}
}
```
### Using a pre-indexed shape definition
When constructing an xy query, you can also reference the name of a shape pre-indexed in another index. Using this method, you can define an xy shape at index time and refer to it by name, providing the following parameters in the `indexed_shape` object.
Parameter | Description
:--- | :---
`index` | The name of the index that contains the pre-indexed shape.
`id` | The document ID of the document that contains the pre-indexed shape.
`path` | The field name of the field that contains the pre-indexed shape as a path.
The following example illustrates referencing the name of a shape pre-indexed in another index. In this example, the index `pre-indexed-shapes` contains the shape that defines the boundaries, and the index `testindex` contains the shapes whose locations are checked against those boundaries.
First, create an index `pre-indexed-shapes` and map the `geometry` field for this index as an `xy_shape`:
```json
PUT pre-indexed-shapes
{
"mappings": {
"properties": {
"geometry": {
"type": "xy_shape"
}
}
}
}
```
Index an envelope that specifies the boundaries and name it `rectangle`:
```json
PUT pre-indexed-shapes/_doc/rectangle
{
"geometry": {
"type": "envelope",
"coordinates" : [ [ 0.0, 6.0], [ 4.0, 2.0] ]
}
}
```
Index a document with a point and a document with a polygon into the index `testindex`:
```json
PUT testindex/_doc/1
{
"geometry": {
"type": "point",
"coordinates": [0.5, 3.0]
}
}
PUT testindex/_doc/2
{
"geometry" : {
"type" : "polygon",
"coordinates" : [
[[2.5, 6.0],
[0.5, 4.5],
[1.5, 2.0],
[3.5, 3.5],
[2.5, 6.0]]
]
}
}
```
Search for documents with shapes that intersect `rectangle` in the index `testindex` using a filter:
```json
GET testindex/_search
{
"query": {
"bool": {
"filter": {
"xy_shape": {
"geometry": {
"indexed_shape": {
"index": "pre-indexed-shapes",
"id": "rectangle",
"path": "geometry"
}
}
}
}
}
}
}
```
The preceding query uses the default spatial relation `INTERSECTS` and returns both the point and the polygon:
```json
{
"took" : 26,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.0,
"hits" : [
{
"_index" : "testindex",
"_id" : "1",
"_score" : 0.0,
"_source" : {
"geometry" : {
"type" : "point",
"coordinates" : [
0.5,
3.0
]
}
}
},
{
"_index" : "testindex",
"_id" : "2",
"_score" : 0.0,
"_source" : {
"geometry" : {
"type" : "polygon",
"coordinates" : [
[
[
2.5,
6.0
],
[
0.5,
4.5
],
[
1.5,
2.0
],
[
3.5,
3.5
],
[
2.5,
6.0
]
]
]
}
}
}
]
}
}
```
## Querying xy points
You can also use an xy query to search for documents that contain xy points.
Create a mapping with `point` as `xy_point`:
```json
PUT testindex1
{
"mappings": {
"properties": {
"point": {
"type": "xy_point"
}
}
}
}
```
Index three points:
```json
PUT testindex1/_doc/1
{
"point": "1.0, 1.0"
}
PUT testindex1/_doc/2
{
"point": "2.0, 0.0"
}
PUT testindex1/_doc/3
{
"point": "-2.0, 2.0"
}
```
Search for points that lie within the circle with the center at (0, 0) and a radius of 2:
```json
GET testindex1/_search
{
"query": {
"xy_shape": {
"point": {
"shape": {
"type": "circle",
"coordinates": [0.0, 0.0],
"radius": 2
}
}
}
}
}
```
xy point only supports the default `INTERSECTS` spatial relation, so you don't need to provide the `relation` parameter.
{: .note}
The following image depicts the example. Points 1 and 2 are within the circle, and point 3 is outside the circle.
<img src="{{site.url}}{{site.baseurl}}/images/xy_query_point.png" alt="xy point query" width="300">
The response returns documents 1 and 2:
```json
{
"took" : 575,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.0,
"hits" : [
{
"_index" : "testindex1",
"_id" : "1",
"_score" : 0.0,
"_source" : {
"point" : "1.0, 1.0"
}
},
{
"_index" : "testindex1",
"_id" : "2",
"_score" : 0.0,
"_source" : {
"point" : "2.0, 0.0"
}
}
]
}
}
```
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