Geo-grid processor
Converts geo-grid definitions of grid tiles or cells to regular bounding boxes or polygons which describe their shape. This is useful if there is a need to interact with the tile shapes as spatially indexable fields. For example the geotile
field value "4/8/3"
could be indexed as a string field, but that would not enable any spatial operations on it. Instead, convert it to the value "POLYGON ((0.0 40.979898069620134, 22.5 40.979898069620134, 22.5 55.77657301866769, 0.0 55.77657301866769, 0.0 40.979898069620134))"
, which can be indexed as a geo_shape
field.
Name | Required | Default | Description |
---|---|---|---|
field |
yes | - | The field to interpret as a geo-tile. The field format is determined by the tile_type . |
tile_type |
yes | - | Three tile formats are understood: geohash , geotile and geohex . |
target_field |
no | field |
The field to assign the polygon shape to, by default field is updated in-place. |
parent_field |
no | - | If specified and a parent tile exists, save that tile address to this field. |
children_field |
no | - | If specified and children tiles exist, save those tile addresses to this field as an array of strings. |
non_children_field |
no | - | If specified and intersecting non-child tiles exist, save their addresses to this field as an array of strings. |
precision_field |
no | - | If specified, save the tile precision (zoom) as an integer to this field. |
ignore_missing |
no | - | If true and field does not exist, the processor quietly exits without modifying the document. |
target_format |
no | "GeoJSON" | Which format to save the generated polygon in. Either WKT or GeoJSON . |
description |
no | - | Description of the processor. Useful for describing the purpose of the processor or its configuration. |
if |
no | - | Conditionally execute the processor. See Conditionally run a processor. |
ignore_failure |
no | false |
Ignore failures for the processor. See Handling pipeline failures. |
on_failure |
no | - | Handle failures for the processor. See Handling pipeline failures. |
tag |
no | - | Identifier for the processor. Useful for debugging and metrics. |
To demonstrate the usage of this ingest processor, consider an index called geocells
with a mapping for a field geocell
of type geo_shape
. In order to populate that index using geotile
and geohex
fields, define two ingest processors:
PUT geocells
{
"mappings": {
"properties": {
"geocell": {
"type": "geo_shape"
}
}
}
}
PUT _ingest/pipeline/geotile2shape
{
"description": "translate rectangular z/x/y geotile to bounding box",
"processors": [
{
"geo_grid": {
"field": "geocell",
"tile_type": "geotile"
}
}
]
}
PUT _ingest/pipeline/geohex2shape
{
"description": "translate H3 cell to polygon",
"processors": [
{
"geo_grid": {
"field": "geocell",
"tile_type": "geohex",
"target_format": "wkt"
}
}
]
}
These two pipelines can be used to index documents into the geocells
index. The geocell
field will be the string version of either a rectangular tile with format z/x/y
or an H3 cell address, depending on which ingest processor we use when indexing the document. The resulting geometry will be represented and indexed as a geo_shape
field in either GeoJSON or the Well-Known Text format.
In this example a geocell
field with a value defined in z/x/y
format is indexed as a GeoJSON Envelope since the ingest-processor above was defined with default target_format
.
PUT geocells/_doc/1?pipeline=geotile2shape
{
"geocell": "4/8/5"
}
GET geocells/_doc/1
The response shows how the ingest-processor has replaced the geocell
field with an indexable geo_shape
:
{
"_index": "geocells",
"_id": "1",
"_version": 1,
"_seq_no": 0,
"_primary_term": 1,
"found": true,
"_source": {
"geocell": {
"type": "Envelope",
"coordinates": [
[ 0.0, 55.77657301866769 ],
[ 22.5, 40.979898069620134 ]
]
}
}
}
In this example a geocell
field with an H3 string address is indexed as a WKT Polygon, since this ingest processor explicitly defined the target_format
.
PUT geocells/_doc/1?pipeline=geohex2shape
{
"geocell": "811fbffffffffff"
}
GET geocells/_doc/1
The response shows how the ingest-processor has replaced the geocell
field with an indexable geo_shape
:
{
"_index": "geocells",
"_id": "1",
"_version": 1,
"_seq_no": 0,
"_primary_term": 1,
"found": true,
"_source": {
"geocell": "POLYGON ((1.1885095294564962 49.470279179513454, 2.0265689212828875 45.18424864858389, 7.509948452934623 43.786609335802495, 12.6773177459836 46.40695743262768, 12.345747342333198 50.55427505169064, 6.259687012061477 51.964770150370896, 3.6300085578113794 50.610463307239115, 1.1885095294564962 49.470279179513454))"
}
}
As described in geo_grid processor options, there are many other fields that can be set, which will enrich the information available. For example, with H3 tiles there are 7 child tiles, but only the first is fully contained by the parent. The remaining six are only partially overlapping the parent, and there exist a further six non-child tiles that overlap the parent. This can be investigated by adding parent and child additional fields to the ingest-processor:
PUT _ingest/pipeline/geohex2shape
{
"description": "translate H3 cell to polygon with enriched fields",
"processors": [
{
"geo_grid": {
"description": "Ingest H3 cells like '811fbffffffffff' and create polygons",
"field": "geocell",
"tile_type": "geohex",
"target_format": "wkt",
"target_field": "shape",
"parent_field": "parent",
"children_field": "children",
"non_children_field": "nonChildren",
"precision_field": "precision"
}
}
]
}
Index the document to see a different result:
PUT geocells/_doc/1?pipeline=geohex2shape
{
"geocell": "811fbffffffffff"
}
GET geocells/_doc/1
The response from this index request:
{
"_index": "geocells",
"_id": "1",
"_version": 1,
"_seq_no": 0,
"_primary_term": 1,
"found": true,
"_source": {
"parent": "801ffffffffffff",
"geocell": "811fbffffffffff",
"precision": 1,
"shape": "POLYGON ((1.1885095294564962 49.470279179513454, 2.0265689212828875 45.18424864858389, 7.509948452934623 43.786609335802495, 12.6773177459836 46.40695743262768, 12.345747342333198 50.55427505169064, 6.259687012061477 51.964770150370896, 3.6300085578113794 50.610463307239115, 1.1885095294564962 49.470279179513454))",
"children": [
"821f87fffffffff",
"821f8ffffffffff",
"821f97fffffffff",
"821f9ffffffffff",
"821fa7fffffffff",
"821faffffffffff",
"821fb7fffffffff"
],
"nonChildren": [
"821ea7fffffffff",
"82186ffffffffff",
"82396ffffffffff",
"821f17fffffffff",
"821e37fffffffff",
"82194ffffffffff"
]
}
}
This additional information will then enable, for example, creating a visualization of the H3 cell, its children and its intersecting non-children cells.