
Elasticsearch 8.x Cookbook
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An extension of the concept of a point is its shape. Elasticsearch provides a type that allows you to manage arbitrary polygons in GeoShape.
You will need an up-and-running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe of Chapter 1, Getting Started.
To be able to use advanced shape management, Elasticsearch requires two JAR libraries in its classpath
(usually the lib
directory), as follows:
To map a geo_shape
type, a user must explicitly provide some parameters:
tree
(the default is geohash
): This is the name of the PrefixTree
implementation – GeohashPrefixTree
and quadtree
for QuadPrefixTree
.precision
: This is used instead of tree_levels
to provide a more human value to be used in the tree level. The precision number can be followed by the unit; that is, 10 m, 10 km, 10 miles, and so on.tree_levels
: This is the maximum number of layers to be used in the prefix tree.distance_error_pct
: This sets the maximum errors that are allowed in a prefix tree (0,025% - max 0,5%
by default).The customer_location
mapping, which we saw in the previous recipe using geo_shape
, will be as follows:
"customer_location": { "type": "geo_shape", "tree": "quadtree", "precision": "1m" },
When a shape is indexed or searched internally, a path tree is created and used.
A path tree is a list of terms that contain geographic information and are computed to improve performance in evaluating geo calculus.
The path tree also depends on the shape's type: point, linestring, polygon, multipoint, or multipolygon.
To understand the logic behind the GeoShape, some good resources are the Elasticsearch page, which tells you about GeoShape, and the sites of the libraries that are used for geographic calculus (https://github.com/spatial4j/spatial4j and http://central.maven.org/maven2/com/vividsolutions/jts/1.13/, respectively).