25 Using GeoJSON Geographic Data

GeoJSON objects are JSON objects that represent geographic data. Examples are provided of creating GeoJSON data, indexing it, and querying it.

GeoJSON Objects: Geometry, Feature, Feature Collection

GeoJSON uses JSON objects that represent various geometrical entities and combinations of these together with user-defined properties.

A position is an array of two or more spatial (numerical) coordinates, the first three of which generally represent longitude, latitude, and altitude.

A geometry object has a type field and (except for a geometry-collection object) a coordinates field, as shown in Table 25-1.

A geometry collection is a geometry object with type GeometryCollection. Instead of a coordinates field it has a geometries field, whose value is an array of geometry objects other than GeometryCollection objects.

Table 25-1 GeoJSON Geometry Objects Other Than Geometry Collections

type Field coordinates Field
Point A position.
MultiPoint An array of positions.
LineString An array of two or more positions.
MultiLineString An array of LineString arrays of positions.
Polygon A MultiLineString, each of whose arrays is a LineString whose first and last positions coincide (are equivalent). If the array of a polygon contains more than one array then the first represents the outside polygon and the others represent holes inside it.
MultiPolygon An array of Polygon arrays, that is, multidimensional array of positions.

A feature object has a type field of value Feature, a geometry field whose value is a geometric object, and a properties field whose value can be any JSON object.

A feature collection object has a type field of value FeatureCollection, and it has a features field whose value is an array of feature objects.

Example 25-1 presents a feature-collection object whose features array has three features. The geometry of the first feature is of type Point; that of the second is of type LineString; and that of the third is of type Polygon.

Query and Index GeoJSON Data

You can use SQL/JSON query functions and conditions to examine GeoJSON data or to project parts of it as non-JSON data, including as Oracle Spatial and Graph SDO_GEOMETRY object-type instances. This is illustrated in Example 25-2, Example 25-3, and Example 25-5.

To improve query performance, you can create an Oracle Spatial and Graph index (type MDSYS.SPATIAL_INDEX) on function json_value applied to GeoJSON data. This is illustrated by Example 25-4.

Example 25-4 indexes only one particular element of an array of geometry features (the first element). A B-tree index on function json_value can target only a scalar value. To improve the performance of queries, such as that of Example 25-3, that target any number of array elements, you can do the following:

  • Create an on-statement, refreshable materialized view of the array data, and place that view in memory.

  • Create a spatial index on the array data.

This is shown in Example 25-6 and Example 25-7.

SDO_GEOMETRY Object-Type Instances and Spatial Operations

You can convert Oracle Spatial and Graph SDO_GEOMETRY object-type instances to GeoJSON objects and GeoJSON objects to SDO_GEOMETRY instances.

You can use Oracle Spatial and Graph operations on SDO_GEOMETRY objects that you obtain from GeoJSON objects. For example, you can use operator sdo_distance in PL/SQL package SDO_GEOM to compute the minimum distance between two geometry objects. This is the distance between the closest two points or two segments, one point or segment from each object. This is illustrated by Example 25-5.

JSON Data Guide Supports GeoJSON Data

A JSON data guide summarizes structural and type information contained in a set of JSON documents. If some of the documents contain GeoJSON data then that data is summarized in a data guide that you create using SQL aggregate function json_dataguide. If you use SQL function json_dataguide to create a view based on such a data guide, and you specify the formatting argument as DBMS_JSON.GEOJSON or DBMS_JSON.GEOJSON+DBMS_JSON.PRETTY, then a column that projects GeoJSON data from the document set is of SQL data type SDO_GEOMETRY.

See Also:

Example 25-1 A Table With GeoJSON Data

This example creates table j_geo, which has a column, geo_doc of GeoJSON documents.

Only one such document is inserted here. It contains a GeoJSON object of type FeatureCollection, and a features array of objects of type Feature. Those objects have geometry, respectively, of type Point, LineString, and Polygon.

CREATE TABLE j_geo
  (id      VARCHAR2 (32) NOT NULL,
   geo_doc VARCHAR2 (4000) CHECK (geo_doc is json));

INSERT INTO j_geo
  VALUES (1,
          '{"type"     : "FeatureCollection",
            "features" : [{"type"       : "Feature",
                           "geometry"   : {"type" : "Point",
                                           "coordinates" : [-122.236111, 37.482778]},
                           "properties" : {"Name" : "Redwood City"}},
                          {"type"       : "Feature",
                           "geometry"   : {"type" : "LineString",
                                           "coordinates" : [[102.0, 0.0],
                                                            [103.0, 1.0],
                                                            [104.0, 0.0],
                                                            [105.0, 1.0]]},
                           "properties" : {"prop0" : "value0",
                                           "prop1" : 0.0}},
                          {"type"       : "Feature",
                           "geometry"   : {"type" : "Polygon",
                                           "coordinates" : [[[100.0, 0.0],
                                                             [101.0, 0.0],
                                                             [101.0, 1.0],
                                                             [100.0, 1.0],
                                                             [100.0, 0.0]]]},
                           "properties" : {"prop0" : "value0",
                                           "prop1" : {"this" : "that"}}}]}');

Example 25-2 Selecting a geometry Object From a GeoJSON Feature As an SDO_GEOMETRY Instance

This example uses SQL/JSON function json_value to select the value of field geometry from the first element of array features. The value is returned as Oracle Spatial and Graph data, not as JSON data, that is, as an instance of PL/SQL object type SDO_GEOMETRY, not as a SQL string or LOB instance.

SELECT json_value(geo_doc, '$.features[0].geometry'
                  RETURNING SDO_GEOMETRY 
                  ERROR ON ERROR)
  FROM j_geo;

The value returned is this, which represents a point with longitude and latitude (coordinates) -122.236111 and 37.482778, respectively.


SDO_GEOMETRY(2001,
             4326,
             SDO_POINT_TYPE(-122.236111, 37.482778, NULL),
             NULL,
             NULL)

See Also:

Oracle Database SQL Language Reference for information about SQL/JSON function json_value

Example 25-3 Retrieving Multiple geometry Objects From a GeoJSON Feature As SDO_GEOMETRY

This example uses SQL/JSON function json_table to project the value of field geometry from each element of array features, as column sdo_val of a virtual table. The retrieved data is returned as SDO_GEOMETRY.

SELECT jt.*
  FROM j_geo,
       json_table(geo_doc, '$.features[*]'
         COLUMNS (sdo_val SDO_GEOMETRY PATH '$.geometry')) jt;

See Also:

Oracle Database SQL Language Reference for information about SQL/JSON function json_table

The following three rows are returned for the query. The first represents the same Point as in Example 25-2. The second represents the LineString array. The third represents the Polygon.

SDO_GEOMETRY(2001,
             4326,
             SDO_POINT_TYPE(-122.236111, 37.482778, NULL),
             NULL,
             NULL)

SDO_GEOMETRY(2002,
             4326,
             NULL,
             SDO_ELEM_INFO_ARRAY(1, 2, 1),
             SDO_ORDINATE_ARRAY(102, 0, 103, 1, 104, 0, 105, 1))

SDO_GEOMETRY(2003,
             4326,
             NULL,
             SDO_ELEM_INFO_ARRAY(1, 1003, 1),
             SDO_ORDINATE_ARRAY(100, 0, 101, 0, 101, 1, 100, 1, 100, 0))

The second and third elements of attribute SDO_ELEM_INFO_ARRAY specify how to interpret the coordinates provided by attribute SDO_ORDINATE_ARRAY. They show that the first row returned represents a line string (2) with straight segments (1), and the second row represents a polygon (2003) of straight segments (1).

Example 25-4 Creating a Spatial Index For Scalar GeoJSON Data

This example creates a json_value function-based index of type MDSYS.SPATIAL_INDEX on field geometry of the first element of array features. This can improve the performance of queries that use json_value to retrieve that value.

CREATE INDEX geo_first_feature_idx
  ON j_geo (json_value(geo_doc, '$.features[0].geometry'
                       RETURNING SDO_GEOMETRY))
  INDEXTYPE IS MDSYS.SPATIAL_INDEX;

Example 25-5 Using GeoJSON Geometry With Spatial Operators

This example selects the documents (there is only one in this table) for which the geometry field of the first features element is within 100 kilometers of a given point. The point is provided literally here (its coordinates are the longitude and latitude of San Francisco, California). The distance is computed from this point to each geometry object.

The query orders the selected documents by the calculated distance. The tolerance in meters for the distance calculation is provided in this query as the literal argument 100.

SELECT id,
       json_value(geo_doc, '$.features[0].properties.Name') "Name",
       SDO_GEOM.sdo_distance(json_value(geo_doc, '$.features[0].geometry'
                                        RETURNING SDO_GEOMETRY),
         SDO_GEOMETRY(2001,
                      4326,
                      SDO_POINT_TYPE(-122.416667, 37.783333, NULL),
                      NULL,
                      NULL),
         100, -- Tolerance in meters
         'unit=KM') "Distance in kilometers"
  FROM  j_geo
  WHERE sdo_within_distance(
          json_value(geo_doc, '$.features[0].geometry'
                     RETURNING SDO_GEOMETRY),
          SDO_GEOMETRY(2001,
                       4326,
                       SDO_POINT_TYPE(-122.416667, 37.783333, NULL),
                       NULL,
                       NULL),
          'distance=100 unit=KM')
        = 'TRUE';

See Also:

Oracle Database SQL Language Reference for information about SQL/JSON function json_value

The query returns a single row:

ID    Name           Distance in kilometers
----- -------------- ----------------------
1     Redwood City   26.9443035

Example 25-6 Creating a Materialized View Over GeoJSON Data

CREATE OR REPLACE MATERIALIZED VIEW geo_doc_view
  BUILD IMMEDIATE
  REFRESH FAST ON STATEMENT WITH ROWID
  AS SELECT g.rowid, jt.*
       FROM j_geo g,
            json_table(geo_doc, '$.features[*]'
              COLUMNS (sdo_val SDO_GEOMETRY PATH '$.geometry')) jt;

Example 25-7 Creating a Spatial Index on a Materialized View Over GeoJSON Data

This example first prepares for the creation of the spatial index by populating some spatial-indexing metadata. It then creates the index on the SDO_GEOMETRY column, sdo_val, of materialized view geo_doc_view, which is created in Example 25-6. Except for the view and column names, the code for populating the indexing metadata is fixed — use it each time you need to create a spatial index on a materialized view.


-- Populate spatial-indexing metadata

INSERT INTO USER_SDO_GEOM_METADATA
  VALUES ('GEO_DOC_VIEW',
          'SDO_VAL',
          MDSYS.sdo_dim_array(
            MDSYS.sdo_dim_element('Longitude', -180, 180, 0.05),
            MDSYS.sdo_dim_element('Latitude', -90, 90, 0.05)),
          7
          4326);

-- Create spatial index on geometry column of materialized view

CREATE INDEX geo_all_features_idx ON geo_doc_view(sdo_val)
  INDEXTYPE IS MDSYS.SPATIAL_INDEX V2;