Functions for Working with Polygons
WKT
Returns a WKT (Well Known Text) geometric object from various Geo Data Types. Supported WKT objects are:
- POINT
- POLYGON
- MULTIPOLYGON
Syntax
WKT(geo_data)
Parameters
geo_data
can be one of the following Geo Data Types or their underlying primitive types:
Returned value
- WKT geometric object
POINT
is returned for a Point. - WKT geometric object
POLYGON
is returned for a Polygon - WKT geometric object
MULTIPOLYGON
is returned for a MultiPolygon.
Examples
POINT from tuple:
SELECT wkt((0., 0.));
POINT(0 0)
POLYGON from an array of tuples or an array of tuple arrays:
SELECT wkt([(0., 0.), (10., 0.), (10., 10.), (0., 10.)]);
POLYGON((0 0,10 0,10 10,0 10))
MULTIPOLYGON from an array of multi-dimensional tuple arrays:
SELECT wkt([[[(0., 0.), (10., 0.), (10., 10.), (0., 10.)], [(4., 4.), (5., 4.), (5., 5.), (4., 5.)]], [[(-10., -10.), (-10., -9.), (-9., 10.)]]]);
MULTIPOLYGON(((0 0,10 0,10 10,0 10,0 0),(4 4,5 4,5 5,4 5,4 4)),((-10 -10,-10 -9,-9 10,-10 -10)))
readWKTMultiPolygon
Converts a WKT (Well Known Text) MultiPolygon into a MultiPolygon type.
Example
SELECT
toTypeName(readWKTMultiPolygon('MULTIPOLYGON(((2 0,10 0,10 10,0 10,2 0),(4 4,5 4,5 5,4 5,4 4)),((-10 -10,-10 -9,-9 10,-10 -10)))')) AS type,
readWKTMultiPolygon('MULTIPOLYGON(((2 0,10 0,10 10,0 10,2 0),(4 4,5 4,5 5,4 5,4 4)),((-10 -10,-10 -9,-9 10,-10 -10)))') AS output FORMAT Markdown
type | output |
---|---|
MultiPolygon | [[[(2,0),(10,0),(10,10),(0,10),(2,0)],[(4,4),(5,4),(5,5),(4,5),(4,4)]],[[(-10,-10),(-10,-9),(-9,10),(-10,-10)]]] |
Input parameters
String starting with MULTIPOLYGON
Returned value
MultiPolygon
readWKTPolygon
Converts a WKT (Well Known Text) MultiPolygon into a Polygon type.
Example
SELECT
toTypeName(readWKTPolygon('POLYGON((2 0,10 0,10 10,0 10,2 0))')) AS type,
readWKTPolygon('POLYGON((2 0,10 0,10 10,0 10,2 0))') AS output
FORMAT Markdown
type | output |
---|---|
Polygon | [[(2,0),(10,0),(10,10),(0,10),(2,0)]] |
Input parameters
String starting with POLYGON
Returned value
Polygon
readWKTPoint
The readWKTPoint
function in ClickHouse parses a Well-Known Text (WKT) representation of a Point geometry and returns a point in the internal ClickHouse format.
Syntax
readWKTPoint(wkt_string)
Arguments
wkt_string
: The input WKT string representing a Point geometry.
Returned value
The function returns a ClickHouse internal representation of the Point geometry.
Example
SELECT readWKTPoint('POINT (1.2 3.4)');
(1.2,3.4)
readWKTLineString
Parses a Well-Known Text (WKT) representation of a LineString geometry and returns it in the internal ClickHouse format.
Syntax
readWKTLineString(wkt_string)
Arguments
wkt_string
: The input WKT string representing a LineString geometry.
Returned value
The function returns a ClickHouse internal representation of the linestring geometry.
Example
SELECT readWKTLineString('LINESTRING (1 1, 2 2, 3 3, 1 1)');
[(1,1),(2,2),(3,3),(1,1)]
readWKTRing
Parses a Well-Known Text (WKT) representation of a Polygon geometry and returns a ring (closed linestring) in the internal ClickHouse format.
Syntax
readWKTRing(wkt_string)
Arguments
wkt_string
: The input WKT string representing a Polygon geometry.
Returned value
The function returns a ClickHouse internal representation of the ring (closed linestring) geometry.
Example
SELECT readWKTRing('POLYGON ((1 1, 2 2, 3 3, 1 1))');
[(1,1),(2,2),(3,3),(1,1)]
polygonsWithinSpherical
Returns true or false depending on whether or not one polygon lies completely inside another polygon. Reference https://www.boost.org/doc/libs/1_62_0/libs/geometry/doc/html/geometry/reference/algorithms/within/within_2.html
Example
select polygonsWithinSpherical([[[(4.3613577, 50.8651821), (4.349556, 50.8535879), (4.3602419, 50.8435626), (4.3830299, 50.8428851), (4.3904543, 50.8564867), (4.3613148, 50.8651279)]]], [[[(4.346693, 50.858306), (4.367945, 50.852455), (4.366227, 50.840809), (4.344961, 50.833264), (4.338074, 50.848677), (4.346693, 50.858306)]]]);
0
Input parameters
Returned value
UInt8, 0 for false, 1 for true
polygonsDistanceSpherical
Calculates the minimal distance between two points where one point belongs to the first polygon and the second to another polygon. Spherical means that coordinates are interpreted as coordinates on a pure and ideal sphere, which is not true for the Earth. Using this type of coordinate system speeds up execution, but of course is not precise.
Example
SELECT polygonsDistanceSpherical([[[(0, 0), (0, 0.1), (0.1, 0.1), (0.1, 0)]]], [[[(10., 10.), (10., 40.), (40., 40.), (40., 10.), (10., 10.)]]])
0.24372872211133834
Input parameters
Two polygons
Returned value
Float64
polygonsDistanceCartesian
Calculates distance between two polygons
Example
SELECT polygonsDistanceCartesian([[[(0, 0), (0, 0.1), (0.1, 0.1), (0.1, 0)]]], [[[(10., 10.), (10., 40.), (40., 40.), (40., 10.), (10., 10.)]]])
14.000714267493642
Input parameters
Two polygons
Returned value
Float64
polygonsEqualsCartesian
Returns true if two polygons are equal
Example
SELECT polygonsEqualsCartesian([[[(1., 1.), (1., 4.), (4., 4.), (4., 1.)]]], [[[(1., 1.), (1., 4.), (4., 4.), (4., 1.), (1., 1.)]]])
1
Input parameters
Two polygons
Returned value
UInt8, 0 for false, 1 for true
polygonsSymDifferenceSpherical
Calculates the spatial set theoretic symmetric difference (XOR) between two polygons
Example
SELECT wkt(arraySort(polygonsSymDifferenceSpherical([[(50., 50.), (50., -50.), (-50., -50.), (-50., 50.), (50., 50.)], [(10., 10.), (10., 40.), (40., 40.), (40., 10.), (10., 10.)], [(-10., -10.), (-10., -40.), (-40., -40.), (-40., -10.), (-10., -10.)]], [[(-20., -20.), (-20., 20.), (20., 20.), (20., -20.), (-20., -20.)]])));
MULTIPOLYGON(((-20 -10.3067,-10 -10,-10 -20.8791,-20 -20,-20 -10.3067)),((10 20.8791,20 20,20 10.3067,10 10,10 20.8791)),((50 50,50 -50,-50 -50,-50 50,50 50),(20 10.3067,40 10,40 40,10 40,10 20.8791,-20 20,-20 -10.3067,-40 -10,-40 -40,-10 -40,-10 -20.8791,20 -20,20 10.3067)))
Input parameters
Polygons
Returned value
MultiPolygon
polygonsSymDifferenceCartesian
The same as polygonsSymDifferenceSpherical
, but the coordinates are in the Cartesian coordinate system; which is more close to the model of the real Earth.
Example
SELECT wkt(polygonsSymDifferenceCartesian([[[(0, 0), (0, 3), (1, 2.9), (2, 2.6), (2.6, 2), (2.9, 1), (3, 0), (0, 0)]]], [[[(1., 1.), (1., 4.), (4., 4.), (4., 1.), (1., 1.)]]]))
MULTIPOLYGON(((1 2.9,1 1,2.9 1,3 0,0 0,0 3,1 2.9)),((1 2.9,1 4,4 4,4 1,2.9 1,2.6 2,2 2.6,1 2.9)))
Input parameters
Polygons
Returned value
MultiPolygon
polygonsIntersectionSpherical
Calculates the intersection (AND) between polygons, coordinates are spherical.
Example
SELECT wkt(arrayMap(a -> arrayMap(b -> arrayMap(c -> (round(c.1, 6), round(c.2, 6)), b), a), polygonsIntersectionSpherical([[[(4.3613577, 50.8651821), (4.349556, 50.8535879), (4.3602419, 50.8435626), (4.3830299, 50.8428851), (4.3904543, 50.8564867), (4.3613148, 50.8651279)]]], [[[(4.346693, 50.858306), (4.367945, 50.852455), (4.366227, 50.840809), (4.344961, 50.833264), (4.338074, 50.848677), (4.346693, 50.858306)]]])))
MULTIPOLYGON(((4.3666 50.8434,4.36024 50.8436,4.34956 50.8536,4.35268 50.8567,4.36794 50.8525,4.3666 50.8434)))
Input parameters
Polygons
Returned value
MultiPolygon
polygonsWithinCartesian
Returns true if the second polygon is within the first polygon.
Example
SELECT polygonsWithinCartesian([[[(2., 2.), (2., 3.), (3., 3.), (3., 2.)]]], [[[(1., 1.), (1., 4.), (4., 4.), (4., 1.), (1., 1.)]]])
1
Input parameters
Two polygons
Returned value
UInt8, 0 for false, 1 for true
polygonConvexHullCartesian
Calculates a convex hull. Reference
Coordinates are in Cartesian coordinate system.
Example
SELECT wkt(polygonConvexHullCartesian([[[(0., 0.), (0., 5.), (5., 5.), (5., 0.), (2., 3.)]]]))
POLYGON((0 0,0 5,5 5,5 0,0 0))
Input parameters
MultiPolygon
Returned value
Polygon
polygonAreaSpherical
Calculates the surface area of a polygon.
Example
SELECT round(polygonAreaSpherical([[[(4.346693, 50.858306), (4.367945, 50.852455), (4.366227, 50.840809), (4.344961, 50.833264), (4.338074, 50.848677), (4.346693, 50.858306)]]]), 14)
9.387704e-8
Input parameters
Polygon
Returned value
Float
polygonsUnionSpherical
Calculates a union (OR).
Example
SELECT wkt(polygonsUnionSpherical([[[(4.3613577, 50.8651821), (4.349556, 50.8535879), (4.3602419, 50.8435626), (4.3830299, 50.8428851), (4.3904543, 50.8564867), (4.3613148, 50.8651279)]]], [[[(4.346693, 50.858306), (4.367945, 50.852455), (4.366227, 50.840809), (4.344961, 50.833264), (4.338074, 50.848677), (4.346693, 50.858306)]]]))
MULTIPOLYGON(((4.36661 50.8434,4.36623 50.8408,4.34496 50.8333,4.33807 50.8487,4.34669 50.8583,4.35268 50.8567,4.36136 50.8652,4.36131 50.8651,4.39045 50.8565,4.38303 50.8429,4.36661 50.8434)))
Input parameters
Polygons
Returned value
MultiPolygon
polygonPerimeterSpherical
Calculates the perimeter of the polygon.
Example
This is the polygon representing Zimbabwe:
POLYGON((30.0107 -15.6462,30.0502 -15.6401,30.09 -15.6294,30.1301 -15.6237,30.1699 -15.6322,30.1956 -15.6491,30.2072 -15.6532,30.2231 -15.6497,30.231 -15.6447,30.2461 -15.6321,30.2549 -15.6289,30.2801 -15.6323,30.2962 -15.639,30.3281 -15.6524,30.3567 -15.6515,30.3963 -15.636,30.3977 -15.7168,30.3993 -15.812,30.4013 -15.9317,30.4026 -16.0012,30.5148 -16.0004,30.5866 -16,30.7497 -15.9989,30.8574 -15.9981,30.9019 -16.0071,30.9422 -16.0345,30.9583 -16.0511,30.9731 -16.062,30.9898 -16.0643,31.012 -16.0549,31.0237 -16.0452,31.0422 -16.0249,31.0569 -16.0176,31.0654 -16.0196,31.0733 -16.0255,31.0809 -16.0259,31.089 -16.0119,31.1141 -15.9969,31.1585 -16.0002,31.26 -16.0235,31.2789 -16.0303,31.2953 -16.0417,31.3096 -16.059,31.3284 -16.0928,31.3409 -16.1067,31.3603 -16.1169,31.3703 -16.1237,31.3746 -16.1329,31.3778 -16.1422,31.384 -16.1488,31.3877 -16.1496,31.3956 -16.1477,31.3996 -16.1473,31.4043 -16.1499,31.4041 -16.1545,31.4027 -16.1594,31.4046 -16.1623,31.4241 -16.1647,31.4457 -16.165,31.4657 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(29.648505, -15.666588), (29.672793, -15.663281), (29.73005, -15.644677), (29.773252, -15.638062), (29.814283, -15.619666), (29.837331, -15.614808), (29.881773, -15.618839), (29.967504, -15.641473), (30.010654, -15.646227)]), 6)
0.45539
Input parameters
Returned value
polygonsIntersectionCartesian
Calculates the intersection of polygons.
Example
SELECT wkt(polygonsIntersectionCartesian([[[(0., 0.), (0., 3.), (1., 2.9), (2., 2.6), (2.6, 2.), (2.9, 1.), (3., 0.), (0., 0.)]]], [[[(1., 1.), (1., 4.), (4., 4.), (4., 1.), (1., 1.)]]]))
MULTIPOLYGON(((1 2.9,2 2.6,2.6 2,2.9 1,1 1,1 2.9)))
Input parameters
Polygons
Returned value
MultiPolygon
polygonAreaCartesian
Calculates the area of a polygon
Example
SELECT polygonAreaCartesian([[[(0., 0.), (0., 5.), (5., 5.), (5., 0.)]]])
25
Input parameters
Polygon
Returned value
Float64
polygonPerimeterCartesian
Calculates the perimeter of a polygon.
Example
SELECT polygonPerimeterCartesian([[[(0., 0.), (0., 5.), (5., 5.), (5., 0.)]]])
15
Input parameters
Polygon
Returned value
Float64
polygonsUnionCartesian
Calculates the union of polygons.
Example
SELECT wkt(polygonsUnionCartesian([[[(0., 0.), (0., 3.), (1., 2.9), (2., 2.6), (2.6, 2.), (2.9, 1), (3., 0.), (0., 0.)]]], [[[(1., 1.), (1., 4.), (4., 4.), (4., 1.), (1., 1.)]]]))
MULTIPOLYGON(((1 2.9,1 4,4 4,4 1,2.9 1,3 0,0 0,0 3,1 2.9)))
Input parameters
Polygons
Returned value
MultiPolygon
For more information on geometry systems, see this presentation about the Boost library, which is what ClickHouse uses.