Add a couple of overview clustering strategies
This commit is contained in:
Javier Goizueta
parent
5c52e7564f
commit
5992304b47
@ -697,6 +697,356 @@ AS $$
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END;
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$$ LANGUAGE PLPGSQL;
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CREATE OR REPLACE FUNCTION _CDB_GridCluster_Reduce_Strategy(reloid REGCLASS, ref_z INTEGER, overview_z INTEGER, grid_px FLOAT8 DEFAULT NULL)
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RETURNS REGCLASS
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AS $$
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DECLARE
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overview_rel TEXT;
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reduction FLOAT8;
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base_name TEXT;
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pixel_m FLOAT8;
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grid_m FLOAT8;
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offset_m FLOAT8;
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offset_x TEXT;
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offset_y TEXT;
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cell_x TEXT;
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cell_y TEXT;
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aggr_attributes TEXT;
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attributes TEXT;
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columns TEXT;
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gtypes TEXT[];
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schema_name TEXT;
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table_name TEXT;
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point_geom TEXT;
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BEGIN
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SELECT _CDB_GeometryTypes(reloid) INTO gtypes;
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IF gtypes IS NULL OR array_upper(gtypes, 1) <> 1 OR gtypes[1] <> 'ST_Point' THEN
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-- This strategy only supports datasets with point geomety
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RETURN NULL;
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END IF;
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--TODO: check applicability: geometry type, minimum number of points...
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overview_rel := _CDB_Overview_Name(reloid, ref_z, overview_z);
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-- Grid size in pixels at Z level overview_z
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IF grid_px IS NULL THEN
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grid_px := 1.0;
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END IF;
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SELECT * FROM _cdb_split_table_name(reloid) INTO schema_name, table_name;
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-- pixel_m: size of a pixel in webmercator units (meters)
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SELECT CDB_XYZ_Resolution(overview_z) INTO pixel_m;
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-- grid size in meters
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grid_m = grid_px * pixel_m;
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attributes := _CDB_Aggregable_Attributes_Expression(reloid);
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aggr_attributes := _CDB_Aggregated_Attributes_Expression(reloid);
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IF attributes <> '' THEN
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attributes := ', ' || attributes;
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END IF;
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IF aggr_attributes <> '' THEN
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aggr_attributes := aggr_attributes || ', ';
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END IF;
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-- Center of each cell:
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cell_x := Format('gx*%1$s + %2$s', grid_m, grid_m/2);
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cell_y := Format('gy*%1$s + %2$s', grid_m, grid_m/2);
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-- Displacement to the nearest pixel center:
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IF MOD(grid_px::numeric, 1.0::numeric) = 0 THEN
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offset_m := pixel_m/2 - MOD((grid_m/2)::numeric, pixel_m::numeric)::float8;
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offset_x := Format('%s', offset_m);
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offset_y := Format('%s', offset_m);
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ELSE
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offset_x := Format('%2$s/2 - MOD((%1$s)::numeric, (%2$s)::numeric)::float8', cell_x, pixel_m);
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offset_y := Format('%2$s/2 - MOD((%1$s)::numeric, (%2$s)::numeric)::float8', cell_y, pixel_m);
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END IF;
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point_geom := Format('ST_SetSRID(ST_MakePoint(%1$s + %3$s, %2$s + %4$s), 3857)', cell_x, cell_y, offset_x, offset_y);
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-- compute the resulting columns in the same order as in the base table
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WITH cols AS (
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SELECT
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CASE c
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WHEN 'cartodb_id' THEN 'cartodb_id'
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WHEN 'the_geom' THEN
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Format('ST_Transform(%s, 4326) AS the_geom', point_geom)
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WHEN 'the_geom_webmercator' THEN
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Format('%s AS the_geom_webmercator', point_geom)
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ELSE c
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END AS column
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FROM CDB_ColumnNames(reloid) c
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)
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SELECT string_agg(s.column, ',') FROM (
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SELECT * FROM cols
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) AS s INTO columns;
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IF NOT columns LIKE '%_feature_count%' THEN
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columns := columns || ', n AS _feature_count';
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END IF;
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EXECUTE Format('DROP TABLE IF EXISTS %I.%I CASCADE;', schema_name, overview_rel);
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-- Now we cluster the data using a grid of size grid_m
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-- and selecte the centroid (average coordinates) of each cluster.
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-- If we had a selected numeric attribute of interest we could use it
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-- as a weight for the average coordinates.
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EXECUTE Format('
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CREATE TABLE %7$I.%3$I AS
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WITH clusters AS (
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SELECT
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%5$s
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count(*) AS n,
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Floor(ST_X(f.the_geom_webmercator)/%2$s)::int AS gx,
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Floor(ST_Y(f.the_geom_webmercator)/%2$s)::int AS gy,
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MIN(cartodb_id) AS cartodb_id
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FROM %1$s f
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GROUP BY gx, gy
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)
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SELECT %6$s FROM clusters
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', reloid::text, grid_m, overview_rel, attributes, aggr_attributes, columns, schema_name);
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RETURN Format('%I.%I', schema_name, overview_rel)::regclass;
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END;
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$$ LANGUAGE PLPGSQL;
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-- This strategy places the aggregation of each cluster at the centroid of the cluster members.
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CREATE OR REPLACE FUNCTION _CDB_GridClusterCentroid_Reduce_Strategy(reloid REGCLASS, ref_z INTEGER, overview_z INTEGER, grid_px FLOAT8 DEFAULT NULL)
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RETURNS REGCLASS
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AS $$
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DECLARE
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overview_rel TEXT;
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reduction FLOAT8;
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base_name TEXT;
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pixel_m FLOAT8;
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grid_m FLOAT8;
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offset_m FLOAT8;
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offset_x TEXT;
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offset_y TEXT;
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cell_x TEXT;
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cell_y TEXT;
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aggr_attributes TEXT;
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attributes TEXT;
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columns TEXT;
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gtypes TEXT[];
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schema_name TEXT;
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table_name TEXT;
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point_geom TEXT;
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BEGIN
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SELECT _CDB_GeometryTypes(reloid) INTO gtypes;
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IF gtypes IS NULL OR array_upper(gtypes, 1) <> 1 OR gtypes[1] <> 'ST_Point' THEN
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-- This strategy only supports datasets with point geomety
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RETURN NULL;
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END IF;
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--TODO: check applicability: geometry type, minimum number of points...
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overview_rel := _CDB_Overview_Name(reloid, ref_z, overview_z);
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-- Grid size in pixels at Z level overview_z
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IF grid_px IS NULL THEN
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grid_px := 1.0;
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END IF;
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SELECT * FROM _cdb_split_table_name(reloid) INTO schema_name, table_name;
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-- pixel_m: size of a pixel in webmercator units (meters)
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SELECT CDB_XYZ_Resolution(overview_z) INTO pixel_m;
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-- grid size in meters
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grid_m = grid_px * pixel_m;
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attributes := _CDB_Aggregable_Attributes_Expression(reloid);
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aggr_attributes := _CDB_Aggregated_Attributes_Expression(reloid);
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IF attributes <> '' THEN
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attributes := ', ' || attributes;
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END IF;
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IF aggr_attributes <> '' THEN
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aggr_attributes := aggr_attributes || ', ';
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END IF;
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-- Center of each cell:
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cell_x := Format('gx*%1$s + %2$s', grid_m, grid_m/2);
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cell_y := Format('gy*%1$s + %2$s', grid_m, grid_m/2);
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-- Displacement to the nearest pixel center:
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IF MOD(grid_px::numeric, 1.0::numeric) = 0 THEN
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offset_m := pixel_m/2 - MOD((grid_m/2)::numeric, pixel_m::numeric)::float8;
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offset_x := Format('%s', offset_m);
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offset_y := Format('%s', offset_m);
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ELSE
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offset_x := Format('%2$s/2 - MOD((%1$s)::numeric, (%2$s)::numeric)::float8', cell_x, pixel_m);
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offset_y := Format('%2$s/2 - MOD((%1$s)::numeric, (%2$s)::numeric)::float8', cell_y, pixel_m);
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END IF;
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point_geom := Format('ST_SetSRID(ST_MakePoint(%1$s + %3$s, %2$s + %4$s), 3857)', cell_x, cell_y, offset_x, offset_y);
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-- compute the resulting columns in the same order as in the base table
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WITH cols AS (
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SELECT
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CASE c
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WHEN 'cartodb_id' THEN 'cartodb_id'
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WHEN 'the_geom' THEN
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'ST_Transform(ST_SetSRID(ST_MakePoint(_sum_of_x/n, _sum_of_y/n), 3857), 4326) AS the_geom'
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WHEN 'the_geom_webmercator' THEN
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'ST_SetSRID(ST_MakePoint(_sum_of_x/n, _sum_of_y/n), 3857) AS the_geom_webmercator'
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ELSE c
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END AS column
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FROM CDB_ColumnNames(reloid) c
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)
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SELECT string_agg(s.column, ',') FROM (
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SELECT * FROM cols
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) AS s INTO columns;
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IF NOT columns LIKE '%_feature_count%' THEN
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columns := columns || ', n AS _feature_count';
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END IF;
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EXECUTE Format('DROP TABLE IF EXISTS %I.%I CASCADE;', schema_name, overview_rel);
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-- Now we cluster the data using a grid of size grid_m
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-- and selecte the centroid (average coordinates) of each cluster.
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-- If we had a selected numeric attribute of interest we could use it
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-- as a weight for the average coordinates.
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EXECUTE Format('
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CREATE TABLE %7$I.%3$I AS
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WITH clusters AS (
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SELECT
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%5$s
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count(*) AS n,
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SUM(ST_X(f.the_geom_webmercator)) AS _sum_of_x,
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SUM(ST_Y(f.the_geom_webmercator)) AS _sum_of_y,
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Floor(ST_Y(f.the_geom_webmercator)/%2$s)::int AS gy,
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Floor(ST_X(f.the_geom_webmercator)/%2$s)::int AS gx,
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MIN(cartodb_id) AS cartodb_id
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FROM %1$s f
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GROUP BY gx, gy
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)
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SELECT %6$s FROM clusters
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', reloid::text, grid_m, overview_rel, attributes, aggr_attributes, columns, schema_name);
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RETURN Format('%I.%I', schema_name, overview_rel)::regclass;
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END;
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$$ LANGUAGE PLPGSQL;
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-- This strategy places the aggregation of each cluster at the position of one of the cluster members.
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-- TODO: the location and the cartodb_id should be chosen to correspond to the same record;
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-- a more efficient alternative to the `first` aggregator should be used
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CREATE OR REPLACE FUNCTION _CDB_GridClusterSample_Reduce_Strategy(reloid REGCLASS, ref_z INTEGER, overview_z INTEGER, grid_px FLOAT8 DEFAULT NULL)
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RETURNS REGCLASS
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AS $$
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DECLARE
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overview_rel TEXT;
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reduction FLOAT8;
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base_name TEXT;
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pixel_m FLOAT8;
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grid_m FLOAT8;
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offset_m FLOAT8;
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offset_x TEXT;
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offset_y TEXT;
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cell_x TEXT;
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cell_y TEXT;
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aggr_attributes TEXT;
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attributes TEXT;
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columns TEXT;
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gtypes TEXT[];
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schema_name TEXT;
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table_name TEXT;
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point_geom TEXT;
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BEGIN
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SELECT _CDB_GeometryTypes(reloid) INTO gtypes;
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IF gtypes IS NULL OR array_upper(gtypes, 1) <> 1 OR gtypes[1] <> 'ST_Point' THEN
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-- This strategy only supports datasets with point geomety
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RETURN NULL;
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END IF;
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--TODO: check applicability: geometry type, minimum number of points...
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overview_rel := _CDB_Overview_Name(reloid, ref_z, overview_z);
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-- Grid size in pixels at Z level overview_z
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IF grid_px IS NULL THEN
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grid_px := 1.0;
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END IF;
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SELECT * FROM _cdb_split_table_name(reloid) INTO schema_name, table_name;
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-- pixel_m: size of a pixel in webmercator units (meters)
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SELECT CDB_XYZ_Resolution(overview_z) INTO pixel_m;
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-- grid size in meters
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grid_m = grid_px * pixel_m;
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attributes := _CDB_Aggregable_Attributes_Expression(reloid);
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aggr_attributes := _CDB_Aggregated_Attributes_Expression(reloid);
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IF attributes <> '' THEN
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attributes := ', ' || attributes;
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END IF;
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IF aggr_attributes <> '' THEN
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aggr_attributes := aggr_attributes || ', ';
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END IF;
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-- Center of each cell:
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cell_x := Format('gx*%1$s + %2$s', grid_m, grid_m/2);
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cell_y := Format('gy*%1$s + %2$s', grid_m, grid_m/2);
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-- Displacement to the nearest pixel center:
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IF MOD(grid_px::numeric, 1.0::numeric) = 0 THEN
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offset_m := pixel_m/2 - MOD((grid_m/2)::numeric, pixel_m::numeric)::float8;
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offset_x := Format('%s', offset_m);
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offset_y := Format('%s', offset_m);
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ELSE
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offset_x := Format('%2$s/2 - MOD((%1$s)::numeric, (%2$s)::numeric)::float8', cell_x, pixel_m);
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offset_y := Format('%2$s/2 - MOD((%1$s)::numeric, (%2$s)::numeric)::float8', cell_y, pixel_m);
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END IF;
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point_geom := Format('ST_SetSRID(ST_MakePoint(%1$s + %3$s, %2$s + %4$s), 3857)', cell_x, cell_y, offset_x, offset_y);
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-- compute the resulting columns in the same order as in the base table
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WITH cols AS (
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SELECT
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CASE c
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WHEN 'cartodb_id' THEN 'cartodb_id'
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ELSE c
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END AS column
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FROM CDB_ColumnNames(reloid) c
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)
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SELECT string_agg(s.column, ',') FROM (
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SELECT * FROM cols
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) AS s INTO columns;
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IF NOT columns LIKE '%_feature_count%' THEN
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columns := columns || ', n AS _feature_count';
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END IF;
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EXECUTE Format('DROP TABLE IF EXISTS %I.%I CASCADE;', schema_name, overview_rel);
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-- Now we cluster the data using a grid of size grid_m
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-- and select the centroid (average coordinates) of each cluster.
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-- If we had a selected numeric attribute of interest we could use it
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-- as a weight for the average coordinates.
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EXECUTE Format('
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CREATE TABLE %7$I.%3$I AS
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WITH clusters AS (
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SELECT
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%5$s
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count(*) AS n,
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first(the_geom) as the_geom,
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first(the_geom_webmercator) as the_geom_webmercator,
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Floor(ST_X(f.the_geom_webmercator)/%2$s)::int AS gx,
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Floor(ST_Y(f.the_geom_webmercator)/%2$s)::int AS gy,
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MIN(cartodb_id) AS cartodb_id
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FROM %1$s f
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GROUP BY gx, gy
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)
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SELECT %6$s FROM clusters
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', reloid::text, grid_m, overview_rel, attributes, aggr_attributes, columns, schema_name);
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RETURN Format('%I.%I', schema_name, overview_rel)::regclass;
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END;
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$$ LANGUAGE PLPGSQL;
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-- Create overview tables for a dataset.
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-- Scope: public
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-- Parameters:
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