867 lines
25 KiB
PL/PgSQL
867 lines
25 KiB
PL/PgSQL
--DO NOT MODIFY THIS FILE, IT IS GENERATED AUTOMATICALLY FROM SOURCES
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-- Complain if script is sourced in psql, rather than via CREATE EXTENSION
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\echo Use "CREATE EXTENSION observatory" to load this file. \quit
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-- Version number of the extension release
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CREATE OR REPLACE FUNCTION cdb_observatory_version()
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RETURNS text AS $$
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SELECT '0.0.1'::text;
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$$ language 'sql' STABLE STRICT;
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-- Internal identifier of the installed extension instence
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-- e.g. 'dev' for current development version
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CREATE OR REPLACE FUNCTION _cdb_observatory_internal_version()
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RETURNS text AS $$
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SELECT installed_version FROM pg_available_extensions where name='observatory' and pg_available_extensions IS NOT NULL;
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$$ language 'sql' STABLE STRICT;
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-- Returns the table name with geoms for the given geometry_id
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-- TODO probably needs to take in the column_id array to get the relevant
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-- table where there is multiple sources for a column from multiple
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-- geometries.
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CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GeomTable(
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geom geometry,
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geometry_id text
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)
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RETURNS TEXT
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AS $$
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DECLARE
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result text;
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BEGIN
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EXECUTE '
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SELECT tablename FROM observatory.OBS_table
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WHERE id IN (
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SELECT table_id
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FROM observatory.OBS_table tab,
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observatory.OBS_column_table coltable,
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observatory.OBS_column col
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WHERE type ILIKE ''geometry''
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AND coltable.column_id = col.id
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AND coltable.table_id = tab.id
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AND col.id = $1
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)
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'
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USING geometry_id, geom
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INTO result;
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return result;
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END;
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$$ LANGUAGE plpgsql;
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-- A type for use with the OBS_GetColumnData function
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CREATE TYPE cdb_observatory.OBS_ColumnData AS (colname text, tablename text, aggregate text);
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-- A function that gets the column data for multiple columns
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-- Old: OBS_GetColumnData
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CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetColumnData(
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geometry_id text,
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column_ids text[],
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timespan text
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)
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RETURNS cdb_observatory.OBS_ColumnData[]
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AS $$
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DECLARE
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result cdb_observatory.OBS_ColumnData[];
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BEGIN
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EXECUTE '
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WITH geomref AS (
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SELECT t.table_id id
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FROM observatory.OBS_column_to_column c2c, observatory.OBS_column_table t
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WHERE c2c.reltype = ''geom_ref''
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AND c2c.target_id = $1
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AND c2c.source_id = t.column_id
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),
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column_ids as (
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select row_number() over () as no, a.column_id as column_id from (select unnest($2) as column_id) a
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)
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SELECT array_agg(ROW(colname, tablename, aggregate)::cdb_observatory.OBS_ColumnData order by column_ids.no)
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FROM column_ids, observatory.OBS_column c, observatory.OBS_column_table ct, observatory.OBS_table t
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WHERE column_ids.column_id = c.id
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AND c.id = ct.column_id
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AND t.id = ct.table_id
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AND t.timespan = $3
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AND t.id in (SELECT id FROM geomref)
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'
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USING geometry_id, column_ids, timespan
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INTO result;
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RETURN result;
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END;
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$$ LANGUAGE plpgsql;
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--Gets the column id for a census variable given a human readable version of it
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-- Old: OBS_LOOKUP_CENSUS_HUMAN
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CREATE OR REPLACE FUNCTION cdb_observatory._OBS_LookupCensusHuman(
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column_names text[],
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-- TODO: change variable name table_name to table_id
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table_name text DEFAULT '"us.census.acs".extract_block_group_5yr_2013_69b156927c'
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)
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RETURNS text[] as $$
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DECLARE
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column_id text;
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result text;
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BEGIN
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EXECUTE format('
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WITH col_names AS (
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select row_number() over() as no, a.column_name as column_name from(
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select unnest($1) as column_name
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) a
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)
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select array_agg(column_id order by col_names.no)
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FROM observatory.OBS_column_table,col_names
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where colname = col_names.column_name
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and table_id = %L limit 1
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', table_name)
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INTO result
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using column_names;
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RETURN result;
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END
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$$ LANGUAGE plpgsql;
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--Test point cause Stuart always seems to make random points in the water
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CREATE OR REPLACE FUNCTION cdb_observatory._TestPoint()
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RETURNS geometry
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AS $$
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BEGIN
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-- new york city
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RETURN CDB_LatLng(40.704512, -73.936669);
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END;
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$$ LANGUAGE plpgsql;
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--Test polygon cause Stuart always seems to make random points in the water
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-- TODO: remove as it's not used anywhere?
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CREATE OR REPLACE FUNCTION cdb_observatory._TestArea()
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RETURNS geometry
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AS $$
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BEGIN
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-- Buffer NYC point by 500 meters
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RETURN ST_Buffer(cdb_observatory._TestPoint()::geography, 500)::geometry;
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END;
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$$ LANGUAGE plpgsql;
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--Used to expand a column based response to a table based one. Give it the desired
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--columns and it will return a partial query for rolling them out to a table.
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CREATE OR REPLACE FUNCTION cdb_observatory._OBS_BuildSnapshotQuery(names text[])
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RETURNS TEXT
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AS $$
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DECLARE
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q text;
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i numeric;
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BEGIN
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q := 'SELECT ';
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FOR i IN 1..array_upper(names,1)
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LOOP
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q = q || format(' vals[%s] As %I', i, names[i]);
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IF i < array_upper(names, 1) THEN
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q= q || ',';
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END IF;
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END LOOP;
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RETURN q;
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END;
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$$ LANGUAGE plpgsql;
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--For Longer term Dev
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--Break out table definitions to types
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--Automate type creation from a script, something like
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----CREATE OR REPLACE FUNCTION OBS_Get<%=tag_name%>(geom GEOMETRY)
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----RETURNS TABLE(
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----<%=get_dimensions_for_tag(tag_name)%>
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----AS $$
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----DECLARE
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----target_cols text[];
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----names text[];
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----vals NUMERIC[];-
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----q text;
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----BEGIN
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----target_cols := Array[<%=get_dimensions_for_tag(tag_name)%>],
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--Functions for augmenting specific tables
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--------------------------------------------------------------------------------
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-- Creates a table of demographic snapshot
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CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetDemographicSnapshot(geom geometry, time_span text default '2009 - 2013', geometry_level text default '"us.census.tiger".block_group')
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RETURNS json
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AS $$
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BEGIN
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RETURN row_to_json(cdb_observatory._OBS_GetDemographicSnapshot(geom, time_span, geometry_level));
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END;
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$$ LANGUAGE plpgsql;
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CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetDemographicSnapshot(geom geometry, time_span text default '2009 - 2013', geometry_level text default '"us.census.tiger".block_group' )
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RETURNS TABLE(
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total_pop NUMERIC,
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male_pop NUMERIC,
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female_pop NUMERIC,
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median_age NUMERIC,
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white_pop NUMERIC,
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black_pop NUMERIC,
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asian_pop NUMERIC,
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hispanic_pop NUMERIC,
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amerindian_pop NUMERIC,
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other_race_pop NUMERIC,
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two_or_more_races_pop NUMERIC,
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not_hispanic_pop NUMERIC,
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--not_us_citizen_pop NUMERIC,
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--workers_16_and_over NUMERIC,
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--commuters_by_car_truck_van NUMERIC,
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--commuters_drove_alone NUMERIC,
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--commuters_by_carpool NUMERIC,
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--commuters_by_public_transportation NUMERIC,
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--commuters_by_bus NUMERIC,
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--commuters_by_subway_or_elevated NUMERIC,
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--walked_to_work NUMERIC,
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--worked_at_home NUMERIC,
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--children NUMERIC, -- TODO we should be able to get this at BG
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households NUMERIC,
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--population_3_years_over NUMERIC,
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--in_school NUMERIC,
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--in_grades_1_to_4 NUMERIC,
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--in_grades_5_to_8 NUMERIC,
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--in_grades_9_to_12 NUMERIC,
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--in_undergrad_college NUMERIC,
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pop_25_years_over NUMERIC,
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high_school_diploma NUMERIC,
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less_one_year_college NUMERIC,
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one_year_more_college NUMERIC,
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associates_degree NUMERIC,
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bachelors_degree NUMERIC,
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masters_degree NUMERIC,
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--pop_5_years_over NUMERIC,
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--speak_only_english_at_home NUMERIC,
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--speak_spanish_at_home NUMERIC,
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--pop_determined_poverty_status NUMERIC,
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--poverty NUMERIC,
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median_income NUMERIC,
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gini_index NUMERIC,
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income_per_capita NUMERIC,
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housing_units NUMERIC,
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vacant_housing_units NUMERIC,
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vacant_housing_units_for_rent NUMERIC,
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vacant_housing_units_for_sale NUMERIC,
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median_rent NUMERIC,
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percent_income_spent_on_rent NUMERIC,
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owner_occupied_housing_units NUMERIC,
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million_dollar_housing_units NUMERIC,
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mortgaged_housing_units NUMERIC,
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--pop_15_and_over NUMERIC,
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--pop_never_married NUMERIC,
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--pop_now_married NUMERIC,
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--pop_separated NUMERIC,
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--pop_widowed NUMERIC,
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--pop_divorced NUMERIC,
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commuters_16_over NUMERIC,
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commute_less_10_mins NUMERIC,
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commute_10_14_mins NUMERIC,
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commute_15_19_mins NUMERIC,
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commute_20_24_mins NUMERIC,
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commute_25_29_mins NUMERIC,
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commute_30_34_mins NUMERIC,
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commute_35_44_mins NUMERIC,
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commute_45_59_mins NUMERIC,
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commute_60_more_mins NUMERIC,
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aggregate_travel_time_to_work NUMERIC,
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income_less_10000 NUMERIC,
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income_10000_14999 NUMERIC,
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income_15000_19999 NUMERIC,
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income_20000_24999 NUMERIC,
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income_25000_29999 NUMERIC,
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income_30000_34999 NUMERIC,
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income_35000_39999 NUMERIC,
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income_40000_44999 NUMERIC,
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income_45000_49999 NUMERIC,
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income_50000_59999 NUMERIC,
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income_60000_74999 NUMERIC,
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income_75000_99999 NUMERIC,
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income_100000_124999 NUMERIC,
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income_125000_149999 NUMERIC,
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income_150000_199999 NUMERIC,
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income_200000_or_more NUMERIC,
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land_area NUMERIC)
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AS $$
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DECLARE
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target_cols text[];
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names text[];
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vals NUMERIC[];
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q text;
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BEGIN
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target_cols := Array['total_pop',
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'male_pop',
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'female_pop',
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'median_age',
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'white_pop',
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'black_pop',
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'asian_pop',
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'hispanic_pop',
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'amerindian_pop',
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'other_race_pop',
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'two_or_more_races_pop',
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'not_hispanic_pop',
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--'not_us_citizen_pop',
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--'workers_16_and_over',
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--'commuters_by_car_truck_van',
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--'commuters_drove_alone',
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--'commuters_by_carpool',
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--'commuters_by_public_transportation',
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--'commuters_by_bus',
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--'commuters_by_subway_or_elevated',
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--'walked_to_work',
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--'worked_at_home',
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--'children',
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'households',
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--'population_3_years_over',
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--'in_school',
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--'in_grades_1_to_4',
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--'in_grades_5_to_8',
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--'in_grades_9_to_12',
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--'in_undergrad_college',
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'pop_25_years_over',
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'high_school_diploma',
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'less_one_year_college',
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'one_year_more_college',
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'associates_degree',
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'bachelors_degree',
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'masters_degree',
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--'pop_5_years_over',
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--'speak_only_english_at_home',
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--'speak_spanish_at_home',
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--'pop_determined_poverty_status',
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--'poverty',
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'median_income',
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'gini_index',
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'income_per_capita',
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'housing_units',
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'vacant_housing_units',
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'vacant_housing_units_for_rent',
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'vacant_housing_units_for_sale',
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'median_rent',
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'percent_income_spent_on_rent',
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'owner_occupied_housing_units',
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'million_dollar_housing_units',
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'mortgaged_housing_units',
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--'pop_15_and_over',
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--'pop_never_married',
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--'pop_now_married',
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--'pop_separated',
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--'pop_widowed',
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--'pop_divorced',
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'commuters_16_over',
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'commute_less_10_mins',
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'commute_10_14_mins',
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'commute_15_19_mins',
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'commute_20_24_mins',
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'commute_25_29_mins',
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'commute_30_34_mins',
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'commute_35_44_mins',
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'commute_45_59_mins',
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'commute_60_more_mins',
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'aggregate_travel_time_to_work',
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'income_less_10000',
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'income_10000_14999',
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'income_15000_19999',
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'income_20000_24999',
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'income_25000_29999',
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'income_30000_34999',
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'income_35000_39999',
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'income_40000_44999',
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'income_45000_49999',
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'income_50000_59999',
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'income_60000_74999',
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'income_75000_99999',
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'income_100000_124999',
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'income_125000_149999',
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'income_150000_199999',
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'income_200000_or_more',
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'land_area'];
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q := 'WITH a As (
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SELECT
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dimension As names,
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dimension_value As vals
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FROM cdb_observatory._OBS_GetCensus($1,$2,$3,$4)
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)' ||
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cdb_observatory._OBS_BuildSnapshotQuery(target_cols) ||
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' FROM a';
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RETURN QUERY
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EXECUTE
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q
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USING geom, target_cols, time_span, geometry_level;
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RETURN;
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END;
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$$ LANGUAGE plpgsql;
|
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|
|
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--Base functions for performing augmentation
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|
----------------------------------------------------------------------------------------
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|
|
|
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--Returns arrays of values for the given census dimension names for a given
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--point or polygon
|
|
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetCensus(
|
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geom geometry,
|
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dimension_names text[],
|
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time_span text DEFAULT '2009 - 2013',
|
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geometry_level text DEFAULT '"us.census.tiger".block_group'
|
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)
|
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RETURNS TABLE(dimension text[], dimension_value NUMERIC[])
|
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AS $$
|
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DECLARE
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ids text[];
|
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BEGIN
|
|
|
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ids := cdb_observatory._OBS_LookupCensusHuman(dimension_names);
|
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|
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RETURN QUERY
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SELECT names, vals FROM cdb_observatory._OBS_Get(geom, ids, time_span, geometry_level);
|
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END;
|
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$$ LANGUAGE plpgsql;
|
|
|
|
|
|
|
|
-- Base augmentation fucntion.
|
|
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_Get(
|
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geom geometry,
|
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column_ids text[],
|
|
time_span text,
|
|
geometry_level text
|
|
)
|
|
RETURNS TABLE(names text[], vals NUMERIC[])
|
|
AS $$
|
|
DECLARE
|
|
results NUMERIC[];
|
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geom_table_name text;
|
|
names text[];
|
|
query text;
|
|
data_table_info cdb_observatory.OBS_ColumnData[];
|
|
BEGIN
|
|
|
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geom_table_name := cdb_observatory._OBS_GeomTable(geom, geometry_level);
|
|
|
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IF geom_table_name IS NULL
|
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THEN
|
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RAISE NOTICE 'Point % is outside of the data region', geom;
|
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RETURN QUERY SELECT '{}'::text[], '{}'::NUMERIC[];
|
|
END IF;
|
|
|
|
data_table_info := cdb_observatory._OBS_GetColumnData(geometry_level,
|
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column_ids,
|
|
time_span);
|
|
|
|
names := (SELECT array_agg((d).colname)
|
|
FROM unnest(data_table_info) As d);
|
|
|
|
IF ST_GeometryType(geom) = 'ST_Point'
|
|
THEN
|
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results := cdb_observatory._OBS_GetPoints(geom,
|
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geom_table_name,
|
|
data_table_info);
|
|
|
|
ELSIF ST_GeometryType(geom) IN ('ST_Polygon', 'ST_MultiPolygon')
|
|
THEN
|
|
results := cdb_observatory._OBS_GetPolygons(geom,
|
|
geom_table_name,
|
|
data_table_info);
|
|
END IF;
|
|
|
|
IF results IS NULL
|
|
THEN
|
|
results := Array[]::numeric[];
|
|
END IF;
|
|
|
|
RETURN QUERY SELECT names, results;
|
|
END;
|
|
$$ LANGUAGE plpgsql;
|
|
|
|
|
|
-- If the variable of interest is just a rate return it as such,
|
|
-- otherwise normalize it to the census block area and return that
|
|
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetPoints(
|
|
geom geometry,
|
|
geom_table_name text,
|
|
data_table_info cdb_observatory.OBS_ColumnData[]
|
|
)
|
|
RETURNS NUMERIC[]
|
|
AS $$
|
|
DECLARE
|
|
result NUMERIC[];
|
|
query text;
|
|
i int;
|
|
geoid text;
|
|
area NUMERIC;
|
|
BEGIN
|
|
|
|
-- TODO: does 'geoid' need to be generalized to geom_ref??
|
|
EXECUTE
|
|
format('SELECT geoid
|
|
FROM observatory.%I
|
|
WHERE ST_WITHIN($1, the_geom)',
|
|
geom_table_name)
|
|
USING geom
|
|
INTO geoid;
|
|
|
|
RAISE NOTICE 'geoid is %, geometry table is % ', geoid, geom_table_name;
|
|
|
|
EXECUTE
|
|
format('SELECT ST_Area(the_geom::geography) / (1000 * 1000)
|
|
FROM observatory.%I
|
|
WHERE geoid = %L',
|
|
geom_table_name,
|
|
geoid)
|
|
INTO area;
|
|
|
|
IF area IS NULL
|
|
THEN
|
|
RAISE NOTICE 'No geometry at %', ST_AsText(geom);
|
|
END IF;
|
|
|
|
query := 'SELECT Array[';
|
|
FOR i IN 1..array_upper(data_table_info, 1)
|
|
LOOP
|
|
IF area is NULL OR area = 0
|
|
THEN
|
|
-- give back null values
|
|
query := query || format('NULL::numeric ');
|
|
ELSIF ((data_table_info)[i]).aggregate != 'sum'
|
|
THEN
|
|
-- give back full variable
|
|
query := query || format('%I ', ((data_table_info)[i]).colname);
|
|
ELSE
|
|
-- give back variable normalized by area of geography
|
|
query := query || format('%I/%s ',
|
|
((data_table_info)[i]).colname,
|
|
area);
|
|
END IF;
|
|
|
|
IF i < array_upper(data_table_info, 1)
|
|
THEN
|
|
query := query || ',';
|
|
END IF;
|
|
END LOOP;
|
|
|
|
query := query || format(' ]::numeric[]
|
|
FROM observatory.%I
|
|
WHERE %I.geoid = %L
|
|
',
|
|
((data_table_info)[1]).tablename,
|
|
((data_table_info)[1]).tablename,
|
|
geoid
|
|
);
|
|
|
|
EXECUTE
|
|
query
|
|
INTO result
|
|
USING geom;
|
|
|
|
RETURN result;
|
|
END;
|
|
$$ LANGUAGE plpgsql;
|
|
|
|
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetPolygons(
|
|
geom geometry,
|
|
geom_table_name text,
|
|
data_table_info cdb_observatory.OBS_ColumnData[]
|
|
)
|
|
RETURNS NUMERIC[]
|
|
AS $$
|
|
DECLARE
|
|
result NUMERIC[];
|
|
q_select text;
|
|
q_sum text;
|
|
q text;
|
|
i NUMERIC;
|
|
BEGIN
|
|
|
|
q_select := 'SELECT geoid, ';
|
|
q_sum := 'SELECT Array[';
|
|
|
|
FOR i IN 1..array_upper(data_table_info, 1)
|
|
LOOP
|
|
q_select := q_select || format( '%I ', ((data_table_info)[i]).colname);
|
|
|
|
IF ((data_table_info)[i]).aggregate ='sum'
|
|
THEN
|
|
q_sum := q_sum || format('sum(overlap_fraction * COALESCE(%I, 0)) ',((data_table_info)[i]).colname,((data_table_info)[i]).colname);
|
|
ELSE
|
|
q_sum := q_sum || ' NULL::numeric ';
|
|
END IF;
|
|
|
|
IF i < array_upper(data_table_info,1)
|
|
THEN
|
|
q_select := q_select || format(',');
|
|
q_sum := q_sum || format(',');
|
|
END IF;
|
|
END LOOP;
|
|
|
|
q = format('
|
|
WITH _overlaps As (
|
|
SELECT ST_Area(
|
|
ST_Intersection($1, a.the_geom)
|
|
) / ST_Area(a.the_geom) As overlap_fraction,
|
|
geoid
|
|
FROM observatory.%I As a
|
|
WHERE $1 && a.the_geom
|
|
),
|
|
values As (
|
|
', geom_table_name);
|
|
|
|
q := q || q_select || format('FROM observatory.%I ', ((data_table_info)[1].tablename));
|
|
|
|
q := q || ' ) ' || q_sum || ' ]::numeric[] FROM _overlaps, values
|
|
WHERE values.geoid = _overlaps.geoid';
|
|
|
|
EXECUTE
|
|
q
|
|
INTO result
|
|
USING geom;
|
|
|
|
RETURN result;
|
|
END;
|
|
$$ LANGUAGE plpgsql;
|
|
|
|
CREATE OR REPLACE FUNCTION OBS_GetSegmentSnapshot(geom geometry, geometry_level text default '"us.census.tiger".census_tract')
|
|
RETURNS json
|
|
AS $$
|
|
BEGIN
|
|
RETURN row_to_json(cdb_observatory._OBS_GetSegmentSnapshot(geom, geometry_level));
|
|
END;
|
|
$$ LANGUAGE plpgsql;
|
|
|
|
CREATE OR REPLACE FUNCTION _OBS_GetSegmentSnapshot(
|
|
geom geometry,
|
|
geometry_level text DEFAULT '"us.census.tiger".census_tract'
|
|
)
|
|
RETURNS TABLE(
|
|
segment_name TEXT,
|
|
total_pop_quantile NUMERIC,
|
|
male_pop_quantile NUMERIC,
|
|
female_pop_quantile NUMERIC,
|
|
median_age_quantile NUMERIC,
|
|
white_pop_quantile NUMERIC,
|
|
black_pop_quantile NUMERIC,
|
|
asian_pop_quantile NUMERIC,
|
|
hispanic_pop_quantile NUMERIC,
|
|
not_us_citizen_pop_quantile NUMERIC,
|
|
workers_16_and_over_quantile NUMERIC,
|
|
commuters_by_car_truck_van_quantile NUMERIC,
|
|
commuters_by_public_transportation_quantile NUMERIC,
|
|
commuters_by_bus_quantile NUMERIC,
|
|
commuters_by_subway_or_elevated_quantile NUMERIC,
|
|
walked_to_work_quantile NUMERIC,
|
|
worked_at_home_quantile NUMERIC,
|
|
children_quantile NUMERIC,
|
|
households_quantile NUMERIC,
|
|
population_3_years_over_quantile NUMERIC,
|
|
in_school_quantile NUMERIC,
|
|
in_grades_1_to_4_quantile NUMERIC,
|
|
in_grades_5_to_8_quantile NUMERIC,
|
|
in_grades_9_to_12_quantile NUMERIC,
|
|
in_undergrad_college_quantile NUMERIC,
|
|
pop_25_years_over_quantile NUMERIC,
|
|
high_school_diploma_quantile NUMERIC,
|
|
bachelors_degree_quantile NUMERIC,
|
|
masters_degree_quantile NUMERIC,
|
|
pop_5_years_over_quantile NUMERIC,
|
|
speak_only_english_at_home_quantile NUMERIC,
|
|
speak_spanish_at_home_quantile NUMERIC,
|
|
pop_determined_poverty_status_quantile NUMERIC,
|
|
poverty_quantile NUMERIC,
|
|
median_income_quantile NUMERIC,
|
|
gini_index_quantile NUMERIC,
|
|
income_per_capita_quantile NUMERIC,
|
|
housing_units_quantile NUMERIC,
|
|
vacant_housing_units_quantile NUMERIC,
|
|
vacant_housing_units_for_rent_quantile NUMERIC,
|
|
vacant_housing_units_for_sale_quantile NUMERIC,
|
|
median_rent_quantile NUMERIC,
|
|
percent_income_spent_on_rent_quantile NUMERIC,
|
|
owner_occupied_housing_units_quantile NUMERIC,
|
|
million_dollar_housing_units_quantile NUMERIC
|
|
)
|
|
AS $$
|
|
DECLARE
|
|
target_cols text[];
|
|
seg_name Text;
|
|
geom_id Text;
|
|
q Text;
|
|
BEGIN
|
|
target_cols := Array[
|
|
'"us.census.acs".B01001001_quantile',
|
|
'"us.census.acs".B01001002_quantile',
|
|
'"us.census.acs".B01001026_quantile',
|
|
'"us.census.acs".B01002001_quantile',
|
|
'"us.census.acs".B03002003_quantile',
|
|
'"us.census.acs".B03002004_quantile',
|
|
'"us.census.acs".B03002006_quantile',
|
|
'"us.census.acs".B03002012_quantile',
|
|
'"us.census.acs".B05001006_quantile',--
|
|
'"us.census.acs".B08006001_quantile',--
|
|
'"us.census.acs".B08006002_quantile',--
|
|
'"us.census.acs".B08006008_quantile',--
|
|
'"us.census.acs".B08006009_quantile',--
|
|
'"us.census.acs".B08006011_quantile',--
|
|
'"us.census.acs".B08006015_quantile',--
|
|
'"us.census.acs".B08006017_quantile',--
|
|
'"us.census.acs".B09001001_quantile',--
|
|
'"us.census.acs".B11001001_quantile',
|
|
'"us.census.acs".B14001001_quantile',--
|
|
'"us.census.acs".B14001002_quantile',--
|
|
'"us.census.acs".B14001005_quantile',--
|
|
'"us.census.acs".B14001006_quantile',--
|
|
'"us.census.acs".B14001007_quantile',--
|
|
'"us.census.acs".B14001008_quantile',--
|
|
'"us.census.acs".B15003001_quantile',
|
|
'"us.census.acs".B15003017_quantile',
|
|
'"us.census.acs".B15003022_quantile',
|
|
'"us.census.acs".B15003023_quantile',
|
|
'"us.census.acs".B16001001_quantile',--
|
|
'"us.census.acs".B16001002_quantile',--
|
|
'"us.census.acs".B16001003_quantile',--
|
|
'"us.census.acs".B17001001_quantile',--
|
|
'"us.census.acs".B17001002_quantile',--
|
|
'"us.census.acs".B19013001_quantile',
|
|
'"us.census.acs".B19083001_quantile',
|
|
'"us.census.acs".B19301001_quantile',
|
|
'"us.census.acs".B25001001_quantile',
|
|
'"us.census.acs".B25002003_quantile',
|
|
'"us.census.acs".B25004002_quantile',
|
|
'"us.census.acs".B25004004_quantile',
|
|
'"us.census.acs".B25058001_quantile',
|
|
'"us.census.acs".B25071001_quantile',
|
|
'"us.census.acs".B25075001_quantile',
|
|
'"us.census.acs".B25075025_quantile'
|
|
];
|
|
|
|
EXECUTE
|
|
$query$
|
|
SELECT (categories)[1]
|
|
FROM cdb_observatory._OBS_GetCategories(
|
|
$1,
|
|
Array['"us.census.spielman_singleton_segments".X10'],
|
|
$2)
|
|
LIMIT 1
|
|
$query$
|
|
INTO segment_name
|
|
USING geom, geometry_level;
|
|
|
|
q :=
|
|
format($query$
|
|
WITH a As (
|
|
SELECT
|
|
names As names,
|
|
vals As vals
|
|
FROM cdb_observatory._OBS_Get($1,
|
|
$2,
|
|
'2009 - 2013',
|
|
$3)
|
|
|
|
), percentiles As (
|
|
%s
|
|
FROM a)
|
|
SELECT $4, percentiles.*
|
|
FROM percentiles
|
|
$query$, cdb_observatory._OBS_BuildSnapshotQuery(target_cols));
|
|
|
|
RETURN QUERY
|
|
EXECUTE
|
|
q
|
|
USING geom, target_cols, geometry_level, segment_name;
|
|
|
|
END;
|
|
$$ LANGUAGE plpgsql;
|
|
|
|
--Get categorical variables from point
|
|
|
|
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetCategories(
|
|
geom geometry,
|
|
dimension_names text[],
|
|
geometry_level text DEFAULT '"us.census.tiger".block_group',
|
|
time_span text DEFAULT '2009 - 2013'
|
|
)
|
|
RETURNS TABLE(names text[], categories text[]) as $$
|
|
DECLARE
|
|
geom_table_name text;
|
|
geoid text;
|
|
names text[];
|
|
results text[];
|
|
query text;
|
|
data_table_info cdb_observatory.OBS_ColumnData[];
|
|
BEGIN
|
|
|
|
geom_table_name := cdb_observatory._OBS_GeomTable(geom, geometry_level);
|
|
|
|
IF geom_table_name IS NULL
|
|
THEN
|
|
RAISE NOTICE 'Point % is outside of the data region', ST_AsText(geom);
|
|
RETURN QUERY SELECT '{}'::text[], '{}'::text[];
|
|
END IF;
|
|
|
|
data_table_info := cdb_observatory._OBS_GetColumnData(geometry_level,
|
|
dimension_names,
|
|
time_span);
|
|
|
|
|
|
names := (SELECT array_agg((d).colname)
|
|
FROM unnest(data_table_info) As d);
|
|
|
|
|
|
EXECUTE
|
|
format('SELECT geoid
|
|
FROM observatory.%I
|
|
WHERE the_geom && $1',
|
|
geom_table_name)
|
|
USING geom
|
|
INTO geoid;
|
|
|
|
query := 'SELECT ARRAY[';
|
|
FOR i IN 1..array_upper(data_table_info, 1)
|
|
LOOP
|
|
query = query || format('%I ', lower(((data_table_info)[i]).colname));
|
|
IF i < array_upper(data_table_info, 1)
|
|
THEN
|
|
query := query || ',';
|
|
END IF;
|
|
END LOOP;
|
|
|
|
query := query || format(' ]::text[]
|
|
FROM observatory.%I
|
|
WHERE %I.geoid = %L
|
|
',
|
|
((data_table_info)[1]).tablename,
|
|
((data_table_info)[1]).tablename,
|
|
geoid
|
|
);
|
|
|
|
EXECUTE
|
|
query
|
|
INTO results
|
|
USING geom;
|
|
|
|
RETURN QUERY
|
|
SELECT names,results
|
|
RETURN;
|
|
|
|
END;
|
|
$$ LANGUAGE plpgsql;
|
|
-- Placeholder for permission tweaks at creation time.
|
|
-- Make sure by default there are no permissions for publicuser
|
|
-- NOTE: this happens at extension creation time, as part of an implicit transaction.
|
|
-- REVOKE ALL PRIVILEGES ON SCHEMA cdb_observatory FROM PUBLIC, publicuser CASCADE;
|
|
|
|
-- Grant permissions on the schema to publicuser (but just the schema)
|
|
-- GRANT USAGE ON SCHEMA cdb_crankshaft TO publicuser;
|
|
|
|
-- Revoke execute permissions on all functions in the schema by default
|
|
-- REVOKE EXECUTE ON ALL FUNCTIONS IN SCHEMA cdb_observatory FROM PUBLIC, publicuser;
|