From 6fa726bcce9e1c92609eb8514c14331cfe23586d Mon Sep 17 00:00:00 2001
From: Javier Goizueta <jgoizueta@gmail.com>
Date: Mon, 22 Feb 2016 13:27:31 +0100
Subject: [PATCH] Sketch of the cdb_population function

---
 pg/sql/0.0.1/population.sql | 136 ++++++++++++++++++++++++++++++++++++
 1 file changed, 136 insertions(+)
 create mode 100644 pg/sql/0.0.1/population.sql

diff --git a/pg/sql/0.0.1/population.sql b/pg/sql/0.0.1/population.sql
new file mode 100644
index 0000000..78b7e51
--- /dev/null
+++ b/pg/sql/0.0.1/population.sql
@@ -0,0 +1,136 @@
+-- Function to obtain an estimate of the population living inside
+-- an area (polygon) from the CartoDB Data Observatory
+CREATE OR REPLACE FUNCTION cdb_population(area geometry)
+RETURNS NUMERIC AS $$
+DECLARE
+  georef_column TEXT;
+  table_id TEXT;
+  tag_value TEXT;
+  table_name TEXT;
+  column_name TEXT;
+  population NUMERIC;
+BEGIN
+
+  -- Note: comments contain pseudo-code that should be implemented
+
+  -- Register metadata tables:
+  /*
+  SELECT cdb_add_remote_table('observatory', 'bmd_column_table');
+  SELECT cdb_add_remote_table('observatory', 'bmd_column_2_column');
+  SELECT cdb_add_remote_table('observatory', 'bmd_table');
+  SELECT cdb_add_remote_table('observatory', 'bmd_column_table');
+  SELECT cdb_add_remote_table('observatory', 'bmd_column_tag');
+  SELECT cdb_add_remote_table('observatory', 'bmd_tag');
+  */
+
+  tag_value := 'population';
+
+
+  -- Determine the georef column id to be used: it must have type 'geometry',
+  -- the maximum weight.
+  -- TODO: in general, multiple columns with maximal weight could be found;
+  -- we should use the timespan of the table to disambiguate (choose the
+  -- most recent). Also a rank of geometry columns should be introduced to
+  -- find select the greatest resolution available.
+  /*
+  WITH selected_tables AS (
+    -- Find tables that have population columns and cover the input area
+    SELECT tab.id AS id
+    FROM observatory.bmd_column col,
+         observatory.bmd_column_table coltab,
+         observatory.bmd_table tab,
+         observatory.bmd_tag tag,
+         observatory.bmd_column_tag coltag
+    WHERE coltab.column_id = col.id
+      AND coltab.table_id = tab.id
+      AND coltag.tag_id = tag.id
+      AND coltag.column_id = col.id
+      AND tag.name ILIKE tag_value
+      AND tab.id = table_id
+      AND tab.bounds && area;
+  )
+  SELECT
+    FROM bmd_column col
+    JOIN bmd_table tab ON col.table_id = tab.id
+    WHERE type = 'geometry'
+      AND tab.id IN (selected_tables)
+    ORDER BY weight DESC LIMIT 1;
+  */
+  georef_column := '"us.census.tiger".block_group_2013';
+
+  -- Now we will query the metadata to find which actual tables correspond
+  -- to this datasource and resolution/timespan
+  -- and choose the 'parent' or more general of them.
+  /*
+  SELECT from_table_geoid.id data_table_id
+  FROM observatory.bmd_column_table from_column_table_geoid,
+       observatory.bmd_column_table to_column_table_geoid,
+       observatory.bmd_column_2_column rel,
+       observatory.bmd_column_table to_column_table_geom,
+       observatory.bmd_table from_table_geoid,
+       observatory.bmd_table to_table_geoid,
+       observatory.bmd_table to_table_geom
+  WHERE from_column_table_geoid.column_id = to_column_table_geoid.column_id
+    AND to_column_table_geoid.column_id = rel.from_id
+    AND rel.reltype = 'geom_ref'
+    AND rel.to_id = to_column_table_geom.column_id
+    AND to_column_table_geom.column_id = georef_column
+    AND from_table_geoid.id = from_column_table_geoid.table_id
+    AND to_table_geoid.id = to_column_table_geoid.table_id
+    AND to_table_geom.id = to_column_table_geom.table_id
+    AND from_table_geoid.bounds && area
+  ORDER by from_table_geoid.timespan desc
+  INTO table_id;
+  */
+  table_id := '"us.census.acs".extract_2013_5yr_block_group';
+
+  -- Next will fetch the columns of that table that are tagged as population:
+  -- and get the more general one (not having a parent or denominator)
+  /*
+  WITH column_ids AS (
+    SELECT col.id AS id
+    FROM observatory.bmd_column col,
+         observatory.bmd_column_table coltab,
+         observatory.bmd_table tab,
+         observatory.bmd_tag tag,
+         observatory.bmd_column_tag coltag
+    WHERE coltab.column_id = col.id
+      AND coltab.table_id = tab.id
+      AND coltag.tag_id = tag.id
+      AND coltag.column_id = col.id
+      AND tag.name ILIKE tag_value
+      AND tab.id = table_id;
+  ),
+  excluded_column_ids AS (
+    SELECT from_id AS id
+    FROM observatory.bmd_column_2_column
+    WHERE from_id in (column_ids)
+      AND reltype in ('parent', 'denominator')
+      AND to_id in (column_ids)
+  ),
+  SELECT bmd_table.tablename, bmd_column_table.colname
+  FROM observatory.bmd_column_table,
+       observatory.bmd_table
+  WHERE bmd_column_table.table_id = bmd_table.id
+    AND bmd_column_table.column_id IN (column_ids)
+    AND NOT bmd_column_table.column_id IN (exclude_column_ids)
+  INTO (table_name, column_name);
+  */
+  table_name := 'us_census_acs2013_5yr_block_group';
+  column_name := 'total_pop';
+
+  -- Register the foreign table
+  SELECT cdb_add_remote_table('observatory', table_name);
+
+  -- Perform the query
+  SELECT cdb_crankshaft.cdb_overlap_sum(
+    area,
+    table_name,
+    table_column,
+    schema_name := 'observatory')
+  INTO population;
+
+  RETURN population;
+END;
+$$
+LANGUAGE plpgsql VOLATILE