colouring-montreal/maintenance/extract_data/export_attributes.sql
Tom Russell 0a86566821 Use Postgres COPY to extract data
- COPY typically runs faster than going via Python
- properly formatted JSON in edit history patches
- assumes postgres and maintenance user both have
  access to /tmp
2019-10-02 15:03:54 +01:00

54 lines
1.2 KiB
SQL

COPY (SELECT
building_id,
ref_toid,
ref_osm_id,
revision_id,
location_name,
location_number,
location_street,
location_line_two,
location_town,
location_postcode,
location_latitude,
location_longitude,
date_year,
date_lower,
date_upper,
date_source,
date_source_detail,
date_link,
facade_year,
facade_upper,
facade_lower,
facade_source,
facade_source_detail,
size_storeys_attic,
size_storeys_core,
size_storeys_basement,
size_height_apex,
size_floor_area_ground,
size_floor_area_total,
size_width_frontage,
likes_total,
planning_portal_link,
planning_in_conservation_area,
planning_conservation_area_name,
planning_in_list,
planning_list_id,
planning_list_cat,
planning_list_grade,
planning_heritage_at_risk_id,
planning_world_list_id,
planning_in_glher,
planning_glher_url,
planning_in_apa,
planning_apa_name,
planning_apa_tier,
planning_in_local_list,
planning_local_list_url,
planning_in_historic_area_assessment,
planning_historic_area_assessment_url
FROM buildings)
TO '/tmp/building_attributes.csv'
WITH CSV HEADER