4e82907a70
Propagates the conformed city key (city_slug) from dim_venues through the full pricing pipeline, eliminating 3 fragile LOWER(TRIM(...)) fuzzy string joins with deterministic key joins. Changes (cascading, task-by-task): - dim_venues: add city_slug computed column (REGEXP_REPLACE slug derivation) - dim_venue_capacity: join foundation.dim_venues instead of stg_playtomic_venues; carry city_slug alongside country_code/city - fct_daily_availability: carry city_slug from dim_venue_capacity - venue_pricing_benchmarks: carry city_slug from fct_daily_availability; add to venue_stats GROUP BY and final SELECT/GROUP BY - city_market_profile: join vpb on city_slug = city_slug (was LOWER(TRIM)) - planner_defaults: add city_slug to city_benchmarks CTE; join on city_slug - pseo_city_pricing: join city_market_profile on city_slug (was LOWER(TRIM)) - pipeline_routes._DAG: dim_venue_capacity now depends on dim_venues, not stg_playtomic_venues Result: dim_venues.city_slug → dim_cities.(country_code, city_slug) forms a fully conformed geographic hierarchy with no fuzzy string comparisons. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
109 lines
3.5 KiB
SQL
109 lines
3.5 KiB
SQL
-- Deduplicated venue dimension combining OSM courts and Playtomic tenants.
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-- Venues from both sources are unioned; near-duplicates (within ~100m) are
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-- collapsed to a single record preferring Playtomic data (richer metadata).
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-- Proximity dedup uses haversine approximation: 1 degree lat ≈ 111 km.
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--
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-- Playtomic venues include court counts, indoor/outdoor split, currency, and timezone.
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MODEL (
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name foundation.dim_venues,
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kind FULL,
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cron '@daily',
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grain venue_id
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);
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WITH playtomic_venues AS (
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SELECT
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'pt:' || v.tenant_id AS venue_id,
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v.tenant_id,
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'playtomic' AS source,
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v.lat,
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v.lon,
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v.country_code,
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v.name,
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v.city,
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v.postcode,
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v.tenant_type,
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v.timezone,
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v.vat_rate,
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v.default_currency,
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-- Court counts from resources
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COUNT(r.resource_id) AS court_count,
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COUNT(r.resource_id) FILTER (WHERE r.resource_type = 'indoor') AS indoor_court_count,
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COUNT(r.resource_id) FILTER (WHERE r.resource_type = 'outdoor') AS outdoor_court_count,
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v.extracted_date
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FROM staging.stg_playtomic_venues v
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LEFT JOIN staging.stg_playtomic_resources r
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ON v.tenant_id = r.tenant_id AND r.is_active = TRUE
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WHERE v.country_code IS NOT NULL
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GROUP BY
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v.tenant_id, v.lat, v.lon, v.country_code, v.name, v.city,
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v.postcode, v.tenant_type, v.timezone, v.vat_rate,
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v.default_currency, v.extracted_date
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),
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osm_venues AS (
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SELECT
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'osm:' || osm_id::TEXT AS venue_id,
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NULL AS tenant_id,
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'osm' AS source,
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lat,
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lon,
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country_code,
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name,
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city,
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postcode,
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NULL AS tenant_type,
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NULL AS timezone,
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NULL AS vat_rate,
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NULL AS default_currency,
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NULL AS court_count,
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NULL AS indoor_court_count,
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NULL AS outdoor_court_count,
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extracted_date
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FROM staging.stg_padel_courts
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WHERE country_code IS NOT NULL
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),
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all_venues AS (
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SELECT * FROM playtomic_venues
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UNION ALL
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SELECT * FROM osm_venues
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),
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ranked AS (
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SELECT *,
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CASE source WHEN 'playtomic' THEN 1 ELSE 2 END AS source_rank
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FROM all_venues
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)
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-- Deduplicate on ~111m grid cells, preferring Playtomic
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SELECT
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MIN(venue_id) OVER (
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PARTITION BY country_code, ROUND(lat, 3)::TEXT, ROUND(lon, 3)::TEXT
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ORDER BY source_rank
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) AS venue_id,
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tenant_id,
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country_code,
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lat,
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lon,
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COALESCE(
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MAX(CASE WHEN source = 'playtomic' THEN name END)
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OVER (PARTITION BY country_code, ROUND(lat,3)::TEXT, ROUND(lon,3)::TEXT),
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name
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) AS name,
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COALESCE(city, '') AS city,
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postcode,
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source,
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tenant_type,
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timezone,
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vat_rate,
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default_currency,
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court_count,
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indoor_court_count,
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outdoor_court_count,
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-- Conformed city key: enables deterministic joins to dim_cities / venue_pricing_benchmarks
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LOWER(REGEXP_REPLACE(LOWER(COALESCE(city, '')), '[^a-z0-9]+', '-')) AS city_slug,
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extracted_date
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FROM ranked
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QUALIFY ROW_NUMBER() OVER (
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PARTITION BY country_code, ROUND(lat, 3)::TEXT, ROUND(lon, 3)::TEXT
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ORDER BY source_rank
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) = 1
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