359 lines
13 KiB
Python
359 lines
13 KiB
Python
#!/usr/bin/env python3
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"""
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Migrate and deduplicate Jordan (Amman, Zarqa, Irbid) Places Dataset into places_jordan table on PostgreSQL.
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Handles Arabic normalization, spatial bounding box filtering (Jordan bounds),
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exact deduplication, spatial near-duplicate filtering (< 50m), popularity scoring,
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and concurrent refresh of unified_search_index.
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"""
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import os
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import sys
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import csv
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import gzip
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import math
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import time
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import argparse
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from collections import defaultdict, Counter
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def haversine(lat1, lon1, lat2, lon2):
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R = 6371000 # meters
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phi1 = math.radians(lat1)
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phi2 = math.radians(lat2)
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delta_phi = math.radians(lat2 - lat1)
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delta_lambda = math.radians(lon2 - lon1)
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a = math.sin(delta_phi / 2)**2 + math.cos(phi1) * math.cos(phi2) * math.sin(delta_lambda / 2)**2
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return 2 * R * math.atan2(math.sqrt(a), math.sqrt(1 - a))
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def normalize_text(t):
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if not t:
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return ''
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s = t.strip()
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# Normalize Arabic alef, teh marbuta, etc.
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s = s.replace('أ', 'ا').replace('إ', 'ا').replace('آ', 'ا').replace('ة', 'ه').replace('ى', 'ي')
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return ' '.join(s.split()).lower()
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def clean_sql_str(val):
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if val is None:
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return 'NULL'
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s = str(val).strip().replace("'", "''")
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return f"'{s}'"
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def calculate_popularity(row):
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# Reviews and rating
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reviews = 0
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try:
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reviews = int(float(row.get('reviews_count') or 0))
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except Exception:
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reviews = 0
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rating = 0.0
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try:
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rating = float(row.get('rating') or 0)
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except Exception:
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rating = 0.0
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score = int(reviews * 0.2 + rating * 5)
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# Heuristic boost for critical POIs
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cat = row.get('category_queried', '')
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if any(k in cat for k in ['مستشفى', 'جامعة', 'كلية', 'مركز صحي', 'طوارئ', 'دفاع مدني']):
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score = max(score, 90)
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elif any(k in cat for k in ['صيدلية', 'بنك', 'صراف آلي', 'سوبر ماركت', 'محطة']):
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score = max(score, 60)
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elif any(k in cat for k in ['مدرسة', 'روضة', 'عيادة', 'بلدية', 'دائرة']):
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score = max(score, 50)
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return min(100, max(10, score))
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def main():
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parser = argparse.ArgumentParser(description="Migrate Jordan places dataset with deduplication.")
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parser.add_argument("--file", default="", help="Path to CSV file.")
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parser.add_argument("--db-host", default="127.0.0.1", help="Database host")
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parser.add_argument("--db-port", type=int, default=5432, help="Database port")
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parser.add_argument("--db-user", default="mapuser", help="Database user")
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parser.add_argument("--db-pass", default="mappass", help="Database password")
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parser.add_argument("--db-name", default="mapdb", help="Database name")
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parser.add_argument("--dry-run", action="store_true", help="Perform validation and deduplication only without inserting.")
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args = parser.parse_args()
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# Find file
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file_path = args.file
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if not file_path:
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candidates = [
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"data/checkpoint_35242_records.csv",
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"/home/hamzadoctor/app/data/checkpoint_35242_records.csv",
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"checkpoint_35242_records.csv"
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]
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for c in candidates:
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if os.path.exists(c):
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file_path = c
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break
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if not file_path or not os.path.exists(file_path):
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print(f"❌ Error: Dataset file not found: {file_path}")
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sys.exit(1)
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print(f"📂 Processing dataset: {file_path}")
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open_fn = gzip.open if file_path.endswith('.gz') else open
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mode = 'rt' if file_path.endswith('.gz') else 'r'
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total_read = 0
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empty_name = 0
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out_of_bounds = 0
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valid_records = []
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gov_counter = Counter()
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t0 = time.time()
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with open_fn(file_path, mode, encoding='utf-8-sig') as f:
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reader = csv.DictReader(f)
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for row in reader:
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total_read += 1
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name = row.get('name', '').strip()
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if not name:
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empty_name += 1
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continue
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try:
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lat = float(row['latitude'])
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lng = float(row['longitude'])
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except Exception:
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out_of_bounds += 1
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continue
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# Jordan bounding box check (29.15 to 33.45 Lat, 34.85 to 39.35 Lng)
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if not (29.15 <= lat <= 33.45 and 34.85 <= lng <= 39.35):
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out_of_bounds += 1
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continue
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category = row.get('category_queried', '').strip() or 'مكان عام'
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sector = row.get('sector', '').strip()
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gov = row.get('governorate', '').strip() or 'الأردن'
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area = row.get('area', '').strip()
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maps_url = row.get('maps_url', '').strip()
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address = f"{area}, {gov}, الأردن" if area else f"{gov}, الأردن"
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desc = sector if sector else 'نقطة اهتمام في الأردن'
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pop_score = calculate_popularity(row)
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gov_counter[gov] += 1
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valid_records.append({
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'name': name,
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'norm_name': normalize_text(name),
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'lat': lat,
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'lng': lng,
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'category': category,
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'city': gov,
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'neighbourhood': area,
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'address': address,
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'description': desc,
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'popularity_score': pop_score,
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'maps_url': maps_url,
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'sector': sector
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})
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print(f"📊 Initial parse complete in {time.time() - t0:.2f}s:")
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print(f" - Total rows in CSV: {total_read:,}")
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print(f" - Out of Jordan bounds / invalid coords: {out_of_bounds:,}")
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print(f" - Valid in Jordan bounds: {len(valid_records):,}")
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print(f" - Governorate distribution: {dict(gov_counter)}")
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# Deduplication Step 1: Exact (norm_name, round(lat, 5), round(lng, 5)) and maps_url
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seen_exact = {}
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seen_urls = {}
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exact_dups = 0
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for r in valid_records:
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k = (r['norm_name'], round(r['lat'], 5), round(r['lng'], 5))
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url = r['maps_url']
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if k in seen_exact:
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exact_dups += 1
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if r['popularity_score'] > seen_exact[k]['popularity_score']:
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seen_exact[k] = r
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continue
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if url and url in seen_urls:
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exact_dups += 1
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if r['popularity_score'] > seen_urls[url]['popularity_score']:
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seen_urls[url] = r
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continue
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seen_exact[k] = r
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if url:
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seen_urls[url] = r
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dedup_step1 = list(seen_exact.values())
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print(f"🔍 Step 1 Deduplication (Exact coords / URL):")
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print(f" - Removed {exact_dups} duplicate records.")
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print(f" - Remaining: {len(dedup_step1):,}")
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# Deduplication Step 2: Spatial near-duplicates (< 50m with identical normalized name)
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by_norm_name = defaultdict(list)
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for r in dedup_step1:
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by_norm_name[r['norm_name']].append(r)
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final_records = []
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near_dups_filtered = 0
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for norm_name, items in by_norm_name.items():
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if len(items) == 1:
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final_records.append(items[0])
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else:
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items.sort(key=lambda x: x['popularity_score'], reverse=True)
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kept = []
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for candidate in items:
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is_dup = False
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for existing in kept:
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d = haversine(candidate['lat'], candidate['lng'], existing['lat'], existing['lng'])
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if d < 50:
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is_dup = True
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near_dups_filtered += 1
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break
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if not is_dup:
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kept.append(candidate)
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final_records.extend(kept)
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print(f"🎯 Step 2 Deduplication (Spatial near-duplicates < 50m):")
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print(f" - Filtered out {near_dups_filtered} near-duplicates.")
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print(f" - Final unique clean places to migrate: {len(final_records):,}")
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final_govs = Counter([r['city'] for r in final_records])
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print(f" - Final Governorates: {dict(final_govs)}")
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if args.dry_run:
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print("💡 Dry run complete. No database changes made.")
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return
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# Database Migration
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import pg8000.native
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print(f"\n🔌 Connecting to PostgreSQL at {args.db_host}:{args.db_port} ({args.db_name})...")
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con = pg8000.native.Connection(
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user=args.db_user,
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password=args.db_pass,
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host=args.db_host,
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port=args.db_port,
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database=args.db_name
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)
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t_db = time.time()
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source_tag = 'checkpoint_35242_amman_zarqa'
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print(f"🗑️ Removing previous '{source_tag}' imports from places_jordan...")
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con.run("BEGIN;")
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con.run(f"DELETE FROM places_jordan WHERE source = '{source_tag}';")
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# Temporarily disable trigger for high-speed bulk ingestion
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print("⚡ Disabling location trigger for high-speed ingestion...")
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con.run("ALTER TABLE places_jordan DISABLE TRIGGER trg_sync_place_location_jordan;")
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batch_size = 2000
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total_inserted = 0
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print(f"🚀 Inserting {len(final_records):,} places in batches of {batch_size}...")
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for i in range(0, len(final_records), batch_size):
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batch = final_records[i:i + batch_size]
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values = []
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for r in batch:
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c_name = clean_sql_str(r['name'])
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c_cat = clean_sql_str(r['category'])
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c_city = clean_sql_str(r['city'])
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c_area = clean_sql_str(r['neighbourhood'])
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c_addr = clean_sql_str(r['address'])
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c_desc = clean_sql_str(r['description'])
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lat = r['lat']
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lng = r['lng']
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pop = r['popularity_score']
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line = (
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f"({c_name}, {c_name}, {lat:.7f}, {lng:.7f}, {c_cat}, {c_city}, {c_area}, "
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f"{c_addr}, {c_desc}, {pop}, '{source_tag}', "
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f"ST_SetSRID(ST_MakePoint({lng:.7f}, {lat:.7f}), 4326))"
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)
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values.append(line)
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sql = (
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"INSERT INTO places_jordan ("
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" name, name_ar, latitude, longitude, category, city, neighbourhood,"
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" address, description, popularity_score, source, location"
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") VALUES " + ",\n".join(values) + ";"
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)
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con.run(sql)
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total_inserted += len(batch)
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print(f" -> Inserted {total_inserted:,} / {len(final_records):,} places...")
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# Re-enable trigger
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print("⚡ Re-enabling location trigger...")
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con.run("ALTER TABLE places_jordan ENABLE TRIGGER trg_sync_place_location_jordan;")
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# Batch update governorate_id for Amman and Zarqa based on city name
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print("🏛️ Updating administrative links for new places...")
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con.run(f"""
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UPDATE places_jordan
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SET governorate_id = 137
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WHERE source = '{source_tag}' AND city = 'عمان';
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""")
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con.run(f"""
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UPDATE places_jordan
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SET governorate_id = 5
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WHERE source = '{source_tag}' AND city = 'الزرقاء';
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""")
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con.run(f"""
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UPDATE places_jordan
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SET governorate_id = 184
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WHERE source = '{source_tag}' AND city = 'إربد';
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""")
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con.run("COMMIT;")
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print(f"✅ Ingestion committed successfully in {time.time() - t_db:.2f}s!")
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# Refresh materialized view
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print("🔄 Refreshing materialized view unified_search_index concurrently...")
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t_mv = time.time()
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con.run("REFRESH MATERIALIZED VIEW CONCURRENTLY unified_search_index;")
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print(f"✅ unified_search_index refreshed in {time.time() - t_mv:.2f}s!")
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# Analyze table
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print("⚡ Running ANALYZE on places_jordan...")
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con.run("ANALYZE places_jordan;")
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# Verification
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print("\n🔍 Verification & Statistics:")
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count_res = con.run("SELECT count(*) FROM places_jordan;")[0][0]
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new_count = con.run(f"SELECT count(*) FROM places_jordan WHERE source = '{source_tag}';")[0][0]
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gov_stats = con.run(f"""
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SELECT city, count(*)
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FROM places_jordan
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WHERE source = '{source_tag}'
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GROUP BY city
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ORDER BY count(*) DESC;
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""")
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print(f" - Total places in places_jordan: {count_res:,}")
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print(f" - Newly added from Amman & Zarqa checkpoint: {new_count:,}")
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print(" - Governorates breakdown:")
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for gov, cnt in gov_stats:
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print(f" * {gov}: {cnt:,} places")
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# Sample Geocoding search test
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test_queries = ['صيدلية في عمان', 'الجبيهة', 'الزرقاء الجديدة', 'وسط البلد عمان', 'الشميساني']
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print("\n🧪 Testing search on unified_search_index:")
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for q in test_queries:
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results = con.run(f"""
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SELECT name, category, city, latitude, longitude
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FROM places_jordan
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WHERE (name ILIKE '%{q}%' OR neighbourhood ILIKE '%{q}%' OR address ILIKE '%{q}%')
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AND source = '{source_tag}'
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LIMIT 2;
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""")
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if results:
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first = results[0]
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print(f" ✓ Query '{q}': Found '{first[0]}' ({first[1]} - {first[2]}) @ {first[3]}, {first[4]}")
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else:
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print(f" - Query '{q}': No direct checkpoint match, checking overall...")
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con.close()
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print("\n🎉 Jordan dataset migration completed successfully!")
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if __name__ == '__main__':
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main()
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