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Aus_F / scripts /create_indexes.py

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"""
MongoDB Index Creation Script
Author: AI Generated
Created: 2025-11-24 (Fixed for actual schema)
Purpose: Create performance indexes matching actual MongoDB structure
"""

from database import db
from config import settings


def create_all_indexes():
    """
    Create all necessary indexes for optimal performance.
    Based on ACTUAL MongoDB structure from models.txt
    """
    
    print("=" * 60)
    print("🔧 Creating MongoDB Indexes (Corrected Schema)")
    print("=" * 60)
    
    # Payment Collection Indexes
    print("\n📊 Payment Collection:")
    
    # Index for event-specific ticket purchases
    db.payments.create_index(
        [("eventCode", 1), ("status", 1), ("userId", 1)],
        name="idx_payment_event_status_user"
    )
    print("  ✓ Created: idx_payment_event_status_user")
    
    # Index for user RFM calculation
    db.payments.create_index(
        [("userId", 1), ("transactionDate", -1)],
        name="idx_payment_user_date"
    )
    print("  ✓ Created: idx_payment_user_date")
    
    # User Collection Indexes (UserFollows is EMBEDDED)
    print("\n👥 User Collection:")
    
    # Index for finding users who follow a specific event
    # UserFollows is an embedded array, so we use dot notation
    db.users.create_index(
        [("UserFollows.eventCode", 1)],
        name="idx_user_follows_event",
        sparse=True  # Skip documents without UserFollows
    )
    print("  ✓ Created: idx_user_follows_event (embedded array)")
    
    # Index for user status (to filter Active users)
    db.users.create_index(
        [("status", 1)],
        name="idx_user_status"
    )
    print("  ✓ Created: idx_user_status")
    
    # PostSocialMedia Collection Indexes
    print("\n💬 PostSocialMedia Collection:")
    
    # Index for event-specific posts
    db.post_social_media.create_index(
        [("eventCode", 1), ("createdAt", -1)],
        name="idx_post_event_date"
    )
    print("  ✓ Created: idx_post_event_date")
    
    # Index for searching comments (nested in Images.UserCommentPosts)
    # Using wildcard for nested arrays
    db.post_social_media.create_index(
        [("eventCode", 1), ("images.userCommentPosts.commentedAt", -1)],
        name="idx_post_comments",
        sparse=True
    )
    print("  ✓ Created: idx_post_comments (nested array)")
    
    # EventAudienceSegment Collection Indexes
    print("\n🎯 EventAudienceSegment Collection:")
    
    # Index for event owner dashboard
    db.event_audience_segments.create_index(
        [("event_code", 1)],
        name="idx_segment_event"
    )
    print("  ✓ Created: idx_segment_event")
    
    # Index for status filtering
    db.event_audience_segments.create_index(
        [("event_code", 1), ("marketing_content.status", 1)],
        name="idx_segment_event_status"
    )
    print("  ✓ Created: idx_segment_event_status")
    
    # EventSentimentSummary Collection Indexes
    print("\n📊 EventSentimentSummary Collection:")
    
    # Index for event sentiment lookup
    db.event_sentiment_summary.create_index(
        [("event_code", 1), ("last_updated", -1)],
        name="idx_sentiment_event_date"
    )
    print("  ✓ Created: idx_sentiment_event_date")
    
    # SentimentAnalysisResult Collection Indexes
    print("\n💭 SentimentAnalysisResult Collection:")
    
    # Index for event-specific sentiment results
    db.sentiment_results.create_index(
        [("event_code", 1), ("analyzed_at", -1)],
        name="idx_sentiment_result_event_date"
    )
    print("  ✓ Created: idx_sentiment_result_event_date")
    
    # Index for sentiment label filtering
    db.sentiment_results.create_index(
        [("event_code", 1), ("sentiment_label", 1)],
        name="idx_sentiment_event_label"
    )
    print("  ✓ Created: idx_sentiment_event_label")
    
    print("\n" + "=" * 60)
    print("✅ All Indexes Created Successfully!")
    print("=" * 60)
    
    # List all indexes for verification
    print("\n📋 Index Summary:")
    print(f"  Payment: {len(list(db.payments.list_indexes()))} indexes")
    print(f"  User: {len(list(db.users.list_indexes()))} indexes")
    print(f"  PostSocialMedia: {len(list(db.post_social_media.list_indexes()))} indexes")
    print(f"  EventAudienceSegment: {len(list(db.event_audience_segments.list_indexes()))} indexes")
    print(f"  EventSentimentSummary: {len(list(db.event_sentiment_summary.list_indexes()))} indexes")
    print(f"  SentimentAnalysisResult: {len(list(db.sentiment_results.list_indexes()))} indexes")


if __name__ == "__main__":
    create_all_indexes()

	"""
	MongoDB Index Creation Script
	Author: AI Generated
	Created: 2025-11-24 (Fixed for actual schema)
	Purpose: Create performance indexes matching actual MongoDB structure
	"""

	from database import db
	from config import settings


	def create_all_indexes():
	"""
	Create all necessary indexes for optimal performance.
	Based on ACTUAL MongoDB structure from models.txt
	"""

	print("=" * 60)
	print("🔧 Creating MongoDB Indexes (Corrected Schema)")
	print("=" * 60)

	# Payment Collection Indexes
	print("\n📊 Payment Collection:")

	# Index for event-specific ticket purchases
	db.payments.create_index(
	[("eventCode", 1), ("status", 1), ("userId", 1)],
	name="idx_payment_event_status_user"
	)
	print(" ✓ Created: idx_payment_event_status_user")

	# Index for user RFM calculation
	db.payments.create_index(
	[("userId", 1), ("transactionDate", -1)],
	name="idx_payment_user_date"
	)
	print(" ✓ Created: idx_payment_user_date")

	# User Collection Indexes (UserFollows is EMBEDDED)
	print("\n👥 User Collection:")

	# Index for finding users who follow a specific event
	# UserFollows is an embedded array, so we use dot notation
	db.users.create_index(
	[("UserFollows.eventCode", 1)],
	name="idx_user_follows_event",
	sparse=True # Skip documents without UserFollows
	)
	print(" ✓ Created: idx_user_follows_event (embedded array)")

	# Index for user status (to filter Active users)
	db.users.create_index(
	[("status", 1)],
	name="idx_user_status"
	)
	print(" ✓ Created: idx_user_status")

	# PostSocialMedia Collection Indexes
	print("\n💬 PostSocialMedia Collection:")

	# Index for event-specific posts
	db.post_social_media.create_index(
	[("eventCode", 1), ("createdAt", -1)],
	name="idx_post_event_date"
	)
	print(" ✓ Created: idx_post_event_date")

	# Index for searching comments (nested in Images.UserCommentPosts)
	# Using wildcard for nested arrays
	db.post_social_media.create_index(
	[("eventCode", 1), ("images.userCommentPosts.commentedAt", -1)],
	name="idx_post_comments",
	sparse=True
	)
	print(" ✓ Created: idx_post_comments (nested array)")

	# EventAudienceSegment Collection Indexes
	print("\n🎯 EventAudienceSegment Collection:")

	# Index for event owner dashboard
	db.event_audience_segments.create_index(
	[("event_code", 1)],
	name="idx_segment_event"
	)
	print(" ✓ Created: idx_segment_event")

	# Index for status filtering
	db.event_audience_segments.create_index(
	[("event_code", 1), ("marketing_content.status", 1)],
	name="idx_segment_event_status"
	)
	print(" ✓ Created: idx_segment_event_status")

	# EventSentimentSummary Collection Indexes
	print("\n📊 EventSentimentSummary Collection:")

	# Index for event sentiment lookup
	db.event_sentiment_summary.create_index(
	[("event_code", 1), ("last_updated", -1)],
	name="idx_sentiment_event_date"
	)
	print(" ✓ Created: idx_sentiment_event_date")

	# SentimentAnalysisResult Collection Indexes
	print("\n💭 SentimentAnalysisResult Collection:")

	# Index for event-specific sentiment results
	db.sentiment_results.create_index(
	[("event_code", 1), ("analyzed_at", -1)],
	name="idx_sentiment_result_event_date"
	)
	print(" ✓ Created: idx_sentiment_result_event_date")

	# Index for sentiment label filtering
	db.sentiment_results.create_index(
	[("event_code", 1), ("sentiment_label", 1)],
	name="idx_sentiment_event_label"
	)
	print(" ✓ Created: idx_sentiment_event_label")

	print("\n" + "=" * 60)
	print("✅ All Indexes Created Successfully!")
	print("=" * 60)

	# List all indexes for verification
	print("\n📋 Index Summary:")
	print(f" Payment: {len(list(db.payments.list_indexes()))} indexes")
	print(f" User: {len(list(db.users.list_indexes()))} indexes")
	print(f" PostSocialMedia: {len(list(db.post_social_media.list_indexes()))} indexes")
	print(f" EventAudienceSegment: {len(list(db.event_audience_segments.list_indexes()))} indexes")
	print(f" EventSentimentSummary: {len(list(db.event_sentiment_summary.list_indexes()))} indexes")
	print(f" SentimentAnalysisResult: {len(list(db.sentiment_results.list_indexes()))} indexes")


	if __name__ == "__main__":
	create_all_indexes()