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06-full-data-set-import

README.md

📂 Phase 06: Full Dataset Import

This phase documents production collection of the complete Steam catalog comprising 240,000+ applications and 1,000,000+ user reviews, establishing the comprehensive dataset foundation for vector embeddings and advanced analytics capabilities.

Overview

Phase 06 scaled collection infrastructure from 5K validation to full production dataset spanning August-September 2025. The session implemented robust batch processing with missing record recovery, analytical report generation, and comprehensive post-import optimization. This production collection achieved 56% API success rate handling delisted games and regional restrictions while maintaining data integrity through systematic validation and establishing the complete dataset for semantic search implementation.

📋 Directory Contents

Document Purpose Link
phase-06-worklog-full-dataset-import.md Complete session log documenting production collection process phase-06-worklog-full-dataset-import.md

Collection Scripts

Script Purpose Link
collect_full_dataset.py Primary full catalog collection script with batch processing collect_full_dataset.py
collect_full_reviews.py Reviews collection for 1M+ user review dataset collect_full_reviews.py
recollect_missing_games.py Recovery script for missing or failed records recollect_missing_games.py
find_missing_appids.py Gap detection identifying incomplete collection records find_missing_appids.py

Database Scripts

Script Purpose Link
setup-steam-full-database.py Production database schema setup for full dataset setup-steam-full-database.py
import-master-data.py Master import orchestration for complete dataset import-master-data.py
post-import-tasks-steamfull.py Post-import optimization and validation tasks post-import-tasks-steamfull.py
post_import_setup_steamfull.sql SQL post-import optimization queries post_import_setup_steamfull.sql

Analysis Scripts

Script Purpose Link
analyze_json_structure.py JSON structure analysis for quality validation analyze_json_structure.py
generate_analytical_report.py Comprehensive dataset analytics and reporting generate_analytical_report.py
analysis_queries.sql Production analytics SQL queries analysis_queries.sql

Configuration

File Purpose Link
.env.example Production environment configuration template .env.example

🗂️ Repository Structure

06-full-data-set-import/
├── 📋 phase-06-worklog-full-dataset-import.md  # Session log
├── 🐍 collect_full_dataset.py                  # Primary collection
├── 🐍 collect_full_reviews.py                  # Reviews collection
├── 🐍 recollect_missing_games.py               # Recovery script
├── 🐍 find_missing_appids.py                   # Gap detection
├── 🐍 setup-steam-full-database.py             # Database setup
├── 🐍 import-master-data.py                    # Import orchestration
├── 🐍 post-import-tasks-steamfull.py           # Post-import tasks
├── 📊 post_import_setup_steamfull.sql          # SQL optimization
├── 🐍 analyze_json_structure.py                # Structure analysis
├── 🐍 generate_analytical_report.py            # Analytics reporting
├── 📊 analysis_queries.sql                     # Analytics SQL
├── 📄 .env.example                             # Configuration
└── 📂 README.md                                # This file

🔗 Related Categories

Category Relationship Documentation
Phase 05: 5K Analysis Validation phase preceding full production collection ../05-5000-steam-game-dataset-analysis/README.md
Phase 07: Vector Embeddings Uses complete dataset for semantic search capabilities ../07-vector-embeddings/README.md
Steam API Collection Methodology Documents collection patterns from this phase ../../docs/methodologies/steam-api-collection.md

Phase Highlights

Collection Results

  • Applications: 239,664 total records (56% success rate from 427K total catalog)
  • Reviews: 1,048,148 user reviews enriching dataset
  • Time Period: August-September 2025 collection window
  • Data Volume: 21GB database including indexes

Technical Achievements

  • Batch Processing: Reliable multi-day collection with periodic saves
  • Error Recovery: Missing record identification and recollection
  • Data Quality: Comprehensive validation ensuring integrity
  • Performance: Optimized indexes and materialization preparation

Document Information

Field Value
Author VintageDon - https://github.com/vintagedon
Created 2025-10-06
Last Updated 2025-10-06
Version 1.0

Tags: phase-06, full-dataset, production-collection, steam-api, batch-processing, reviews