Introduction | Data Files | AWK and Operating Systems | Examples | Using combined.fread | Skipping Unnecessary Rows | Delimiters | Using filtered.fread | Headers | Using pattern.fread | Using record.count | Using aggregated.fread | Computing Streaming Medians | Using Correlation

Introduction | Setup and Installation | Python Dependencies | Quick installation (default environment) | Troubleshooting the Python environment | Finding and selecting the correct Python environment | The Core Verbs | Chaining Verbs with the Pipe | Viewing the Python Code | Customizing the Generated Code with table_name

Introduction | Platform Compatibility | Reading Data | Showing the Underlying grep Command | Reading and Pre-Filtering Data | Special Options | Aggregating Data from Multiple Files | Counting Records | Discussion

Introduction | A Complete Workflow Example | 1. The Example Data | 2. Defining Metadata with table_info() | Understanding the Metadata Columns | 3. create_metadata_registry() and add_table() | 4. Discovering Join Paths with map_join_paths() | Combining Both Methods | 5. Creating an Execution Plan with create_join_plan() | 6. Visualizing the Plan | 7. Executing the Plan | Conclusion

Introduction to the Planner | 1. Define Metadata | 2. Create Join Plan | 3. Handling Invalid Requests

Introduction | Case 1: Standard Joins via Metadata | Case 2: Multi-Variable Key Joins | Case 3: Inferring Joins from Data | Combining Both Methods

Introduction | The table_info() Function | Example 1: The Customers Table | Example 2: The Products Table | Example 3: The Transactions Table | Assembling a Master Metadata Table

Introduction | Create the Master Metadata | Generate Aggregation Code | Execute the Generated Code | Conclusion