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Generated Columns

Learn how to use generated columns in Tacnode to enhance your database functionality. Explore examples and best practices in our comprehensive guide.

Generated columns are a powerful feature that automatically compute and store values based on expressions involving other columns in the same table. These columns eliminate the need for application-level calculations and ensure data consistency by maintaining computed values directly within the database.

What Are Generated Columns?

Generated columns are database columns whose values are automatically calculated from expressions rather than being explicitly inserted or updated. The database engine handles all computation, ensuring that derived values remain consistent with their source data.

Key Characteristics

  • Automatic Computation: Values are calculated automatically when base columns change
  • Storage Options: Currently, Tacnode supports STORED generated columns (computed values are physically stored)
  • Read-Only: Cannot be directly modified through INSERT or UPDATE statements
  • Index Support: Can be indexed like regular columns to improve query performance
  • Consistency: Always reflect the current state of their dependent columns

Basic Syntax

column_name data_type GENERATED ALWAYS AS (expression) STORED

Components:

  • column_name: The name of the generated column
  • data_type: The data type of the computed result
  • expression: A deterministic expression using other columns in the same table
  • STORED: Indicates the computed value is physically stored in the table

Common Use Cases and Examples

Financial Calculations

Generated columns excel at maintaining calculated financial values that depend on multiple factors.

CREATE TABLE invoices (
    invoice_id SERIAL PRIMARY KEY,
    subtotal DECIMAL(10,2) NOT NULL,
    tax_rate DECIMAL(5,4) NOT NULL,
    discount_amount DECIMAL(10,2) DEFAULT 0,
    
    -- Generated columns for automatic calculations
    tax_amount DECIMAL(10,2) GENERATED ALWAYS AS (subtotal * tax_rate) STORED,
    discounted_subtotal DECIMAL(10,2) GENERATED ALWAYS AS (subtotal - discount_amount) STORED,
    total_amount DECIMAL(10,2) GENERATED ALWAYS AS ((subtotal - discount_amount) * (1 + tax_rate)) STORED
);

-- Example data insertion
INSERT INTO invoices (subtotal, tax_rate, discount_amount) 
VALUES (1000.00, 0.0825, 50.00);

-- Query automatically shows computed values
SELECT subtotal, tax_rate, discount_amount, tax_amount, total_amount 
FROM invoices;

String Manipulation and Formatting

Generate formatted strings or extract information from existing text columns.

CREATE TABLE customers (
    customer_id SERIAL PRIMARY KEY,
    first_name VARCHAR(50) NOT NULL,
    last_name VARCHAR(50) NOT NULL,
    email VARCHAR(100) NOT NULL,
    phone VARCHAR(20),
    
    -- Generated columns for string operations
    full_name VARCHAR(101) GENERATED ALWAYS AS (first_name || ' ' || last_name) STORED,
    email_domain VARCHAR(50) GENERATED ALWAYS AS (SUBSTRING(email FROM '@(.*)$')) STORED,
    initials CHAR(2) GENERATED ALWAYS AS (LEFT(first_name, 1) || LEFT(last_name, 1)) STORED
);

-- Example usage
INSERT INTO customers (first_name, last_name, email, phone) 
VALUES ('John', 'Smith', 'john.smith@example.com', '555-0123');

-- Query shows computed string values
SELECT full_name, email_domain, initials 
FROM customers;

Date and Time Calculations

Automatically compute age, duration, or other time-based values.

CREATE TABLE employees (
    employee_id SERIAL PRIMARY KEY,
    first_name VARCHAR(50) NOT NULL,
    last_name VARCHAR(50) NOT NULL,
    birth_date DATE NOT NULL,
    hire_date DATE NOT NULL,
    
    -- Generated columns for date calculations
    age_years INTEGER GENERATED ALWAYS AS (
        EXTRACT(YEAR FROM AGE(CURRENT_DATE, birth_date))
    ) STORED,
    
    tenure_years INTEGER GENERATED ALWAYS AS (
        EXTRACT(YEAR FROM AGE(CURRENT_DATE, hire_date))
    ) STORED,
    
    years_to_retirement INTEGER GENERATED ALWAYS AS (
        65 - EXTRACT(YEAR FROM AGE(CURRENT_DATE, birth_date))
    ) STORED
);

Data Classification and Categorization

Automatically categorize data based on computed criteria.

CREATE TABLE sales_transactions (
    transaction_id SERIAL PRIMARY KEY,
    customer_id INTEGER NOT NULL,
    transaction_amount DECIMAL(10,2) NOT NULL,
    transaction_date DATE NOT NULL,
    product_category VARCHAR(50),
    
    -- Generated columns for classification
    amount_category VARCHAR(20) GENERATED ALWAYS AS (
        CASE 
            WHEN transaction_amount >= 1000 THEN 'High Value'
            WHEN transaction_amount >= 100 THEN 'Medium Value'
            ELSE 'Low Value'
        END
    ) STORED,
    
    quarter_year VARCHAR(7) GENERATED ALWAYS AS (
        'Q' || EXTRACT(QUARTER FROM transaction_date) || '-' || EXTRACT(YEAR FROM transaction_date)
    ) STORED,
    
    is_recent_transaction BOOLEAN GENERATED ALWAYS AS (
        transaction_date >= CURRENT_DATE - INTERVAL '30 days'
    ) STORED
);

Geometric and Mathematical Calculations

Perform complex mathematical operations automatically.

CREATE TABLE geometric_shapes (
    shape_id SERIAL PRIMARY KEY,
    shape_type VARCHAR(20) NOT NULL,
    length DECIMAL(8,2),
    width DECIMAL(8,2),
    radius DECIMAL(8,2),
    
    -- Generated columns for geometric calculations
    area DECIMAL(12,4) GENERATED ALWAYS AS (
        CASE shape_type
            WHEN 'rectangle' THEN length * width
            WHEN 'circle' THEN PI() * radius * radius
            WHEN 'square' THEN length * length
        END
    ) STORED,
    
    perimeter DECIMAL(12,4) GENERATED ALWAYS AS (
        CASE shape_type
            WHEN 'rectangle' THEN 2 * (length + width)
            WHEN 'circle' THEN 2 * PI() * radius
            WHEN 'square' THEN 4 * length
        END
    ) STORED
);

Advanced Features and Optimizations

Indexing Generated Columns

Generated columns can be indexed to improve query performance, especially for filtering and sorting operations.

-- Create indexes on generated columns
CREATE INDEX idx_invoices_total_amount ON invoices (total_amount);
CREATE INDEX idx_customers_email_domain ON customers (email_domain);
CREATE INDEX idx_transactions_amount_category ON sales_transactions (amount_category);

-- Efficient queries using generated column indexes
SELECT * FROM invoices WHERE total_amount > 1000;
SELECT COUNT(*) FROM customers GROUP BY email_domain;
SELECT * FROM sales_transactions WHERE amount_category = 'High Value';

Using Generated Columns in Complex Queries

Generated columns can simplify complex analytical queries.

-- Analysis using generated columns
SELECT 
    quarter_year,
    amount_category,
    COUNT(*) as transaction_count,
    SUM(transaction_amount) as total_sales,
    AVG(transaction_amount) as avg_transaction
FROM sales_transactions
WHERE is_recent_transaction = true
GROUP BY quarter_year, amount_category
ORDER BY quarter_year, amount_category;

Best Practices and Guidelines

Expression Design

Use Deterministic Functions Only:

-- ✅ Good: Deterministic expressions
birth_year INTEGER GENERATED ALWAYS AS (EXTRACT(YEAR FROM birth_date)) STORED

-- ❌ Avoid: Volatile functions
created_timestamp TIMESTAMP GENERATED ALWAYS AS (NOW()) STORED  -- This won't work

Keep Expressions Simple and Efficient:

-- ✅ Good: Simple, efficient calculation
full_name VARCHAR(100) GENERATED ALWAYS AS (first_name || ' ' || last_name) STORED

-- ⚠️ Consider carefully: Complex expressions may impact performance
complex_score INTEGER GENERATED ALWAYS AS (
    -- Very complex calculation with multiple nested functions
    -- Consider if this belongs in application logic instead
) STORED

Data Type Considerations

Ensure generated column data types can accommodate the full range of possible computed values:

-- Example: Ensure adequate precision for calculations
CREATE TABLE financial_records (
    principal DECIMAL(12,2),
    interest_rate DECIMAL(8,6),
    
    -- Adequate precision for interest calculation
    interest_amount DECIMAL(15,8) GENERATED ALWAYS AS (
        principal * interest_rate
    ) STORED
);

Performance Optimization

Strategic Indexing:

  • Index generated columns that are frequently used in WHERE clauses
  • Consider composite indexes combining generated and regular columns
  • Monitor query performance and adjust indexing strategy accordingly

Expression Efficiency:

  • Avoid overly complex expressions that may slow down INSERT/UPDATE operations
  • Consider splitting complex calculations into multiple generated columns
  • Test performance impact with realistic data volumes

Maintenance Considerations

Documentation:

  • Document the business logic behind generated column expressions
  • Maintain clear naming conventions for generated columns
  • Keep track of dependencies between columns

Schema Evolution:

  • Plan for potential changes to source columns that affect generated columns
  • Test schema migrations carefully when generated columns are involved
  • Consider the impact on existing indexes when modifying generated column expressions

Limitations and Considerations

Current Limitations

  1. Expression Restrictions:

    • No volatile functions (e.g., NOW(), RANDOM())
    • No subqueries or references to other tables
    • No user-defined functions that aren’t marked as IMMUTABLE

  2. Storage Mode:

    • Currently only STORED generated columns are supported
    • All computed values are physically stored, consuming disk space

  3. Modification Restrictions:

    • Generated columns cannot be directly updated
    • Values change only when dependent columns are modified

Performance Considerations

  • INSERT/UPDATE Impact: Complex expressions may slow down data modification operations
  • Storage Overhead: Generated columns consume additional disk space
  • Index Maintenance: Indexes on generated columns require maintenance when base data changes

When to Use Alternatives

Consider application-level calculations or views when:

  • Expressions are extremely complex or frequently changing
  • Storage space is at a premium
  • Calculations involve data from multiple tables
  • Real-time computation is preferred over stored values

Summary

Generated columns provide a powerful way to maintain computed data directly within your database tables. They offer benefits including:

  • Consistency: Automatically maintained derived values
  • Performance: Can be indexed for fast query execution
  • Simplicity: Eliminate application-level calculation logic
  • Reliability: Database-enforced computation ensures accuracy

By following best practices and understanding their limitations, generated columns can significantly enhance your table design and query performance in Tacnode applications.

In summary, Generated Columns streamline SQL operations by automatically computing derived columns, a significant feature of Tacnode.

For additional information, please refer to Generated Columns.