Designing Solid Databases: Why NOT NULL in Composite Primary Keys Matters


There are issues with allowing null values (missing data) in composite primary keys. Here's why:

  1. Uniqueness: A primary key needs to be absolutely unique to identify each row. Null, by definition, is uncertain and can't guarantee uniqueness. Imagine two rows with null values in the same composite key columns. How would you tell them apart?

  2. Comparisons: Databases struggle to compare null values. Even checking if null equals null can be tricky. This can lead to unexpected results when searching or filtering data.

  3. Foreign Keys: Foreign keys in other tables often reference the primary key. If the primary key allows nulls, it becomes difficult to ensure referential integrity, meaning a foreign key might not definitively point to a specific row.

  4. Data Integrity: While nulls might seem convenient for optional data, they can indicate underlying problems in your data model. It's generally better to design your tables to avoid nulls in primary keys whenever possible.

There are alternative approaches to handle optional data in composite primary keys:

  • Make the columns NOT NULL: This enforces that every row must have a value in each key column.
  • Use a separate table: If nulls are truly necessary for some rows, consider creating a separate table to handle those cases.

MySQL (Not recommended):

CREATE TABLE my_table (
  id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,  -- Regular auto-increment ID
  CONSTRAINT unique_combo UNIQUE (col1, col2) -- Enforce uniqueness (alternative to PK with nulls)

Note: MySQL doesn't allow nulls in composite primary keys by default. This example uses an auto-incrementing ID as the primary key and a separate unique constraint on the nullable columns (col1, col2).

PostgreSQL (Generally not recommended):

CREATE TABLE my_table (
  PRIMARY KEY (col1, col2)  -- Not recommended due to potential null issues

Note: PostgreSQL technically allows nulls in composite primary keys, but it's generally discouraged due to the limitations mentioned earlier.

Entity Framework (C#):

public class MyEntity
  public int Id { get; set; } // Auto-increment ID (primary key)
  public string Col1 { get; set; }
  public int? Col2 { get; set; } // Nullable for optional data

  1. Separate Surrogate Key:

This is a common and recommended approach. Here's the idea:

  • Add a separate column to your table that acts as the primary key. This can be an auto-incrementing integer (like an ID) or a Universally Unique Identifier (UUID). This column is guaranteed to be unique and never null.
  • Keep your original columns (those you wanted in the composite key) but make them NOT NULL. This ensures data is present for these columns.

This approach maintains data integrity and simplifies queries and relationships with other tables.

  1. Partial Keys and Unique Constraints:

If you truly need some columns to be nullable, consider splitting your composite key idea:

  • Define a primary key with a subset of columns that are guaranteed to be NOT NULL. This ensures uniqueness for core data.
  • Create a separate UNIQUE constraint on the remaining columns (including the nullable ones). This allows for rows with missing data in those specific columns, but still enforces uniqueness for combinations where those values are present.

Here's an example (MySQL):

CREATE TABLE my_table (
  col1 VARCHAR(255) NOT NULL,  -- Enforced for core data
  UNIQUE (col1, col2)  -- Unique constraint for combinations where col2 has a value

This approach offers some flexibility for optional data but requires careful consideration of data integrity and potential query complexity.

  1. Separate Table for Optional Data:

If a significant portion of your data has missing values in some columns you consider part of the key, it might be better to design a separate table:

  • Create a primary key table with the core, non-nullable columns.
  • Create a separate table with a foreign key referencing the primary key table and include the nullable columns here.

This approach clearly separates "core" data from optional data and simplifies queries on the core data. However, it adds some complexity to managing relationships between the tables.

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