FK Strategies

Seedling provides multiple strategies for distributing FK values, handling real-world patterns like Pareto distributions, many-to-many joins, and self-referencing hierarchies.

Strategies

Uniform (Default)

Parent rows are selected uniformly at random. Each child row gets a random parent FK.

orders:
  user_id:
    generator: fk_pool
    params:
      strategy: uniform

Sequential

Parent rows are assigned sequentially. Useful for ordered data like time-series.

logs:
  session_id:
    generator: fk_pool
    params:
      strategy: sequential

Weighted

Some parent rows receive more children than others. Follows a configurable distribution.

comments:
  post_id:
    generator: fk_pool
    params:
      strategy: weighted
      distribution:
        - weight: 80  # top 20% of posts get 80% of comments
        - weight: 20

Exclusive

Each child row gets a dedicated parent row (1:1 relationship).

user_profiles:
  user_id:
    generator: fk_pool
    params:
      strategy: exclusive

Self-Referencing FKs

For tables with self-referencing foreign keys (e.g., employees.manager_id → employees.id), Seedling uses a multi-pass generation strategy:

Pass 1: Generate a batch of rows with NULL in the self-FK column
Pass 2: Assign FK values from pass 1 rows (or earlier pass rows) to fill in references

employees:
  manager_id:
    generator: self_fk
    params:
      max_depth: 3
      null_probability: 0.2

Parameter	Description	Default
`max_depth`	Maximum hierarchy depth	`5`
`null_probability`	Probability a row has no parent (top-level)	`0.1`

Overview

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Contributing

FK Strategies

FK Strategies

Strategies

Uniform (Default)

Sequential

Weighted

Exclusive

Self-Referencing FKs

​FK Strategies

​Strategies

​Uniform (Default)

​Sequential

​Weighted

​Exclusive

​Self-Referencing FKs

FK Strategies

Strategies

Uniform (Default)

Sequential

Weighted

Exclusive

Self-Referencing FKs