Principle:DataExpert io Data engineer handbook Database Seeding

Overview

Database Seeding refers to the process of initializing a database with a predefined set of schema definitions and data from dump files. This technique is fundamental to bootstrapping development, testing, and staging environments so that engineers can work against a consistent, reproducible dataset without relying on live production systems.

In the context of the Dimensional Data Modeling workflow, database seeding provides the foundational dataset (such as the actor_films table) upon which all subsequent modeling exercises, verification queries, and SCD transformations are performed.

Theoretical Basis

The pg_dump / pg_restore Cycle

PostgreSQL provides a robust pair of utilities for exporting and importing database state:

• pg_dump -- Extracts a PostgreSQL database into a dump file. The dump can be produced in several formats:
  • Plain text (.sql) -- A sequence of SQL commands that can be replayed via psql.
  • Custom format (.dump) -- A compressed, flexible archive format designed for use with pg_restore.
  • Directory format -- Splits the dump into per-table files for parallel restoration.
• pg_restore -- Restores a PostgreSQL database from a non-plain-text dump file. Key capabilities include:
  • Selective restoration of specific tables or schemas.
  • Reordering of restoration steps to satisfy dependency constraints.
  • Parallel restoration for large datasets.

The cycle works as follows:

Production DB  -->  pg_dump (custom format)  -->  data.dump  -->  pg_restore  -->  Dev/Test DB

This cycle ensures that the target environment receives an exact replica of the source schema and data, subject to any filtering or transformation flags applied during the dump or restore phases.

Idempotent Initialization Scripts

A well-designed seeding script should be idempotent -- running it multiple times against the same target database should produce the same final state. This is achieved through several strategies:

• Drop-and-recreate -- The script drops existing objects before recreating them, ensuring a clean slate on each execution.
• IF NOT EXISTS guards -- Schema creation statements use conditional logic to avoid errors on repeated runs.
• Transaction wrapping -- The entire seeding operation runs inside a transaction so that partial failures do not leave the database in an inconsistent state.
• set -e in shell scripts -- The script exits immediately on any error, preventing cascading failures from corrupting the database state.

Supplementary SQL Execution

After the primary dump is restored, additional SQL scripts may be executed to:

• Create exercise-specific tables or views.
• Insert supplementary seed data for homework assignments.
• Apply schema modifications needed for specific modeling exercises (e.g., creating the actors table for cumulative modeling, or the actors_history_scd table for SCD Type 2 exercises).

This two-phase approach (restore base dump, then apply overlays) provides flexibility while maintaining a stable core dataset.

When to Use Database Seeding

Database seeding from dump files is most appropriate in the following scenarios:

• Bootstrapping development environments -- New team members can spin up a fully populated database in minutes rather than hours.
• Continuous integration pipelines -- Automated tests require a known dataset to validate query logic and transformations.
• Training and educational contexts -- Students working through dimensional data modeling exercises need a consistent starting point (e.g., the actor_films dataset).
• Reproducible analytics -- Data analysts can reset their environment to a known state before running experimental queries.

Database seeding is not recommended when:

• The dataset is extremely large and network transfer of dump files is impractical.
• Real-time data freshness is required (use replication or streaming instead).
• Schema drift between source and target environments has not been reconciled.

Key Concepts

Concept	Description
Dump File	A serialized representation of database schema and data, produced by pg_dump.
Restore	The process of loading a dump file into a target database using pg_restore or psql.
Idempotency	The property that running the seeding script multiple times yields the same result.
Environment Variables	Configuration values (e.g., $POSTGRES_USER, $POSTGRES_DB) injected at runtime to decouple scripts from specific environments.
Overlay Scripts	Additional SQL files executed after the primary restore to customize the database for specific use cases.

Related Pages

• Implementation:DataExpert_io_Data_engineer_handbook_Pg_restore_Init_Script
• Implementation:DataExpert_io_Data_engineer_handbook_Pg_restore_Init_Script -- The shell script that implements this seeding principle using pg_restore and iterative psql execution.
• Principle:DataExpert_io_Data_engineer_handbook_Docker_Environment_Setup -- The containerized environment within which database seeding is typically performed.
• Principle:DataExpert_io_Data_engineer_handbook_SQL_Verification_Queries -- Verification queries used to confirm that seeding completed successfully.

Metadata

• Knowledge Sources: Data Engineer Handbook
• Domains: Data_Engineering, SQL, Infrastructure
• Last Updated: 2026-02-09 06:00 GMT