ent/doc/md/migration/trigger.mdx

---
title: Using Database Triggers in Ent Schema
id: trigger
slug: triggers
---

import InstallationInstructions from '../components/_installation_instructions.mdx';

Triggers are useful tools in relational databases that allow you to execute custom code when specific events occur on a
table. For instance, triggers can automatically populate the audit log table whenever a new mutation is applied to a different table.
This way we ensure that all changes (including those made by other applications) are meticulously recorded, enabling the enforcement
on the database-level and reducing the need for additional code in the applications.

This guide explains how to attach triggers to your Ent types (objects) and configure the schema migration to manage
both the triggers and the Ent schema as a single migration unit using Atlas.

:::info [Atlas Pro Feature](https://atlasgo.io/features#pro-plan)
Atlas support for [Triggers](https://atlasgo.io/atlas-schema/hcl#trigger) used in this guide is available exclusively
to Pro users. To use this feature, run:
```
atlas login
```
:::

## Install Atlas

<InstallationInstructions />

## Login to Atlas

```shell
$ atlas login a8m
//highlight-next-line-info
You are now connected to "a8m" on Atlas Cloud.
```

## Composite Schema

An `ent/schema` package is mostly used for defining Ent types (objects), their fields, edges and logic. Table triggers
or any other database native objects do not have representation in Ent models. A trigger function can be defined once,
and used in multiple triggers in different tables.

In order to extend our PostgreSQL schema to include both our Ent types and their triggers, we configure Atlas to
read the state of the schema from a [Composite Schema](https://atlasgo.io/atlas-schema/projects#data-source-composite_schema)
data source. Follow the steps below to configure this for your project:

1\. Let's define a simple schema with two types (tables): `users` and `user_audit_logs`:

```go title="ent/schema/user.go"
// User holds the schema definition for the User entity.
type User struct {
	ent.Schema
}

// Fields of the User.
func (User) Fields() []ent.Field {
	return []ent.Field{
		field.String("name"),
	}
}

// UserAuditLog holds the schema definition for the UserAuditLog entity.
type UserAuditLog struct {
	ent.Schema
}

// Fields of the UserAuditLog.
func (UserAuditLog) Fields() []ent.Field {
	return []ent.Field{
		field.String("operation_type"),
		field.String("operation_time"),
		field.String("old_value").
			Optional(),
		field.String("new_value").
			Optional(),
	}
}
```

Now, suppose we want to log every change to the `users` table and save it in the `user_audit_logs` table.
To achieve this, we need to create a trigger function on `INSERT`, `UPDATE` and `DELETE` operations and attach it to
the `users` table.

2\. Next step, we define a trigger function ( `audit_users_changes`) and attach it to the `users` table using the `CREATE TRIGGER` commands:

```sql title="schema.sql" {23,26,29}
-- Function to audit changes in the users table.
CREATE OR REPLACE FUNCTION audit_users_changes()
RETURNS TRIGGER AS $$
BEGIN
    IF (TG_OP = 'INSERT') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, new_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(NEW));
        RETURN NEW;
    ELSIF (TG_OP = 'UPDATE') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, old_value, new_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(OLD), row_to_json(NEW));
        RETURN NEW;
    ELSIF (TG_OP = 'DELETE') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, old_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(OLD));
        RETURN OLD;
    END IF;
    RETURN NULL;
END;
$$ LANGUAGE plpgsql;

-- Trigger for INSERT operations.
CREATE TRIGGER users_insert_audit AFTER INSERT ON users FOR EACH ROW EXECUTE FUNCTION audit_users_changes();

-- Trigger for UPDATE operations.
CREATE TRIGGER users_update_audit AFTER UPDATE ON users FOR EACH ROW EXECUTE FUNCTION audit_users_changes();

-- Trigger for DELETE operations.
CREATE TRIGGER users_delete_audit AFTER DELETE ON users FOR EACH ROW EXECUTE FUNCTION audit_users_changes();
```


3\. Lastly, we create a simple `atlas.hcl` config file with a `composite_schema` that includes both our Ent schema and
the custom triggers defined in `schema.sql`:

```hcl title="atlas.hcl"
data "composite_schema" "app" {
  # Load the ent schema first with all tables.
  schema "public" {
    url = "ent://ent/schema"
  }
  # Then, load the triggers schema.
  schema "public" {
    url = "file://schema.sql"
  }
}

env "local" {
  src = data.composite_schema.app.url
  dev = "docker://postgres/15/dev?search_path=public"
}
```

## Usage

After setting up our composite schema, we can get its representation using the `atlas schema inspect` command, generate
schema migrations for it, apply them to a database, and more. Below are a few commands to get you started with Atlas:

#### Inspect the Schema

The `atlas schema inspect` command is commonly used to inspect databases. However, we can also use it to inspect our
`composite_schema` and print the SQL representation of it:

```shell
atlas schema inspect \
  --env local \
  --url env://src \
  --format '{{ sql . }}'
```

The command above prints the following SQL. Note, the `audit_users_changes` function and the triggers are defined after
the `users` and `user_audit_logs` tables:

```sql
-- Create "user_audit_logs" table
CREATE TABLE "user_audit_logs" ("id" bigint NOT NULL GENERATED BY DEFAULT AS IDENTITY, "operation_type" character varying NOT NULL, "operation_time" character varying NOT NULL, "old_value" character varying NULL, "new_value" character varying NULL, PRIMARY KEY ("id"));
-- Create "users" table
CREATE TABLE "users" ("id" bigint NOT NULL GENERATED BY DEFAULT AS IDENTITY, "name" character varying NOT NULL, PRIMARY KEY ("id"));
-- Create "audit_users_changes" function
CREATE FUNCTION "audit_users_changes" () RETURNS trigger LANGUAGE plpgsql AS $$
BEGIN
    IF (TG_OP = 'INSERT') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, new_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(NEW));
        RETURN NEW;
    ELSIF (TG_OP = 'UPDATE') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, old_value, new_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(OLD), row_to_json(NEW));
        RETURN NEW;
    ELSIF (TG_OP = 'DELETE') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, old_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(OLD));
        RETURN OLD;
    END IF;
    RETURN NULL;
END;
$$;
-- Create trigger "users_delete_audit"
CREATE TRIGGER "users_delete_audit" AFTER DELETE ON "users" FOR EACH ROW EXECUTE FUNCTION "audit_users_changes"();
-- Create trigger "users_insert_audit"
CREATE TRIGGER "users_insert_audit" AFTER INSERT ON "users" FOR EACH ROW EXECUTE FUNCTION "audit_users_changes"();
-- Create trigger "users_update_audit"
CREATE TRIGGER "users_update_audit" AFTER UPDATE ON "users" FOR EACH ROW EXECUTE FUNCTION "audit_users_changes"();
```

#### Generate Migrations For the Schema

To generate a migration for the schema, run the following command:

```shell
atlas migrate diff \
  --env local
```

Note that a new migration file is created with the following content:

```sql title="migrations/20240712090543.sql"
-- Create "user_audit_logs" table
CREATE TABLE "user_audit_logs" ("id" bigint NOT NULL GENERATED BY DEFAULT AS IDENTITY, "operation_type" character varying NOT NULL, "operation_time" character varying NOT NULL, "old_value" character varying NULL, "new_value" character varying NULL, PRIMARY KEY ("id"));
-- Create "users" table
CREATE TABLE "users" ("id" bigint NOT NULL GENERATED BY DEFAULT AS IDENTITY, "name" character varying NOT NULL, PRIMARY KEY ("id"));
-- Create "audit_users_changes" function
CREATE FUNCTION "audit_users_changes" () RETURNS trigger LANGUAGE plpgsql AS $$
BEGIN
    IF (TG_OP = 'INSERT') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, new_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(NEW));
        RETURN NEW;
    ELSIF (TG_OP = 'UPDATE') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, old_value, new_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(OLD), row_to_json(NEW));
        RETURN NEW;
    ELSIF (TG_OP = 'DELETE') THEN
        INSERT INTO user_audit_logs(operation_type, operation_time, old_value)
        VALUES (TG_OP, CURRENT_TIMESTAMP, row_to_json(OLD));
        RETURN OLD;
    END IF;
    RETURN NULL;
END;
$$;
-- Create trigger "users_delete_audit"
CREATE TRIGGER "users_delete_audit" AFTER DELETE ON "users" FOR EACH ROW EXECUTE FUNCTION "audit_users_changes"();
-- Create trigger "users_insert_audit"
CREATE TRIGGER "users_insert_audit" AFTER INSERT ON "users" FOR EACH ROW EXECUTE FUNCTION "audit_users_changes"();
-- Create trigger "users_update_audit"
CREATE TRIGGER "users_update_audit" AFTER UPDATE ON "users" FOR EACH ROW EXECUTE FUNCTION "audit_users_changes"();
```

#### Apply the Migrations

To apply the migration generated above to a database, run the following command:

```
atlas migrate apply \
  --env local \
  --url "postgres://postgres:pass@localhost:5432/database?search_path=public&sslmode=disable"
```

:::info Apply the Schema Directly on the Database

Sometimes, there is a need to apply the schema directly to the database without generating a migration file. For example,
when experimenting with schema changes, spinning up a database for testing, etc. In such cases, you can use the command
below to apply the schema directly to the database:

```shell
atlas schema apply \
  --env local \
  --url "postgres://postgres:pass@localhost:5432/database?search_path=public&sslmode=disable"
```

:::

The code for this guide can be found in [GitHub](https://github.com/ent/ent/tree/master/examples/triggers).