Using Functional Indexes in Ent Schema
A functional index is an index whose key parts are based on expression values, rather than column values. This index type is helpful for indexing the results of functions or expressions that are not stored in the table. Supported by MySQL, MariaDB, PostgreSQL and SQLite.
This guide explains how to extend your Ent schema with functional indexes, and configure the schema migration to manage both functional indexes and the Ent schema as a single migration unit using Atlas.
Atlas support for Composite Schema used in this guide is available exclusively to Pro users. To use this feature, run:
atlas login
Install Atlas
To install the latest release of Atlas, simply run one of the following commands in your terminal, or check out the Atlas website:
- macOS + Linux
- Homebrew
- Docker
- Windows
curl -sSf https://atlasgo.sh | sh
brew install ariga/tap/atlas
docker pull arigaio/atlas
docker run --rm arigaio/atlas --help
If the container needs access to the host network or a local directory, use the --net=host
flag and mount the desired directory:
docker run --rm --net=host \
-v $(pwd)/migrations:/migrations \
arigaio/atlas migrate apply
--url "mysql://root:pass@:3306/test"
Download the latest release and move the atlas binary to a file location on your system PATH.
Login to Atlas
$ atlas login a8m
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. Functional indexes, do not have representation in Ent schema, as Ent supports defining indexes on fields, edges (foreign-keys), and the combination of them.
In order to extend our PostgreSQL schema migration with functional indexes to our Ent types (tables), we configure Atlas to read the state of the schema from a Composite Schema data source. Follow the steps below to configure this for your project:
- Let’s define a simple schema with one type (table):
User
(tableusers
):
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").
Comment("A unique index is defined on lower(name) in schema.sql"),
}
}
- Next step, we define a functional index on the
name
field in theschema.sql
file:
schema.sql
-- Create a functional (unique) index on the lowercased name column.
CREATE UNIQUE INDEX unique_name ON "users" ((lower("name")));
- Create a simple
atlas.hcl
config file with acomposite_schema
that includes both the functional indexes defined inschema.sql
and your Ent schema:
atlas.hcl
data "composite_schema" "app" {
# Load the ent schema first with all tables.
schema "public" {
url = "ent://ent/schema"
}
# Then, load the functional indexes.
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:
atlas schema inspect \
--env local \
--url env://src \
--format '{{ sql . }}'
The command above prints the following SQL.
-- Create "users" table
CREATE TABLE "users" ("id" bigint NOT NULL GENERATED BY DEFAULT AS IDENTITY, "name" character varying NOT NULL, PRIMARY KEY ("id"));
-- Create index "unique_name" to table: "users"
CREATE UNIQUE INDEX "unique_name" ON "users" ((lower((name)::text)));
Note, our functional index is defined on the name
field in the users
table.
Generate Migrations For the Schema
To generate a migration for the schema, run the following command:
atlas migrate diff \
--env local
Note that a new migration file is created with the following content:
migrations/20240712090543.sql
-- Create "users" table
CREATE TABLE "users" ("id" bigint NOT NULL GENERATED BY DEFAULT AS IDENTITY, "name" character varying NOT NULL, PRIMARY KEY ("id"));
-- Create index "unique_name" to table: "users"
CREATE UNIQUE INDEX "unique_name" ON "users" ((lower((name)::text)));
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"
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:
atlas schema apply \
--env local \
--url "postgres://postgres:pass@localhost:5432/database?sslmode=disable"
Or, using the Atlas Go SDK:
ac, err := atlasexec.NewClient(".", "atlas")
if err != nil {
log.Fatalf("failed to initialize client: %w", err)
}
// Automatically update the database with the desired schema.
// Another option, is to use 'migrate apply' or 'schema apply' manually.
if _, err := ac.SchemaApply(ctx, &atlasexec.SchemaApplyParams{
Env: "local",
URL: "postgres://postgres:pass@localhost:5432/database?sslmode=disable",
}); err != nil {
log.Fatalf("failed to apply schema changes: %w", err)
}
Code Example
After setting up our Ent schema with functional indexes, we expect the database to enforce the uniqueness of the name
field in the users
table:
// Test that the unique index is enforced.
client.User.Create().SetName("Ariel").SaveX(ctx)
err = client.User.Create().SetName("ariel").Exec(ctx)
require.EqualError(t, err, `ent: constraint failed: pq: duplicate key value violates unique constraint "unique_name"`)
// Type-assert returned error.
var pqerr *pq.Error
require.True(t, errors.As(err, &pqerr))
require.Equal(t, `duplicate key value violates unique constraint "unique_name"`, pqerr.Message)
require.Equal(t, user.Table, pqerr.Table)
require.Equal(t, "unique_name", pqerr.Constraint)
require.Equal(t, pq.ErrorCode("23505"), pqerr.Code, "unique violation")
The code for this guide can be found in GitHub.