Github link: https://github.com/bokwoon95/sqddl
sqddl is a zero-configuration database migration tool for Go. It can generate migrations based on a declarative schema (defined as Go structs).
Notable features:
//go:embed
) and run them automatically on startup.$ go install -tags=fts5 github.com/bokwoon95/sqddl/sqddl@latest
sqddl has 12 subcommands. Click on each of them to find out more.
There are 2 global flags that all subcommands accept: -db and -history-table. You can pass these flags to the sqddl command and they will get forwarded to the subcommand. This allows you to press up in the shell and backspace a little bit to change the subcommand (reusing the -db and -history-table flags) rather than having to navigate all the way back in the line just to change the subcommand.
# The two commands below are equivalent
$ sqddl ls -db 'postgres://user:pass@localhost:5432/sakila'
# ^ subcommand
$ sqddl -db 'postgres://user:pass@localhost:5432/sakila' ls
# ^ subcommand
-db is the database url needed to connect to your database. For sqlite this is a file path.
SQLite examples
# <filename>.{sqlite,sqlite3,db,db3}
relative/path/to/file.sqlite
./relative/path/to/file.sqlite3
/absolute/path/to/file.db
file:/absolute/path/to/file.db3
# sqlite:<filepath>
sqlite:relative/path/to/file
sqlite:./relative/path/to/file
sqlite:/absolute/path/to/file
sqlite:file:/absolute/path/to/file
Postgres examples
# postgres://<username>:<password>@<host>:<port>/<database>
postgres://user:pass@localhost:5432/sakila
postgres://admin1:Hunter2!@127.0.0.1:5433/mydatabase
MySQL examples
# <username>:<password>@tcp(<host>:<port>)/<database>
user:pass@tcp(localhost:3306)/sakila
root:Hunter2!@tcp(127.0.0.1:3307)/mydatabase
# mysql://<username>:<password>@<host>:<port>/<database>
mysql://user:pass@localhost:3306/sakila
mysql://root:Hunter2!@127.0.0.1:3307/mydatabase
# mysql://<username>:<password>@tcp(<host>:<port>)/<database>
mysql://user:pass@tcp(localhost:3306)/sakila
mysql://root:Hunter2!@tcp(127.0.0.1:3307)/mydatabase
SQL Server examples
# sqlserver://<username>:<password>@<host>:<port>?database=<database>
sqlserver://user:pass@localhost:1433?database=sakila
sqlserver://sa:Hunter2!@127.0.0.1:1434?database=mydatabase
# sqlserver://<username>:<password>@<host>:<port>/<database>
sqlserver://user:pass@localhost:1433/sakila
sqlserver://sa:Hunter2!@127.0.0.1:1434/mydatabase
If you don't want to include the database URL directly in the command, you can pass in a filename (prefixed with file:
) where the file contains the database URL.
# file:<filepath>
file:relative/path/to/file
file:./relative/path/to/file
file:/absolute/path/to/file.txt
$ sqddl migrate -db file:/absolute/path/to/database_url.txt
The file should contain the database URL as-is.
$ cat /absolute/path/to/database_url.txt
postgres://user:pass@localhost:5432/sakila
file:<filepath>
may also reference an SQLite database. The first 16 bytes of the file are inspected to differentiate between an SQLite database and a plaintext file.
The history table stores the history of the applied migrations. The default name of the table is "sqddl_history". You can override it with the -history-table flag, but try not to do so unless you really have a table name that conflicts with the default.
This is the schema for the history table.
CREATE TABLE sqddl_history (
filename VARCHAR(255) PRIMARY KEY NOT NULL,
checksum VARCHAR(64),
started_at DATETIME, -- postgres uses TIMESTAMPTZ, sqlserver uses DATETIMEOFFSET
time_taken_ns BIGINT,
success BOOLEAN -- sqlserver uses BIT
);
The migrate subcommand runs pending migrations in some directory (specified with -dir). No output means no pending migrations. Once a migration has been run, it will be recorded in a history table so that it doesn't get run again.
Any top-level *.sql file in the migration directory is considered a migration. You are free to use any naming convention for your migrations, but keep in mind that they will be run in alphabetical order.
# sqddl migrate -db <DATABASE_URL> -dir <MIGRATION_DIR> [FLAGS] [FILENAMES...]
$ sqddl migrate -db 'postgres://user:pass@localhost:5432/sakila' -dir ./migrations
BEGIN
[OK] 01_extensions_types.sql (22.4397ms)
[OK] 02_sakila.sql (194.1385ms)
[OK] 03_webpage.sql (29.5218ms)
[OK] 04_extras.sql (20.1678ms)
COMMIT
The migrate subcommand ignores any SQL file named "schema.sql", "indexes.sql" or "constraints.sql". Those files are reserved by the dump and load subcommands to contain the overall schema definition of the database.
There are no up and down migrations, nor is there the concept of a "migration version" that you can roll back to. All that matters is whether a migration has or has not been applied. To revert the database schema back to a previous state, you have to create a new migration to undo the changes. Because schema definitions are declarative (using table structs), you just have to update your schema definition and let sqddl generate the new migrations.
# revert the file tables/tables.go to its previous working state in commit c5f567
$ git checkout c5f567 -- tables/tables.go
# generate a new migration from tables/tables.go
$ sqddl generate \
-src postgres://user:pass@localhost:5432/sakila \
-dest tables/tables.go \
-output-dir ./migrations
Because migrations are meant to be run only once, it is perfectly fine to include data modifying commands like INSERT or UPDATE inside a migration.
Because migrations are meant to be run only once, once they are run you can delete them from the migrations directory. No other ceremony is needed. This keeps the size of the migration directory from growing indefinitely. Don't worry about losing schema history, because sqddl is able to introspect your database and produce a schema.sql from it. By regularly updating that schema.sql (and its associated schema.json) in version control you can get track your schema history.
Instead of running all pending migrations, you can run specific migrations by passing them in as arguments.
# sqddl migrate -db <DATABASE_URL> -dir <MIGRATION_DIR> [FLAGS] [FILENAMES...]
$ sqddl migrate \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
02_sakila.sql 04_extras.sql # only run 02_sakila.sql and 04_extras.sql
A migration has already been run will not be run again, even if it was explicitly passed in as an argument.
You can use globbing to pass in multiple filenames matching a certain pattern. Filenames can optionally be prefixed with the name of the migration directory, allowing you to glob on files in the migration directory.
# sqddl migrate -db <DATABASE_URL> -dir <MIGRATION_DIR> [FLAGS] [FILENAMES...]
$ sqddl migrate \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
./migrations/2022*.sql # only run migrations that start with 2022
All migrations are run inside a single transaction until a *.tx.sql or *.txoff.sql migration is encountered. At which point the *.tx.sql or *.txoff.sql migrations are run separately, then subsequent migrations will continue running inside a single transaction again following the same logic. The following diagram illustrates the point:
01.sql # ┐
02.sql # ├── transaction 1
03.sql # ┘
04.tx.sql # ─── transaction 2
05.tx.sql # ─── transaction 3
06.sql # ┐
07.sql # ├── transaction 4
08.sql # ┘
09.txoff.sql # ─── no transaction
10.sql # ┐
11.sql # ├── transaction 5
12.sql # ┘
MySQL is an exception because it does not support transactional DDL. For MySQL, each migration is run outside a transaction.
If a migration filename ends in *.tx.sq, it will be run inside a new transaction. This applies even to MySQL (for example if you have some INSERT or UPDATE migrations that you want to run inside a transaction).
01.sql # ┐
02.sql # ├── transaction 1
03.sql # ┘
04.tx.sql # ─── transaction 2
05.tx.sql # ─── transaction 3
If a migration filename ends in *.txoff.sql, it will be run outside a transaction. This is already the default for MySQL, but you might want to do this for something like Postgres if the migration contains a CREATE INDEX CONCURRENTLY command (which has to be run outside a transaction).
01.sql # ┐
02.sql # ├── transaction 1
03.sql # ┘
04.txoff.sql # ─── no transaction
05.txoff.sql # ─── no transaction
CAVEAT: If you have multiple SQL statements in a file, this doesn't actually work (for Postgres and SQL Server). Due to a Postgres and SQL Server driver limitation, if you run more than one statement in an Exec
the entire thing gets implicitly wrapped in a transaction. The SQLite and MySQL drivers do not have this limitation.
As a workaround, if you need to disable transactions for Postgres and SQL Server make sure there is only one statement in the *.txoff.sql file. In practice this is not really a big deal, as the only time you need to disable transactional DDL is if you run CREATE INDEX CONCURRENTLY in Postgres.
When a non-transactional migration fails, a corresponding undo migration (if one exists) will be called to cleanup the effects of the failed migration. An undo migration is identified by <name>.undo.sql, where <name> is obtained from either <name>.sql or <name>.txoff.sql.
# This example is for MySQL, which doesn't have transactional migrations and so
# undo migrations must be defined for rollback on failure.
01_init.sql
01_init.undo.sql
02_create_index.txoff.sql
02_create_index.undo.sql
03_misc.sql
03_misc.undo.sql
Undo migrations are not down migrations. They are run only when a migration fails. Furthermore they are run only for non-transactional migrations, because if a transactional migration fails its effects will be rolled back cleanly (so no undo migration is needed).
Any migration inside a special repeatable
subdirectory is considered a repeatable migration. They are re-run whenever the contents of their file changes (based on a SHA256 checksum stored in the history table). Unlike normal migrations, repeatable migrations are sourced recursively inside the repeatable
subdirectory. This allows you to organize your repeatable migrations into further subdirectories as you wish.
01_extensions_types.sql # ┐
02_sakila.sql # ├─ migrations
03_webpage.sql # │
04_extras.sql # ┘
repeatable/ # ┐
├── functions/ # │
│ ├── film_in_stock.sql # ├─ repeatable migrations
│ └── rewards_report.sql # │
├── actor_info.sql # │
└── staff_list.sql # ┘
By default, an aggressive table lock timeout of 1 second is applied when running migrations. This means if an ALTER TABLE command cannot acquire a lock within 1 second it will fail. That is for your own good, as ALTER TABLE commands are extremely dangerous if they are left waiting for a lock (it will freeze all SQL queries running against the table).
(NOTE: an ALTER TABLE is allowed to run for more than 1 second, it is just not allowed to wait for more than 1 second for some other query to finish touching the table)
To mitigate this, retryable migrations that time out waiting for a lock are automatically retried (up to 10 times). A migration is considered retryable if it is a transactional migration or consists of a single SQL statement (which is naturally transactional). An exponentially-increasing random delay (up to 5 minutes) is inserted between attempts to maximize the chances of successfully acquiring a lock with the minimum number of attempts. If a retryable migration fails for any other reason not due to a lock timeout, it will fail normally and no further retries will be made.
You can increase the timeout duration by supplying a -lock-timeout flag.
# sqddl migrate -db <DATABASE_URL> -dir <MIGRATION_DIR> [FLAGS] [FILENAMES...]
$ sqddl migrate \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
-lock-timeout '10s' # lock timeout duration of 10 seconds
$ sqddl migrate \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
-lock-timeout '2m30s' # lock timeout duration of 2 minutes and 30 seconds
You can call migrate from Go code almost as if you were calling it from the command line.
migrateCmd, err := ddl.MigrateCommand("-db", "postgres://user:pass@localhost:5432/sakila", "-dir", "./migrations")
err = migrateCmd.Run()
You can also instantiate the struct fields directly (instead of passing in string arguments).
db, err := sql.Open("postgres", "postgres://user:pass@localhost:5432/sakila")
migrateCmd := &ddl.MigrateCmd{
Dialect: "postgres",
DB: db,
DirFS: os.DirFS("./migrations"),
}
err = migrateCmd.Run()
Note that ddl library by itself doesn't have automatic lock timeout retries because the detection of lock timeout errors is driver-specific and the ddl library avoids importing any drivers. That behaviour has to be registered by importing the following helper packages and calling their Register() function:
To run embedded migrations (using //go:embed
) on startup, create a MigrateCmd as normal and assign an embed.FS to the DirFS field. The DirFS field accepts anything that implements the fs.FS interface.
//go:embed migrations
var rootDir embed.FS
db, err := sql.Open("postgres", "postgres://user:pass@localhost:5432/sakila")
migrationsDir, err := fs.Sub(rootDir, "migrations")
cmd := &ddl.MigrateCmd{
Dialect: "postgres",
DB: db,
Dir: migrationsDir,
}
err = cmd.Run()
The ls subcommand shows the pending migrations to be run. No output means no pending migrations.
# sqddl ls -db <DATABASE_URL> -dir <MIGRATION_DIR> [FLAGS]
$ sqddl ls -db 'postgres://user:pass@localhost:5432/sakila' -dir ./migrations
[pending] 01_extensions_types.sql
[pending] 02_sakila.sql
[pending] 03_webpage.sql
[pending] 04_extras.sql
The touch subcommand upserts migrations into the history table without running them.
# sqddl touch -db <DATABASE_URL> -dir <MIGRATION_DIR> [FILENAMES...]
$ sqddl touch \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
02_sakila.sql 04_extras.sql # add 02_sakila.sql and 04_extras.sql to the history table without running them
2 rows affected
If you are introducing sqddl to an existing project, your database already has a bunch of migrations applied to it which you do not want to run again. So you add them to the history table in order to prevent them from being run. Alternatively, you can just delete the migrations from the directory.
You can use globbing to pass in multiple filenames matching a certain pattern. Filenames can optionally be prefixed with the name of the migration directory, allowing you to glob on files in the migration directory.
# sqddl touch -db <DATABASE_URL> -dir <MIGRATION_DIR> [FILENAMES...]
$ sqddl touch \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
./migrations/2022*.sql # add all migrations starting with 2022*
The rm subcommand removes migrations from the history table (it does not remove the actual migration files from the directory). This is useful if you accidentally added migrations to the history table using touch, or if you want to deregister the migration from the history table so that migrate will run it again.
# sqddl rm -db <DATABASE_URL> [FILENAMES...]
$ sqddl rm \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
02_sakila.sql 04_extras.sql # remove 02_sakila.sql and 04_extras.sql from the history table
2 rows affected
You can use globbing to pass in multiple filenames matching a certain pattern. Filenames can optionally be prefixed with the name of the migration directory, allowing you to glob on files in the migration directory.
# sqddl rm -db <DATABASE_URL> [FILENAMES...]
$ sqddl rm \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
./migrations/2022*.sql # remove all migrations starting with 2022*
The mv subcommand renames migrations in the history table. This is useful if you manually renamed the filename of a migration that was already run (for example a repeatable migration) and you want to update its entry in the history table.
# sqddl mv -db <DATABASE_URL> <OLD_FILENAME> <NEW_FILENAME>
$ sqddl mv \
-db 'postgres://user:pass@localhost:5432/sakila' \
-dir ./migrations \
old_name.sql new_name.sql # renames old_name.sql to new_name.sql in the history table
1 row affected
The tables subcommand generates table structs from the database.
# sqddl tables -db <DATABASE_URL> [FLAGS]
$ sqddl tables -db 'postgres://user:pass@localhost:5432/sakila' -pkg tables
You can include and exclude specific schemas and tables in the output. The history table (default "sqddl_history") is always excluded.
# sqddl tables -db <DATABASE_URL> [FLAGS]
# Include all tables in the 'public' schema.
$ sqddl tables \
-db 'postgres://user:pass@localhost:5432/sakila' \
-schemas public
# Include all tables called 'actor' or 'film'.
$ sqddl tables \
-db 'postgres://user:pass@localhost:5432/sakila' \
-tables actor,film
# Include the table called 'actor' in the 'public' schema.
$ sqddl tables \
-db 'postgres://user:pass@localhost:5432/sakila' \
-schemas public \
-tables actor
# Exclude all tables in the 'customer1', 'customer2' and 'customer3' schemas.
$ sqddl tables \
-db 'postgres://user:pass@localhost:5432/sakila' \
-exclude-schemas customer1,customer2,customer3
# Exclude all tables called 'country', 'city' or 'address'.
$ sqddl tables \
-db 'postgres://user:pass@localhost:5432/sakila' \
-exclude-tables country,city,address
The views subcommand generates view structs from the database.
# sqddl views -db <DATABASE_URL> [FLAGS]
$ sqddl views -db 'postgres://user:pass@localhost:5432/sakila' -pkg tables
You can include and exclude specific schemas and views in the output.
# sqddl views -db <DATABASE_URL> [FLAGS]
# Include all views in the 'public' schema.
$ sqddl views \
-db 'postgres://user:pass@localhost:5432/sakila' \
-schemas public
# Include all views called 'actor_info' or 'staff_list'.
$ sqddl views \
-db 'postgres://user:pass@localhost:5432/sakila' \
-views actor_info,staff_list
# Include the view called 'actor_info' in the 'public' schema.
$ sqddl views \
-db 'postgres://user:pass@localhost:5432/sakila' \
-schemas public \
-views actor_info
# Exclude all views in the 'customer1', 'customer2' and 'customer3' schemas.
$ sqddl views \
-db 'postgres://user:pass@localhost:5432/sakila' \
-exclude-schemas customer1,customer2,customer3
# Exclude all views called 'customer_list', 'film_list' or 'staff_list'.
$ sqddl views \
-db 'postgres://user:pass@localhost:5432/sakila' \
-exclude-views customer_list,film_list,staff_list
The generate subcommand generates migrations needed to get from a source schema to a destination schema. The source is typically a database URL/DSN (same as the -db flag), while the destination is typically a Go source file containing table structs. No output means no migrations were generated.
# sqddl generate -src <SRC_SCHEMA> -dest <DEST_SCHEMA> [FLAGS]
$ sqddl generate \
-src 'postgres://user:pass@localhost:5432/mydatabase' \
-dest tables/tables.go \
-output-dir ./migrations
./migrations/20060102150405_01_schemas.sql
./migrations/20060102150405_02_tables.sql
./migrations/20060102150405_03_add_person_country_fkeys.tx.sql
$ sqddl generate -dialect sqlite -dest tables/tables.go -dry-run
-- 20060102150405.sql
CREATE TABLE actor (
actor_id INTEGER PRIMARY KEY AUTOINCREMENT
,first_name TEXT NOT NULL
,last_name TEXT NOT NULL
,last_update DATETIME NOT NULL DEFAULT (unixepoch())
);
CREATE INDEX actor_last_name_idx ON actor (last_name);
CREATE TABLE category (
category_id INTEGER PRIMARY KEY
,name TEXT NOT NULL
,last_update DATETIME NOT NULL DEFAULT (unixepoch())
);
There are three types of values are accepted by the -src and -dest flags.
postgres://user:pass@localhost:5432/sakila
tables/tables.go
schema.json
sakila.zip
, sakila.tgz
The generate subcommand is only able to generate a subset of DDL:
Any DDL statement not supported here has to be added as a migration manually. CHECK and EXCLUDE constraints are also not supported, you will have to add them manually.
Generated migrations are safe by default i.e. they can be run against a database without blocking normal DML (SELECT, INSERT, UPDATE, DELETE) for too long (no longer than 1s). If there is anything potentially unsafe, a warning will be generated.
SQLite only allows one writer at a time, so most of this is not applicable.
CREATE TABLE is always safe because no existing code could possibly be referencing the table (since it doesn't yet exist). Same for CREATE SCHEMA.
DROP TABLE is always safe because existing code should no longer be referencing the table (you should have already removed them). Same for DROP SCHEMA.
CREATE INDEX is always created CONCURRENTLY for Postgres.
WITH (ONLINE = ON)
yourself.DROP INDEX is a fast operation, so setting a low lock timeout value should be enough to ensure it is safe.
ALTER TABLE ADD COLUMN is a fast operation, so setting a low lock timeout value should be enough to ensure it is safe.
ALTER TABLE DROP COLUMN is a fast operation, so setting a low lock timeout value should be enough to ensure it is safe.
ALTER TABLE ALTER COLUMN is usually unsafe, if unsafe a warning will be explicitly printed.
For ALTER TABLE ADD CONSTRAINT only PRIMARY KEY, FOREIGN KEY and UNIQUE constraints are supported.
WITH (ONLINE = ON)
so it will not be generated. You should add that into the migration yourself if you have the Enterprise Edition.ALTER TABLE DROP CONSTRAINT is a fast operation, so setting a low lock timeout value should be enough to ensure it is safe.
Some of the migrations generated may be unsafe and will generate warnings. You can choose to proceed anyway despite these warnings by passing in the -accept-warnings flag.
# sqddl generate -src <SRC_SCHEMA> -dest <DEST_SCHEMA> [FLAGS]
$ sqddl generate \
-src 'postgres://user:pass@localhost:5432/mydatabase' \
-dest tables/tables.go \
-output-dir ./migrations \
-accept-warnings
users: column "user_id" changing type from "TEXT" to "INT" may be unsafe
users: column "email" changing type from "TEXT" to "VARCHAR(255)" is unsafe
users: setting NOT NULL on column "email" is unsafe for large tables. Upgrade to Postgres 12+ to avoid this issue
users: column "bio" decreasing limit from "VARCHAR(1000)" to "VARCHAR(255)" is unsafe
users: column "height_meters" changing scale from "NUMERIC(1,2)" to "NUMERIC(1,4)" is unsafe
users: column "weight_kilos" decreasing precision from "NUMERIC(5,2)" to "NUMERIC(3,2)" is unsafe
users: adding column "is_active" with DEFAULT is unsafe for large tables. Upgrade to Postgres 11+ to avoid this issue. If not, you should add a column without the default first, backfill the default values, then set the column default
./migrations/20060102150405_01_alter_user.tx.sql
./migrations/20060102150405_02_validate_user_not_null.tx.sql
./migrations/20060102150405_03_alter_country.tx.sql
The wipe subcommand wipes a database of all views, tables, routines, enums, domains and extensions.
# sqddl wipe -db <DATABASE_URL> [FLAGS]
$ sqddl wipe -db 'postgres://user:pass@localhost:5432/sakila'
To view the SQL commands first without running them, pass in the -dry-run flag.
# sqddl wipe -db <DATABASE_URL> [FLAGS]
$ sqddl wipe -db 'postgres://user:pass@localhost:5432/sakila' -dry-run
DROP TABLE IF EXISTS actor CASCADE;
DROP TABLE IF EXISTS address CASCADE;
DROP TABLE IF EXISTS category CASCADE;
DROP TABLE IF EXISTS city CASCADE;
DROP TABLE IF EXISTS country CASCADE;
DROP TABLE IF EXISTS customer CASCADE;
DROP TABLE IF EXISTS data CASCADE;
DROP TABLE IF EXISTS film CASCADE;
DROP TABLE IF EXISTS film_actor CASCADE;
DROP TABLE IF EXISTS film_category CASCADE;
DROP TABLE IF EXISTS inventory CASCADE;
DROP TABLE IF EXISTS language CASCADE;
DROP TABLE IF EXISTS payment CASCADE;
DROP TABLE IF EXISTS rental CASCADE;
DROP TABLE IF EXISTS staff CASCADE;
DROP TABLE IF EXISTS store CASCADE;
DROP TABLE IF EXISTS template CASCADE;
DROP TABLE IF EXISTS webpage CASCADE;
DROP TABLE IF EXISTS webpage_data CASCADE;
DROP TYPE IF EXISTS mpaa_rating CASCADE;
DROP DOMAIN IF EXISTS year CASCADE;
DROP EXTENSION IF EXISTS btree_gist CASCADE;
DROP EXTENSION IF EXISTS "uuid-ossp" CASCADE;
You can call wipe from Go code almost as if you were calling it from the command line.
wipeCmd, err := ddl.WipeCommand("-db", "postgres://user:pass@localhost:5432/sakila", "-dry-run")
err = wipeCmd.Run()
You can also instantiate the struct fields directly (instead of passing in string arguments).
db, err := sql.Open("postgres", "postgres://user:pass@localhost:5432/sakila")
wipeCmd := &ddl.WipeCmd{
Dialect: "postgres",
DB: db,
DryRun: true,
}
err = wipeCmd.Run()
The dump subcommand can dump a database's schema and data.
actor
, the CSV file will be called actor.csv
.# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump -db 'postgres://user:pass@localhost:5432/sakila' -output-dir ./db
./db/schema.json
./db/schema.sql
./db/indexes.sql
./db/constraints.sql
./db/actor.csv
./db/address.csv
./db/category.csv
./db/city.csv
./db/country.csv
./db/customer.csv
./db/data.csv
./db/film.csv
./db/film_actor.csv
./db/film_category.csv
./db/inventory.csv
./db/language.csv
./db/payment.csv
./db/rental.csv
./db/staff.csv
./db/store.csv
Pass in the -schema-only flag. Only schema.json, schema.sql, indexes.sql and constraints.sql will be dumped.
# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump -db 'postgres://user:pass@localhost:5432/sakila' -output-dir ./db -schema-only
./db/schema.json
./db/schema.sql
./db/indexes.sql
./db/constraints.sql
Pass in the -data-only flag. Only the CSV files will be dumped.
# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump -db 'postgres://user:pass@localhost:5432/sakila' -output-dir ./db -data-only
./db/actor.csv
./db/address.csv
./db/category.csv
./db/city.csv
./db/country.csv
./db/customer.csv
./db/data.csv
./db/film.csv
./db/film_actor.csv
./db/film_category.csv
./db/inventory.csv
./db/language.csv
./db/payment.csv
./db/rental.csv
./db/staff.csv
./db/store.csv
Pass in the -tables flag. You can additionally pass in -schemas to restrict it to a particular schema.
# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump \
-db 'postgres://user:pass@localhost:5432/sakila' \
-output-dir ./db \
-tables actor,language,film
./db/actor.csv
./db/language.csv
./db/film.csv
You may choose to dump the contents directly into a .zip or .tgz archive instead by passing in the -zip or -tgz flag.
# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump -db 'postgres://user:pass@localhost:5432/sakila' -output-dir ./db -zip sakila.zip
./db/sakila.zip
$ sqddl dump -db 'postgres://user:pass@localhost:5432/sakila' -output-dir ./db -tgz sakila.tgz
./db/sakila.tgz
The downside is that this will be slower than dumping into a directory because CSV files are written one at a time (as compared to dumping into a directory where CSV files are written concurrently). If you have many tables to dump and you want to compress the result, consider dumping the files into a directory first then manually compressing it.
You can dump a referentially-intact subset of the database by passing in the -subset flag followed by a query that pulls in the data subset you want. -subset may be passed in multiple times. Each subset query must contain a "{*}
" as a placeholder for the columns to be selected, and the table being dumped must be wrapped in curly braces e.g. "{film}
". The table name may optionally be prefixed by the schema e.g. "{public.film}
".
# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump \
-db 'postgres://user:pass@localhost:5432/sakila' \
-output-dir ./db \
-data-only \
-subset 'SELECT {*} FROM {film} ORDER BY film_id LIMIT 10' # dump the first 10 films
-subset 'SELECT {*} FROM {actor}' # dump all actors
./db/actor.csv
./db/film.csv
./db/language.csv # language.csv is included because the film table references the language table
Rows from other tables will be dumped accordingly to keep the dumped data referentially intact. However because the subsetting algorithm depends on primary keys to deduplicate rows, tables without primary keys will not be dumped. If you want to dump a table that does not have a primary key, it is suggested that you dump the entire table separately (without any subsetting).
A -subset dump only includes the target table and any tables that the target table depends on directly or indirectly. This will likely not involve every table in the database. If you want a single subset query to pull in every table, you should use the -extended-subset flag instead. It includes any table that directly or indirectly depends on the target table, followed by the rest of the tables that are directly or indirectly depended on. In practice this means every table that can be joined to the target table in some way will be involved.
# sqddl dump -db <DATABASE_URL> [FLAGS]
$ sqddl dump \
-db 'postgres://user:pass@localhost:5432/sakila' \
-output-dir ./db \
-data-only \
-extended-subset 'SELECT {*} FROM {film} ORDER BY film_id LIMIT 10'
./db/actor.csv
./db/address.csv
./db/category.csv
./db/city.csv
./db/country.csv
./db/customer.csv
./db/data.csv
./db/film.csv
./db/film_actor.csv
./db/film_category.csv
./db/inventory.csv
./db/language.csv
./db/payment.csv
./db/rental.csv
./db/staff.csv
./db/store.csv
A current limitation is that your subset queries cannot pull in too many rows, because their values will be materialized into the query used to dump each table. If your subset query pulls in one million rows, there will be one million lines in the resultant query which is likely going to cause it to fail. There is an upcoming feature to add a -temp-table flag that dumps values into temporary tables first, to avoid materializing so many values into the query. That is a work in progress.
The load subcommand loads SQL scripts and CSV files into a database. It can also load directories and zip/tar gzip archives created by the dump subcommand.
# sqddl load -db <DATABASE_URL> [FLAGS] [FILENAMES...]
$ sqddl load \
-db 'postgres://user:pass@localhost:5432/sakila' \
./db/schema.sql ./db/actor.csv ./db/language.csv ./db/indexes.sql ./db/constraints.sql
$ sqddl load -db 'postgres://user:pass@localhost:5432/sakila' ./db
$ sqddl load -db 'postgres://user:pass@localhost:5432/sakila' ./db/sakila.zip
$ sqddl load -db 'postgres://user:pass@localhost:5432/sakila' ./db/sakila.tgz
If the filename passed in is an SQL file, it will be run as a normal SQL script.
If the filename passed in is a CSV file, which table the data will be loaded into depends on the filename.
01_actor.csv
.actor.csv => INSERT INTO actor
01_actor.csv => INSERT INTO actor
02_country.csv => INSERT INTO country
03_category.csv => INSERT INTO category
public.actor.csv => INSERT INTO public.actor
public.my table.csv => INSERT INTO public."my table"
The first line must include the column headers. The CSV format follows the same rules as Go's csv package:
film_id,title,cost,special_features
1,ACADEMY DINOSAUR,20.99,"[""Deleted Scenes"", ""Behind the Scenes""]"
2,ACE GOLDFINGER,12.99,"[""Trailers"", ""Deleted Scenes""]"
3,ADAPTATION HOLES,18.99,"[""Trailers"", ""Deleted Scenes""]"
4,AFFAIR PREJUDICE,26.99,"[""Commentaries"", ""Behind the Scenes""]"
If the CSV includes primary key columns, the CSV data will be upserted based on the primary key. So, it is safe to load CSV files containing lines of duplicate data.
If the filename passed in is a directory or a .zip/.tgz/.tar.gzip archive, files inside are loaded in a specific order:
load will coerce strings into a more suitable format to fit the column type (where it would otherwise fail).
(Postgres) Binary literals of form 0x267f4bdb50a041399704c26a16f8f019
(length must be 32) are converted to UUID strings if the column type is UUID. So you can use strings like 0x267f4bdb50a041399704c26a16f8f019
to represent UUIDs across all databases.
(Postgres) JSON arrays are converted to Postgres arrays if the column type is an array (e.g. TEXT[], INT[], etc). So you can use JSON arrays to represent arrays across all databases.
You can call load from Go code almost as if you were calling it from the command line.
loadCmd, err := ddl.LoadCommand(
"-db", "postgres://user:pass@localhost:5432/sakila",
"-dir", "./db",
"schema.sql",
"actor.csv",
"language.csv",
"indexes.sql",
"constraints.sql",
)
err = loadCmd.Run()
You can also instantiate the struct fields directly (instead of passing in string arguments).
db, err := sql.Open("postgres", "postgres://user:pass@localhost:5432/sakila")
loadCmd := &ddl.LoadCmd{
Dialect: "postgres",
DB: db,
DirFS: os.DirFS("./db"),
Filenames: []string{
"schema.sql",
"actor.csv",
"language.csv",
"indexes.sql",
"constraints.sql",
},
}
err = loadCmd.Run()
To load embedded files (using //go:embed
), just assign the embed.FS to the DirFS field of the LoadCmd and run it normally. The DirFS field accepts anything that implements the fs.FS interface.
//go:embed db
var rootDir embed.FS
db, err := sql.Open("postgres", "postgres://user:pass@localhost:5432/sakila")
dbDir, err := fs.Sub(rootDir, "db")
loadCmd := &ddl.LoadCmd{
Dialect: "postgres",
DB: db,
DirFS: dbDir,
Filenames: []string{
"schema.sql",
"actor.csv",
"language.csv",
"indexes.sql",
"constraints.sql",
},
}
err = loadCmd.Run()
For greater space savings, you can embed an entire .tgz archive and load that instead. This is particularly useful for test fixtures. Each test fixture can be encapsulated into its own .tgz archive (created from the dump command) and loaded for each test that spins up a new database instance e.g. an in-memory SQLite database.
//go:embed sakila.tgz
var rootDir embed.FS
db, err := sql.Open("postgres", "postgres://user:pass@localhost:5432/sakila")
loadCmd := &ddl.LoadCmd{
Dialect: "postgres",
DB: db,
DirFS: rootDir,
Filenames: []string{"sakila.tgz"},
}
err = loadCmd.Run()
The automigrate subcommand automatically migrates a database based on a declarative schema (defined as table structs). It is equivalent to running generate followed by migrate, except the generated migrations are created in-memory and will not be added to the history table.
# sqddl automigrate -db <DATABASE_URL> -dest <DEST_SCHEMA> [FLAGS]
$ sqddl automigrate -db 'postgres://user:pass@localhost:5432/sakila' -dest tables/tables.go
BEGIN
[OK] automigrate_01_schemas.sql (604.834µs)
[OK] automigrate_02_tables.sql (6.896833ms)
COMMIT
BEGIN
[OK] automigrate_03_add_person_country_fkeys.tx.sql (1.40075ms)
COMMIT
Your table structs serve as a declarative schema for your tables. Each table struct maps to an SQL table, and encodes CREATE TABLE information in ddl struct tags.
type ACTOR struct {
sq.TableStruct // sq.TableStruct must be the first field to mark this as a table struct.
ACTOR_ID sq.NumberField `ddl:"notnull primarykey identity"`
FIRST_NAME sq.StringField `ddl:"type=VARCHAR(45) notnull"`
LAST_NAME sq.StringField `ddl:"type=VARCHAR(45) notnull index"`
LAST_UPDATE sq.TimeField `ddl:"notnull default=CURRENT_TIMESTAMP"`
}
A table struct is meant to be directly usable by the sq query builder so no code generation is necessary. You maintain the schema definitions (the structs) by hand and can use them as a source of truth when generating migrations.
The table name and column names are translated from the struct name and struct field names by lowercasing them. So a struct ACTOR
will be translated to a table called actor
, and a field ACTOR_ID
will be translated to a column called actor_id
.
If you wish to use a different naming convention (for example in PascalCase), you can explicitly specify the name inside an sq struct tag.
type ACTOR struct {
sq.TableStruct `sq:"Actor"`
ACTOR_ID sq.NumberField `sq:"ActorID" ddl:"notnull primarykey identity"`
FIRST_NAME sq.StringField `sq:"FirstName" ddl:"type=VARCHAR(45) notnull"`
LAST_NAME sq.StringField `sq:"LastName" ddl:"type=VARCHAR(45) notnull index"`
LAST_UPDATE sq.TimeField `sq:"LastUpdate" ddl:"notnull default=CURRENT_TIMESTAMP"`
}
There are 10 available field types that you can use in your table structs. Each field is associated with a default SQL type which will be used in the CREATE TABLE command if you don't explicitly mention its type.
You will need to import the sq package in order to use these fields.
Field | Default SQL Type |
---|---|
sq.NumberField | INT |
sq.StringField |
SQLite, Postgres - TEXT MySQL - VARCHAR(255) SQL Server - NVARCHAR(255) |
sq.TimeField |
SQLite, MySQL - DATETIME Postgres - TIMESTAMPTZ SQL Server - DATETIMEOFFSET |
sq.BooleanField |
SQLite, Postgres, MySQL - BOOLEAN SQL Server - BIT |
sq.BinaryField |
SQLite - BLOB Postgres - BYTEA MySQL - MEDIUMBLOB SQL Server - VARBINARY(MAX) |
sq.ArrayField |
SQLite, MySQL - JSON Postgres - TEXT[] SQL Server - NVARCHAR(MAX) |
sq.EnumField |
SQLite, Postgres - TEXT MySQL - VARCHAR(255) SQL Server - NVARCHAR(255) |
sq.JSONField |
SQLite, MySQL - JSON Postgres - JSONB SQL Server - NVARCHAR(MAX) |
sq.UUIDField |
SQLite, Postgres - UUID MySQL, SQL Server - BINARY(16) |
sq.AnyField | A catch-all field type that can substitute as any of the 9 other field types. Use this to represent types like TSVECTOR that don't have a corresponding Field representation. There is no default SQL type, so a type always has to be specified. |
NOTE: If you already have an existing database, you should generate your table structs rather than manually create the table structs and struct tags. That will give you a feel of what kind of struct tag modifiers there are and how to use them.
A ddl
struct tag consists of one or more modifiers. Modifiers are delimited by spaces.
type ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"notnull primarykey identity"`
// └─────┘ └────────┘ └──────┘
// modifier modifier modifier
}
CREATE TABLE actor (
actor_id INT NOT NULL GENERATED BY DEFAULT AS IDENTITY
,CONSTRAINT actor_actor_id_pkey PRIMARY KEY (actor_id)
);
To see all available modifiers, check out the modifier list.
Modifiers may have values associated with them on the right hand side of an equals '=' sign. No spaces are allowed around the '=' sign, since a space would start a new modifier.
In the example below, the modifier value DATETIME('now')
has no spaces so no {brace quoting} is necessary.
type ACTOR struct {
sq.TableStruct
// modifier value modifier value
// ┌───────┐ ┌─────────────┐
LAST_UPDATE sq.TimeField `ddl:"type=TIMESTAMP notnull default=DATETIME('now')"`
// └────────────┘ └─────┘ └─────────────────────┘
// modifier modifier modifier
}
CREATE TABLE actor (
last_update TIMESTAMP NOT NULL DEFAULT (DATETIME('now'))
);
If a modifier value does contain spaces, the entire value has to be {brace quoted} to ensure it remains a single unit.
type FILM_ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"notnull references=actor.actor_id"`
// brace quoted because of whitespace
// ┌────────────────────────────┐
LAST_UPDATE sq.TimeField `ddl:"notnull default={DATETIME('now', 'localtime')}"`
// └─────┘ └────────────────────────────────────┘
// modifier modifier
}
CREATE TABLE film_actor (
actor_id INT NOT NULL
,last_update DATETIME NOT NULL DEFAULT (DATETIME('now', 'localtime'))
-- ↑
-- whitespace
,CONSTRAINT film_actor_actor_id_fkey FOREIGN KEY (actor_id) REFERENCES actor (actor_id)
);
A modifier may have additional submodifiers. They are expressed as a {brace quoted} raw value that contains a value and additional space-delimited submodifiers.
<modifier>
┌────────────────────────────────────────────────────────────┐
<name>={<value> <submodifier> <submodifier> <submodifier> ...}
└────┘ └─────────────────────────────────────────────────────┘
<name> <raw value>
type FILM_ACTOR struct {// modifier
sq.TableStruct // ┌────────────────────────────────────────────────────────────┐
// modifier │ value submodifier submodifier │
// ┌─────┐ │ ┌────────────┐ ┌──────────────┐ ┌───────────────┐│
ACTOR_ID sq.NumberField `ddl:"notnull references={actor.actor_id onupdate=cascade ondelete=restrict}"`
// └────────┘ └─────────────────────────────────────────────────┘
// name raw value
LAST_UPDATE sq.TimeField `ddl:"notnull default=CURRENT_TIMESTAMP"`
// └─────┘ └───────────────┘
// name raw value
}
CREATE TABLE actor (
actor_id INT NOT NULL
,last_update DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP
,CONSTRAINT film_actor_actor_id_fkey FOREIGN KEY (actor_id) REFERENCES actor (actor_id) ON UPDATE CASCADE ON DELETE RESTRICT
);
Struct tag modifiers defined on one of the 10 field types are considered column-level modifiers. Modifiers defined on a column implicitly take that column as their argument, unless explicitly specified otherwise.
type ACTOR struct {
sq.TableStruct // implicit: PRIMARY KEY (actor_id)
ACTOR_ID sq.NumberField `ddl:"primarykey"`
FIRST_NAME sq.StringField
}
type ACTOR struct {
sq.TableStruct // explicit: PRIMARY KEY (first_name)
ACTOR_ID sq.NumberField `ddl:"primarykey=first_name"`
FIRST_NAME sq.StringField
}
Struct tag modifiers defined on an sq.TableStruct
are considered table-level modifiers. There is no implicit column attached to the context, so column arguments must always be defined.
type ACTOR struct {
sq.TableStruct `ddl:"primarykey"` // Error: no column provided
ACTOR_ID sq.NumberField
FIRST_NAME sq.StringField
}
type ACTOR struct {
sq.TableStruct `ddl:"primarykey=actor_id"` // PRIMARY KEY (actor_id)
ACTOR_ID sq.NumberField
FIRST_NAME sq.StringField
}
Sometimes table-level modifiers can get really long and there's limited space in an sq.TableStruct
struct tag and struct tags cannot be broken into multiple lines, so as a workaround you can define table-level modifiers on additional unnamed _
struct fields of struct{}
type.
type ACTOR struct {
sq.TableStruct `ddl:"primarykey=actor_id"` // PRIMARY KEY (actor_id)
ACTOR_ID sq.NumberField
FIRST_NAME sq.StringField
LAST_NAME sq.StringField
LATEST_FILM_ID sq.NumberField
// CREATE UNIQUE INDEX ON actor (first_name, last_name)
_ struct{} `ddl:"index={first_name,last_name unique}"`
// FOREIGN KEY (latest_film_id) REFERENCES film (film_id) ON UPDATE CASCADE ON DELETE RESTRICT DEFERRABLE INITIALLY DEFERRED
_ struct{} `ddl:"foreignkey={latest_film_id references=film.film_id onupdate=cascade ondelete=restrict deferred}"`
}
A modifier may be prefixed by one or more SQL dialects like this: <dialect>,<dialect>,...:<modifier>
. This indicates that the modifier is only applicable for those dialects. This is used for defining table structs that use different DDL definitions depending on the dialect.
The currently valid dialect prefixes are: sqlite
, postgres
, mysql
and sqlserver
.
Modifiers are evaluated left-to-right, and so putting a dialectless modifier at the end will always override any dialect-specific modifier defined earlier.
Some modifiers are already dialect-specific e.g. auto_increment
only applies to MySQL, identity
only applies to Postgres and SQL Server. In such cases no dialect prefix is needed, ddl
will automatically ignore the modifier if it is not applicable for the current dialect.
Dialect prefix example
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"sqlite:type=INTEGER primarykey auto_increment identity"`
TITLE sq.StringField `ddl:"mysql,sqlserver:type=VARCHAR(50)"`
SPECIAL_FEATURES sq.ArrayField `ddl:"type=JSON postgres:type=TEXT[] sqlserver:type=NVARCHAR(MAX)"`
}
The above table struct will generate different CREATE TABLE statements for each dialect.
-- sqlite
CREATE TABLE film (
film_id INTEGER PRIMARY KEY
,title TEXT
,special_features JSON
);
-- postgres
CREATE TABLE film (
film_id INT GENERATED BY DEFAULT AS IDENTITY
,title TEXT
,special_features TEXT[]
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
-- mysql
CREATE TABLE film (
film_id INT AUTO_INCREMENT
,title VARCHAR(50)
,special_features JSON
,PRIMARY KEY (film_id)
);
-- sqlserver
CREATE TABLE film (
film_id INT IDENTITY
,title VARCHAR(50)
,special_features NVARCHAR(MAX)
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
Column-level modifier.
Accepts a value representing the column type. The value is literally passed to the database, spaces and all (make sure to use {brace quoting}).
type FILM struct {
sq.TableStruct
TITLE sq.StringField `ddl:"type=VARCHAR(50)"`
LAST_UPDATE sq.TimeField `ddl:"type={TIMESTAMP WITH TIME ZONE}"`
}
CREATE TABLE film (
title VARCHAR(50)
,last_update TIMESTAMP WITH TIME ZONE
);
This is also where you can define special types like SERIAL or ENUM.
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"type=SERIAL primarykey"`
FILM_RATING sq.StringField `ddl:"type={ENUM('G', 'PG', 'PG-13', 'R', 'NC-17')} default='G'"`
}
CREATE TABLE film (
film_id SERIAL PRIMARY KEY
,film_rating ENUM('G', 'PG', 'PG-13', 'R', 'NC-17') DEFAULT 'G'
);
NOTE: if your Postgres version is 10 or higher, you should not be using SERIAL. Instead, use identity
.
Column-level modifier.
Accepts a value representing the column's character limit. Also sets the column type to VARCHAR (for Postgres and MySQL) or NVARCHAR (for SQL Server). It has no effect on SQLite.
type FILM struct {
sq.TableStruct
TITLE sq.StringField `ddl:"len=50"`
DESCRIPTION sq.StringField `ddl:"len=5000"`
}
-- Postgres, MySQL
CREATE TABLE film (
title VARCHAR(50)
,description VARCHAR(5000)
);
-- SQL Server
CREATE TABLE film (
title NVARCHAR(50)
,description NVARCHAR(5000)
);
Column-level modifier. Only valid for MySQL, ignored otherwise.
Sets the column to be AUTO_INCREMENT
.
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"primarykey auto_increment"`
}
-- MySQL
CREATE TABLE film (
film_id INT AUTO_INCREMENT
,PRIMARY KEY (film_id)
);
Column-level modifier. Only valid for SQLite, ignored otherwise.
Sets the column to be AUTOINCREMENT
.
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"type=INTEGER primarykey autoincrement"`
}
-- SQLite
CREATE TABLE film (
film_id INTEGER PRIMARY KEY AUTOINCREMENT
);
Column-level modifier. Only valid for Postgres or SQL Server, ignored otherwise.
(Postgres) Sets the column to GENERATED BY DEFAULT AS IDENTITY
.
(SQL Server) Sets the column to IDENTITY
.
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"primarykey identity"`
}
-- Postgres
CREATE TABLE film (
film_id INT GENERATED BY DEFAULT AS IDENTITY
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
-- SQL Server
CREATE TABLE film (
film_id INT IDENTITY
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
Column-level modifier. Only valid for Postgres or SQL Server, ignored otherwise.
(Postgres) Sets the column to GENERATED ALWAYS AS IDENTITY
.
(SQL Server) Sets the column to IDENTITY
.
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"primarykey alwaysidentity"`
}
-- Postgres
CREATE TABLE film (
film_id INT GENERATED ALWAYS AS IDENTITY
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
-- SQL Server
CREATE TABLE film (
film_id INT IDENTITY
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
Column-level modifier.
Sets the column to be NOT NULL
.
type ACTOR struct {
sq.TableStruct
FIRST_NAME sq.StringField `ddl:"type=VARCHAR(255) notnull"`
}
CREATE TABLE actor (
first_name VARCHAR(255) NOT NULL
);
Column-level modifier. Only valid for MySQL, ignored otherwise.
Enables ON UPDATE CURRENT_TIMESTAMP
for the column.
type ACTOR struct {
sq.TableStruct
LAST_UPDATE sq.TimeField `ddl:"default=CURRENT_TIMESTAMP onupdatecurrenttimestamp"`
}
-- MySQL
CREATE TABLE actor (
last_update DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
);
Column-level modifier.
Accepts a value representing the column collation.
type FILM_ACTOR_REVIEW struct {
sq.TableStruct
REVIEW_BODY sq.StringField `ddl:"collate=C"`
}
CREATE TABLE film_actor_review (
review_body TEXT COLLATE "C"
);
Column-level modifier.
Accepts a value representing the column default.
If the column default is anything other than a string, number, TRUE
, FALSE
, CURRENT_DATE
, CURRENT_TIME
or CURRENT_TIMESTAMP
, it will be considered an SQL expression. Default SQL expressions are automatically wrapped in brackets (unless the dialect is Postgres).
For SQL Server, TRUE
and FALSE
are automatically converted to 1
and 0
so you can use TRUE
and FALSE
as default values.
type FILM struct {
sq.TableStruct
TITLE sq.StringField `ddl:"default=''"`
RENTAL_RATE sq.NumberField `ddl:"type=DECIMAL(4,2) default=4.99"`
RATING sq.StringField `ddl:"default='G'"`
LAST_UPDATE sq.NumberField `ddl:"default=DATETIME('now')"`
}
CREATE TABLE film (
title TEXT DEFAULT ''
rental_rate DECIMAL(4,2) DEFAULT 4.99
rating TEXT DEFAULT 'G'
last_update DATETIME DEFAULT (DATETIME('now'))
);
Column-level modifier.
Indicates that the column is a generated column.
Defining the generated expression inside the struct tag itself is not supported. You should add generated columns manually via a migration.
type ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"primarykey"`
FIRST_NAME sq.StringField
LAST_NAME sq.StringField
FULL_NAME sq.StringField `ddl:"generated"`
}
CREATE TABLE actor (
actor_id INT PRIMARY KEY
,first_name TEXT
,last_name TEXT
);
Added manually via a migration:
ALTER TABLE actor ADD COLUMN full_name TEXT GENERATED ALWAYS AS first_name || ' ' || last_name;
Column-level and table-level modifier.
Accepts a comma-separated list of dialects. The table or column will only be applicable for those dialects. The dialect value cannot be blank.
type FILM struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl"primarykey"`
TITLE sq.StringField `ddl:"len=50"`
FULLTEXT sq.AnyField `ddl:"dialect=postgres type=TSVECTOR index={fulltext using=GIN}"`
}
type FILM_TEXT struct {
sq.TableStruct `ddl:"dialect=mysql"`
FILM_ID sq.NumberField
TITLE sq.StringField `ddl:"index={title using=FULLTEXT}"`
}
-- Postgres
CREATE TABLE film (
film_id INT
,title VARCHAR(50)
,fulltext TSVECTOR
,CONSTRAINT film_film_id_pkey PRIMARY KEY (film_id)
);
CREATE INDEX film_fulltext_idx ON film USING gin (fulltext);
-- MySQL
CREATE TABLE film (
film_id INT
,title VARCHAR(50)
,PRIMARY KEY (film_id)
);
CREATE TABLE film_text (
film_id INT
,title TEXT
);
CREATE FULLTEXT INDEX film_text_title_idx ON film_text (title);
If dialect appears as a column-level modifier, it sets the dialect prefix for the rest of the modifiers on the right (modifiers are evaluated left-to-right).
type FILM struct {
sq.TableStruct
FULLTEXT sq.AnyField `ddl:"notnull dialect=postgres type=TSVECTOR index={fulltext using=GIN}"`
// ^ dialect modifier
}
/* is equivalent to */
type FILM struct {
sq.TableStruct
FULLTEXT sq.AnyField `ddl:"notnull postgres:type=TSVECTOR postgres:index={fulltext using=GIN}"`
// ^ dialect prefix ^ dialect prefix
}
Column-level and table-level modifier.
Accepts a value and additional submodifiers. The value is the comma-separated list of columns in the index.
type EMPLOYEE_DEPARTMENT struct {
sq.TableStruct `index=employee_id,department_id`
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
}
CREATE TABLE employee_department (
employee_id INT
,department_id INT
);
CREATE INDEX employee_department_employee_id_department_id_idx ON employee_department (employee_id, department_id);
The value can be omitted if the column being indexed is the same column the struct tag is declared on.
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"index"`
}
CREATE TABLE customer (
email TEXT
);
CREATE INDEX customer_email_idx ON customer (email);
Additional submodifiers can be specified after the value, delimited by spaces.
type EMPLOYEE_DEPARTMENT struct {
sq.TableStruct `index={employee_id,department_id unique}`
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
}
CREATE TABLE employee_department (
employee_id INT
,department_id INT
);
CREATE UNIQUE INDEX employee_department_employee_id_department_id_idx ON employee_department (employee_id, department_id);
If submodifiers are present, the value always has to be specified (or the submodifier will be mistaken as a value).
As a shortcut, a dot '.' can be used to represent the same column the struct tag is declared on.
// WRONG
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"index={unique}"` // Error: no such column "unique"
}
// RIGHT
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"index={email unique}"`
}
/* is equivalent to */
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"index={. unique}"`
}
CREATE TABLE customer (
email TEXT
);
CREATE UNIQUE INDEX customer_email_idx ON customer (email);
index
submodifier.
Marks the index as UNIQUE
.
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"index={email unique}"`
}
CREATE TABLE customer (
email TEXT
);
CREATE UNIQUE INDEX customer_email_idx ON customer (email);
index
submodifier. Only valid for Postgres or MySQL, ignored otherwise.
Accepts a value representing the index type. Possible values:
Most of the time you don't have to specify the index type because "BTREE" is the default (which is what you will be using most of the time).
type FILM struct {
sq.TableStruct `mysql:index={title,description using=FULLTEXT}`
TITLE sq.StringField
DESCRIPTION sq.StringField
FULLTEXT sq.CustomField `ddl:"dialect=postgres type=TSVECTOR index={fulltext using=GIN}"`
}
-- Postgres
CREATE TABLE film (
title TEXT
,description TEXT
,fulltext TSVECTOR
);
CREATE INDEX film_fulltext_idx ON film USING GIST (fulltext);
-- MySQL
CREATE TABLE film (
,title VARCHAR(255)
,description VARCHAR(255)
);
CREATE FULLTEXT INDEX film_title_description_idx ON film (title, description);
Column-level and table-level modifier.
Accepts a value and additional submodifiers. The value is the comma-separated list of columns in the primary key.
type EMPLOYEE_DEPARTMENT struct {
sq.TableStruct `primarykey=employee_id,department_id`
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
}
CREATE TABLE employee_department (
employee_id INT
,department_id INT
,CONSTRAINT employee_department_employee_id_department_id_pkey PRIMARY KEY (employee_id, department_id)
);
The value can be omitted if the primary key column is the same column the struct tag is declared on.
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"primarykey"`
}
CREATE TABLE customer (
email TEXT
,CONSTRAINT customer_email_pkey PRIMARY KEY (email)
);
Additional submodifiers can be specified after the value, delimited by spaces.
type EMPLOYEE_DEPARTMENT struct {
sq.TableStruct `primarykey={employee_id,department_id deferrable}`
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
}
CREATE TABLE employee_department (
employee_id INT
,department_id INT
,CONSTRAINT employee_department_employee_id_department_id_pkey PRIMARY KEY (employee_id, department_id) DEFERRABLE
);
If submodifiers are present, the value always has to be specified (or the submodifier will be mistaken as a value).
As a shortcut, a dot '.' can be used to represent the same column the struct tag is declared on.
// WRONG
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"primarykey={deferrable}"` // Error: no such column "deferrable"
}
// RIGHT
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"primarykey={email deferrable}"`
}
/* is equivalent to */
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"primarykey={. deferrable}"`
}
CREATE TABLE customer (
email TEXT
,CONSTRAINT customer_email_pkey PRIMARY KEY (email) DEFERRABLE
);
primarykey
submodifier. Only valid for Postgres, ignored otherwise.
Sets the primary key constraint to DEFERRABLE
.
type ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"primarykey={actor_id deferrable}"`
}
CREATE TABLE actor (
actor_id INT
,CONSTRAINT actor_actor_id_pkey PRIMARY KEY (actor_id) DEFERRABLE
);
primarykey
submodifier. Only valid for Postgres, ignored otherwise.
Sets the primary key constraint to DEFERRABLE INITIALLY DEFERRED
.
type ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"primarykey={actor_id deferred}"`
}
CREATE TABLE actor (
actor_id INT
,CONSTRAINT actor_actor_id_pkey PRIMARY KEY (actor_id) DEFERRABLE INITIALLY DEFERRED
);
Column-level modifier.
Accepts a value and additional submodifiers. The value is the column being referenced by the foreign key and can take one of three forms:
<table>
(if the columns have the same name)
film
<table>.<column>
film.film_id
<schema>.<table>.<column>
(if the foreign key points at another schema)
public.film.film_id
type FILM_ACTOR struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"references=film"`
ACTOR_ID sq.NumberField `ddl:"references=actor.actor_id"`
CHARACTER_ID sq.NumberField `ddl:"references=schema1.characters.character_id"`
}
CREATE TABLE film_actor (
film_id INT
,actor_id INT
,character_id INT
,CONSTRAINT film_actor_film_id_fkey FOREIGN KEY (film_id) REFERENCES film (film_id)
,CONSTRAINT film_actor_actor_id_fkey FOREIGN KEY (actor_id) REFERENCES actor (actor_id)
,CONSTRAINT film_actor_character_id_fkey FOREIGN KEY (character_id) REFERENCES schema1.characters (character_id)
);
The references
modifier only supports foreign keys containing one column. To support foreign keys containing multiple columns, use the foreignkey
modifier instead.
references
submodifier.
Creates an index on the foreign key column.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"references={language.language_id index}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id)
);
CREATE INDEX film_language_id_idx ON film (language_id);
references
submodifier.
Accepts a value for the ON UPDATE
action of the foreign key. Possible values: cascade
, restrict
, noaction
, setnull
or setdefault
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"references={language.language_id onupdate=cascade}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) ON UPDATE CASCADE
);
references
submodifier.
Accepts a value for the ON DELETE
action of the foreign key. Possible values: cascade
, restrict
, noaction
, setnull
or setdefault
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"references={language.language_id ondelete=restrict}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) ON DELETE RESTRICT
);
references
submodifier. Only valid for SQLite or Postgres, ignored otherwise.
Sets the foreign key constraint to DEFERRABLE
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"references={language.language_id deferrable}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) DEFERRABLE
);
references
submodifier. Only valid for SQLite or Postgres, ignored otherwise.
Sets the foreign key constraint to DEFERRABLE INITIALLY DEFERRED
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"references={language.language_id deferred}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) DEFERRABLE INITIALLY DEFERRED
);
Table-level modifier.
Accepts a value and additional submodifiers. The value is the comma-separated list of columns in the foreign key. The references
submodifier value must always be provided (its format is the same as the references
modifier).
type FILM_ACTOR struct {
sq.TableStruct
FILM_ID sq.NumberField `ddl:"foreignkey={film_id references=film}"`
ACTOR_ID sq.NumberField `ddl:"foreignkey={actor_id references=actor.actor_id}"`
CHARACTER_ID sq.NumberField `ddl:"foreignkey={character_id references=schema1.characters.character_id}"`
}
CREATE TABLE film_actor (
film_id INT
,actor_id INT
,character_id INT
,CONSTRAINT film_actor_film_id_fkey FOREIGN KEY (film_id) REFERENCES film (film_id)
,CONSTRAINT film_actor_actor_id_fkey FOREIGN KEY (actor_id) REFERENCES actor (actor_id)
,CONSTRAINT film_actor_character_id_fkey FOREIGN KEY (character_id) REFERENCES schema1.characters (character_id)
);
Here is how to define a foreign key with multiple columns.
type TASK struct {
sq.TableStruct
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
_ struct{} `ddl:"foreignkey={employee_id,department_id references=employee_department.employee_id,department_id onupdate=cascade}"`
}
/* is equivalent to */
type TASK struct {
sq.TableStruct
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
_ struct{} `ddl:"foreignkey={employee_id,department_id references=employee_department onupdate=cascade}"`
}
CREATE TABLE task (
employee_id INT
,department_id INT
,CONSTRAINT task_employee_id_department_id_fkey FOREIGN KEY (employee_id, department_id) REFERENCES employee_department (employee_id, department_id) ON UPDATE CASCADE
);
foreignkey
submodifier.
Accepts a value representing the column(s) being referenced by the foreign key. Must always be provided for the foreignkey
modifier. Refer to the foreignkey
modifier for an example.
foreignkey
submodifier.
Creates an index on the foreign key column(s).
type TASK struct {
sq.TableStruct
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
_ struct{} `ddl:"foreignkey={employee_id,department_id references=employee_department index}"`
}
CREATE TABLE task (
employee_id INT
,department_id INT
,CONSTRAINT task_employee_id_department_id_fkey FOREIGN KEY (employee_id, department_id) REFERENCES employee_department (employee_id, department_id)
);
CREATE INDEX task_employee_id_department_id_idx ON task (employee_id, department_id);
foreignkey
submodifier.
Accepts a value for the ON UPDATE
action of the foreign key. Possible values: cascade
, restrict
, noaction
, setnull
or setdefault
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"foreignkey={language_id references=language.language_id onupdate=cascade}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) ON UPDATE CASCADE
);
foreignkey
submodifier.
Accepts a value for the ON DELETE
action of the foreign key. Possible values: cascade
, restrict
, noaction
, setnull
or setdefault
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"foreignkey={language_id references=language.language_id ondelete=restrict}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) ON DELETE RESTRICT
);
foreignkey
submodifier. Only valid for SQLite or Postgres, ignored otherwise.
Sets the foreign key constraint to DEFERRABLE
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"foreignkey={language_id references=language.language_id deferrable}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) DEFERRABLE
);
foreignkey
submodifier. Only valid for SQLite or Postgres, ignored otherwise.
Sets the foreign key constraint to DEFERRABLE INITIALLY DEFERRED
.
type FILM struct {
sq.TableStruct
LANGUAGE_ID sq.NumberField `ddl:"foreignkey={language_id references=language.language_id deferred}"`
}
CREATE TABLE film (
language_id INT
,CONSTRAINT film_language_id_fkey FOREIGN KEY (language_id) REFERENCES language (language_id) DEFERRABLE INITIALLY DEFERRED
);
Column-level and table-level modifier.
Accepts a value and additional submodifiers. The value is the comma-separated list of columns in the unique constraint.
type EMPLOYEE_DEPARTMENT struct {
sq.TableStruct `unique=employee_id,department_id`
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
}
CREATE TABLE employee_department (
employee_id INT
,department_id INT
,CONSTRAINT employee_department_employee_id_department_id_key UNIQUE (employee_id, department_id)
);
The value can be omitted if the primary key column is the same column the struct tag is declared on.
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"unique"`
}
CREATE TABLE customer (
email TEXT
,CONSTRAINT customer_email_key UNIQUE (email)
);
Additional submodifiers can be specified after the value, delimited by spaces.
type EMPLOYEE_DEPARTMENT struct {
sq.TableStruct `unique={employee_id,department_id deferrable}`
EMPLOYEE_ID sq.NumberField
DEPARTMENT_ID sq.NumberField
}
CREATE TABLE employee_department (
employee_id INT
,department_id INT
,CONSTRAINT employee_department_employee_id_department_id_key UNIQUE (employee_id, department_id) DEFERRABLE
);
If submodifiers are present, the value always has to be specified (or the submodifier will be mistaken as a value).
As a shortcut, a dot '.' can be used to represent the same column the struct tag is declared on.
// WRONG
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"unique={deferrable}"` // Error: no such column "deferrable"
}
// RIGHT
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"unique={email deferrable}"`
}
/* is equivalent to */
type CUSTOMER struct {
sq.TableStruct
EMAIL sq.StringField `ddl:"unique={. deferrable}"`
}
CREATE TABLE customer (
email TEXT
,CONSTRAINT customer_email_pkey PRIMARY KEY (email) DEFERRABLE
);
unique
submodifier. Only valid for Postgres, ignored otherwise.
Sets the unique constraint to DEFERRABLE
.
type ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"unique={actor_id deferrable}"`
}
CREATE TABLE actor (
actor_id INT
,CONSTRAINT actor_actor_id_key UNIQUE (actor_id) DEFERRABLE
);
unique
submodifier. Only valid for Postgres, ignored otherwise.
Sets the unique constraint to DEFERRABLE INITIALLY DEFERRED
.
type ACTOR struct {
sq.TableStruct
ACTOR_ID sq.NumberField `ddl:"unique={actor_id deferrable}"`
}
CREATE TABLE actor (
actor_id INT
,CONSTRAINT actor_actor_id_key UNIQUE (actor_id) DEFERRABLE
);