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* Two scripts are basically entry_points already * Move and rename scripts/* to synapse/_scripts/*.py * Delete sync_room_to_group.pl * Expose entry points in setup.py * Update linter script and config * Fixup scripts & docs mentioning scripts that moved Co-authored-by: Andrew Morgan <1342360+anoadragon453@users.noreply.github.com>
193 lines
7.6 KiB
Markdown
193 lines
7.6 KiB
Markdown
# Synapse database schema files
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Synapse's database schema is stored in the `synapse.storage.schema` module.
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## Logical databases
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Synapse supports splitting its datastore across multiple physical databases (which can
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be useful for large installations), and the schema files are therefore split according
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to the logical database they apply to.
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At the time of writing, the following "logical" databases are supported:
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* `state` - used to store Matrix room state (more specifically, `state_groups`,
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their relationships and contents).
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* `main` - stores everything else.
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Additionally, the `common` directory contains schema files for tables which must be
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present on *all* physical databases.
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## Synapse schema versions
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Synapse manages its database schema via "schema versions". These are mainly used to
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help avoid confusion if the Synapse codebase is rolled back after the database is
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updated. They work as follows:
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* The Synapse codebase defines a constant `synapse.storage.schema.SCHEMA_VERSION`
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which represents the expectations made about the database by that version. For
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example, as of Synapse v1.36, this is `59`.
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* The database stores a "compatibility version" in
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`schema_compat_version.compat_version` which defines the `SCHEMA_VERSION` of the
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oldest version of Synapse which will work with the database. On startup, if
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`compat_version` is found to be newer than `SCHEMA_VERSION`, Synapse will refuse to
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start.
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Synapse automatically updates this field from
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`synapse.storage.schema.SCHEMA_COMPAT_VERSION`.
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* Whenever a backwards-incompatible change is made to the database format (normally
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via a `delta` file), `synapse.storage.schema.SCHEMA_COMPAT_VERSION` is also updated
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so that administrators can not accidentally roll back to a too-old version of Synapse.
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Generally, the goal is to maintain compatibility with at least one or two previous
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releases of Synapse, so any substantial change tends to require multiple releases and a
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bit of forward-planning to get right.
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As a worked example: we want to remove the `room_stats_historical` table. Here is how it
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might pan out.
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1. Replace any code that *reads* from `room_stats_historical` with alternative
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implementations, but keep writing to it in case of rollback to an earlier version.
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Also, increase `synapse.storage.schema.SCHEMA_VERSION`. In this
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instance, there is no existing code which reads from `room_stats_historical`, so
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our starting point is:
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v1.36.0: `SCHEMA_VERSION=59`, `SCHEMA_COMPAT_VERSION=59`
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2. Next (say in Synapse v1.37.0): remove the code that *writes* to
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`room_stats_historical`, but don’t yet remove the table in case of rollback to
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v1.36.0. Again, we increase `synapse.storage.schema.SCHEMA_VERSION`, but
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because we have not broken compatibility with v1.36, we do not yet update
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`SCHEMA_COMPAT_VERSION`. We now have:
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v1.37.0: `SCHEMA_VERSION=60`, `SCHEMA_COMPAT_VERSION=59`.
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3. Later (say in Synapse v1.38.0): we can remove the table altogether. This will
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break compatibility with v1.36.0, so we must update `SCHEMA_COMPAT_VERSION` accordingly.
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There is no need to update `synapse.storage.schema.SCHEMA_VERSION`, since there is no
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change to the Synapse codebase here. So we end up with:
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v1.38.0: `SCHEMA_VERSION=60`, `SCHEMA_COMPAT_VERSION=60`.
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If in doubt about whether to update `SCHEMA_VERSION` or not, it is generally best to
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lean towards doing so.
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## Full schema dumps
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In the `full_schemas` directories, only the most recently-numbered snapshot is used
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(`54` at the time of writing). Older snapshots (eg, `16`) are present for historical
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reference only.
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### Building full schema dumps
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If you want to recreate these schemas, they need to be made from a database that
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has had all background updates run.
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To do so, use `scripts-dev/make_full_schema.sh`. This will produce new
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`full.sql.postgres` and `full.sql.sqlite` files.
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Ensure postgres is installed, then run:
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```sh
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./scripts-dev/make_full_schema.sh -p postgres_username -o output_dir/
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```
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NB at the time of writing, this script predates the split into separate `state`/`main`
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databases so will require updates to handle that correctly.
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## Delta files
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Delta files define the steps required to upgrade the database from an earlier version.
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They can be written as either a file containing a series of SQL statements, or a Python
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module.
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Synapse remembers which delta files it has applied to a database (they are stored in the
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`applied_schema_deltas` table) and will not re-apply them (even if a given file is
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subsequently updated).
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Delta files should be placed in a directory named `synapse/storage/schema/<database>/delta/<version>/`.
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They are applied in alphanumeric order, so by convention the first two characters
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of the filename should be an integer such as `01`, to put the file in the right order.
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### SQL delta files
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These should be named `*.sql`, or — for changes which should only be applied for a
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given database engine — `*.sql.posgres` or `*.sql.sqlite`. For example, a delta which
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adds a new column to the `foo` table might be called `01add_bar_to_foo.sql`.
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Note that our SQL parser is a bit simple - it understands comments (`--` and `/*...*/`),
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but complex statements which require a `;` in the middle of them (such as `CREATE
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TRIGGER`) are beyond it and you'll have to use a Python delta file.
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### Python delta files
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For more flexibility, a delta file can take the form of a python module. These should
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be named `*.py`. Note that database-engine-specific modules are not supported here –
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instead you can write `if isinstance(database_engine, PostgresEngine)` or similar.
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A Python delta module should define either or both of the following functions:
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```python
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import synapse.config.homeserver
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import synapse.storage.engines
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import synapse.storage.types
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def run_create(
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cur: synapse.storage.types.Cursor,
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database_engine: synapse.storage.engines.BaseDatabaseEngine,
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) -> None:
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"""Called whenever an existing or new database is to be upgraded"""
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...
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def run_upgrade(
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cur: synapse.storage.types.Cursor,
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database_engine: synapse.storage.engines.BaseDatabaseEngine,
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config: synapse.config.homeserver.HomeServerConfig,
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) -> None:
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"""Called whenever an existing database is to be upgraded."""
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...
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```
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## Boolean columns
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Boolean columns require special treatment, since SQLite treats booleans the
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same as integers.
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There are three separate aspects to this:
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* Any new boolean column must be added to the `BOOLEAN_COLUMNS` list in
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`synapse/_scripts/synapse_port_db.py`. This tells the port script to cast
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the integer value from SQLite to a boolean before writing the value to the
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postgres database.
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* Before SQLite 3.23, `TRUE` and `FALSE` were not recognised as constants by
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SQLite, and the `IS [NOT] TRUE`/`IS [NOT] FALSE` operators were not
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supported. This makes it necessary to avoid using `TRUE` and `FALSE`
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constants in SQL commands.
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For example, to insert a `TRUE` value into the database, write:
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```python
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txn.execute("INSERT INTO tbl(col) VALUES (?)", (True, ))
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```
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* Default values for new boolean columns present a particular
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difficulty. Generally it is best to create separate schema files for
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Postgres and SQLite. For example:
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```sql
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# in 00delta.sql.postgres:
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ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT FALSE;
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```
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```sql
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# in 00delta.sql.sqlite:
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ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT 0;
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```
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Note that there is a particularly insidious failure mode here: the Postgres
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flavour will be accepted by SQLite 3.22, but will give a column whose
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default value is the **string** `"FALSE"` - which, when cast back to a boolean
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in Python, evaluates to `True`.
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