* 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>
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Synapse database schema files
Synapse's database schema is stored in the synapse.storage.schema
module.
Logical databases
Synapse supports splitting its datastore across multiple physical databases (which can be useful for large installations), and the schema files are therefore split according to the logical database they apply to.
At the time of writing, the following "logical" databases are supported:
state
- used to store Matrix room state (more specifically,state_groups
, their relationships and contents).main
- stores everything else.
Additionally, the common
directory contains schema files for tables which must be
present on all physical databases.
Synapse schema versions
Synapse manages its database schema via "schema versions". These are mainly used to help avoid confusion if the Synapse codebase is rolled back after the database is updated. They work as follows:
-
The Synapse codebase defines a constant
synapse.storage.schema.SCHEMA_VERSION
which represents the expectations made about the database by that version. For example, as of Synapse v1.36, this is59
. -
The database stores a "compatibility version" in
schema_compat_version.compat_version
which defines theSCHEMA_VERSION
of the oldest version of Synapse which will work with the database. On startup, ifcompat_version
is found to be newer thanSCHEMA_VERSION
, Synapse will refuse to start.Synapse automatically updates this field from
synapse.storage.schema.SCHEMA_COMPAT_VERSION
. -
Whenever a backwards-incompatible change is made to the database format (normally via a
delta
file),synapse.storage.schema.SCHEMA_COMPAT_VERSION
is also updated so that administrators can not accidentally roll back to a too-old version of Synapse.
Generally, the goal is to maintain compatibility with at least one or two previous releases of Synapse, so any substantial change tends to require multiple releases and a bit of forward-planning to get right.
As a worked example: we want to remove the room_stats_historical
table. Here is how it
might pan out.
-
Replace any code that reads from
room_stats_historical
with alternative implementations, but keep writing to it in case of rollback to an earlier version. Also, increasesynapse.storage.schema.SCHEMA_VERSION
. In this instance, there is no existing code which reads fromroom_stats_historical
, so our starting point is:v1.36.0:
SCHEMA_VERSION=59
,SCHEMA_COMPAT_VERSION=59
-
Next (say in Synapse v1.37.0): remove the code that writes to
room_stats_historical
, but don’t yet remove the table in case of rollback to v1.36.0. Again, we increasesynapse.storage.schema.SCHEMA_VERSION
, but because we have not broken compatibility with v1.36, we do not yet updateSCHEMA_COMPAT_VERSION
. We now have:v1.37.0:
SCHEMA_VERSION=60
,SCHEMA_COMPAT_VERSION=59
. -
Later (say in Synapse v1.38.0): we can remove the table altogether. This will break compatibility with v1.36.0, so we must update
SCHEMA_COMPAT_VERSION
accordingly. There is no need to updatesynapse.storage.schema.SCHEMA_VERSION
, since there is no change to the Synapse codebase here. So we end up with:v1.38.0:
SCHEMA_VERSION=60
,SCHEMA_COMPAT_VERSION=60
.
If in doubt about whether to update SCHEMA_VERSION
or not, it is generally best to
lean towards doing so.
Full schema dumps
In the full_schemas
directories, only the most recently-numbered snapshot is used
(54
at the time of writing). Older snapshots (eg, 16
) are present for historical
reference only.
Building full schema dumps
If you want to recreate these schemas, they need to be made from a database that has had all background updates run.
To do so, use scripts-dev/make_full_schema.sh
. This will produce new
full.sql.postgres
and full.sql.sqlite
files.
Ensure postgres is installed, then run:
./scripts-dev/make_full_schema.sh -p postgres_username -o output_dir/
NB at the time of writing, this script predates the split into separate state
/main
databases so will require updates to handle that correctly.
Delta files
Delta files define the steps required to upgrade the database from an earlier version. They can be written as either a file containing a series of SQL statements, or a Python module.
Synapse remembers which delta files it has applied to a database (they are stored in the
applied_schema_deltas
table) and will not re-apply them (even if a given file is
subsequently updated).
Delta files should be placed in a directory named synapse/storage/schema/<database>/delta/<version>/
.
They are applied in alphanumeric order, so by convention the first two characters
of the filename should be an integer such as 01
, to put the file in the right order.
SQL delta files
These should be named *.sql
, or — for changes which should only be applied for a
given database engine — *.sql.posgres
or *.sql.sqlite
. For example, a delta which
adds a new column to the foo
table might be called 01add_bar_to_foo.sql
.
Note that our SQL parser is a bit simple - it understands comments (--
and /*...*/
),
but complex statements which require a ;
in the middle of them (such as CREATE TRIGGER
) are beyond it and you'll have to use a Python delta file.
Python delta files
For more flexibility, a delta file can take the form of a python module. These should
be named *.py
. Note that database-engine-specific modules are not supported here –
instead you can write if isinstance(database_engine, PostgresEngine)
or similar.
A Python delta module should define either or both of the following functions:
import synapse.config.homeserver
import synapse.storage.engines
import synapse.storage.types
def run_create(
cur: synapse.storage.types.Cursor,
database_engine: synapse.storage.engines.BaseDatabaseEngine,
) -> None:
"""Called whenever an existing or new database is to be upgraded"""
...
def run_upgrade(
cur: synapse.storage.types.Cursor,
database_engine: synapse.storage.engines.BaseDatabaseEngine,
config: synapse.config.homeserver.HomeServerConfig,
) -> None:
"""Called whenever an existing database is to be upgraded."""
...
Boolean columns
Boolean columns require special treatment, since SQLite treats booleans the same as integers.
There are three separate aspects to this:
-
Any new boolean column must be added to the
BOOLEAN_COLUMNS
list insynapse/_scripts/synapse_port_db.py
. This tells the port script to cast the integer value from SQLite to a boolean before writing the value to the postgres database. -
Before SQLite 3.23,
TRUE
andFALSE
were not recognised as constants by SQLite, and theIS [NOT] TRUE
/IS [NOT] FALSE
operators were not supported. This makes it necessary to avoid usingTRUE
andFALSE
constants in SQL commands.For example, to insert a
TRUE
value into the database, write:txn.execute("INSERT INTO tbl(col) VALUES (?)", (True, ))
-
Default values for new boolean columns present a particular difficulty. Generally it is best to create separate schema files for Postgres and SQLite. For example:
# in 00delta.sql.postgres: ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT FALSE;
# in 00delta.sql.sqlite: ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT 0;
Note that there is a particularly insidious failure mode here: the Postgres flavour will be accepted by SQLite 3.22, but will give a column whose default value is the string
"FALSE"
- which, when cast back to a boolean in Python, evaluates toTrue
.