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< h1 id = "synapse-database-schema-files" > < a class = "header" href = "#synapse-database-schema-files" > Synapse database schema files< / a > < / h1 >
< p > Synapse's database schema is stored in the < code > synapse.storage.schema< / code > module.< / p >
< h2 id = "logical-databases" > < a class = "header" href = "#logical-databases" > Logical databases< / a > < / h2 >
< p > 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.< / p >
< p > At the time of writing, the following " logical" databases are supported:< / p >
< ul >
< li > < code > state< / code > - used to store Matrix room state (more specifically, < code > state_groups< / code > ,
their relationships and contents).< / li >
< li > < code > main< / code > - stores everything else.< / li >
< / ul >
< p > Additionally, the < code > common< / code > directory contains schema files for tables which must be
present on < em > all< / em > physical databases.< / p >
< h2 id = "synapse-schema-versions" > < a class = "header" href = "#synapse-schema-versions" > Synapse schema versions< / a > < / h2 >
< p > 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:< / p >
< ul >
< li >
< p > The Synapse codebase defines a constant < code > synapse.storage.schema.SCHEMA_VERSION< / code >
which represents the expectations made about the database by that version. For
example, as of Synapse v1.36, this is < code > 59< / code > .< / p >
< / li >
< li >
< p > The database stores a " compatibility version" in
< code > schema_compat_version.compat_version< / code > which defines the < code > SCHEMA_VERSION< / code > of the
oldest version of Synapse which will work with the database. On startup, if
< code > compat_version< / code > is found to be newer than < code > SCHEMA_VERSION< / code > , Synapse will refuse to
start.< / p >
< p > Synapse automatically updates this field from
< code > synapse.storage.schema.SCHEMA_COMPAT_VERSION< / code > .< / p >
< / li >
< li >
< p > Whenever a backwards-incompatible change is made to the database format (normally
via a < code > delta< / code > file), < code > synapse.storage.schema.SCHEMA_COMPAT_VERSION< / code > is also updated
so that administrators can not accidentally roll back to a too-old version of Synapse.< / p >
< / li >
< / ul >
< p > 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.< / p >
< p > As a worked example: we want to remove the < code > room_stats_historical< / code > table. Here is how it
might pan out.< / p >
< ol >
< li >
< p > Replace any code that < em > reads< / em > from < code > room_stats_historical< / code > with alternative
implementations, but keep writing to it in case of rollback to an earlier version.
Also, increase < code > synapse.storage.schema.SCHEMA_VERSION< / code > . In this
instance, there is no existing code which reads from < code > room_stats_historical< / code > , so
our starting point is:< / p >
< p > v1.36.0: < code > SCHEMA_VERSION=59< / code > , < code > SCHEMA_COMPAT_VERSION=59< / code > < / p >
< / li >
< li >
< p > Next (say in Synapse v1.37.0): remove the code that < em > writes< / em > to
< code > room_stats_historical< / code > , but don’
v1.36.0. Again, we increase < code > synapse.storage.schema.SCHEMA_VERSION< / code > , but
because we have not broken compatibility with v1.36, we do not yet update
< code > SCHEMA_COMPAT_VERSION< / code > . We now have:< / p >
< p > v1.37.0: < code > SCHEMA_VERSION=60< / code > , < code > SCHEMA_COMPAT_VERSION=59< / code > .< / p >
< / li >
< li >
< p > 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 < code > SCHEMA_COMPAT_VERSION< / code > accordingly.
There is no need to update < code > synapse.storage.schema.SCHEMA_VERSION< / code > , since there is no
change to the Synapse codebase here. So we end up with:< / p >
< p > v1.38.0: < code > SCHEMA_VERSION=60< / code > , < code > SCHEMA_COMPAT_VERSION=60< / code > .< / p >
< / li >
< / ol >
< p > If in doubt about whether to update < code > SCHEMA_VERSION< / code > or not, it is generally best to
lean towards doing so.< / p >
< h2 id = "full-schema-dumps" > < a class = "header" href = "#full-schema-dumps" > Full schema dumps< / a > < / h2 >
< p > In the < code > full_schemas< / code > directories, only the most recently-numbered snapshot is used
(< code > 54< / code > at the time of writing). Older snapshots (eg, < code > 16< / code > ) are present for historical
reference only.< / p >
< h3 id = "building-full-schema-dumps" > < a class = "header" href = "#building-full-schema-dumps" > Building full schema dumps< / a > < / h3 >
< p > If you want to recreate these schemas, they need to be made from a database that
has had all background updates run.< / p >
< p > To do so, use < code > scripts-dev/make_full_schema.sh< / code > . This will produce new
< code > full.sql.postgres< / code > and < code > full.sql.sqlite< / code > files.< / p >
< p > Ensure postgres is installed, then run:< / p >
< pre > < code class = "language-sh" > ./scripts-dev/make_full_schema.sh -p postgres_username -o output_dir/
< / code > < / pre >
< p > NB at the time of writing, this script predates the split into separate < code > state< / code > /< code > main< / code >
databases so will require updates to handle that correctly.< / p >
< h2 id = "delta-files" > < a class = "header" href = "#delta-files" > Delta files< / a > < / h2 >
< p > 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.< / p >
< p > Synapse remembers which delta files it has applied to a database (they are stored in the
< code > applied_schema_deltas< / code > table) and will not re-apply them (even if a given file is
subsequently updated).< / p >
< p > Delta files should be placed in a directory named < code > synapse/storage/schema/< database> /delta/< version> /< / code > .
They are applied in alphanumeric order, so by convention the first two characters
of the filename should be an integer such as < code > 01< / code > , to put the file in the right order.< / p >
< h3 id = "sql-delta-files" > < a class = "header" href = "#sql-delta-files" > SQL delta files< / a > < / h3 >
< p > These should be named < code > *.sql< / code > , or — for changes which should only be applied for a
given database engine — < code > *.sql.posgres< / code > or < code > *.sql.sqlite< / code > . For example, a delta which
adds a new column to the < code > foo< / code > table might be called < code > 01add_bar_to_foo.sql< / code > .< / p >
< p > Note that our SQL parser is a bit simple - it understands comments (< code > --< / code > and < code > /*...*/< / code > ),
but complex statements which require a < code > ;< / code > in the middle of them (such as < code > CREATE TRIGGER< / code > ) are beyond it and you'll have to use a Python delta file.< / p >
< h3 id = "python-delta-files" > < a class = "header" href = "#python-delta-files" > Python delta files< / a > < / h3 >
< p > For more flexibility, a delta file can take the form of a python module. These should
be named < code > *.py< / code > . Note that database-engine-specific modules are not supported here –
instead you can write < code > if isinstance(database_engine, PostgresEngine)< / code > or similar.< / p >
< p > A Python delta module should define either or both of the following functions:< / p >
< pre > < code class = "language-python" > 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." " "
...
< / code > < / pre >
< h2 id = "boolean-columns" > < a class = "header" href = "#boolean-columns" > Boolean columns< / a > < / h2 >
< p > Boolean columns require special treatment, since SQLite treats booleans the
same as integers.< / p >
< p > There are three separate aspects to this:< / p >
< ul >
< li >
< p > Any new boolean column must be added to the < code > BOOLEAN_COLUMNS< / code > list in
< code > synapse/_scripts/synapse_port_db.py< / code > . This tells the port script to cast
the integer value from SQLite to a boolean before writing the value to the
postgres database.< / p >
< / li >
< li >
< p > Before SQLite 3.23, < code > TRUE< / code > and < code > FALSE< / code > were not recognised as constants by
SQLite, and the < code > IS [NOT] TRUE< / code > /< code > IS [NOT] FALSE< / code > operators were not
supported. This makes it necessary to avoid using < code > TRUE< / code > and < code > FALSE< / code >
constants in SQL commands.< / p >
< p > For example, to insert a < code > TRUE< / code > value into the database, write:< / p >
< pre > < code class = "language-python" > txn.execute(" INSERT INTO tbl(col) VALUES (?)" , (True, ))
< / code > < / pre >
< / li >
< li >
< p > 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:< / p >
< pre > < code class = "language-sql" > # in 00delta.sql.postgres:
ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT FALSE;
< / code > < / pre >
< pre > < code class = "language-sql" > # in 00delta.sql.sqlite:
ALTER TABLE tbl ADD COLUMN col BOOLEAN DEFAULT 0;
< / code > < / pre >
< p > 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 < strong > string< / strong > < code > " FALSE" < / code > - which, when cast back to a boolean
in Python, evaluates to < code > True< / code > .< / p >
< / li >
< / ul >
< h2 id = "event_id-global-uniqueness" > < a class = "header" href = "#event_id-global-uniqueness" > < code > event_id< / code > global uniqueness< / a > < / h2 >
< p > < code > event_id< / code > 's can be considered globally unique although there has been a lot of
debate on this topic in places like
< a href = "https://github.com/matrix-org/matrix-spec-proposals/issues/2779" > MSC2779< / a > and
< a href = "https://github.com/matrix-org/matrix-spec-proposals/pull/2848" > MSC2848< / a > which
has no resolution yet (as of 2022-09-01). There are several places in Synapse
and even in the Matrix APIs like < a href = "https://spec.matrix.org/v1.1/server-server-api/#get_matrixfederationv1eventeventid" > < code > GET /_matrix/federation/v1/event/{eventId}< / code > < / a >
where we assume that event IDs are globally unique.< / p >
< p > When scoping < code > event_id< / code > in a database schema, it is often nice to accompany it
with < code > room_id< / code > (< code > PRIMARY KEY (room_id, event_id)< / code > and a < code > FOREIGN KEY(room_id) REFERENCES rooms(room_id)< / code > ) which makes flexible lookups easy. For example it
makes it very easy to find and clean up everything in a room when it needs to be
purged (no need to use sub-< code > select< / code > query or join from the < code > events< / code > table).< / p >
< p > A note on collisions: In room versions < code > 1< / code > and < code > 2< / code > it's possible to end up with
two events with the same < code > event_id< / code > (in the same or different rooms). After room
version < code > 3< / code > , that can only happen with a hash collision, which we basically hope
will never happen (SHA256 has a massive big key space).< / p >
< / main >
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