DDL replication v4
DDL stands for data definition language, the subset of the SQL language that creates, alters, and drops database objects.
For operational convenience and correctness, BDR replicates most DDL actions, with these exceptions:
- Temporary or unlogged relations
- Certain DDL statements (mostly long running ); See DDL statements with restrictions)
- Locking commands (
- Table maintenance commands (
- Actions of autovacuum
- Operational commands (
- Actions related to databases or tablespaces
Automatic DDL replication makes certain DDL changes easier without having to manually distribute the DDL change to all nodes and ensure that they are consistent.
In the default replication set, DDL is replicated to all nodes by default. To replicate DDL, you must add a DDL replication filter to the replication set. See DDL replication filtering.
BDR is significantly different from standalone PostgreSQL when it comes to DDL replication. Treating it the same is the most common issue with BDR.
The main difference from table replication is that DDL replication doesn't replicate the result of the DDL but the statement itself. This works very well in most cases, although it introduces the requirement that the DDL must execute similarly on all nodes. A more subtle point is that the DDL must be immutable with respect to all datatype-specific parameter settings, including any datatypes introduced by extensions (not built-in). For example, the DDL statement must execute correctly in the default encoding used on each node.
bdr.ddl_replication parameter specifies replication behavior.
bdr.ddl_replication = on is the default and replicates DDL to the
default replication set, which by default means all nodes. Nondefault
replication sets don't replicate DDL unless they have a
defined for them.
You can also replicate DDL to specific replication sets using the
bdr.replicate_ddl_command(). This can be helpful if you
want to run DDL commands when a node is down or if you want to have
indexes or partitions that exist on a subset of nodes or rep sets,
for example, all nodes at site1.
While we don't recommend it, you can skip automatic DDL replication and
execute it manually on each node using
When set, it makes BDR skip both the global locking and the replication of executed DDL commands. You must then run the DDL manually on all nodes.
Executing DDL manually on each node without global locking can cause the whole BDR group to stop replicating if conflicting DDL or DML executes concurrently.
bdr.ddl_replication parameter can be set only by the bdr_superuser,
by superuser, or in the
A BDR group isn't the same as a standalone PostgreSQL server. It's based on asynchronous multi-master replication without central locking and without a transaction coordinator. This has important implications when executing DDL.
DDL that executes in parallel continues to do so with BDR. DDL execution respects the parameters that affect parallel operation on each node as it executes, so you might notice differences in the settings between nodes.
Prevent the execution of conflicting DDL, otherwise DDL replication causes errors and the replication stops.
BDR offers three levels of protection against those problems:
ddl_locking = 'dml' is the best option for operations, usable when you execute
DDL from only one node at a time. This isn't the default, but we recommend
that you use this setting if you can control where DDL is executed from. Doing so
ensures that there are no inter-node conflicts. Intra-node conflicts are already
handled by PostgreSQL.
ddl_locking = on is the strictest option and is best when DDL might execute
from any node concurrently and you want to ensure correctness.
ddl_locking = off is the least strict option and is dangerous in general use.
This option skips locks altogether, avoiding any performance overhead, which makes
it a useful option when creating a new and empty database schema.
These options can be set only by the bdr_superuser, by the superuser, or in the
When using the
bdr.replicate_ddl_command, you can set this
parameter directly with the third argument, using the specified
bdr.ddl_locking setting only for the DDL commands passed to that
Two kinds of locks enforce correctness of replicated DDL with BDR.
The first kind is known as a global DDL lock and is used only when
ddl_locking = on.
A global DDL lock prevents any other DDL from executing on the cluster while
each DDL statement runs. This ensures full correctness in the general case but
is too strict for many simple cases. BDR acquires a global lock on
DDL operations the first time in a transaction where schema changes are made.
This effectively serializes the DDL-executing transactions in the cluster. In
other words, while DDL is running, no other connection on any node can run
another DDL command, even if it affects different tables.
To acquire a lock on DDL operations, the BDR node executing DDL contacts the other nodes in a BDR group and asks them to grant it the exclusive right to execute DDL. The lock request is sent by the regular replication stream, and the nodes respond by the replication stream as well. So it's important that nodes (or at least a majority of the nodes) run without much replication delay. Otherwise it might take a long time for the node to acquire the DDL lock. Once the majority of nodes agrees, the DDL execution is carried out.
The ordering of DDL locking is decided using the Raft protocol. DDL statements executed on one node are executed in the same sequence on all other nodes.
To ensure that the node running a DDL has seen effects of all prior DDLs run in the cluster, it waits until it has caught up with the node that ran the previous DDL. If the node running the current DDL is lagging behind in replication with respect to the node that ran the previous DDL, then it might take a long time to acquire the lock. Hence it's preferable to run DDLs from a single node or the nodes that have nearly caught up with replication changes originating at other nodes.
The second kind is known as a relation DML lock. This kind of lock is used when
ddl_locking = on or
ddl_locking = dml, and the DDL statement might cause
in-flight DML statements to fail. These failures can occur when you add or modify a constraint
such as a unique constraint, check constraint, or NOT NULL constraint.
Relation DML locks affect only one relation at a time. Relation DML
locks ensure that no DDL executes while there are changes in the queue that
might cause replication to halt with an error.
To acquire the global DML lock on a table, the BDR node executing the DDL contacts all other nodes in a BDR group, asking them to lock the table against writes and waiting while all pending changes to that table are drained. Once all nodes are fully caught up, the originator of the DML lock is free to perform schema changes to the table and replicate them to the other nodes.
The global DML lock holds an EXCLUSIVE LOCK on the table on each node, so it blocks DML, other DDL, VACUUM, and index commands against that table while it runs. This is true even if the global DML lock is held for a command that normally doesn't take an EXCLUSIVE LOCK or higher.
Waiting for pending DML operations to drain can take a long time and even longer if replication is currently lagging. This means that schema changes affecting row representation and constraints, unlike with data changes, can be performed only while all configured nodes can be reached and are keeping up reasonably well with the current write rate. If such DDL commands must be performed while a node is down, first remove the down node from the configuration.
If a DDL statement isn't replicated, no global locks are acquired.
Locking behavior is specified by the
bdr.ddl_locking parameter, as
explained in Executing DDL on BDR systems:
ddl_locking = ontakes global DDL lock and, if needed, takes relation DML lock.
ddl_locking = dmlskips global DDL lock and, if needed, takes relation DML lock.
ddl_locking = offskips both global DDL lock and relation DML lock.
Some BDR functions make DDL changes. For those functions, DDL locking behavior applies. This is noted in the docs for each function.
ddl_locking = dml is safe only when you can guarantee that
no conflicting DDL is executed from other nodes. With this setting,
the statements that require only the global DDL lock don't use the global
locking at all.
ddl_locking = off is safe only when you can guarantee that there are no
conflicting DDL and no conflicting DML operations on the database objects
DDL executes on. If you turn locking off and then experience difficulties,
you might lose in-flight changes to data. The user application team needs to resolve any issues caused.
In some cases, concurrently executing DDL can properly be serialized. If these serialization failures occur, the DDL might reexecute.
DDL replication isn't active on logical standby nodes until they are promoted.
Some BDR management functions act like DDL, meaning that they attempt to take global locks, and their actions are replicated if DDL replication is active. The full list of replicated functions is listed in BDR functions that behave like DDL.
DDL executed on temporary tables never need global locks.
ALTER or DROP of an object created in the current transaction doesn't required global DML lock.
Monitoring of global DDL locks and global DML locks is shown in Monitoring.
Good operational advice for any database, these points become even more important with BDR:
To minimize the impact of DDL, make transactions performing DDL short, don't combine them with lots of row changes, and avoid long running foreign key or other constraint rechecks.
ALTER TABLE, use
ADD CONSTRAINT NOT VALIDfollowed by another transaction with
VALIDATE CONSTRAINTrather than using
VALIDATE CONSTRAINTwaits until replayed on all nodes, which gives a noticeable delay to receive confirmations.
When indexing, use the
CONCURRENTLYoption whenever possible.
An alternate way of executing long-running DDL is to disable DDL replication and then to execute the DDL statement separately on each node. You can still do this using a single SQL statement, as shown in the following example. Global locking rules still apply, so be careful not to lock yourself out with this type of usage, which is more of a workaround.
We recommend using the
bdr.run_on_all_nodes() technique with
INDEX CONCURRENTLY, noting that DDL replication must be disabled for the whole
CREATE INDEX CONCURRENTLY is a multi-transaction command.
CREATE INDEX on production systems
since it prevents writes while it executes.
REINDEX is replicated in versions up to 3.6 but not with BDR 3.7 or later.
REINDEX because of the AccessExclusiveLocks it holds.
REINDEX CONCURRENTLY (or
which is available in PG12+ or 2QPG11+.
You can disable DDL replication when using command-line utilities like this:
Multiple DDL statements might benefit from bunching into a single transaction rather than fired as individual statements, so take the DDL lock only once. This might not be desirable if the table-level locks interfere with normal operations.
If DDL is holding up the system for too long, you can safely
cancel the DDL on the originating node with
Control-C in psql or with
You can't cancel a DDL lock from any other node.
You can control how long the global lock takes with optional
global locking timeout settings.
bdr.global_lock_timeout limits how long the wait
for acquiring the global lock can take before it's canceled.
bdr.global_lock_statement_timeout limits the runtime length of any statement
in transaction that holds global locks, and
sets the maximum allowed idle time (time between statements) for a transaction
holding any global locks. You can disable all of these timeouts by setting
their values to zero.
Once the DDL operation has committed on the originating node, you can't cancel or abort it. The BDR group must wait for it to apply successfully on other nodes that confirmed the global lock and for them to acknowledge replay. For this reason, keep DDL transactions short and fast.
If the node initiating the global DDL lock goes down after it acquired the global lock (either DDL or DML), the lock stays active. The global locks don't time out, even if timeouts were set. In case the node comes back up, it releases all the global locks that it holds.
If it stays down for a long time (or indefinitely),
remove the node from the BDR group to release the global locks. This
is one reason for executing emergency DDL using the
SET command as
the bdr_superuser to update the
If one of the other nodes goes down after it confirmed the global lock but before the command acquiring it executed, the execution of that command requesting the lock continues as if the node were up.
As mentioned earlier, the global DDL lock requires only a majority of the nodes to respond, and so it works if part of the cluster is down, as long as a majority is running and reachable. But the DML lock can't be acquired unless the whole cluster is available.
With global DDL or global DML lock, if another node goes down, the command continues normally, and the lock is released.
Not all commands can be replicated automatically. Such commands
are generally disallowed, unless DDL replication is turned off
BDR prevents some DDL statements from running when it's active on a database. This protects the consistency of the system by disallowing statements that can't be replicated correctly or for which replication isn't yet supported. Statements that are supported with some restrictions are covered in DDL statements with restrictions. Commands that are entirely disallowed in BDR are covered in prohibited DDL statements.
If a statement isn't permitted under BDR, you can often find
another way to do the same thing. For example, you can't do an
which adds a column with a volatile default value. But generally you can
rephrase that as a series of independent
ALTER TABLE and
Generally unsupported statements are prevented from being
executed, raising a
Any DDL that references or relies on a temporary object can't be replicated by BDR and throws an error if executed with DDL replication enabled.
The following table describes the utility or DDL commands that are allowed, the ones that are replicated, and the type of global lock they take when they're replicated.
For some more complex statements like
ALTER TABLE, these can differ depending
on the subcommands executed. Every such command has detailed explanation
under the following table.
|ALTER DATABASE LINK||Y||Y||DDL|
|ALTER DEFAULT PRIVILEGES||Y||Y||DDL|
|ALTER EVENT TRIGGER||Y||Y||DDL|
|ALTER FOREIGN DATA WRAPPER||Y||Y||DDL|
|ALTER FOREIGN TABLE||Y||Y||DDL|
|ALTER LARGE OBJECT||N||N||N|
|ALTER MATERIALIZED VIEW||Y||N||N|
|ALTER OPERATOR CLASS||Y||Y||DDL|
|ALTER OPERATOR FAMILY||Y||Y||DDL|
|ALTER QUEUE TABLE||Y||Y||DDL|
|ALTER REDACTION POLICY||Y||Y||DDL|
|ALTER RESOURCE GROUP||Y||N||N|
|ALTER TEXT SEARCH CONFIGURATION||Y||Y||DDL|
|ALTER TEXT SEARCH DICTIONARY||Y||Y||DDL|
|ALTER TEXT SEARCH PARSER||Y||Y||DDL|
|ALTER TEXT SEARCH TEMPLATE||Y||Y||DDL|
|ALTER USER MAPPING||Y||Y||DDL|
|CLOSE CURSOR ALL||Y||N||N|
|CREATE ACCESS METHOD||Y||Y||DDL|
|CREATE DATABASE LINK||Y||Y||DDL|
|CREATE EVENT TRIGGER||Y||Y||DDL|
|CREATE FOREIGN DATA WRAPPER||Y||Y||DDL|
|CREATE FOREIGN TABLE||Y||Y||DDL|
|CREATE MATERIALIZED VIEW||Y||N||N|
|CREATE OPERATOR CLASS||Y||Y||DDL|
|CREATE OPERATOR FAMILY||Y||Y||DDL|
|CREATE PACKAGE BODY||Y||Y||DDL|
|CREATE QUEUE TABLE||Y||Y||DDL|
|CREATE REDACTION POLICY||Y||Y||DDL|
|CREATE RESOURCE GROUP||Y||N||N|
|CREATE TABLE AS||Details||Y||DDL|
|CREATE TEXT SEARCH CONFIGURATION||Y||Y||DDL|
|CREATE TEXT SEARCH DICTIONARY||Y||Y||DDL|
|CREATE TEXT SEARCH PARSER||Y||Y||DDL|
|CREATE TEXT SEARCH TEMPLATE||Y||Y||DDL|
|CREATE TYPE BODY||Y||Y||DDL|
|CREATE USER MAPPING||Y||Y||DDL|
|DROP ACCESS METHOD||Y||Y||DDL|
|DROP DATABASE LINK||Y||Y||DDL|
|DROP EVENT TRIGGER||Y||Y||DDL|
|DROP FOREIGN DATA WRAPPER||Y||Y||DDL|
|DROP FOREIGN TABLE||Y||Y||DDL|
|DROP MATERIALIZED VIEW||Y||N||N|
|DROP OPERATOR CLASS||Y||Y||DDL|
|DROP OPERATOR FAMILY||Y||Y||DDL|
|DROP PACKAGE BODY||Y||Y||DDL|
|DROP QUEUE TABLE||Y||Y||DDL|
|DROP REDACTION POLICY||Y||Y||DDL|
|DROP RESOURCE GROUP||Y||N||N|
|DROP TEXT SEARCH CONFIGURATION||Y||Y||DDL|
|DROP TEXT SEARCH DICTIONARY||Y||Y||DDL|
|DROP TEXT SEARCH PARSER||Y||Y||DDL|
|DROP TEXT SEARCH TEMPLATE||Y||Y||DDL|
|DROP TYPE BODY||Y||Y||DDL|
|DROP USER MAPPING||Y||Y||DDL|
|IMPORT FOREIGN SCHEMA||Y||Y||DDL|
|LOAD ROW DATA||Y||Y||DDL|
|REFRESH MATERIALIZED VIEW||Y||N||N|
ALTER SEQUENCE is supported, but when using global
sequences, some options have no effect.
ALTER SEQUENCE ... RENAME isn't supported on galloc sequences (only).
ALTER SEQUENCE ... SET SCHEMA isn't supported on galloc sequences (only).
ALTER TABLE commands are allowed. However, several
subcommands aren't supported.
Some variants of
ALTER TABLE currently aren't allowed on a BDR node:
ADD COLUMN ... DEFAULT (non-immutable expression)— This is not allowed because it currently results in different data on different nodes. See Adding a column for a suggested workaround.
ADD CONSTRAINT ... EXCLUDE— Exclusion constraints aren't supported for now. Exclusion constraints don't make much sense in an asynchronous system and lead to changes that can't be replayed.
ALTER TABLE ... SET WITH[OUT] OIDS— Isn't supported for the same reasons as in
ALTER COLUMN ... SET STORAGE external— Is rejected if the column is one of the columns of the replica identity for the table.
RENAME— Can't rename an Autopartitioned table.
SET SCHEMA— Can't set the schema of an Autopartitioned table.
ALTER COLUMN ... TYPE— Changing a column's type isn't supported if the command causes the whole table to be rewritten, which occurs when the change isn't binary coercible. Binary coercible changes might be allowed only one way. For example, the change from
VARCHAR(256)is binary coercible and therefore allowed, whereas the change
VARCHAR(128)isn't binary coercible and therefore normally disallowed. Nonreplicated
ALTER COLUMN ... TYPE, can be allowed if the column is automatically castable to the new type (it doesn't contain the
USINGclause). An example follows. Table rewrites hold an AccessExclusiveLock for extended periods on larger tables, so such commands are likely to be infeasible on highly available databases in any case. See Changing a column's type for a suggested workaround.
ALTER TABLE ... ADD FOREIGN KEY— Isn't supported if current user doesn't have permission to read the referenced table or if the referenced table has RLS restrictions enabled that the current user can't bypass.
The following example fails because it tries to add a constant value of type
onto a column of type
timestamptz. The cast between
relies on the time zone of the session and so isn't immutable.
Starting in BDR 3.7.4, you can add certain types of constraints, such as
FOREIGN KEY constraints, without taking a DML lock. But
this requires a two-step process of first creating a
NOT VALID constraint
and then validating the constraint in a separate transaction with the
ALTER TABLE ... VALIDATE CONSTRAINT
command. See Adding a CONSTRAINT
for more details.
The following variants of
ALTER TABLE take only DDL lock and not a
ALTER TABLE ... ADD COLUMN ... (immutable) DEFAULT
ALTER TABLE ... ALTER COLUMN ... SET DEFAULT expression
ALTER TABLE ... ALTER COLUMN ... DROP DEFAULT
ALTER TABLE ... ALTER COLUMN ... TYPEif it doesn't require rewrite
ALTER TABLE ... ALTER COLUMN ... SET STATISTICS
ALTER TABLE ... VALIDATE CONSTRAINT
ALTER TABLE ... ATTACH PARTITION
ALTER TABLE ... DETACH PARTITION
ALTER TABLE ... ENABLE TRIGGER(
ENABLE REPLICA TRIGGERstill takes a DML lock)
ALTER TABLE ... CLUSTER ON
ALTER TABLE ... SET WITHOUT CLUSTER
ALTER TABLE ... SET ( storage_parameter = value [, ... ] )
ALTER TABLE ... RESET ( storage_parameter = [, ... ] )
ALTER TABLE ... OWNER TO
All other variants of
ALTER TABLE take a DML lock on the table being modified.
Some variants of
ALTER TABLE have restrictions, noted below.
This next example works because the type change is binary coercible and so doesn't cause a table rewrite. It executes as a catalog-only change.
However, making this change to reverse the command isn't possible because
the change from
VARCHAR(20) isn't binary coercible.
For workarounds, see Restricted DDL workarounds.
It's useful to provide context for different types of
ALTER TABLE ...
ALTER COLUMN TYPE (ATCT) operations that are possible in general and in
Some ATCT operations update only the metadata of the underlying column type and don't require a rewrite of the underlying table data. This is typically the case when the existing column type and the target type are binary coercible. For example:
You can also change the column type to
data types because of binary coercibility. Again, this is just a metadata
update of the underlying column type.
However, if you want to reduce the size of col2, then that leads to a rewrite of the underlying table data. Rewrite of a table is normally restricted.
To give an example with nontext types, consider col3 above with type INTEGER. An ATCT operation that tries to convert to SMALLINT or BIGINT fails in a similar manner as above.
In both of these failing cases, there's an automatic assignment cast from the current types to the target types. However, there's no binary coercibility, which ends up causing a rewrite of the underlying table data.
In such cases, in controlled DBA environments, you can change the type of a column to an automatically castable one by adopting a rolling upgrade for the type of this column in a nonreplicated environment on all the nodes, one by one. Suppose the DDL isn't replicated and the change of the column type is to an automatically castable one. You can then allow the rewrite locally on the node performing the alter, along with concurrent activity on other nodes on this same table. You can then repeat this nonreplicated ATCT operation on all the nodes one by one to bring about the desired change of the column type across the entire BDR cluster. Because this involves a rewrite, the activity still takes the DML lock for a brief period and thus requires that the whole cluster is available. With these specifics in place, you can carry out the rolling upgrade of the nonreplicated alter activity like this:
Due to automatic assignment casts being available for many data types,
this local nonreplicated ATCT operation supports a wide variety of
conversions. Also, ATCT operations that use a
are likely to fail because of the lack of automatic assignment casts.
This example shows a few common conversions with automatic assignment casts:
This example isn't an exhaustive list of possibly allowable ATCT operations in a nonreplicated environment. Not all ATCT operations work. The cases where no automatic assignment is possible fail even if you disable DDL replication. So, while conversion from numeric types to text types works in a nonreplicated environment, conversion back from text type to numeric types fails.
While the ATCT operations in nonreplicated environments support a
variety of type conversions, the rewrite
can still fail if the underlying table data contains values that you can't
assign to the new data type. For example, suppose the current type for
a column is
VARCHAR(256) and you try a nonreplicated ATCT
operation to convert it into
VARCHAR(128). If there's any existing data
in the table that's wider than 128 bytes, then the rewrite operation
If underlying table data meets the characteristics of the new type, then the rewrite succeeds. However, replication might fail if other nodes that haven't yet performed the nonreplicated rolling data type upgrade introduce new data that is wider than 128 bytes concurrently to this local ATCT operation. This brings replication to a halt in the cluster. So be aware of the data type restrictions and characteristics at the database and application levels while performing these nonreplicated rolling data type upgrade operations. We strongly recommend that you perform and test such ATCT operations in controlled and fully aware DBA environments. These ATCT operations are asymmetric, and backing out certain changes that fail can lead to table rewrites that take a long time.
Also, you can't perform the implicit castable ALTER activity in transaction blocks.
ALTER TYPE is replicated, but a global DML lock isn't
applied to all tables that use that data type, since PostgreSQL doesn't
record those dependencies. See Restricted DDL workarounds.
All variants of
COMMENT ON are allowed, but
COMMENT ON TABLESPACE/DATABASE/LARGE OBJECT isn't replicated.
CREATE SEQUENCE is supported, but when using global
sequences, some options have no effect.
CREATE TABLE is supported, but
CREATE TABLE WITH OIDS isn't
allowed on a BDR node.
CREATE TABLE AS and
SELECT INTO are allowed only if all subcommands are
EXPLAIN is allowed, but because
EXPLAIN ANALYZE can have side
effects on the database, there are some restrictions on it.
EXPLAIN ANALYZE follows replication rules of the analyzed statement.
EXPLAIN ANALYZE follows locking rules of the analyzed statement.
REVOKE statements are supported, however
GRANT/REVOKE ON TABLESPACE/LARGE OBJECT aren't replicated.
LOCK TABLE isn't replicated, but it might acquire the global DML lock when
bdr.lock_table_locking is set
You can also use The
bdr.global_lock_table() function to explicitly request a global DML
All variants of
SECURITY LABEL are allowed, but
SECURITY LABEL ON TABLESPACE/DATABASE/LARGE OBJECT isn't replicated.
TRUNCATE command is replicated as DML, not as a DDL statement. Whether
TRUNCATE on table is replicated depends on replication settings for
each affected table.
TRUNCATE isn't replicated the same way as other DDL, it can acquire
the global DML lock when
bdr.truncate_locking is set to
Users are global objects in a PostgreSQL instance, which means they span multiple databases while BDR operates on an individual database level. This means that role manipulation statement handling needs extra thought.
BDR requires that any roles that are referenced by any replicated DDL must exist on all nodes. The roles don't have to have the same grants, password, and so on, but they must exist.
BDR replicates role manipulation statements if
enabled (default) and role manipulation statements are run in a BDR-enabled
The role manipulation statements include the following:
In general, either:
Configure the system with
bdr.role_replication = offand deploy all role changes (user and group) by external orchestration tools like Ansible, Puppet, and Chef or explicitly replicated by
Configure the system so that exactly one BDR-enabled database on the PostgreSQL instance has
bdr.role_replication = onand run all role management DDL on that database.
We recommended that you run all role management commands in one database.
If role replication is turned off, then the administrator must ensure that any roles used by DDL on one node also exist on the other nodes. Otherwise BDR apply stalls with an error until the role is created on the other nodes.
BDR doesn't capture and replicate role management statements when they
run on a non-BDR-enabled database in a BDR-enabled PostgreSQL instance.
For example, if you have DBs 'bdrdb' (bdr group member) and 'postgres' (bare db),
bdr.role_replication = on, then a
CREATE USER run in
replicated, but a
CREATE USER run in
Some of the limitations of BDR DDL operation handling can be worked around. Often splitting up the operation into smaller changes can produce the desired result that either isn't allowed as a single statement or requires excessive locking.
You can add
FOREIGN KEY constraints without requiring a DML lock.
This involves a two-step process.
ALTER TABLE ... ADD CONSTRAINT ... NOT VALID
ALTER TABLE ... VALIDATE CONSTRAINT
Execute these steps in two different transactions. Both these steps take DDL lock only on the table and hence can be run even when one or more nodes are down. But to validate a constraint, BDR must ensure that:
- All nodes in the cluster see the
- The node validating the constraint applied replication changes from all other nodes prior to creating the NOT VALID constraint on those nodes.
So even though the new mechanism doesn't need all nodes
to be up while validating the constraint, it still requires that all
nodes applied the
ALTER TABLE .. ADD CONSTRAINT ... NOT VALID
command and made enough progress. BDR waits for a consistent
state to be reached before validating the constraint.
The new facility requires the cluster to run with Raft protocol version 24 and beyond. If the Raft protocol isn't yet upgraded, the old mechanism is used, resulting in a DML lock request.
To add a column with a volatile default, run these commands in separate transactions:
This approach splits schema changes and row changes into separate transactions that BDR can execute and results in consistent data across all nodes in a BDR group.
For best results, batch the update into chunks so that you don't update more than
a few tens or hundreds of thousands of rows at once. You can do this using
PROCEDURE with embedded transactions.
The last batch of changes must run in a transaction that takes a global DML lock on the table. Otherwise you can miss rows that are inserted concurrently into the table on other nodes.
If required, you can run
ALTER TABLE mytable ALTER COLUMN newcolumn NOT NULL; after the
UPDATE has finished.
PostgreSQL causes a table rewrite in some cases where it could be avoided, for example:
You can rewrite this statement to avoid a table rewrite by making the restriction a table constraint rather than a datatype change. The constraint can then be validated in a subsequent command to avoid long locks, if you want.
If the validation fails, then you can
UPDATE just the failing rows.
You can use this technique for
length() or with
NUMERIC datatype using
In the general case for changing column type, first add a column of the desired type:
Create a trigger defined as
BEFORE INSERT OR UPDATE ON mytable FOR EACH ROW ..,
NEW.oldcolumn so that new writes to the
table update the new column automatically.
UPDATE the table in batches to copy the value of
newcolumn using a
PROCEDURE with embedded transactions. Batching the work
helps reduce replication lag if it's a big table. Updating by range of
IDs or whatever method you prefer is fine. Alternatively, you can update the whole table in one pass for
CREATE INDEX ... any required indexes on the new column. It's safe to
CREATE INDEX ... CONCURRENTLY run individually without DDL replication
on each node to reduce lock durations.
ALTER the column to add a
NOT NULL and
CHECK constraints, if required.
DROPthe trigger you added.
ALTER TABLEto add any
DEFAULTrequired on the column.
DROPthe old column.
ALTER TABLE mytable RENAME COLUMN newcolumn TO oldcolumn.
Because you're dropping a column, you might have to re-create views, procedures,
and so on that depend on the table. Be careful if you
CASCADE drop the column,
as you must be sure you re-create everything that referred to it.
ALTER TYPE statement is replicated, but affected tables aren't locked.
When this DDL is used, ensure that the statement has successfully
executed on all nodes before using the new type. You can achieve this using
This example ensures that the DDL is written to all nodes before using the new value in DML statements:
The following BDR management functions act like DDL. This means that, if DDL replication is active and DDL filter settings allow it, they attempt to take global locks and their actions are replicate. For detailed information, see the documentation for the individual functions.
Replication set management