Stream triggers v5
PGD introduces new types of triggers that you can use for additional data processing on the downstream/target node:
- Conflict triggers
- Transform triggers
Together, these types of triggers are known as stream triggers.
Permissions required
Stream triggers are a PGD feature that requires permission. Any user wanting to create or drop triggers must have at least the bdr_application role assigned to them.
Stream triggers are designed to be trigger-like in syntax. They leverage the PostgreSQL BEFORE trigger architecture and are likely to have similar performance characteristics as PostgreSQL BEFORE triggers.
Multiple trigger definitions can use one trigger function, just as with
normal PostgreSQL triggers.
A trigger function is a program defined in this form:
CREATE FUNCTION ... RETURNS TRIGGER
. Creating the trigger doesn't
require use of the CREATE TRIGGER
command. Instead, create stream triggers
using the special PGD functions
bdr.create_conflict_trigger()
and bdr.create_transform_trigger()
.
Once created, the trigger is visible in the catalog table pg_trigger
.
The stream triggers are marked as tgisinternal = true
and
tgenabled = 'D'
and have the name suffix '_bdrc' or '_bdrt'. The view
bdr.triggers
provides information on the triggers in relation to the table,
the name of the procedure that's being executed, the event that triggers it,
and the trigger type.
Stream triggers aren't enabled for normal SQL processing.
Because of this, the ALTER TABLE ... ENABLE TRIGGER
is blocked for stream
triggers in both its specific name variant and the ALL variant. This mechanism prevents
the trigger from executing as a normal SQL trigger.
These triggers execute on the downstream or target node. There's no
option for them to execute on the origin node. However, you might want to consider
the use of row_filter
expressions on the origin.
Also, any DML that's applied while executing a stream trigger isn't replicated to other PGD nodes and doesn't trigger the execution of standard local triggers. This is intentional. You can use it, for example, to log changes or conflicts captured by a stream trigger into a table that's crash-safe and specific to that node. See Stream triggers examples for a working example.
Trigger execution during apply
Transform triggers execute first—once for each incoming change in the triggering table. These triggers fire before we attempt to locate a matching target row, allowing a very wide range of transforms to be applied efficiently and consistently.
Next, for UPDATE and DELETE changes, we locate the target row. If there's no target row, then no further processing occurs for those change types.
We then execute any normal triggers that previously were explicitly enabled as replica triggers at table level:
We then decide whether a potential conflict exists. If so, we then call any conflict trigger that exists for that table.
Missing-column conflict resolution
Before transform triggers are executed, PostgreSQL tries to match the incoming tuple against the row-type of the target table.
Any column that exists on the input row but not on the target table
triggers a conflict of type target_column_missing
. Conversely, a
column existing on the target table but not in the incoming row
triggers a source_column_missing
conflict. The default resolutions
for those two conflict types are respectively ignore_if_null
and
use_default_value
.
This is relevant in the context of rolling schema upgrades, for
example, if the new version of the schema introduces a new
column. When replicating from an old version of the schema to a new
one, the source column is missing, and the use_default_value
strategy is appropriate, as it populates the newly introduced column
with the default value.
However, when replicating from a node having the new schema version to
a node having the old one, the column is missing from the target
table. The ignore_if_null
resolver isn't appropriate for a
rolling upgrade because it breaks replication as soon as a user
inserts a tuple with a non-NULL value
in the new column in any of the upgraded nodes.
In view of this example, the appropriate setting for rolling schema
upgrades is to configure each node to apply the ignore
resolver in
case of a target_column_missing
conflict.
You can do this with the following query, which you must execute
separately on each node. Replace node1
with the actual
node name.
Data loss and divergence risk
Setting the conflict resolver to ignore
can lead to data loss and cluster divergence.
Consider the following example: table t
exists on nodes 1 and 2, but
its column col
exists only on node 1.
If the conflict resolver is set to ignore
, then there can be rows on
node 1 where c
isn't null, for example, (pk=1, col=100)
. That row is
replicated to node 2, and the value in column c
is discarded,
for example, (pk=1)
.
If column c
is then added to the table on node 2, it's at first
set to NULL on all existing rows, and the row considered above
becomes (pk=1, col=NULL)
. The row having pk=1
is no longer
identical on all nodes, and the cluster is therefore divergent.
The default ignore_if_null
resolver isn't affected by
this risk because any row replicated to node 2 has
col=NULL
.
Based on this example, we recommend running LiveCompare against the
whole cluster at the end of a rolling schema upgrade where the
ignore
resolver was used. This practice helps to ensure that you detect and fix any divergence.
Terminology of row-types
PGD uses these row-types:
SOURCE_OLD
is the row before update, that is, the key.SOURCE_NEW
is the new row coming from another node.TARGET
is the row that exists on the node already, that is, the conflicting row.
Conflict triggers
Conflict triggers execute when a conflict is detected by PGD. They decide what happens when the conflict occurs.
- If the trigger function returns a row, the action is applied to the target.
- If the trigger function returns a NULL row, the action is skipped.
For example, if the trigger is called for a DELETE
, the trigger
returns NULL if it wants to skip the DELETE
. If you want the DELETE
to proceed,
then return a row value: either SOURCE_OLD
or TARGET
works.
When the conflicting operation is either INSERT
or UPDATE
, and the
chosen resolution is to delete the conflicting row, the trigger
must explicitly perform the deletion and return NULL.
The trigger function can perform other SQL actions as it chooses, but
those actions are only applied locally, not replicated.
When a real data conflict occurs between two or more nodes, two or more concurrent changes are occurring. When the changes are applied, the conflict resolution occurs independently on each node. This means the conflict resolution occurs once on each node and can occur with a significant time difference between them. As a result, communication between the multiple executions of the conflict trigger isn't possible. It's the responsibility of the author of the conflict trigger to ensure that the trigger gives exactly the same result for all related events. Otherwise, data divergence occurs.
Warning
- You can specify multiple conflict triggers on a single table, but they must match a distinct event. That is, each conflict must match only a single conflict trigger.
- We don't recommend multiple triggers matching the same event on the same table. They might result in inconsistent behavior and will not be allowed in a future release.
If the same conflict trigger matches more than one event, you can use the TG_OP
variable in the trigger to identify the operation that
produced the conflict.
By default, PGD detects conflicts by observing a change of replication origin for a row. Hence, you can call a conflict trigger even when only one change is occurring. Since, in this case, there's no real conflict, this conflict detection mechanism can generate false-positive conflicts. The conflict trigger must handle all of those identically.
In some cases, timestamp conflict detection doesn't detect a
conflict at all. For example, in a concurrent UPDATE
/DELETE
where the
DELETE
occurs just after the UPDATE
, any nodes that see first the UPDATE
and then the DELETE
don't see any conflict. If no conflict is seen,
the conflict trigger is never called. In the same situation but using
row-version conflict detection, a conflict is seen, which a conflict trigger can then
handle.
The trigger function has access to additional state information as well as the data row involved in the conflict, depending on the operation type:
- On
INSERT
, conflict triggers can access theSOURCE_NEW
row from the source andTARGET
row. - On
UPDATE
, conflict triggers can access theSOURCE_OLD
andSOURCE_NEW
row from the source andTARGET
row. - On
DELETE
, conflict triggers can access theSOURCE_OLD
row from the source andTARGET
row.
You can use the function bdr.trigger_get_row()
to retrieve SOURCE_OLD
, SOURCE_NEW
,
or TARGET
rows, if a value exists for that operation.
Changes to conflict triggers happen transactionally and are protected by
global DML locks during replication of the configuration change. This behavior is similar
to how some variants of ALTER TABLE
are handled.
If primary keys are updated inside a conflict trigger, it can sometimes lead to unique constraint violations errors due to a difference in timing of execution. Hence, avoid updating primary keys in conflict triggers.
Transform triggers
These triggers are similar to conflict triggers, except they're executed
for every row on the data stream against the specific table. The behavior of
return values and the exposed variables is similar, but transform triggers
execute before a target row is identified, so there's no TARGET
row.
You can specify multiple transform triggers on each table in PGD. Transform triggers execute in alphabetical order.
A transform trigger can filter away rows, and it can do additional operations
as needed. It can alter the values of any column or set them to NULL
. The
return value decides the next action taken:
- If the trigger function returns a row, it's applied to the target.
- If the trigger function returns a
NULL
row, there's no further action to perform. Unexecuted triggers never execute. - The trigger function can perform other actions as it chooses.
The trigger function has access to additional state information as well as rows involved in the conflict:
- On
INSERT
, transform triggers can access theSOURCE_NEW
row from the source. - On
UPDATE
, transform triggers can access theSOURCE_OLD
andSOURCE_NEW
row from the source. - On
DELETE
, transform triggers can access theSOURCE_OLD
row from the source.
You can use the function bdr.trigger_get_row()
to retrieve SOURCE_OLD
or SOURCE_NEW
rows. TARGET
row isn't available, since this type of trigger executes before such
a target row is identified, if any.
Transform triggers look very similar to normal BEFORE row triggers but have these important differences:
A transform trigger gets called for every incoming change. BEFORE triggers aren't called at all for
UPDATE
andDELETE
changes if a matching row in a table isn't found.Transform triggers are called before partition-table routing occurs.
Transform triggers have access to the lookup key via
SOURCE_OLD
, which isn't available to normal SQL triggers.
Row contents
The SOURCE_NEW
, SOURCE_OLD
, and TARGET
contents depend on the operation, REPLICA
IDENTITY setting of a table, and the contents of the target table.
The TARGET row is available only in conflict triggers. The TARGET row
contains data only if a row was found when applying UPDATE
or DELETE
in the target
table. If the row isn't found, the TARGET is NULL
.
Execution order
Execution order for triggers:
- Transform triggers — Execute once for each incoming row on the target.
- Normal triggers — Execute once per row.
- Conflict triggers — Execute once per row where a conflict exists.
Stream triggers examples
A conflict trigger that provides similar behavior as the update_if_newer
conflict resolver:
A conflict trigger that applies a delta change on a counter column and uses SOURCE_NEW for all other columns:
A transform trigger that logs all changes to a log table instead of applying them:
This example shows a conflict trigger that implements trusted-source
conflict detection, also known as trusted site, preferred node, or Always Wins
resolution. It uses the bdr.trigger_get_origin_node_id()
function to provide
a solution that works with three or more nodes.