31.3. Row Filters

By default, all data from all published tables will be replicated to the appropriate subscribers. The replicated data can be reduced by using a row filter. A user might choose to use row filters for behavioral, security or performance reasons. If a published table sets a row filter, a row is replicated only if its data satisfies the row filter expression. This allows a set of tables to be partially replicated. The row filter is defined per table. Use a WHERE clause after the table name for each published table that requires data to be filtered out. The WHERE clause must be enclosed by parentheses. See CREATE PUBLICATION for details.

31.3.1. Row Filter Rules

Row filters are applied before publishing the changes. If the row filter evaluates to false or NULL then the row is not replicated. The WHERE clause expression is evaluated with the same role used for the replication connection (i.e. the role specified in the CONNECTION clause of the CREATE SUBSCRIPTION). Row filters have no effect for TRUNCATE command.

31.3.2. Expression Restrictions

The WHERE clause allows only simple expressions. It cannot contain user-defined functions, operators, types, and collations, system column references or non-immutable built-in functions.

If a publication publishes UPDATE or DELETE operations, the row filter WHERE clause must contain only columns that are covered by the replica identity (see REPLICA IDENTITY). If a publication publishes only INSERT operations, the row filter WHERE clause can use any column.

31.3.3. UPDATE Transformations

Whenever an UPDATE is processed, the row filter expression is evaluated for both the old and new row (i.e. using the data before and after the update). If both evaluations are true, it replicates the UPDATE change. If both evaluations are false, it doesn't replicate the change. If only one of the old/new rows matches the row filter expression, the UPDATE is transformed to INSERT or DELETE, to avoid any data inconsistency. The row on the subscriber should reflect what is defined by the row filter expression on the publisher.

If the old row satisfies the row filter expression (it was sent to the subscriber) but the new row doesn't, then, from a data consistency perspective the old row should be removed from the subscriber. So the UPDATE is transformed into a DELETE.

If the old row doesn't satisfy the row filter expression (it wasn't sent to the subscriber) but the new row does, then, from a data consistency perspective the new row should be added to the subscriber. So the UPDATE is transformed into an INSERT.

Table 31.1 summarizes the applied transformations.

Table 31.1. `UPDATE` Transformation Summary

Old row New row Transformation

Old row	New row	Transformation
no match	no match	don't replicate
no match	match	`INSERT`
match	no match	`DELETE`
match	match	`UPDATE`

no match

don't replicate

no match

match

INSERT

match

no match

DELETE

match

UPDATE

31.3.4. Partitioned Tables

If the publication contains a partitioned table, the publication parameter publish_via_partition_root determines which row filter is used. If publish_via_partition_root is true, the root partitioned table's row filter is used. Otherwise, if publish_via_partition_root is false (default), each partition's row filter is used.

31.3.5. Initial Data Synchronization

If the subscription requires copying pre-existing table data and a publication contains WHERE clauses, only data that satisfies the row filter expressions is copied to the subscriber.

If the subscription has several publications in which a table has been published with different WHERE clauses, rows that satisfy any of the expressions will be copied. See Section 31.3.6 for details.

Warning

Because initial data synchronization does not take into account the publish parameter when copying existing table data, some rows may be copied that would not be replicated using DML. Refer to Section 31.7.1, and see Section 31.2.2 for examples.

Note

If the subscriber is in a release prior to 15, copy pre-existing data doesn't use row filters even if they are defined in the publication. This is because old releases can only copy the entire table data.

31.3.6. Combining Multiple Row Filters

If the subscription has several publications in which the same table has been published with different row filters (for the same publish operation), those expressions get ORed together, so that rows satisfying any of the expressions will be replicated. This means all the other row filters for the same table become redundant if:

One of the publications has no row filter.
One of the publications was created using FOR ALL TABLES. This clause does not allow row filters.
One of the publications was created using FOR TABLES IN SCHEMA and the table belongs to the referred schema. This clause does not allow row filters.

31.3.7. Examples

Create some tables to be used in the following examples.

test_pub=# CREATE TABLE t1(a int, b int, c text, PRIMARY KEY(a,c));
CREATE TABLE
test_pub=# CREATE TABLE t2(d int, e int, f int, PRIMARY KEY(d));
CREATE TABLE
test_pub=# CREATE TABLE t3(g int, h int, i int, PRIMARY KEY(g));
CREATE TABLE

Create some publications. Publication p1 has one table (t1) and that table has a row filter. Publication p2 has two tables. Table t1 has no row filter, and table t2 has a row filter. Publication p3 has two tables, and both of them have a row filter.

test_pub=# CREATE PUBLICATION p1 FOR TABLE t1 WHERE (a > 5 AND c = 'NSW');
CREATE PUBLICATION
test_pub=# CREATE PUBLICATION p2 FOR TABLE t1, t2 WHERE (e = 99);
CREATE PUBLICATION
test_pub=# CREATE PUBLICATION p3 FOR TABLE t2 WHERE (d = 10), t3 WHERE (g = 10);
CREATE PUBLICATION

psql can be used to show the row filter expressions (if defined) for each publication.

test_pub=# \dRp+
                               Publication p1
  Owner   | All tables | Inserts | Updates | Deletes | Truncates | Via root
----------+------------+---------+---------+---------+-----------+----------
 postgres | f          | t       | t       | t       | t         | f
Tables:
    "public.t1" WHERE ((a > 5) AND (c = 'NSW'::text))

                               Publication p2
  Owner   | All tables | Inserts | Updates | Deletes | Truncates | Via root
----------+------------+---------+---------+---------+-----------+----------
 postgres | f          | t       | t       | t       | t         | f
Tables:
    "public.t1"
    "public.t2" WHERE (e = 99)

                               Publication p3
  Owner   | All tables | Inserts | Updates | Deletes | Truncates | Via root
----------+------------+---------+---------+---------+-----------+----------
 postgres | f          | t       | t       | t       | t         | f
Tables:
    "public.t2" WHERE (d = 10)
    "public.t3" WHERE (g = 10)

psql can be used to show the row filter expressions (if defined) for each table. See that table t1 is a member of two publications, but has a row filter only in p1. See that table t2 is a member of two publications, and has a different row filter in each of them.

test_pub=# \d t1
                 Table "public.t1"
 Column |  Type   | Collation | Nullable | Default
--------+---------+-----------+----------+---------
 a      | integer |           | not null |
 b      | integer |           |          |
 c      | text    |           | not null |
Indexes:
    "t1_pkey" PRIMARY KEY, btree (a, c)
Publications:
    "p1" WHERE ((a > 5) AND (c = 'NSW'::text))
    "p2"

test_pub=# \d t2
                 Table "public.t2"
 Column |  Type   | Collation | Nullable | Default
--------+---------+-----------+----------+---------
 d      | integer |           | not null |
 e      | integer |           |          |
 f      | integer |           |          |
Indexes:
    "t2_pkey" PRIMARY KEY, btree (d)
Publications:
    "p2" WHERE (e = 99)
    "p3" WHERE (d = 10)

test_pub=# \d t3
                 Table "public.t3"
 Column |  Type   | Collation | Nullable | Default
--------+---------+-----------+----------+---------
 g      | integer |           | not null |
 h      | integer |           |          |
 i      | integer |           |          |
Indexes:
    "t3_pkey" PRIMARY KEY, btree (g)
Publications:
    "p3" WHERE (g = 10)

On the subscriber node, create a table t1 with the same definition as the one on the publisher, and also create the subscription s1 that subscribes to the publication p1.

test_sub=# CREATE TABLE t1(a int, b int, c text, PRIMARY KEY(a,c));
CREATE TABLE
test_sub=# CREATE SUBSCRIPTION s1
test_sub-# CONNECTION 'host=localhost dbname=test_pub application_name=s1'
test_sub-# PUBLICATION p1;
CREATE SUBSCRIPTION

Insert some rows. Only the rows satisfying the t1 WHERE clause of publication p1 are replicated.

test_pub=# INSERT INTO t1 VALUES (2, 102, 'NSW');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (3, 103, 'QLD');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (4, 104, 'VIC');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (5, 105, 'ACT');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (6, 106, 'NSW');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (7, 107, 'NT');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (8, 108, 'QLD');
INSERT 0 1
test_pub=# INSERT INTO t1 VALUES (9, 109, 'NSW');
INSERT 0 1

test_pub=# SELECT * FROM t1;
 a |  b  |  c
---+-----+-----
 2 | 102 | NSW
 3 | 103 | QLD
 4 | 104 | VIC
 5 | 105 | ACT
 6 | 106 | NSW
 7 | 107 | NT
 8 | 108 | QLD
 9 | 109 | NSW
(8 rows)

test_sub=# SELECT * FROM t1;
 a |  b  |  c
---+-----+-----
 6 | 106 | NSW
 9 | 109 | NSW
(2 rows)

Update some data, where the old and new row values both satisfy the t1 WHERE clause of publication p1. The UPDATE replicates the change as normal.

test_pub=# UPDATE t1 SET b = 999 WHERE a = 6;
UPDATE 1

test_pub=# SELECT * FROM t1;
 a |  b  |  c
---+-----+-----
 2 | 102 | NSW
 3 | 103 | QLD
 4 | 104 | VIC
 5 | 105 | ACT
 7 | 107 | NT
 8 | 108 | QLD
 9 | 109 | NSW
 6 | 999 | NSW
(8 rows)

test_sub=# SELECT * FROM t1;
 a |  b  |  c
---+-----+-----
 9 | 109 | NSW
 6 | 999 | NSW
(2 rows)

Update some data, where the old row values did not satisfy the t1 WHERE clause of publication p1, but the new row values do satisfy it. The UPDATE is transformed into an INSERT and the change is replicated. See the new row on the subscriber.

test_pub=# UPDATE t1 SET a = 555 WHERE a = 2;
UPDATE 1

test_pub=# SELECT * FROM t1;
  a  |  b  |  c
-----+-----+-----
   3 | 103 | QLD
   4 | 104 | VIC
   5 | 105 | ACT
   7 | 107 | NT
   8 | 108 | QLD
   9 | 109 | NSW
   6 | 999 | NSW
 555 | 102 | NSW
(8 rows)

test_sub=# SELECT * FROM t1;
  a  |  b  |  c
-----+-----+-----
   9 | 109 | NSW
   6 | 999 | NSW
 555 | 102 | NSW
(3 rows)

Update some data, where the old row values satisfied the t1 WHERE clause of publication p1, but the new row values do not satisfy it. The UPDATE is transformed into a DELETE and the change is replicated. See that the row is removed from the subscriber.

test_pub=# UPDATE t1 SET c = 'VIC' WHERE a = 9;
UPDATE 1

test_pub=# SELECT * FROM t1;
  a  |  b  |  c
-----+-----+-----
   3 | 103 | QLD
   4 | 104 | VIC
   5 | 105 | ACT
   7 | 107 | NT
   8 | 108 | QLD
   6 | 999 | NSW
 555 | 102 | NSW
   9 | 109 | VIC
(8 rows)

test_sub=# SELECT * FROM t1;
  a  |  b  |  c
-----+-----+-----
   6 | 999 | NSW
 555 | 102 | NSW
(2 rows)

The following examples show how the publication parameter publish_via_partition_root determines whether the row filter of the parent or child table will be used in the case of partitioned tables.

Create a partitioned table on the publisher.

test_pub=# CREATE TABLE parent(a int PRIMARY KEY) PARTITION BY RANGE(a);
CREATE TABLE
test_pub=# CREATE TABLE child PARTITION OF parent DEFAULT;
CREATE TABLE

Create the same tables on the subscriber.

test_sub=# CREATE TABLE parent(a int PRIMARY KEY) PARTITION BY RANGE(a);
CREATE TABLE
test_sub=# CREATE TABLE child PARTITION OF parent DEFAULT;
CREATE TABLE

Create a publication p4, and then subscribe to it. The publication parameter publish_via_partition_root is set as true. There are row filters defined on both the partitioned table (parent), and on the partition (child).

test_pub=# CREATE PUBLICATION p4 FOR TABLE parent WHERE (a < 5), child WHERE (a >= 5)
test_pub-# WITH (publish_via_partition_root=true);
CREATE PUBLICATION

test_sub=# CREATE SUBSCRIPTION s4
test_sub-# CONNECTION 'host=localhost dbname=test_pub application_name=s4'
test_sub-# PUBLICATION p4;
CREATE SUBSCRIPTION

Insert some values directly into the parent and child tables. They replicate using the row filter of parent (because publish_via_partition_root is true).

test_pub=# INSERT INTO parent VALUES (2), (4), (6);
INSERT 0 3
test_pub=# INSERT INTO child VALUES (3), (5), (7);
INSERT 0 3

test_pub=# SELECT * FROM parent ORDER BY a;
 a
---
 2
 3
 4
 5
 6
 7
(6 rows)

test_sub=# SELECT * FROM parent ORDER BY a;
 a
---
 2
 3
 4
(3 rows)

Repeat the same test, but with a different value for publish_via_partition_root. The publication parameter publish_via_partition_root is set as false. A row filter is defined on the partition (child).

test_pub=# DROP PUBLICATION p4;
DROP PUBLICATION
test_pub=# CREATE PUBLICATION p4 FOR TABLE parent, child WHERE (a >= 5)
test_pub-# WITH (publish_via_partition_root=false);
CREATE PUBLICATION

test_sub=# ALTER SUBSCRIPTION s4 REFRESH PUBLICATION;
ALTER SUBSCRIPTION

Do the inserts on the publisher same as before. They replicate using the row filter of child (because publish_via_partition_root is false).

test_pub=# TRUNCATE parent;
TRUNCATE TABLE
test_pub=# INSERT INTO parent VALUES (2), (4), (6);
INSERT 0 3
test_pub=# INSERT INTO child VALUES (3), (5), (7);
INSERT 0 3

test_pub=# SELECT * FROM parent ORDER BY a;
 a
---
 2
 3
 4
 5
 6
 7
(6 rows)

test_sub=# SELECT * FROM child ORDER BY a;
 a
---
 5
 6
 7
(3 rows)

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Last updated 1 year ago

31.3.1. Row Filter Rules

31.3.2. Expression Restrictions

31.3.3. UPDATE Transformations

Table 31.1. UPDATE Transformation Summary

31.3.4. Partitioned Tables

31.3.5. Initial Data Synchronization

Warning

Note

31.3.6. Combining Multiple Row Filters

31.3.7. Examples

Table 31.1. `UPDATE` Transformation Summary