Transparent Logical DDL Replication (pgl_ddl_deploy)

Transparent DDL replication for Postgres 9.5+ for both pglogical and native logical replication.

Overview

• Release Notes
• High Level Description
• Features
• A Full Example
• Installation

Setup and Deployment

• Configuration
• Permissions
• Deployment
• Monitoring and Administration

Limitations and Restrictions

• DDL involving multiple tables
• Unsupported Commands
• Multi-Statement Client SQL Limitations
• Native Logical Supported Configurations

Resolving DDL Replication Issues

• Resolving Failed DDL on Subscribers
• Resolving Unhandled DDL
• Disable DDL Replication on Subscriber

For Developers

• Help Wanted Features
• Regression testing

Overview

Since the original release of this extension, version 2.0 introduces the major change of support for native logical replication. Read the Original Release Summary here: https://innovation.enova.com/pursuing-postgres-ddl-replication/

Release Notes

Release 2.2

Summary of changes:

• Support for Postgres 16

Release 2.0

Summary of changes:

• Support for DDL replication using Native Logical Replication
• Support for Postgres 13

Release 1.7

Summary of changes:

• Support for Postgres 12
• Support for pglogical 2.3.0

High Level Description

With any current logical replication technology for Postgres, we normally have excellent ways to replicate DML events (INSERT, UPDATE, DELETE), but are left to figure out propagating DDL changes on our own. That is, when we create new tables, alter tables, and the like, we have to manage this separately in our application deployment process in order to make those same changes on logical replicas, and add such tables to replication.

As of Postgres 13, there is no native way to do "transparent DDL replication" to other Postgres clusters alongside any logical replication technology, built on standard Postgres.

This project is an attempt to do just that. The framework is built on the following concepts:

• Event triggers always fire on DDL events, and thus give us immediate access to what we want
• Event triggers gives us access (from 9.5+) to what objects are being altered
• We can see what SQL the client is executing within an event trigger
• We can validate and choose to propagate that SQL statement to subscribers
• We can add new tables to replication at the point of creation, prior to any DML execution

In many environments, this may cover most if not all DDL statements that are executed in an application environment. We know this doesn't cover 100% of edge cases, but we believe the functionality and robustness is significant enough to add great value in many Postgres environments. It will work especially well in these two use cases:

• When you want to replicate all user tables
• When you want to replicate only a subset of tables in a schema that will not have any foreign key dependencies to other schemas

We also think it's possible to expand this concept by further leveraging the Postgres parser. There is much detail below on what the Limitations and Restrictions are of this framework.

Features

• Any DDL SQL statement can be propagated directly to subscribers without your developers needing to overhaul their migration process or know the intricacies of replication.

• Tables can be automatically added to replication upon creation (include_schema_regex option).

• Filtering by schema (regular expression) is supported. This allows you to selectively replicate only certain schemas within a publication/replication set.

• Filtering by a specific set of tables is supported, which is most useful to replicate a small set of tables and maintain things like columns added/dropped

• There is an option to deploy in a lock-safe way on subscribers. Note that this means replication will lag until all blockers finish running or are terminated.

• There is an option to fail certain events on the subscriber to be retried later. This is useful for example if you are replicating VIEW DDL but do not want that to block replication on failure.

• In some edge cases, alerting can be built around provided logging for the DBA to then handle possible manual deployments

• ALTER TABLE statements can be filtered by subcommand tags. For example, if you are using selective replication and want to ignore things like DISABLE TRIGGER which may not exist on the subscriber, this is useful to add robustness to DDL replication.

• Optional support for automatically killing blocking processes on the subscriber system that is preventing DDL execution.

A Full Example

Since we always look for documentation by example, we show this first. Assuming logical replication is already setup with an active subscription, and given these publications/replication sets:

• default - replicate every event
• insert_update - replicate only inserts and updates

Provider:

CREATE EXTENSION pgl_ddl_deploy;

--Setup permissions
SELECT pgl_ddl_deploy.add_role(oid) FROM pg_roles WHERE rolname in('app_owner', 'replication_role'); 

--Setup configs
INSERT INTO pgl_ddl_deploy.set_configs
(set_name,
include_schema_regex,
lock_safe_deployment,
allow_multi_statements)
VALUES ('default',
  '.*',
  true,
  true),
  ('insert_update',
  '.*happy.*',
  true,
  true);

Subscribers (run on both default and insert_update subscribers):

CREATE EXTENSION pgl_ddl_deploy;

--Setup permissions for the same role on subscriber to have DDL permissions 
CREATE ROLE app_owner WITH NOLOGIN;
SELECT pgl_ddl_deploy.add_role(oid) FROM pg_roles WHERE rolname in('app_owner', 'replication_role');

--Be sure that on the subscriber, app_owner role has the following perms:
GRANT CREATE ON DATABASE :DBNAME TO app_owner;

--If schemas already exist on subscriber that you want the app_owner
--role to be able to modify with any DDL, then you must do this: 
ALTER TABLE foo OWNER TO app_owner; --...etc

Here is a way to fix the subscriber table owner based on the tables already in replication on provider for the same publication/replication set and ddl configuration you just setup on provider (shell command - pglogical example):

PGSERVICE=provider_cluster psql provider_db << EOM | PGSERVICE=subscriber_cluster psql subscriber_db
COPY
(
SELECT 'ALTER TABLE '||quote_ident(n.nspname)||'.'||quote_ident(c.relname)||' OWNER TO app_owner;'
FROM pglogical.replication_set rs
INNER JOIN pgl_ddl_deploy.set_configs sc
  ON sc.set_name = rs.set_name
INNER JOIN pgl_ddl_deploy.rep_set_table_wrapper() rsr
  ON rsr.set_id = rs.set_id
INNER JOIN pg_class c ON c.oid = rsr.set_reloid
INNER JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE rs.set_name = 'insert_update'
  AND n.nspname ~* sc.include_schema_regex
  AND n.nspname !~* pgl_ddl_deploy.exclude_regex()
)
TO STDOUT;
EOM

Provider:

--Deploy DDL replication
SELECT pgl_ddl_deploy.deploy(set_name)
FROM pgl_ddl_deploy.set_configs;

Subscriber - only required if using native in order to add the pgl_ddl_deploy.queue table to replication.

ALTER SUBSCRIPTION default REFRESH PUBLICATION WITH (COPY_DATA = false);

Provider:

--App deployment role
SET ROLE app_owner;

--Let's make some data!
CREATE TABLE foo(id serial primary key);
ALTER TABLE foo ADD COLUMN bla INT;
INSERT INTO foo (bla) VALUES (1),(2),(3);

CREATE SCHEMA happy;
CREATE TABLE happy.foo(id serial primary key);

NOTE - after creating a table using schema-regex-based DDL replication with native logical replication, it is necessary to manually execute on the subscriber the command SELECT pgl_ddl_deploy.retry_all_subscriber_logs(); to complete the process of adding the new table to replication. This is because of the bug https://www.postgresql.org/message-id/CAMa1XUh7ZVnBzORqjJKYOv4_pDSDUCvELRbkF0VtW7pvDW9rZw@mail.gmail.com preventing the safety of running ALTER SUBSCRIPTION ... REFRESH PUBLICATION in a replication process. This will be updated as soon as a patch becomes available.

ALTER TABLE happy.foo ADD COLUMN bla INT;
INSERT INTO happy.foo (bla) VALUES (1),(2),(3);
DELETE FROM happy.foo WHERE bla = 3;

Subscriber to default:

SELECT * FROM foo;
 id | bla
----+-----
  1 | 1
  2 | 2
  3 | 3
(3 rows)

SELECT * FROM happy.foo;
 id | bla
----+-----
  1 | 1
  2 | 2
(3 rows)

Note that both tables are replicated based on configuration, as are all events (inserts, updates, and deletes).

Subscriber to insert_update:

SELECT * FROM foo;
ERROR:  relation "foo" does not exist
LINE 1: SELECT * FROM foo;

SELECT * FROM happy.foo;
 id | bla
----+-----
  1 | 1
  2 | 2
  3 | 3
(3 rows)

Note that the foo table (in public schema) was not replicated. Also, because we are not replicating deletes here, happy.foo still has all data.

Installation

The functionality of this requires postgres version 9.5+ and a working install of pglogical.

DEB available on official PGDG repository as postgresql-${PGSQL_VERSION}-pgl-ddl-deploy see installation instruction on https://wiki.postgresql.org/wiki/Apt

See the notes below on requirements to run the regression suite.

This extension requires pglogical to be installed before you can create the extension in any database. Then the extension can be deployed as any postgres extension:

CREATE EXTENSION pgl_ddl_deploy;

This extension needs to be installed on provider and all subscribers. As of version 1.5.0, you must have the same pgl_ddl_deploy version on both the provider and subscriber (NOT necessarily the same Postgres version).

To update to pgl_ddl_deploy 1.5 from a previous version, install the latest version packages on your server(s), then run in the database(s):

ALTER EXTENSION pgl_ddl_deploy UPDATE;

Setup and Deployment

Configuration

For native logical replication, DDL replication is configured on a per-publication basis. For pglogical, DDL replication is configured on a per-replication set basis.

There are three basic types of configuration:

• include_only_repset_tables - Only tables already in a publication/replication set are maintained. This means only ALTER TABLE or COMMENT statements are replicated.
• include_schema_regex - Provide a regular expression to match both current and future schemas to be automatically added to replication. This supports all event types except for ones like GRANT which do not provide access to information about which schema an object exists in.
• include_everything - Propagate all DDL events regardless of schema. This is for cases like GRANT which do not provide access to information about which schema an object exists in

The above 3 options are mutually exclusive. You can, however, use an additional option ddl_only_replication either with include_schema_regex or include_everything. This only means tables are not automatically added to replication. Its use is if you want to keep the schema of two systems in sync, but not necessarily replicate data for all tables.

Add rows to pgl_ddl_deploy.set_configs in order to configure (but not yet deploy) DDL replication for a particular publication/replication set. Note especially that driver controls which replication technology this is for, native or pglogical. For example:

--Only some options are shown.  See below for all options

--This type of configuration will DDL replicate all user schemas, and auto-add
--new matching schemas/tables to replication:
INSERT INTO pgl_ddl_deploy.set_configs (set_name, include_schema_regex, driver)
VALUES ('default', '.*', 'native'::pgl_ddl_deploy.driver);

--This type of configuration will maintain only the specific set of tables
--in the given replication set for any `ALTER TABLE` statements:
INSERT INTO pgl_ddl_deploy.set_configs (set_name, include_only_repset_tables, driver)
VALUES ('my_special_tables', TRUE, 'native'::pgl_ddl_deploy.driver);

The relevant settings:

• driver: native or pglogical (type pgl_ddl_deploy.driver) - DEFAULT pglogical
• set_name: publication name OR pglogical replication_set name
• include_schema_regex: a regular expression for which schemas to include in DDL replication. This can be used to auto-add new tables to replication. This option is incompatible with include_only_repset_tables.
• lock_safe_deployment: if true, DDL will execute in a low lock_timeout loop on subscriber
• allow_multi_statements: if true, multiple SQL statements sent by client can be propagated under certain conditions. See below for more details on caveats and edge cases. If false, only a single SQL statement (technically speaking - a SQL statement with a single node parsetree) will be eligible for propagation.
• include_only_repset_tables: if true, only tables that are in replication will be maintained by DDL replication. Thus only ALTER TABLE statements are permitted here. This option is incompatible with include_schema_regex.
• queue_subscriber_failures: if true, DDL will be allowed to fail on subscriber without breaking replication, and queued for retry using function pgl_ddl_deploy.retry_all_subscriber_logs(). This is useful for example if you are replicating VIEW DDL but do not want failures to block data replication. It is NOT recommendeded that you use this with any TABLE replication, since those events are likely to break data replication.
• create_tags: the set of command tags for which the create event triggers will fire. Change with caution. These are defaulted to the appropriate default set for either include_schema_regex or include_only_repset_tables.
• drop_tags: the set of command tags for which the drop event triggers will fire. Change with caution. These are defaulted to the appropriate default set for either include_schema_regex or include_only_repset_tables.
• blacklisted_tags: These are command tags that are never permitted to be propagated to subscribers. It is configurable, but the default is pgl_ddl_deploy.blacklisted_tags()
• exclude_alter_table_subcommands: if you want to exclude certain ALTER TABLE subcommand tags, here is the place to do it. The standard list can be found as the function pgl_ddl_deploy.common_exclude_alter_table_subcommands(). You can also simply choose only select tags from this list to exclude.
• ddl_only_replication: for use with include_schema_regex only. Allows you to only replicate the schema without auto-adding tables to replication. This is useful in particular if you want to keep the structure of two systems fully synchronized, but you don't necessarily want to replicate data for all tables.
• include_everything: Propagate all DDL events regardless of schema. This is for cases like GRANT which do not provide access to information about which schema an object exists in.
• signal_blocking_subscriber_sessions: Kill processes on the subscriber holding any kind of lock on the target table which would prevent DDL execution. cancel will use pg_cancel_backend, terminate will use pg_terminate_backend. cancel_then_terminate will try to cancel and if not successful, will go to terminate. NULL disables this feature. Killed sessions will be logged to the subscriber table pgl_ddl_deploy.killed_blockers, which has a field reported and reported_at which are designed for monitoring where you can notify users of killed queries, and then mark those queries as reported to users. ** NOTE ** - currently, we do not support figuring out dependent locks with native partitioning. You may miss killing blocking processes when native partitioning is involved.
• subscriber_lock_timeout: Only for use with signal_blocking_subscriber_sessions. This is an optional parameter for lock_timeout for DDL execution on subscriber in milliseconds before killing blockers. Default 3000 (3 seconds).

There is already a pattern of schemas excluded always that you need not worry about. You can view them in this function:

SELECT pgl_ddl_deploy.exclude_regex();

You can use this query to check what your current configs will pull in for schemas if you are using include_schema_regex:

SELECT sc.set_name, n.nspname
FROM pg_namespace n
INNER JOIN pgl_ddl_deploy.set_configs sc
  ON nspname !~* pgl_ddl_deploy.exclude_regex()
  AND n.nspname ~* sc.include_schema_regex
ORDER BY sc.set_name, n.nspname;

You can use this query to test a new regex for what existing schemas it matches:

SELECT n.nspname
FROM pg_namespace n
WHERE nspname !~* pgl_ddl_deploy.exclude_regex()
  AND n.nspname ~* 'test'
ORDER BY n.nspname;

There are no stored procedures to insert/update set_configs, which we don't think would add much value at this point. There are check constraints and triggers in place to ensure the regex is valid and the other conditions of uniqueness are met for config options.

Permissions

It is important to consider which role will be allowed to run DDL in a given provider. As it stands, this role will need to exist on the subscriber as well, because this same role will be used to try to deploy on the subscriber. pgl_ddl_deploy provides a function to provide permissions needed for a given role to use DDL deployment. This needs to run provider and all subscribers:

SELECT pgl_ddl_deploy.add_role(oid)
FROM pg_roles
WHERE rolname IN('app_owner_role');

Note that in upgrading to version 1.5, we are automatically re-applying the permissions you have already granted using add_role to the new tables in this version.

Deployment of Automatic DDL Replication

To deploy (meaning activate) DDL replication for a given replication set, run:

--Deploy any set_configs with given set_name:
SELECT pgl_ddl_deploy.deploy(set_name);

--Deploy only a single set_config_id:
SELECT pgl_ddl_deploy.deploy(set_config_id);

• From this point on, the event triggers are live and will fire on the following events (by default, unless you have customized create_tags or drop_tags):

   command_tag
-----------------
 ALTER FUNCTION
 ALTER SEQUENCE
 ALTER TABLE
 ALTER TYPE
 ALTER VIEW
 CREATE FUNCTION
 CREATE SCHEMA
 CREATE SEQUENCE
 CREATE TABLE
 CREATE TABLE AS
 CREATE TYPE
 CREATE VIEW
 DROP FUNCTION
 DROP SCHEMA
 DROP SEQUENCE
 DROP TABLE
 DROP TYPE
 DROP VIEW
 SELECT INTO

• Not all of these events are handled in the same way - see Limitations and Restrictions below
• Note that if, based on your configuration, you have tables that should be added to replication already, but are not, you will not be allowed to deploy. This is because DDL replication should only be expected to automatically add new tables to replication. To override this, add the tables to replication manually and sync as necessary.

DDL replication can be disabled/enabled (this will disable/enable event triggers):

--By set_name
SELECT pgl_ddl_deploy.disable(set_name);
SELECT pgl_ddl_deploy.enable(set_name);

--By set_config_id
SELECT pgl_ddl_deploy.disable(set_name);
SELECT pgl_ddl_deploy.enable(set_name);

You can also undeploy DDL replication, which means dropping all event triggers and functions for a given config:

SELECT pgl_ddl_deploy.undeploy(set_name);
SELECT pgl_ddl_deploy.undeploy(set_config_id);

If you want to change the configuration in set_configs, you can re-deploy by again running pgl_ddl_deploy.deploy on the given set_name. There is currently no enforcement/warning if you have changed configuration but not deployed, but should be easy to add such a feature.

Note that you are able to override the event triggers completely, for example, if you are an administrator who wants to run DDL and you know you don't want that propagated to subscribers. You can do this with SESSION_REPLICATION_ROLE, i.e.:

SET SESSION_REPLICATION_ROLE TO REPLICA;

-- I don't care to send this to subscribers (note that you can also exclude statements
-- like this by using exclude_alter_table_subcommands)
ALTER TABLE foo SET (autovacuum_vacuum_threshold = 1000);

RESET SESSION_REPLICATION_ROLE;

Monitoring and Administration

This framework will log all DDL changes that attempt to be propagated. It is also generous in allowing DDL replication procedures to fail in order not to prevent application deployments of DDL. An exception will never be allowed to block a DDL statement. The most that will happen is log_level WARNING will be raised. This feature is based on the assumption that we do not want replication issues to ever block client-facing application functionality.

Several tables are setup to manage DDL replication and log exceptions, in addition to server log warnings raised at WARNING level in case of issues:

• events - Logs replicated DDL events on the provider
• subscriber_logs - Logs replicated DDL events executed on subscribers
• commands - Logs detailed output from pg_event_trigger_ddl_commands() and pg_event_trigger_dropped_objects()
• unhandled - Any DDL that is captured but cannot be handled by this framework (see details below) is logged here.
• exceptions - Any unexpected exception raise by the event trigger functions are logged here

There are resolved fields on the unhandled and exceptions tables that can be marked so that monitoring will show only new problems based on this table by using functions:

• pgl_ddl_deploy.resolve_unhandled(unhandled_id INT, notes TEXT = NULL)
• pgl_ddl_deploy.resolve_exception(exception_id INT, notes TEXT = NULL)

Limitations and Restrictions

DDL involving multiple tables

A single DDL SQL statement which alters tables both replicated and non-replicated cannot be supported. For example, if I have include_schema_regex which includes only the regex '^replicated.*', this is unsupported:

DROP TABLE replicated.foo, notreplicated.bar;

Likewise, the following can be problematic if you are using filtered replication:

ALTER TABLE replicated.foo ADD COLUMN foo_id INT REFERENCES unreplicated.foo (id);

Depending on your environment, such cases may be very rare, or possibly common. For example, such edge cases are far less likely when you want to do 1:1 replication of just about all tables in your application database. Also, if you are not likely to have relationships between schemas you both are and are not replicating, then edge cases will be unlikely. As mentioned above, this framework will work best with these two use cases:

• When you want to replicate all user tables
• When you want to replicate only a subset of tables in a schema that will not have any foreign key dependencies to other schemas

Some of these edge cases can be minimized with the exclude_alter_table_subcommands option, which was developed precisely because for us, the most common failures were things like DISABLE TRIGGER for a trigger that does not exist on the subscriber.

In this case, the DDL statement could fail on the subscriber. To resolve this, see Resolving Failed DDL on Subscribers.

Unsupported Commands

CREATE TABLE AS and SELECT INTO are not supported to replicate DDL due to limitations on transactional consistency. That is, if a table is created from a set of data on the provider, to run the same SQL on the subscriber will in no way guarantee consistent data. For example:

CREATE TABLE foo AS
SELECT field_1, field_2, now() AS refreshed_at
FROM table_1;

Not only is it possible that table_1 doesn't even exist on the subscriber, even if it does it may not be fully up to date with the provider, in which case the data created in the table on the subscriber would not match. Worse, is that the now() function is basically guaranteed to be different on the subscriber.

It is recommended instead that the DDL statement creating the table and the DML inserting into the table are separated. Continuing the above example:

CREATE TABLE foo (field_1 INT PRIMARY KEY, field_2 TEXT, refreshed_at TIMESTAMPTZ);
INSERT INTO foo (field_1, field_2, refreshed_at)
SELECT field_1, field_2, now() AS refreshed_at
FROM table_1;

The above is completely supported by this framework, bearing in mind some of the edge cases with multi-statements. The CREATE TABLE will automatically be replicated by this framework, and the table will be added to replication since it has a primary key. Then the INSERT will be replicated by normal logical replication.

NOTE that temp tables are not affected by this limitation, since temp objects are always excluded from DDL replication anyway.

To resolve these, see Resolving Unhandled DDL.

Multi-Statement Client SQL Limitations

It is important to understand that limitations on multi-statement client SQL has nothing to do with executing multiple SQL statements at once, or in one transaction. Of course, it is assumed that will often or even usually be the case, and this framework can handle that just fine.

The complexities and limitations come when the client sends all SQL statements as one single string to Postgres. Assume the following SQL statements:

CREATE TABLE foo (id serial primary key, bla text);
INSERT INTO foo (bla) VALUES ('hello world');

If this was in a file that I called via psql, it would run as two separate SQL command strings.

However, if in python or ruby's ActiveRecord I create a single string as above and execute it, then it would be sent to Postgres as 1 single SQL command string. In such a case, this framework is aware that a multi-statement is being executed by using Postgres' parser to get the command tags of the full SQL statement. You have a little freedom here with the allow_multi_statements option:

• If false, pgl_ddl_deploy will only auto-replicate a client SQL statement that contains 1 command tag that matches the event trigger command tag. That's really safe, but it means you may have a lot more unhandled deployments.
• If true, pgl_ddl_deploy will only auto-replicate DDL that contains safe command tags to propagate. For example, mixed DDL and DML is forbidden, because executing such a statement would in effect double-execute DML on both provider and subscriber. However, if you have a CREATE TABLE and ALTER TABLE in one command, assuming the table should be included in replication based on your configuration, then such a statement will be sent to subscribers. But of course, we can't guarantee that all DDL statements in this command are on the same table - so there could be edge cases.

In any case that a SQL statement cannot be automatically run on the subscriber based on these analyses, instead it will be logged as a WARNING and put into the unhandled table for manual processing.

To resolve these, see Resolving Unhandled DDL.

The regression suite in the sql folder has examples of several of these cases.

Thus, limitations on multi-statement SQL is largely based on how your client sends its messages in SQL to Postgres, and likewise how your developers tend to write SQL. The good thing about this is that it ought to be much easier to train developers to logically separate SQL in their migrations, as opposed to far more work we need to do when we don't have any kind of transparent DDL replication.

These limitations obviously have to be weighed against the cost of not using a framework like this at all in your environment.

The unhandled table and WARNING logs are designed to be leveraged with monitoring to create alerting around when manual intervention is required for DDL changes.

Native Logical Supported Configurations

The only known configuration limitation for native logical DDL replication is that only a publication that includes replicating inserts can support DDL replication. This relates to how the DDL queueing mechanism works. The default CREATE PUBLICATION in postgres includes publishing inserts. It can also be configured specifically with WITH (publish = 'insert'). For more details see https://www.postgresql.org/docs/current/sql-createpublication.html.

Resolving DDL Replication Issues

Resolving Failed DDL on Subscribers

In some cases, you may propagate DDL that fails on the subscriber, and replication will break, unless you have enabled queue_subscriber_failures. You will then need to:

• Manually deploy with the same SQL statement modified so that it excludes the failing portion. For the example above of both adding a column and adding a foreign key, assuming we don't have that unreplicated table, then you would run:

ALTER TABLE replicated.foo ADD COLUMN foo_id INT;

• Consume the change in affected replication slot using pg_logical_slot_get_changes up to specific LSN of the transaction which included the DDL statement to get replication working again (this is only human readable for pglogical, not native).
• You could also "trick" the DDL into applying - for example, by creating a dummy object that will allow the DDL to apply even if you don't need it, then discarding those objects once replication is working again.
• Re-enable replication for affected subscriber(s)

If you are using queue_subscriber_failures, any DDL failures for your given configuration will be logged as failed in pgl_ddl_deploy.subscriber_logs. You can resolve issues, and attempt to re-deploy by using functions:

--Retry all failed, in transactional order
SELECT pgl_ddl_deploy.retry_all_subscriber_logs();

--Retry only a single failed log
SELECT pgl_ddl_deploy.retry_subscriber_log(subscriber_log_id);

When you retry subscriber logs, new rows are created for the retries, thus the rows with succeeded = f still remain.

Queries like this are helpful:

SELECT id,
  LEFT(ddl_sql, 30) AS sql,
  origin_subscriber_log_id,
  next_subscriber_log_id,
  succeeded
FROM pgl_ddl_deploy.subscriber_logs
WHERE NOT succeeded;

Then to check retry:

WITH old AS (
SELECT id,
  LEFT(ddl_sql, 30) AS sql,
  origin_subscriber_log_id,
  next_subscriber_log_id,
  succeeded
FROM pgl_ddl_deploy.subscriber_logs
WHERE NOT succeeded)

SELECT id,
  LEFT(ddl_sql, 30) AS sql,
  origin_subscriber_log_id,
  next_subscriber_log_id,
  succeeded
FROM pgl_ddl_deploy.subscriber_logs
WHERE id IN (SELECT next_subscriber_log_id FROM old);

No resolution: Last resort

The following is only applicable to native replication.

Sometimes there are cases where things are broken and you either can't figure out how to work around it, or it may in fact be impossible to process a particular set of operations within a transaction automatically. Although we would welcome a more proper feature to disable DDL replication on the subscriber, you can do so manually with the following command on the subscriber:

ALTER TABLE pgl_ddl_deploy.queue DISABLE TRIGGER execute_queued_ddl;

NOTE that DDL replication will be disabled so long as you have done this, although you will see any changes come through as new rows in the queue table. BE SURE to re-enable the trigger as a REPLICA TRIGGER properly afterwards:

ALTER TABLE pgl_ddl_deploy.queue ENABLE REPLICA TRIGGER execute_queued_ddl;

Resolving Unhandled DDL

At present, an unhandled DDL deployment may not break replication by itself. If the DDL statement that could not be deployed doesn't actually affect any data being replicated (for example, a brand new table is added), then replication will continue. However, the situation should be resolved ASAP because it is assumed that whatever table(s) that were involved in the DDL should be propagated to subscribers. It is also possible that replication will break immediately. For example, if a column is added to the table, and data is replicating, it will fail immediately because of a column mismatch. In such cases you will need to:

• Manually deploy the unhandled SQL statement modified so that it excludes the unhandled portion. For the example of a multi-statement SQL above, you would need to exclude the INSERT portion of the SQL and run:

CREATE TABLE foo (id serial primary key, bla text);

• If a new table is involved, in this case you also will need to manually add the table to replication using ALTER PUBLICATION ADD TABLE or pglogical.replication_set_add_table depending on driver.
• If a new table is involved, you may need to resynchronize the table if data has been replicating for it
• If a new table is NOT involved (for example ALTER TABLE ADD COLUMN), then replication will simply continue where it broke
• Re-enable replication for affected subscriber(s)
• Mark your unhandled records as resolved using function:

SELECT pgl_ddl_deploy.resolve_unhandled(unhandled_id INT, notes TEXT = NULL);

To be more conservative, we may want a feature that forces replication to break if there is an unhandled deployment, for example, by sending an exception through replicate_ddl_command. But such a feature may cause additional and unnecessary administration overhead, since it is likely the strictness of replication will cause the system to break when it should.

Disable DDL Replication on Subscriber

The following applies to native logical replication only.

As a last resort, you might find some unexpected problem where you want to disable DDL replication on the subscriber because you are in an error loop. This should be done very cautiously and as a last resort.

Disable the trigger on the DDL queue table to ignore all DDL replication on subscriber:

ALTER TABLE pgl_ddl_deploy.queue DISABLE TRIGGER execute_queued_ddl;

Do what you need to do for manual fixes. If you suspect a bug, please report it. When you are finished, you MUST ENABLE THE TRIGGER IN REPLICATION MODE ONLY:

ALTER TABLE pgl_ddl_deploy.queue ENABLE REPLICA TRIGGER execute_queued_ddl;

For Developers

Help Wanted Features

We are currently using the parser only to get the list of command tags. One big advantage to this is that it isn't going to be difficult to maintain as Postgres develops. One disadvantage is that it tells us nothing about the actual objects being modified, nor the type of modification.

We believe it is feasible to use the parser to actually only process the parts of a multi-statement SQL command that we want to, but this far more ambitious, and would be more work to maintain. We would need to leverage the different structures of each DDL command's parsetree to determine if the table is in a schema we care to replicate. Then, we would need to use the parser's lex code to take out the piece(s) we want.

Theoretically speaking, don't we have all that we need in the SQL statement + the parser to programatically use only what we want and send it to subscribers? I think we do, but lots of work would be required, and we would welcome those with more comfort in the parser code to help if interested.

SQL files

To build the higher version SQL files (i.e. 2.0) from the lower versions + the upgrade patch SQL files, run pgl_ddl_deploy-sql-maker.sh.

Note the script correct_2.0_for_no_pglogical.py. This was used to edit the long .sql files to safely remove the hard dependency on pglogical. This should not be needed long-term (i.e. once moving to versions above 2.0).

Regression testing

The building of the regression suite has changed since adding native logical support. There are several scripts involved to manage this. Basically, I am duplicating the entire original test suite and making in-place changes in order to create a separate test flow for native logical replication, but also supporting the other pg versions prior to pg10. Here is a brief explanation: 1. The script duplicate_tests_for_native.py copies all of the tests, adding conditionals where needed. It's not pretty but was the most efficient way of managing the test suite with these 2 test flows. It is not perfect, but once it has been run, the test failures can be seen to be only white space issues that then can be easily resolved by re-copying the results file to expected. It is desirable to have as few changes as possible between the two test suites. 2. The script generate_new_native_tests.py is to generate numerically a brand new test only applicable to native logical replication.

You can run the regression suite, which must be on a server that has pglogical packages available, and a cluster that is configured to allow creating the pglogical extension (i.e. adding it to shared_preload_libraries). Note that the regression suite does not do any cross-server replication testing, but it does cover a wide variety of replication cases and the core of what is needed to verify DDL replication.

As with any Postgres extension:

make install
make installcheck

# There is support for testing both 1.4 and the upgraded path from 1.4 to 1.5
FROMVERSION=1.4 make installcheck   # Test from 1.4 upgrade to 1.5
FROMVERSION=1.5 make installcheck