Managing a Cluster
Managing Exceptions

Managing Exceptions during Replication

The processes documented on this page apply to users of Spock extension version 4.0 and higher. You can use the pgEdge Platform UM module to upgrade your installed version of the Spock extension.

Spock extension version 4.0 (and later) includes functionality that allows you to write some exceptions to the exception log table. This functionality can prevent interruptions in replication, and allow you to gracefully handle replication errors at a time that best suits your schedule and the server traffic. The exception table also provides visibility into the history of replication errors, and provides enough information to later remediate the errors with tools like pgEdge ACE.

pgEdge Platform clusters running Spock extension 4.0 and later also include a mechanism that allows you to make changes on one node, while not replicating those changes to other nodes (a repair mode). You can use repair mode when fixing data anomalies on a single node, to ensure the modifications don’t propagate to other nodes in the cluster.

Protective Pause Mode If you do not configure your cluster to log errors to the exception log table and the cluster encounters an error in replication, the Spock extension will enter a protective pause mode. During a protective pause, replication stops and the extension continues to retry the failing operation until the issue is resolved. No other transactions are replicated to standby nodes while the conflict remains.

One example of a replication error that can induce a protective pause occurs if you attempt to UPDATE a row that exists only on one node with a unique primary key. The Spock extension will attempt to update the row on other nodes until it is successful, not replicating any operations that come after the update until the conflict is resolved. When the UPDATE is successful, and the protective pause is lifted, the Spock extension will be self-healing (whether the conflict is resolved automatically or manually with repair mode), and replication will continue.

Enabling Exception Logging

You can customize exception logging related to a failed INSERT, UPDATE, or DELETE statement for your pgEdge Platform cluster by setting the GUC values that follow. These GUCs allow you to specify behaviors on a granular level, applying the actions you choose fors operations within a transaction, rather than to an entire transaction. Note that changes to these GUCs require a system restart to apply.

To simplify setting the values, you can use the pgEdge CLI db guc-set command:

./pgedge db guc-set guc_name guc_value

For example, to set spock.exception_behavior to discard, navigate into the pgedge directory and invoke the command:

./pgedge db guc-set spock.exception_behaviour discard

The default values for these GUCs are transdiscard and all; by default, if an error occurs all operations within a transaction are rolled back if one returns an ERROR, and are recorded in spock.exception_log, regardless of whether the individual operation succeeded or failed.

spock.exception_behaviour

Use this GUC to specify the commit behavior of pgEdge platform when it encounters an ERROR within a transaction:

  • transdiscard (the default) - Set spock.exception_behaviour to transdiscard to instruct the server to discard a transaction if any operation within that transaction returns an ERROR.
  • discard - Set spock.exception_behaviour to discard to log failed operations and continue processing (and replicating) without interrupting server use. The server will commit any operation (any portion of a transaction) that does not return an ERROR statement.

spock.exception_logging

Use this GUC to specify which operations/transactions are written to the exception log table:

  • all (the default) - Set spock.exception_logging to all to instruct the server to record all transactions that contain one or more failed operations in the spock.exception_log table. Note that this setting will log all operations that are part of a transaction if one operation fails.
  • discard - Add a row to the spock.exception_log table for any discarded operation; successful transactions are not logged.
  • none - Instructs the server to not log any operation or transactions to the exception log table.

The Table Structure

You can use information stored in the exception log table to identify operations or transactions that need to be repaired or rolled back. The exception log table contains the following information:

ColumnType
remote_originoid NOT NULL
remote_commit_tstimestamptz NOT NULL
command_counterinteger NOT NULL
remote_xid bigintNOT NULL
local_originoid
local_commit_tstimestamptz
table_schematext
table_nametext
operationtext
local_tupjsonb
remote_old_tupjsonb
remote_new_tupjsonb
ddl_statementtext
ddl_usertext
error_messagetext NOT NULL
retry_errored_attimestamptz NOT NULL
PRIMARY KEYCompound: remote_origin, remote_commit_ts, command_counter

Using spock.repair_mode() when Repairing Transactions

Spock extension versions 4.0 (and later) include a function that you can control at the PSQL command line that places your pgEdge Platform cluster into repair mode while you modify data. The function is useful when fixing errors recorded in the exception log table, but can also be used in other situations where you need to interrupt replication.

Before you start repairing a transaction, set spock.repair_mode to true to interrupt replication to other nodes:

SELECT spock.repair_mode(true);

When you COMMIT or ROLLBACK a transaction, spock.repair_mode is returned to false automatically.

In the following example, the row that contains (3,Smith,sales) already exists on n2, but does not exist on n1. To remediate the issue, you can perform the following steps on n1 to add this row without it replicating to n2:

demo=# BEGIN;
BEGIN
demo=*# SELECT spock.repair_mode('True');
-[ RECORD 1 ]----------
repair_mode | 0/1C5AFD0
 
demo=*# INSERT INTO employeeid VALUES (`3`,`Smith`,`sales`);
INSERT 0 1
demo=*# COMMIT;

Logged Exception Types

The following examples demonstrate the types of replication errors that might be logged to the exception table. This is not a comprehensive list of logged errors.

Missing Primary Key Exception

In the following example:

  • Node n1 has two records in our sample table (foo) with primary key values of 1 and 2.
  • Node n2 has three records in our sample table (foo) with primary key values of 1, 2, and 3.

Both tables are added to replication, and then the row with a primary key value of 3 is updated on n2. This row is successfully updated on n2, but when replicated to n1 a row with a primary key value of 3 is not found.

If this error occurs while the exception behavior GUCs are set to their default values, the following entry is captured in the spock.exception_log table:

demo=# SELECT * FROM spock.exception_log;
-[ RECORD 1 ]----+---------------------------------------------------------------------------------------------------
remote_origin	| 26863
remote_commit_ts | 2024-07-02 19:10:04.317346+00
command_counter  | 1
remote_xid   	| 756
local_origin 	|
local_commit_ts  |
table_schema 	| public
table_name   	| foo
operation    	| UPDATE
local_tup    	|
remote_old_tup   |
remote_new_tup   | [{"value": 3, "attname": "a", "atttype": "int4"}, {"value": 2, "attname": "b", "atttype": "int4"}]
ddl_statement	|
ddl_user     	|
error_message	| logical replication did not find row to be updated in replication target relation (public.foo)
retry_errored_at | 2024-07-02 19:10:05.058789+00

Duplicate Primary Key Exception

In the following example:

  • Node n1 has one record in our sample table (foo) with a primary key value of 1.
  • Node n2 has two records in our sample table (foo) with primary key values of 1 and 2.

After adding both tables to the replication set, we update the foo table on n1, adding a row with a primary key value of 2. The row is successfully inserted on n1, but when replicated to n2, the addition results in a duplicate primary key error.

If this error occurs while the exception behavior GUCs are set to their default values, the following entry is captured in the spock.exception_log table:

remote_origin	| 49708
remote_commit_ts | 2024-07-02 19:07:09.602248+00
command_counter  | 1
remote_xid   	| 747
local_origin 	|
local_commit_ts  |
table_schema 	| public
table_name   	| foo
operation    	| INSERT
local_tup    	|
remote_old_tup   |
remote_new_tup   | [{"value": 2, "attname": "a", "atttype": "int4"}, {"value": 3, "attname"
: "b", "atttype": "int4"}]
ddl_statement	|
ddl_user     	|
error_message	| duplicate key value violates unique constraint "foo_pkey"
retry_errored_at | 2024-07-02 19:07:10.298847+00

DDL Exception

In the following example:

  • Node n1 has one row in our sample table (foo) with columns a, b, and c.
  • Node n2 has one row in our sample table (foo) with columns a and b.

If we then enable Auto DDL (to replicate DDL statements through the default replication set) and manually perform an update statement to drop column c from n1, the DDL statement is replicated to n2. Since the table (foo) on n2 does not have this column, the update statement returns an ERROR: “column "c" of relation "foo" does not exist”.

If this error occurs while the exception behavior GUCs are set to their default values, the following entry is captured in the spock.exception_log table:

demo=# select * from spock.exception_log;
-[ RECORD 1 ]----+-------------------------------------------------------------------------
remote_origin	| 49708
remote_commit_ts | 2024-07-02 17:01:32.837093+00
command_counter  | 1
remote_xid   	| 744
local_origin 	|
local_commit_ts  |
table_schema 	| spock
table_name   	| queue
operation    	| INSERT
local_tup    	|
remote_old_tup   |
remote_new_tup   | [{"value": "2024-07-02T17:01:32.83675+00:00", "attname": "queued_at", "a
tttype": "timestamptz"}, {"value": "pgedge", "attname": "role", "atttype": "name"}, {"value
": ["default_insert_only"], "attname": "replication_sets", "atttype": "_text"}, {"value": "
D", "attname": "message_type", "atttype": "char"}, {"value": "SET search_path TO \"$user\",
 public; alter table foo drop column c", "attname": "message", "atttype": "json"}]
ddl_statement	|
ddl_user     	|
error_message	|
retry_errored_at | 2024-07-02 17:01:33.609419+00
-[ RECORD 2 ]----+-------------------------------------------------------------------------
remote_commit_ts | 2024-07-02 17:01:32.837093+00
command_counter  | 2
remote_xid   	| 744
local_origin 	|
local_commit_ts  |
table_schema 	|
table_name   	|
operation    	| DDL
local_tup    	|
remote_old_tup   |
remote_new_tup   |
ddl_statement	| SET search_path TO "$user", public; alter table foo drop column c
ddl_user     	| pgedge
error_message	| column "c" of relation "foo" does not exist
retry_errored_at | 2024-07-02 17:01:33.610043+00

Exception Log Table Limitations

The following cases are not currently captured by the exception log table:

  • A mismatched number of columns: If n1 has 3 columns in a table, while n2 has 2 columns in the same table, an INSERT into the table on n1 will cause uncaptured exception on n2.
  • Data anomalies resulting from columns with different data types.