Replication lag

This page describes how to troubleshoot and fix replication lag for Cloud SQL read replicas.


Cloud SQL read replicas use MySQL row-based replication using global transaction identifiers (GTIDs). Changes are written to the binary log of the primary instance and sent to the replica, where they are received and then applied to the database.

Replication lag can happen in a few scenarios, such as:

  • The primary instance can't send the changes fast enough to the replica.
  • The replica can't receive the changes quickly enough.
  • The replica can't apply the changes quickly enough.
Use the network_lag metric to monitor the first two scenarios when the primary instance can't send changes fast enough or the replica can't receive changes quickly enough.

The total lag is observed with the replica_lag metric. The difference between replica_lag and the network_lag can indicate the third reason when the replica can't apply replication changes fast enough. These metrics are described in the Monitor replication lag section below.

Faster replica configuration

We have two ways to make a MySQL replica apply changes faster. Users can configure their replicas with the following options:

  • Parallel replication
  • High performance flushing

Parallel replication

Parallel replication might help replication lag by configuring the replica to use multiple threads acting in parallel to apply changes on the replica. For information about using parallel replication, see Configuring parallel replication.

High performance flushing

By default, Cloud SQL for MySQL flushes the redo logs to disk after each transaction. High performance flushing reduces the frequency with which the redo logs are flushed to the disk to once per second, which improves write performance.

Set the innodb_flush_log_at_trx_commit flag on the read replica to 2. You must also set the sync_binlog flag to a higher value for the innodb_flush_log_at_trx_commit flag to be effective.

See Tips for working with flags for more information about this flag.

When the innodb_flush_log_at_trx_commit flag is set on the read replica and Cloud SQL detects that a crash might have occurred, Cloud SQL automatically recreates the replica.

Optimize queries and schema

This section suggests some common query and schema optimizations you can make to improve replication performance.

Query isolation level in the read replica

The REPEATABLE READ and SERIALIZABLE transaction isolation levels acquire locks that might block the replication changes. Consider reducing the isolation level for your queries in the replica. The READ COMMITTED transaction isolation level might perform better.

Long-running transactions in the primary database

If a large number of rows are updated in a single transaction, it can cause a sudden spike in the number of changes that need to be applied to the primary instance and then sent to the replica. This applies to single-statement updates or deletes that affect many rows at once. Changes are sent to the replica after they are committed. Applying a sudden spike of changes in the replica can increase the possibility of lock contention in the replica if the query load on the replica is also high, leading to replication lag.

Consider breaking large transactions into multiple smaller transactions.

Missing primary keys

Cloud SQL read replicas use row-based replication, which performs poorly if the MySQL tables that are replicated don't have primary keys. We recommend that all of the replicated tables have primary keys.

For MySQL 8 or later, we recommend that you set the flag sql_require_primary_key to ON to require tables in your database to have primary keys.

Exclusive locks due to DDL

Data definition language (DDL) commands, such as ALTER TABLE and CREATE INDEX, can cause replication lag in the replica due to exclusive locks. To avoid lock contention, consider scheduling DDL execution during times when the query load is lower on the replicas.

Overloaded replica

If a read replica is receiving too many queries, replication could be blocked. Consider splitting the reads among multiple replicas to reduce the load on each one.

To avoid query spikes, consider throttling replica read queries in your application logic or in a proxy layer if you use one.

If there are spikes of activity on the primary instance, consider spreading out updates.

Monolithic primary database

Consider sharding the primary database vertically (or horizontally) to prevent one or more lagging tables from holding back all the other tables.

Monitor replication lag

You can use the replica_lag and network_lag metrics to monitor replication lag and identify whether the cause of the lag is in the primary database, the network, or the replica.

Replication lag

The number of seconds that the replica's state is lagging behind the state of the primary instance. This is the difference between the current time and the original timestamp at which the primary database committed the transaction that is currently being applied on the replica. In particular, writes might be counted as lagging even if they have been received by the replica, if the replica hasn't yet applied the write to the database.

This metric reports the value of Seconds_Behind_Master when SHOW SLAVE STATUS is run on the replica. For more information, see Checking Replication Status in the MySQL Reference Manual.

Last I/O thread error number

Indicates the last error that caused the I/O thread to fail. If this is non-zero, replication is broken. This is rare, but it might happen. Check MySQL documentation to understand what the error code indicates. For example, binlog files in the primary instance might have been deleted before the replica received them. Cloud SQL usually automatically recreates the replica if replication is broken. This last_io_errno metric might tell you the reason why.

Last SQL thread error number

Indicates the last error that caused the SQL thread to fail. If this is non-zero, replication is broken. This is rare, but it might happen. Check MySQL documentation to understand what the error code indicates. Cloud SQL will usually automatically recreate the replica if replication is broken. This last_sql_errno metric can tell you the reason why.

Network lag

The length of time, in seconds, that it takes from writing the binlog in the primary database to reaching the IO thread in the replica.

If the network_lag is zero, or negligible, but the replica_lag is high, it indicates that the SQL thread is not able to apply replication changes fast enough.

Verify replication

To verify that replication is working, run the following statement against the replica:

*************************** 1. row ***************************
               Slave_IO_State: Queueing master event to the relay log
                  Master_User: cloudsqlreplica
                  Master_Port: 3306
                Connect_Retry: 60
              Master_Log_File: mysql-bin.199927
          Read_Master_Log_Pos: 83711956
               Relay_Log_File: relay-log.000025
                Relay_Log_Pos: 24214376
        Relay_Master_Log_File: mysql-bin.199898
             Slave_IO_Running: Yes
            Slave_SQL_Running: Yes
                   Last_Errno: 0
                 Skip_Counter: 0
          Exec_Master_Log_Pos: 24214163
              Relay_Log_Space: 3128686571
              Until_Condition: None
                Until_Log_Pos: 0
           Master_SSL_Allowed: Yes
           Master_SSL_CA_File: master_server_ca.pem
           Master_SSL_CA_Path: /mysql/datadir
              Master_SSL_Cert: replica_cert.pem
               Master_SSL_Key: replica_pkey.pem
        Seconds_Behind_Master: 2627
Master_SSL_Verify_Server_Cert: No
                Last_IO_Errno: 0
               Last_SQL_Errno: 0
             Master_Server_Id: 321071839
                  Master_UUID: 437d04e9-8456-11e8-b13d-42010a80027b
             Master_Info_File: mysql.slave_master_info
                    SQL_Delay: 0
          SQL_Remaining_Delay: NULL
      Slave_SQL_Running_State: System lock
           Master_Retry_Count: 86400
           Retrieved_Gtid_Set: 437d04e9-8456-11e8-b13d-42010a80027b:52111095710-52120776390
            Executed_Gtid_Set: 437d04e9-8456-11e8-b13d-42010a80027b:1-52113039508
                Auto_Position: 1
1 row in set (0.00 sec)

If replication is happening, the Slave_IO_State (first column) shows Waiting for master to send event or a similar message. Also, the Last_IO_Error field is empty.

If replication is not happening, the Slave_IO_State column shows the status Connecting to master and the Last_IO_Error column shows the status error connecting to master cloudsqlreplica@x.x.x.x:3306.

According to the MySQL documentation, a few other interesting fields that relate to replication lag are:

The name of the source binary log file that the I/O thread is currently reading from.
The position in the current source binary log file the I/O thread has read up to.
The name of the relay log file the SQL thread is currently reading and executing from.
The position in the current relay log file the SQL thread has read and executed up to.
The name of the source binary log file containing the most recent event executed by the SQL thread.

In the above example Relay_Master_Log_File has the value mysql-bin.199898. Master_Log_File has the value mysql-bin.199927. The numeric suffix 199898 is less than 199927. This means that even though the replica has received a newer mysql-bin.199927 log file, it's still applying the older mysql-bin.199898.

In this case, the SQL thread is lagging in the replica.

You can also connect to the primary database and execute:


This command shows you which binlog file is being written in the primary database.

If the primary database binary log file is newer than the Master_Log_File in the replica, it means that the I/O thread is lagging. The replica is still reading an older binary log file from the primary database.

When the I/O thread is lagging, the network_lag metric is also high. When the SQL thread is lagging, but the I/O thread is not, then the network_lag metric isn't as high, but the replica_lag is high.

The previous commands let you observe lag details while the lag is happening, but the metrics network_lag and replica_lag provide you a way to look into the past occurrences of the lag.