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MySQL 8.0 Reference Manual
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18.6.2 Flow Control

Group Replication ensures that a transaction only commits after a majority of the members in a group have received it and agreed on the relative order between all transactions that were sent concurrently. This approach works well if the total number of writes to the group does not exceed the write capacity of any member in the group. If it does and some of the members have less write throughput than others, particularly less than the writer members, those members can start lagging behind of the writers.

Having some members lagging behind the group brings some problematic consequences, particularly, the reads on such members may externalize very old data. Depending on why the member is lagging behind, other members in the group may have to save more or less replication context to be able to fulfil potential data transfer requests from the slow member.

There is however a mechanism in the replication protocol to avoid having too much distance, in terms of transactions applied, between fast and slow members. This is known as the flow control mechanism. It tries to address several goals:

  1. to keep the members close enough to make buffering and de-synchronization between members a small problem;

  2. to adapt quickly to changing conditions like different workloads or more writers in the group;

  3. to give each member a fair share of the available write capacity;

  4. to not reduce throughput more than strictly necessary to avoid wasting resources.

Given the design of Group Replication, the decision whether to throttle or not may be decided taking into account two work queues: (i) the certification queue; (ii) and on the binary log applier queue. Whenever the size of one of these queues exceeds the user-defined threshold, the throttling mechanism is triggered. Only configure: (i) whether to do flow control at the certifier or at the applier level, or both; and (ii) what is the threshold for each queue.

The flow control depends on two basic mechanisms:

  1. the monitoring of members to collect some statistics on throughput and queue sizes of all group members to make educated guesses on what is the maximum write pressure each member should be subjected to;

  2. the throttling of members that are trying to write beyond their fair-share of the available capacity at each moment in time.