Management of Slow Receivers
You have several options for handling slow members that receive data distribution. The slow receiver options control only to peer-to-peer communication between distributed regions using TCP/IP. This topic does not apply to client/server or multi-site communication, or to communication using the UDP unicast or IP multicast protocols.
Most of the options for handling slow members are related to on-site configuration during system integration and tuning. For this information, see Slow Receivers with TCP/IP.
Slowing is more likely to occur when applications run many threads, send large messages (due to large entry values), or have a mix of region configurations.
Note: If you are experiencing slow performance and are sending large objects (multiple megabytes), before implementing these slow receiver options make sure your socket buffer sizes are large enough for the objects you distribute. The socket buffer size is set using gemfire.socket-buffer-size.
By default, distribution between system members is performed synchronously. With synchronous communication, when one member is slow to receive, it can cause its producer members to slow down as well. This can lead to general performance problems in the cluster.
The specifications for handling slow receipt primarily affect how your members manage distribution for regions with distributed-no-ack scope, but it can affect other distributed scopes as well. If no regions have distributed-no-ack scope, this mechanism is unlikely to kick in at all. When slow receipt handling does kick in, however, it affects all distribution between the producer and consumer, regardless of scope. Partitioned regions ignore the scope attribute, but for the purposes of this discussion you should think of them as having an implicit distributed-ack scope.
The slow receiver options are set in the producer member’s region attribute, enable-async-conflation, and in the consumer member’s async*
If the receiver fails to receive a message, the sender continues to attempt to deliver the message as long as the receiving member is still in the cluster. During the retry cycle, throws warnings that include this string:
The warnings are followed by an info message when the delivery finally succeeds.
Asynchronous Queueing For Slow Receivers
Your consumer members can be configured so that their producers switch to asynchronous messaging if the consumers are slow to respond to cache message distribution.
When a producer switches, it creates a queue to hold and manage that consumer’s cache messages. When the queue empties, the producer switches back to synchronous messaging for the consumer. The settings that cause the producers to switch are specified on the consumer side in
gemfire.properties file settings.
If you configure your consumers for slow receipt queuing, and your region scope is distributed-no-ack, you can also configure the producer to conflate entry update messages in its queues. This configuration option is set as the region attribute enable-async-conflation. By default distributed-no-ack entry update messages are not conflated.
Depending on the application, conflation can greatly reduce the number of messages the producer needs to send to the consumer. With conflation, when an entry update is added to the queue, if the last operation queued for that key is also an update operation, the previously enqueued update is removed, leaving only the latest update to be sent to the consumer. Only entry update messages originating in a region with distributed-no-ack scope are conflated. Region operations and entry operations other than updates are not conflated.
Some conflation may not occur because entry updates are sent to the consumer before they can be conflated. For this example, assume no messages are sent while the update for Key A is added.
Note: This method of conflation behaves the same as server-to-client conflation.
You can enable queue conflation on a region-by-region basis. You should always enable it unless it is incompatible with your application needs. Conflation reduces the amount of data queued and distributed.
These are reasons why conflation might not work for your application:
- With conflation, earlier entry updates are removed from the queue and replaced by updates sent later in the queue. This is problematic for applications that depend on a specific ordering of entry modifications. For example, if your receiver has a CacheListener that needs to know about every state change, you should disable conflation.
- If your queue remains in use for a significant period and you have entries that are updated frequently, you could have a series of update message replacements resulting in a notable delay in the arrival of any update for some entries. Imagine that update 1, before it is sent, is removed in favor of a later update 2. Then, before update 2 can be sent, it is removed in favor of update 3, and so on. This could result in unacceptably stale data on the receiver.