Getting Started with AMPS Queues
To add a simple queue to AMPS, add the following options to your configuration file.
First, create a transaction log that will record the messages for the queue and the state of the queue, as described in Record and Replay Messages. You add the transaction log entry if your AMPS configuration does not already have one. Otherwise, you can simply add a Topic
statement or modify an existing Topic
statement to record the messages. The sample below captures any JSON messages published to the Work
topic, and also tracks the state of the queue itself:
Next, declare the queue topic itself. Queues are defined in the SOW element of the AMPSConfig
file, as shown below:
These simple configuration changes create an AMPS message queue. Notice that the Topic
for the queue in this case is WorkToDo
, which includes every message published to the underlying topic Work
. You could also use a regular expression to include messages to more than one topic, or leave out the UnderlyingTopic
to include only messages published to the topic with the same name as the queue.
This simple queue provides each message that arrives for the queue to at most one subscriber. After AMPS delivers the message to one subscriber, AMPS removes the message from the queue without waiting for the subscriber to acknowledge the message.
While it's easy to create a simple queue, AMPS offers a rich queuing model that is designed to meet a wide variety of queuing needs. The options are described in the following sections and the AMPS Configuration Reference.
Queue Replication Types
AMPS supports three different replication types for a queue. The configuration tag used to define a queue specifies the replication type for the queue.
By default, AMPS queues are distributed queues. That is, if the queue topic or the underlying topics are replicated, AMPS provides the queue delivery guarantees (that is, at-most-once
or at-least-once
delivery) as though all of the instances were delivering messages from a single queue.
AMPS provides local queues (where each instance has a separate, independent queue) when a queue is defined with the LocalQueue
tag. In this case, AMPS does not allow replication of the queue topic, and all management of the queue is local to the individual instance.
AMPS also supports distributed queues that are restricted to a set of instances within a mesh of replicated instances. These queues are defined with the GroupLocalQueue
tag, to indicate that the queue is restricted to a subset of the servers involved in replication. In this case, only the servers that define the GroupLocalQueue
participate in message delivery for the queue. In addition, the group must choose the instance that will initially own messages for the queue, as described in the section on replicated queues and queue message ownership. In version 5.3.4 and later, the identity of a GroupLocalQueue
is defined by the Name
of the queue combined with the GroupLocalQueueDomain
, if one is set, or the Group
of the AMPS instance if the definition does not include a GroupLocalQueueDomain
tag. In previous versions of AMPS, the identity of the queue is determined only by the Name
of the group local queue, regardless of the instance that defines the queue.
When defining a GroupLocalQueue
, the instances that participate in the queue do not need to be in the same replication group: any instance in a replicated mesh that defines the queue can host an instance of the queue, regardless of whether the instance is in the same replication group or not. However, if the instances that host the queue are in different groups, the queue definitions should set the same GroupLocalQueueDomain
to be considered to be the same queue.
Each instance of AMPS manages its own subscriptions and backlog, regardless of the replication model. Delivery guarantees are provided by managing the ownership of each message in the queue, as described in the Replicated Queues section. Only messages owned by the current instance will be delivered to subscribers, and only the subscriptions on the current instance are considered for delivery fairness and limits such as MaxBacklog
(the overall limit for leases from the queue).
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