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Queue Processor rules
A Queue Processor rule is an internal background process on the server that you can use for queue management and asynchronous processing. You can use standard or dedicated Queue Processor rules.
Queue Processor rules replace standard agents. You can use standard queue processors
for simple queue management, or dedicated queue processors for customized or delayed
processing of messages. Queue Processor rules support higher scaling throughput than
agents. Each queue processor can process messages across 20 partitions, which means
that Queue Processor rules can support up to 20 separate processing threads
simultaneously with no conflict. Utilize Queue Processor rules by using the
Queue-for-Processing
method or the Run in Background smart
shape.
Standard Queue Processor rules
Pega Platform provides the following default queue processors that you can use in your application:- pyProcessNotification
- A queue processor that sends notifications to customers and runs the pxNotify activity to calculate data such as the list of recipients, the message, or the channel. The possible channels include an email, a gadget notification, or a Push notification.
- pzStandardProcessor
-
A queue processor that you can use for standard asynchronous processing
when:
- Processing does not require high-throughput or processing resources can be slightly delayed
- Default and standard queue behaviors are acceptable
- pyFTSIncrementalIndexer
- A queue processor that performs incremental indexing in the background. This queue processor posts Rule, Data and Work objects into the Search subsystem, as soon as you create or change them. This helps to keep search data current, and reflects the content of the database closely.
Dedicated Queue Processor rules
You can create dedicated Queue Processor rules to meet your specific needs and use these rules when you perform a high-throughput, distributed process that is critical to an application. You can use dedicated Queue Processor rules when the background process requires vertical and horizontal scaling, for tasks such as inbound batch file processing.
You can use these rules for immediate processing, for tasks such as updating a database of
user names. If you select this option, an item is pushed immediately to the queue. You can
also use dedicated Queue Processor rules for delayed processing, for tasks that you want to
be processed with a specified delay. For example, when you want to process an activity to
send an email to a user two hours after the deadline. Utilize the dedicated Queue Processor
rules by using the Queue-for-Processing
method or a Run in Background smart
shape.
Queue Processor management
Create standard and dedicated queue processors in Dev Studio. Use the Queue processor landing page in Admin Studio to trace and override Queue Processor rules in your application. To create and manage Queue Processor rules, make sure that you have one of the following privileges:
- pzQueueProcessorAdministrator
- pzClusterAdministrator
For more information about the Queue Processor rule, see Use Job Scheduler and Queue Processor rules instead of agents on Pega Community.
- Creating a Queue Processor rule
Create a Queue Processor rule to queue your items. You can use a Queue Processor rule for immediate or delayed processing, for tasks such as sending emails to users or updating the database of user logins.
- Queue-For-Processing method
Use this method to specify the details of queue processors that run in your application.
- Node classification for Queue Processor rules
For better performance, use node classification for your Queue Processor rules. Decide on which nodes your Queue Processor rules run by associating node types with Queue Processor rules.
- Stream node configurations for a Queue Processor rule
A Queue Processor rule requires at least one stream node to run. Without a stream node, messages cannot be queued to or retrieved from the Kafka server.
- Stopping and starting a queue processor
When a queue processor rule causes issues, you can stop the queue processor rule temporarily from Admin Studio.
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