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Update PgQ (#3856)

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Kamran Ahmed
2023-04-24 15:29:21 +01:00
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src/data/roadmaps/postgresql-dba/content/109-application-skills/101-queues/101-skytools-pgq.md
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@@ -13,23 +13,4 @@ Here's a brief overview of some core concepts of PGQ:
- **Producer**: A producer application adds events to the queue. Producers can be external applications or built using PL/pgSQL functions.
- **Consumer**: A consumer application processes the events from the queue. Consumers can be implemented in any programming language capable of interfacing with the PostgreSQL database.
## Benefits of Using PGQ
Integrating PGQ into your PostgreSQL database solution provides several advantages:
- **Scalability**: PGQ can handle a high volume of events, making it suitable for large databases and distributed systems.
- **Fault-tolerance**: PGQ ensures a consistent and reliable event processing by preventing duplicate and lost events.
- **Concurrency**: Multiple consumers can work on the same queue concurrently without affecting each other’s performance.
- **Consistency**: With transactional support, PGQ guarantees the atomicity of event processing, ensuring both the event and its associated data modifications are in sync.
## Getting Started with PGQ
To start using Skytools PGQ, follow these basic steps:
- [Download and install Skytools](https://github.com/pgq/skytools) on your system.
- Create a queue in your PostgreSQL database using the provided functions, for example, `create_queue('queue_name')`.
- Implement a producer to insert events into the queue using SQL statements or PL/pgSQL functions.
- Implement a consumer to process the events from the queue. Skytools provides a Python library [`skytools.pgq`](http://skytools.projects.pgfoundry.org/docs/skytools-3.2/python-api.html) to facilitate consumer development.
- Register your consumer application using the provided Skytools functions, for example, `register_consumer('queue_name', 'consumer_name')`.
By incorporating PGQ into your PostgreSQL workflows, you'll gain a powerful and flexible queuing system that can help you manage and process your data with greater efficiency and reliability.
- [PgQ — Generic Queue for PostgreSQL](https://github.com/pgq)