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15 posts tagged with "Streams"

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Delivery Optimization for RabbitMQ Streams

· 6 min read

RabbitMQ Streams are designed for high-throughput scenarios, but what happens when your ingress rate is low? Low message rates can significantly impact delivery performance, reducing message consumption rates by an order of magnitude. RabbitMQ 4.2 introduces an optimization that dramatically improves delivery rates for low-throughput streams, benefiting all supported protocols.

Broker-Side SQL Filtering with RabbitMQ Streams

· 5 min read

RabbitMQ 4.2 introduces SQL filter expressions for streams, enabling powerful broker-side message filtering.

In our benchmarks, combining SQL filters with Bloom filters achieved filtering rates of more than 4 million messages per second — in highly selective scenarios with high ingress rates. This means only the messages your consumers actually care about leave the broker, greatly reducing network traffic and client-side processing overhead.

Go Stream client 1.5.8 is released with a critical fix

· One min read

RabbitMQ Go Stream client 1.5.8 is a newbug fix release that includes a critical fix.

The fix reverts the pull request 393 that introduced a dangerous bug where the library skipped chunk delivery when the channel's maximum capacity was reached. In practical terms, message dispatch to the application would stop.

The bug was triggered when the consumer was experiencing a near peak delivery pressure for some time, or when the consumer was consistently slow to process the deliveries.

Affected versions

The bug affects the following versions: 1.5.5, 1.5.6 and 1.5.7.

We strongly recommend updating the client to 1.5.8 as soon as possible.

AMQP 1.0 Filter Expressions

· 6 min read

RabbitMQ 4.1 introduces an exciting new feature: AMQP filter expressions for streams.

This feature enables RabbitMQ to support multiple concurrent clients, each consuming only a specific subset of messages while preserving message order. Additionally, it minimizes network traffic between RabbitMQ and its clients by dispatching only the messages that match the clients' interests.

In this blog post, we’ll explore what AMQP filter expressions are and walk through a simple Java example of how to use them.

RabbitMQ 3.11 Feature Preview: Super Streams

· 7 min read

RabbitMQ 3.11 will bring a feature with one of the coolest names in its history: super streams. Super streams are a way to scale out by partitioning a large stream into smaller streams. They integrate with single active consumer to preserve message order within a partition.

This blog post gives an overview of super streams and the use cases they unlock. Read on to learn more, we value your feedback to make this feature the best it can be.

RabbitMQ 3.11 Feature Preview: Single Active Consumer for Streams

· 10 min read

RabbitMQ 3.11 will bring a noteworthy feature to streams: single active consumer. Single active consumer provides exclusive consumption and consumption continuity on a stream. It is also critical to get the most out of super streams, our solution for partitioning, that provide scalability for streams.

Read on to find out more about single active consumer for streams and don't hesitate to experiment with what is already available: try it, break it, tell us what you like and don't like, what's missing. Your feedback is essential to make this feature the best it can be.