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Last updated : Nov 30, 2017
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar Understand more
Nov 2017
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。

Avro is a framework for data serialization. By storing schema along with the message content, it encourages schema evolution. Producers can edit field names, add new fields or delete existing fields and Avro guarantees that the clients continue to consume the messages. Having a schema allows data to be written without overhead which results in compact data encoding and faster data processing. Although the exchange of structure-less messages between producer and consumer is flexible, we've seen teams facing issues with incompatible unprocessed messages in the queue during deployments. We've used Avro in a number of projects and would recommend using it over just sending unstructured messages.

Mar 2017
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。

Avro is a framework for data serialization. By storing schema along with the message content, it encourages schema evolution. Producers can edit field names, add new fields or delete existing fields and Avro guarantees that the clients continue to consume the messages. Having a schema allows data to be written without overhead which results in compact data encoding and faster data processing. Although the exchange of structure-less messages between producer and consumer is flexible, we've seen teams facing issues with incompatible unprocessed messages in the queue during deployments. We've used Avro in a number of projects and would recommend using it over just sending unstructured messages.

已发布 : Mar 29, 2017
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