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Last updated : Nov 30, 2017
不在本期内容中
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
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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