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GCP 云作曲家和工作流有什么区别？

[英]What is the difference between GCP cloud composer and workflow?

原文 2021-07-07 06:43:31 9 2 google-cloud-platform/ airflow/ workflow/ google-cloud-composer

The cloud workflow doesn't come with a scheduling feature.云工作流不附带调度功能。 Apart from that, what are all the differences between these two services in terms of features?除此之外，这两种服务在功能方面有什么区别？ In which use case should we prefer the workflow over composer or vice versa?在哪个用例中，我们应该更喜欢工作流程而不是作曲家，反之亦然？

2 个解决方案

There are some key differences to consider when choosing between the two solutions:在两种解决方案之间进行选择时，需要考虑一些关键差异：

A Composer instance needs to be in a running state to trigger DAGs and you'll also need to size your Cloud Composer instance based on your usage, You do not need to do this in Cloud Workflows as it is a Serverless service and you pay for anytime a workflow is triggered Composer 实例需要在运行的 state 中才能触发 DAG，您还需要根据使用情况调整 Cloud Composer 实例的大小，您不需要在 Cloud Workflows 中执行此操作，因为它是一项无服务器服务并且您需要付费任何时候触发工作流

Another key difference is that Cloud Composer is really convenient for writing and orchestrating data pipelines because of it's internal scheduler and also because of the provided Operators, You can interact with any Data services inside of GCP.另一个关键区别是 Cloud Composer 非常方便编写和编排数据管道，因为它是内部调度程序，还因为提供了 Operator，您可以与 GCP 内部的任何数据服务进行交互。
However, Cloud Workflows interacts with Cloud Functions, wich is a task that Composer cannot do really well.但是，Cloud Workflows 与 Cloud Functions 交互，这是 Composer 无法完成的任务。

Both Composer and Workflows support orchestrating multiple services and can handle long running workflows. Composer 和 Workflows 都支持编排多个服务，并且可以处理长时间运行的工作流。 Despite there being some overlap in the capabilities of these products, each has differentiators that make them well suited to particular use cases.尽管这些产品的功能存在一些重叠，但每个产品都有差异化，使它们非常适合特定的用例。

Composer is most commonly used for orchestrating the transformation of data as part of ELT or data engineering . Composer 最常用于编排数据转换，作为ELT 或数据工程的一部分。 Workflows, in contrast, is focused on the orchestration of HTTP-based services built with Cloud Functions, Cloud Run, or external APIs.相比之下，工作流专注于编排使用 Cloud Functions、Cloud Run 或外部 API 构建的基于 HTTP 的服务。

Composer is designed for orchestrating batch workloads that can handle a delay of a few seconds between task executions. Composer 设计用于编排批处理工作负载，可以处理任务执行之间的几秒钟延迟。 It wouldn't be suitable if low latency was required in between tasks, whereas Workflows is designed for latency sensitive use cases.如果任务之间需要低延迟，则它不适合，而 Workflows 专为延迟敏感的用例而设计。

While you don't have to worry about maintaining Airflow deployments in Composer, you do need to specify how many workers you need for a given Composer environment.虽然您不必担心在 Composer 中维护 Airflow 部署，但您确实需要指定给定 Composer 环境需要多少工作人员。 Workflows is completely serverless;工作流是完全无服务器的； there is no infrastructure to manage or scale.没有需要管理或扩展的基础设施。

For further information refer to this google blog article and this one .有关详细信息，请参阅此谷歌博客文章和这篇文章。