[英]what's difference between dataproc cluster on GKE vs Compute engine?
We can now create dataproc clusters using compute engine or GKE .我们现在可以使用计算引擎或GKE创建 dataproc 集群。 What are the major advantages of creating a cluster on GKE vs Compute Engine.
在 GKE 与 Compute Engine 上创建集群的主要优势是什么。 We have faced problem of
insufficient resources in zone
error multiple times while creating cluster on compute engine.在计算引擎上创建集群时,我们多次面临
insufficient resources in zone
问题。 Will it solve this issue if we use GKE for cluster and what are the cost difference between them.如果我们将 GKE 用于集群,它会解决这个问题吗?它们之间的成本差异是多少。
To solve the error message “insufficient resources in zone”, You may refer to this GCP documentation .要解决“区域资源不足”的错误消息,您可以参考此 GCP 文档。
To answer your question, what's the difference between dataproc cluster on GKE vs GCE.要回答您的问题,GKE 与 GCE 上的 dataproc 集群有什么区别。
In GKE, You can directly create a Dataproc cluster and do your deployments.在 GKE 中,您可以直接创建 Dataproc 集群并进行部署。
You may also check the advantages of GKE in documentation or check the GKE features below:您还可以在文档中查看 GKE 的优势或查看以下 GKE 功能:
While in GCE, you have to manually install Kubernetes, then create your Dataproc cluster and do your deployments.在 GCE 中,您必须手动安装 Kubernetes,然后创建 Dataproc 集群并进行部署。
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