How can multiple compute resources be used on the same pipeline in AWS Data Pipeline?
A.
You can use multiple compute resources on the same pipeline by defining multiple cluster objects in your definition file and associating the cluster to use for each activity via its runs On field.
B.
You can use multiple compute resources on the same pipeline by defining multiple cluster definition files
C.
You can use multiple compute resources on the same pipeline by defining multiple clusters for your activity.
D.
You cannot use multiple compute resources on the same pipeline.
Suggested Answer:A🗳️
Multiple compute resources can be used on the same pipeline in AWS Data Pipeline by defining multiple cluster objects in your definition file and associating the cluster to use for each activity via its runs On field, which allows pipelines to combine AWS and on premise resources, or to use a mix of instance types for their activities. Reference: https://aws.amazon.com/datapipeline/faqs/
A. You can use multiple compute resources on the same pipeline by defining multiple cluster objects in your definition file and associating the cluster to use for each activity via its runs On field.
A. You can use multiple compute resources on the same pipeline by defining multiple cluster objects in your definition file and associating the cluster to use for each activity via its runs On field.
A.
https://aws.amazon.com/datapipeline/faqs/#:~:text=Q%3A%20Can%20multiple%20compute%20resources,activity%20via%20its%20runsOn%20field.
Q: Can multiple compute resources be used on the same pipeline?
Yes, simply define multiple cluster objects in your definition file and associate the cluster to use for each activity via its runsOn field. This allows pipelines to combine AWS and on-premise resources, or to use a mix of instance types for their activities – for example, you may want to use a t1.micro to execute a quick script cheaply, but later on the pipeline may have an Amazon EMR job that requires the power of a cluster of larger instances.
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