Hybrid billing lets you provision elastic computing resources on top of your subscription, combining pay-as-you-go flexibility with subscription cost-effectiveness. This topic covers use cases, billing rules, and how to enable and use elastic computing resources.
Precautions
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Pay-as-you-go for elastic resources can be enabled only for subscription workspaces that are in the running state.
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Hybrid billing workspaces cannot be converted to subscription or pay-as-you-go workspaces.
Hybrid billing description
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Attribute |
Description |
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Scenarios |
Your business has a stable baseline of resource usage but experiences temporary usage spikes. |
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Billing rule |
Hybrid billing workspace cost = Subscription quota cost + Elastic resource usage cost
Important
The subscription quota cost is based on the subscription payment page or the final bill. For elastic computing resource costs, see your bill. For more information, see Query bills. For example, a workspace in the China (Hong Kong) region has the following configuration: pay-as-you-go quota limit of 100 CU at USD 0.074048 per CU/hour, and a subscription quota of 50 CU at USD 35.54 per CU/month. The workspace uses 100 CUs for one hour during daily peak times and stays within 50 CUs at other times. The estimated monthly fees are as follows:
The estimated total monthly cost for the workspace is |
Enable and use elastic resources
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Go to the EMR Serverless Spark workspace page.
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Log on to the E-MapReduce console.
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In the left-side navigation pane, choose EMR Serverless > Spark.
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On the Spark page, find the target subscription workspace, and in the Actions column, click .
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In the dialog box, set the Maximum Pay-as-you-go Quota (CUs) parameter, and then click OK.
Note-
After you enable hybrid billing, the Billing Method for the workspace changes from Subscription to Mixed Payment.
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After you enable hybrid billing, elastic computing resources are allocated to the pay_as_you_go resource queue by default. To change this allocation, go to the Resource Management page and click the Queues tab. For more information, see Manage resource queues.
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Submit tasks to a queue that has elastic computing resources as needed.
View elastic computing resource usage
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Go to the EMR Serverless Spark workspace page.
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Log on to the E-MapReduce console.
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In the left-side navigation pane, choose EMR Serverless > Spark.
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On the Spark page, click the name of the target workspace.
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In the left navigation pane, click Resource Management. On the Queues tab, you can view the allocation and usage of elastic computing resources.