Pay-as-you-go: the billing mode of all nodes in a cluster is pay-as-you-go. For more information on node types, please see Node Type Description.
When you purchase an EMR cluster, the unit price of the cluster will be displayed by hour. During bill settlement, the price will be calculated based on the number of seconds of actual usage, and the fees will be rounded to 2 decimal places. The billing starts at the time point when the cluster is created and ends at the time point when termination of the cluster is completed.
When you purchase a pay-as-you-go cluster, the amount of 2 hours' usage fees for the current configuration will be frozen in advance. Bills will be settled on the hour (Beijing time), and fees will be deducted based on the actual usage time of the cluster in the previous hour.
When the configuration of a pay-as-you-go node is adjusted, the amount frozen during purchase will be unfrozen, and a new amount of 2 hour's usage fees will be frozen at the latest unit price. When you terminate a pay-as-you-go cluster, the system will unfreeze the frozen amount.
EMR provides elastic computing cluster capabilities, so that you can select and combine multiple EMR specifications in a customized manner. EMR fees will be charged for all nodes in each cluster.
The prices of nodes in Beijing, Shanghai, and Guangzhou regions are as listed below:
- The prices on our official website are subject to change. Please check periodically for the latest prices.
- For the prices of disks, please see CBS Price Overview.
- The following prices are for configuration fees of CPU and memory, excluding fees of images, system cloud disks, data cloud disks, and bandwidth.
- Some models may be sold out in the actual situation. For more information, please see the model list on the purchase page.
Model | CPU | Memory (GB) | Beijing, Shanghai, and Guangzhou |
---|---|---|---|
Standard S2 | 2 | 4 | 0.12 |
Standard S2 | 4 | 8 | 0.23 |
Standard S2 | 4 | 16 | 0.34 |
Standard S2 | 8 | 16 | 0.45 |
Standard S2 | 8 | 32 | 0.67 |
Standard S2 | 12 | 24 | 0.67 |
Standard S2 | 16 | 32 | 0.89 |
Standard S2 | 16 | 64 | 1.33 |
Standard S2 | 24 | 48 | 1.33 |
Standard S2 | 24 | 96 | 1.99 |
Standard S2 | 32 | 64 | 1.77 |
Standard S2 | 32 | 128 | 2.65 |
Standard S2 | 48 | 125 | 3.05 |
High-IO I2 | 8 | 16 | 0.45 |
High-IO I2 | 8 | 32 | 0.67 |
High-IO I2 | 12 | 24 | 0.67 |
High-IO I2 | 16 | 32 | 0.89 |
High-IO I2 | 16 | 64 | 1.33 |
High-IO I2 | 24 | 96 | 1.99 |
High-IO I2 | 32 | 64 | 1.77 |
High-IO I2 | 32 | 128 | 2.65 |
MEM Optimized M2 | 2 | 16 | 0.23 |
MEM Optimized M2 | 8 | 64 | 0.91 |
MEM Optimized M2 | 12 | 96 | 1.36 |
MEM Optimized M2 | 16 | 128 | 1.81 |
MEM Optimized M2 | 24 | 192 | 2.71 |
MEM Optimized M2 | 32 | 256 | 3.61 |
Computing C2 | 4 | 8 | 0.33 |
Computing C2 | 4 | 16 | 0.5 |
Computing C2 | 16 | 32 | 1.31 |
Computing C2 | 16 | 60 | 1.89 |
Computing C2 | 32 | 120 | 3.78 |
Big Data D1 | 8 | 32 | 0.72 |
Big Data D1 | 16 | 64 | 1.44 |
Big Data D1 | 24 | 96 | 2.16 |
Big Data D1 | 32 | 128 | 2.88 |
Big Data D1 | 56 | 224 | 5.03 |
Big Data D2 | 8 | 32 | 0.68 |
Big Data D2 | 16 | 64 | 1.36 |
Big Data D2 | 24 | 96 | 2.04 |
Big Data D2 | 32 | 128 | 2.72 |
Big Data D2 | 64 | 256 | 5.44 |
Big Data D2 | 76 | 320 | 6.68 |
MEM Optimized M4 | 2 | 4 | 0.11 |
MEM Optimized M4 | 4 | 32 | 0.46 |
MEM Optimized M4 | 8 | 64 | 0.91 |
MEM Optimized M4 | 12 | 96 | 1.36 |
MEM Optimized M4 | 12 | 144 | 1.85 |
MEM Optimized M4 | 16 | 128 | 1.81 |
MEM Optimized M4 | 16 | 192 | 2.47 |
MEM Optimized M4 | 32 | 256 | 3.61 |
MEM Optimized M4 | 32 | 384 | 4.94 |
MEM Optimized M4 | 64 | 512 | 7.22 |
MEM Optimized M4 | 72 | 648 | 8.86 |
Standard S3 | 2 | 4 | 0.12 |
Standard S3 | 2 | 8 | 0.17 |
Standard S3 | 4 | 8 | 0.23 |
Standard S3 | 4 | 16 | 0.34 |
Standard S3 | 8 | 16 | 0.45 |
Standard S3 | 8 | 32 | 0.67 |
Standard S3 | 16 | 32 | 0.89 |
Standard S3 | 16 | 64 | 1.33 |
Standard S3 | 24 | 48 | 1.33 |
Standard S3 | 24 | 96 | 1.99 |
Standard S3 | 32 | 64 | 1.77 |
Standard S3 | 32 | 128 | 2.65 |
Standard S3 | 48 | 96 | 2.65 |
Standard S3 | 48 | 192 | 3.98 |
Standard S3 | 64 | 128 | 3.54 |
Standard S3 | 64 | 256 | 5.3 |
High-IO I3 | 8 | 32 | 0.68 |
High-IO I3 | 16 | 64 | 1.35 |
High-IO I3 | 24 | 96 | 2.02 |
High-IO I3 | 32 | 128 | 2.69 |
High-IO I3 | 48 | 192 | 4.03 |
High-IO I3 | 64 | 256 | 5.38 |
High-IO I3 | 80 | 320 | 6.72 |
Standard S4 | 1 | 4 | 0.09 |
Standard S4 | 2 | 4 | 0.12 |
Standard S4 | 2 | 8 | 0.17 |
Standard S4 | 4 | 8 | 0.23 |
Standard S4 | 4 | 16 | 0.34 |
Standard S4 | 8 | 16 | 0.46 |
Standard S4 | 8 | 32 | 0.68 |
Standard S4 | 16 | 32 | 0.91 |
Standard S4 | 16 | 64 | 1.35 |
Standard S4 | 24 | 48 | 1.36 |
Standard S4 | 24 | 96 | 2.02 |
Standard S4 | 32 | 64 | 1.81 |
Standard S4 | 32 | 128 | 2.69 |
Standard S4 | 48 | 96 | 2.71 |
Standard S4 | 48 | 192 | 4.03 |
Standard S4 | 64 | 128 | 3.61 |
Standard S4 | 64 | 256 | 5.38 |
Standard S4 | 72 | 288 | 6.05 |
Big Data DS2 | 8 | 32 | 0.68 |
Big Data DS2 | 16 | 64 | 1.36 |
Big Data DS2 | 24 | 96 | 2.04 |
Big Data DS2 | 32 | 128 | 2.72 |
Standard Network Optimized SN3ne | 2 | 4 | 0.12 |
Standard Network Optimized SN3ne | 4 | 8 | 0.23 |
Standard Network Optimized SN3ne | 4 | 16 | 0.34 |
Standard Network Optimized SN3ne | 8 | 16 | 0.46 |
Standard Network Optimized SN3ne | 8 | 32 | 0.68 |
Standard Network Optimized SN3ne | 12 | 24 | 0.68 |
Standard Network Optimized SN3ne | 16 | 32 | 0.91 |
Standard Network Optimized SN3ne | 16 | 64 | 1.35 |
Standard Network Optimized SN3ne | 24 | 48 | 1.36 |
Standard Network Optimized SN3ne | 24 | 96 | 2.02 |
Standard Network Optimized SN3ne | 32 | 64 | 1.81 |
Standard Network Optimized SN3ne | 32 | 128 | 2.69 |
Standard Network Optimized SN3ne | 48 | 96 | 2.71 |
Standard Network Optimized SN3ne | 64 | 128 | 3.61 |
Standard Network Optimized SN3ne | 64 | 192 | 4.49 |
Standard Network Optimized SN3ne | 64 | 256 | 5.38 |
Standard Network Optimized SN3ne | 72 | 288 | 6.05 |
Standard Network Optimized SN3ne | 76 | 192 | 4.84 |
Standard Network Optimized SN3ne | 76 | 256 | 5.72 |
MEM Optimized M5 | 2 | 16 | 0.23 |
MEM Optimized M5 | 4 | 32 | 0.46 |
MEM Optimized M5 | 8 | 64 | 0.91 |
MEM Optimized M5 | 12 | 96 | 1.36 |
MEM Optimized M5 | 32 | 256 | 3.61 |
Standard S5 | 2 | 4 | 0.07 |
Standard S5 | 2 | 8 | 0.11 |
Standard S5 | 4 | 8 | 0.14 |
Standard S5 | 4 | 16 | 0.21 |
Standard S5 | 8 | 16 | 0.28 |
Standard S5 | 8 | 32 | 0.41 |
Standard S5 | 16 | 32 | 0.55 |
Standard S5 | 16 | 64 | 0.82 |
Standard S5 | 24 | 48 | 0.82 |
Standard S5 | 24 | 64 | 0.95 |
Standard S5 | 24 | 96 | 1.23 |
Standard S5 | 32 | 64 | 1.09 |
Standard S5 | 32 | 128 | 1.63 |
Standard S5 | 48 | 96 | 1.63 |
Standard S5 | 48 | 192 | 2.45 |
Standard S5 | 64 | 192 | 2.72 |
Standard S5 | 64 | 256 | 3.26 |
Standard S5 | 76 | 256 | 3.46 |
High-IO IT3 | 16 | 64 | 1.44 |
High-IO IT3 | 32 | 128 | 2.88 |
High-IO IT3 | 64 | 256 | 5.75 |
High-IO IT3 | 76 | 160 | 4.67 |
Computing Network Enhanced CN3 | 4 | 8 | 0.28 |
Computing Network Enhanced CN3 | 4 | 16 | 0.42 |
Computing Network Enhanced CN3 | 8 | 16 | 0.56 |
Computing Network Enhanced CN3 | 8 | 32 | 0.83 |
Computing Network Enhanced CN3 | 16 | 32 | 1.11 |
Computing Network Enhanced CN3 | 16 | 64 | 1.66 |
Computing Network Enhanced CN3 | 32 | 64 | 2.21 |
Computing Network Enhanced CN3 | 32 | 128 | 3.32 |
Standard SA2 | 2 | 4 | 0.14 |
Standard SA2 | 4 | 4 | 0.07 |
Standard SA2 | 4 | 8 | 0.09 |
Standard SA2 | 8 | 8 | 0.14 |
Standard SA2 | 8 | 16 | 0.18 |
Standard SA2 | 16 | 32 | 0.36 |
Standard SA2 | 16 | 64 | 0.53 |
Standard SA2 | 32 | 64 | 0.71 |
Standard SA2 | 64 | 128 | 1.41 |
Standard SA2 | 64 | 192 | 1.77 |
Standard SA2 | 80 | 160 | 1.77 |
Standard SA2 | 128 | 256 | 2.82 |
Standard SA2 | 160 | 320 | 3.53 |
Computing C3 | 4 | 8 | 0.35 |
Computing C3 | 4 | 16 | 0.52 |
Computing C3 | 8 | 16 | 0.69 |
Computing C3 | 8 | 32 | 1.04 |
Computing C3 | 16 | 32 | 1.38 |
Computing C3 | 16 | 64 | 2.08 |
Computing C3 | 32 | 64 | 2.76 |
Computing C3 | 32 | 128 | 4.16 |
Other billable items that may incur fees when you use an EMR cluster include network traffic, metadata storage, and COS.
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