Dataproc pricing

Dataproc pricing is based on the size of Dataproc clusters and the duration of time that they run. The size of a cluster is based on the aggregate number of virtual CPUs (vCPUs) across the entire cluster, including the master and worker nodes. The duration of a cluster is the length of time between cluster creation and cluster deletion.

The Dataproc pricing formula is: $0.010 * # of vCPUs * hourly duration.

Although the pricing formula is expressed as an hourly rate, Dataproc is billed by the second, and all Dataproc clusters are billed in one-second clock-time increments, subject to a 1-minute minimum billing. Usage is stated in fractional hours (for example, 30 minutes is expressed as 0.5 hours) in order to apply hourly pricing to second-by-second use.

Dataproc pricing is in addition to the Compute Engine per-instance price for each virtual machine (see Use of other Google Cloud resources).

Pricing example

As an example, consider a cluster (with master and worker nodes) that has the following configuration:

Item Machine Type Virtual CPUs Attached persistent disk Number in cluster
Master Node n1-standard-4 4 500 GB 1
Worker Nodes n1-standard-4 4 500 GB 5

This Dataproc cluster has 24 virtual CPUs, 4 for the master and 20 spread across the workers. For Dataproc billing purposes, the pricing for this cluster would be based on those 24 virtual CPUs and the length of time the cluster ran (assuming no nodes are scaled down or preempted). If the cluster runs for 2 hours, the Dataproc pricing would use the following formula:

Dataproc charge = # of vCPUs * hours * Dataproc price = 24 * 2 * $0.01 = $0.48

In this example, the cluster would also incur charges for Compute Engine and Standard Persistent Disk Provisioned Space in addition to the Dataproc charge (see Use of other Google Cloud resources). The billing calculator can be used to determine separate Google Cloud resource costs.

Use of other Google Cloud resources

As a managed and integrated solution, Dataproc is built on top of other Google Cloud technologies. Dataproc clusters consume the following resources, each billed at its own pricing:

Dataproc clusters can optionally utilize the following resources, each billed at its own pricing, including but not limited to:

What's next

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