pyspark.resource.ExecutorResourceRequest#

class pyspark.resource.ExecutorResourceRequest(resourceName, amount, discoveryScript='', vendor='')[source]#

An Executor resource request. This is used in conjunction with the ResourceProfile to programmatically specify the resources needed for an RDD that will be applied at the stage level.

This is used to specify what the resource requirements are for an Executor and how Spark can find out specific details about those resources. Not all the parameters are required for every resource type. Resources like GPUs are supported and have same limitations as using the global spark configs spark.executor.resource.gpu.*. The amount, discoveryScript, and vendor parameters for resources are all the same parameters a user would specify through the configs: spark.executor.resource.{resourceName}.{amount, discoveryScript, vendor}.

For instance, a user wants to allocate an Executor with GPU resources on YARN. The user has to specify the resource name (gpu), the amount or number of GPUs per Executor, the discovery script would be specified so that when the Executor starts up it can discovery what GPU addresses are available for it to use because YARN doesn’t tell Spark that, then vendor would not be used because its specific for Kubernetes.

See the configuration and cluster specific docs for more details.

Use pyspark.ExecutorResourceRequests class as a convenience API.

New in version 3.1.0.

Parameters

resourceNamestr: Name of the resource
amountstr: Amount requesting
discoveryScriptstr, optional: Optional script used to discover the resources. This is required on some cluster managers that don’t tell Spark the addresses of the resources allocated. The script runs on Executors startup to discover the addresses of the resources available.
vendorstr, optional: Vendor, required for some cluster managers

`amount`	Returns
`discoveryScript`	Returns
`resourceName`	Returns
`vendor`	Returns