RuntimeConfig

Runtime configuration for a workload.

JSON representation 
{
  "version": string,
  "containerImage": string,
  "properties": {
    string: string,
    ...
  },
  "repositoryConfig": {
    object (RepositoryConfig)
  },
  "autotuningConfig": {
    object (AutotuningConfig)
  },
  "cohort": string
}
Fields
version

string

Optional. Version of the batch runtime.
containerImage

string

Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties

map (key: string, value: string)

Optional. A mapping of property names to values, which are used to configure workload execution.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
repositoryConfig

object (RepositoryConfig)

Optional. Dependency repository configuration.
autotuningConfig

object (AutotuningConfig)

Optional. Autotuning configuration of the workload.
cohort

string

Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.

RepositoryConfig

Configuration for dependency repositories

JSON representation 
{
  "pypiRepositoryConfig": {
    object (PyPiRepositoryConfig)
  }
}
Fields
pypiRepositoryConfig

object (PyPiRepositoryConfig)

Optional. Configuration for PyPi repository.

PyPiRepositoryConfig

Configuration for PyPi repository

JSON representation 
{
  "pypiRepository": string
}
Fields
pypiRepository

string

Optional. PyPi repository address

AutotuningConfig

Autotuning configuration of the workload.

JSON representation 
{
  "scenarios": [
    enum (Scenario)
  ]
}
Fields
scenarios[]

enum (Scenario)

Optional. Scenarios for which tunings are applied.

Scenario

Scenario represents a specific goal that autotuning will attempt to achieve by modifying workloads.

Enums
SCENARIO_UNSPECIFIED Default value.
SCALING Scaling recommendations such as initialExecutors.
BROADCAST_HASH_JOIN Adding hints for potential relation broadcasts.
MEMORY Memory management for workloads.