PySparkJob

A Cloud Dataproc job for running Apache PySpark applications on YARN.

JSON representation
{
  "mainPythonFileUri": string,
  "args": [
    string
  ],
  "pythonFileUris": [
    string
  ],
  "jarFileUris": [
    string
  ],
  "fileUris": [
    string
  ],
  "archiveUris": [
    string
  ],
  "properties": {
    string: string,
    ...
  },
  "loggingConfig": {
    object(LoggingConfig)
  }
}
Fields
mainPythonFileUri

string

Required. The HCFS URI of the main Python file to use as the driver. Must be a .py file.

args[]

string

Optional. The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.

pythonFileUris[]

string

Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

jarFileUris[]

string

Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.

fileUris[]

string

Optional. HCFS URIs of files to be copied to the working directory of Python drivers and distributed tasks. Useful for naively parallel tasks.

archiveUris[]

string

Optional. HCFS URIs of archives to be extracted in the working directory of .jar, .tar, .tar.gz, .tgz, and .zip.

properties

map (key: string, value: string)

Optional. A mapping of property names to values, used to configure PySpark. Properties that conflict with values set by the Cloud Dataproc API may be overwritten. Can include properties set in /etc/spark/conf/spark-defaults.conf and classes in user code.

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

loggingConfig

object(LoggingConfig)

Optional. The runtime log config for job execution.

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