Struct google_dataproc1::PySparkJob[][src]

pub struct PySparkJob {
    pub main_python_file_uri: Option<String>,
    pub jar_file_uris: Option<Vec<String>>,
    pub logging_config: Option<LoggingConfig>,
    pub args: Option<Vec<String>>,
    pub file_uris: Option<Vec<String>>,
    pub archive_uris: Option<Vec<String>>,
    pub python_file_uris: Option<Vec<String>>,
    pub properties: Option<HashMap<String, String>>,
}

A Cloud Dataproc job for running Apache PySpark (https://spark.apache.org/docs/0.9.0/python-programming-guide.html) applications on YARN.

This type is not used in any activity, and only used as part of another schema.

Fields

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

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

Optional. The runtime log config for job execution.

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.

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

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

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

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.

Trait Implementations

impl Default for PySparkJob
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Returns the "default value" for a type. Read more

impl Clone for PySparkJob
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Returns a copy of the value. Read more

Performs copy-assignment from source. Read more

impl Debug for PySparkJob
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Formats the value using the given formatter. Read more

impl Part for PySparkJob
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Auto Trait Implementations

impl Send for PySparkJob

impl Sync for PySparkJob