Struct google_api_proto::google::cloud::dataproc::v1::PySparkJob

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

A Dataproc job for running Apache PySpark applications on YARN.

Fields

main_python_file_uri: String

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

args: Vec<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.

python_file_uris: Vec<String>

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

jar_file_uris: Vec<String>

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

file_uris: Vec<String>

Optional. HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

archive_uris: Vec<String>

Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.

properties: BTreeMap<String, String>

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

logging_config: Option<LoggingConfig>

Optional. The runtime log config for job execution.

Trait Implementations

impl Clone for PySparkJob

fn clone(&self) -> PySparkJob

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for PySparkJob

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for PySparkJob

fn default() -> Self

Returns the “default value” for a type.

impl Message for PySparkJob

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for PySparkJob

fn eq(&self, other: &PySparkJob) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for PySparkJob