pulumi-google-native-kotlin/com.pulumi.googlenative.dataproc.v1.kotlin.inputs/SparkRJobArgs

SparkRJobArgs

data class SparkRJobArgs(val archiveUris: Output<List<String>>? = null, val args: Output<List<String>>? = null, val fileUris: Output<List<String>>? = null, val loggingConfig: Output<LoggingConfigArgs>? = null, val mainRFileUri: Output<String>, val properties: Output<Map<String, String>>? = null) : ConvertibleToJava<SparkRJobArgs>

A Dataproc job for running Apache SparkR (https://spark.apache.org/docs/latest/sparkr.html) applications on YARN.

Constructors

SparkRJobArgs

fun SparkRJobArgs(archiveUris: Output<List<String>>? = null, args: Output<List<String>>? = null, fileUris: Output<List<String>>? = null, loggingConfig: Output<LoggingConfigArgs>? = null, mainRFileUri: Output<String>, properties: Output<Map<String, String>>? = null)

Functions

toJava

open override fun toJava(): SparkRJobArgs

Properties

archiveUris

val archiveUris: Output<List<String>>? = null

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.

args

val args: Output<List<String>>? = null

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.

fileUris

val fileUris: Output<List<String>>? = null

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

loggingConfig

val loggingConfig: Output<LoggingConfigArgs>? = null

Optional. The runtime log config for job execution.

mainRFileUri

val mainRFileUri: Output<String>

The HCFS URI of the main R file to use as the driver. Must be a .R file.

properties

val properties: Output<Map<String, String>>? = null

Optional. A mapping of property names to values, used to configure SparkR. 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.