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Dataproc MCP Server

by warrenzhu25

create_batch_job

Submit and manage batch jobs on Google Cloud Dataproc. Define job types (Spark, PySpark, Spark SQL), include main files, JARs, arguments, and configure properties for efficient job execution.

Instructions

Create a Dataproc batch job.

Args: project_id: Google Cloud project ID region: Dataproc region batch_id: Unique identifier for the batch job job_type: Type of batch job (spark, pyspark, spark_sql) main_file: Main file/class for the job args: Job arguments jar_files: JAR files to include properties: Job properties service_account: Service account email network_uri: Network URI subnetwork_uri: Subnetwork URI

Input Schema

NameRequiredDescriptionDefault
argsNo
batch_idYes
jar_filesNo
job_typeYes
main_fileYes
network_uriNo
project_idYes
propertiesNo
regionYes
service_accountNo
subnetwork_uriNo

Input Schema (JSON Schema)

{ "properties": { "args": { "default": null, "items": { "type": "string" }, "title": "Args", "type": "array" }, "batch_id": { "title": "Batch Id", "type": "string" }, "jar_files": { "default": null, "items": { "type": "string" }, "title": "Jar Files", "type": "array" }, "job_type": { "title": "Job Type", "type": "string" }, "main_file": { "title": "Main File", "type": "string" }, "network_uri": { "default": null, "title": "Network Uri", "type": "string" }, "project_id": { "title": "Project Id", "type": "string" }, "properties": { "additionalProperties": { "type": "string" }, "default": null, "title": "Properties", "type": "object" }, "region": { "title": "Region", "type": "string" }, "service_account": { "default": null, "title": "Service Account", "type": "string" }, "subnetwork_uri": { "default": null, "title": "Subnetwork Uri", "type": "string" } }, "required": [ "project_id", "region", "batch_id", "job_type", "main_file" ], "title": "create_batch_jobArguments", "type": "object" }

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