Submit a Python project to Dataproc job

Question

I have a python project, whose folder has the structure

main_directory - lib - lib.py
               - run - script.py

script.py

Answer 1

To zip the dependencies -

cd base-path-to-python-modules
zip -qr deps.zip ./* -x script.py

Copy deps.zip to hdfs/gs. Use uri when submitting the job as shown below.

Submit a python project (pyspark) using Dataproc' Python connector

from google.cloud import dataproc_v1
from google.cloud.dataproc_v1.gapic.transports import (
    job_controller_grpc_transport)

region = <cluster region>
cluster_name = <your cluster name>
project_id = <gcp-project-id>

job_transport = (
    job_controller_grpc_transport.JobControllerGrpcTransport(
        address='{}-dataproc.googleapis.com:443'.format(region)))
dataproc_job_client = dataproc_v1.JobControllerClient(job_transport)

job_file = <gs://bucket/path/to/main.py or hdfs://file/path/to/main/job.py>

# command line for the main job file
args = ['args1', 'arg2']

# required only if main python job file has imports from other modules
# can be one of .py, .zip, or .egg. 
addtional_python_files = ['hdfs://path/to/deps.zip', 'gs://path/to/moredeps.zip']

job_details = {
    'placement': {
        'cluster_name': cluster_name
    },
    'pyspark_job': {
        'main_python_file_uri': job_file,
        'args': args,
        'python_file_uris': addtional_python_files
    }
}

res = dataproc_job_client.submit_job(project_id=project_id,
                                     region=region, 
                                     job=job_details)
job_id = res.reference.job_id

print(f'Submitted dataproc job id: {job_id}')

Answer 2

If you want to preserve project structure when submitting Dataroc job then you should package your project into a .zip file and specify it in --py-files parameter when submitting a job:

gcloud dataproc jobs submit pyspark --cluster=$CLUSTER_NAME --region=$REGION \
  --py-files lib.zip \
  run/script.py

To create zip archive you need to run script:

cd main_directory/
zip -x run/script.py -r libs.zip .

Refer to this blog post for more details on how to package dependencies in zip archive for PySpark jobs.