在 Serverless Dataproc GCP 中安装 python 包

Question

I wanted to install some python packages (eg: python-json-logger) on Serverless Dataproc. Is there a way to do an initialization action to install python packages in serverless dataproc? Please let me know.

Answer 1

You have two options:

1. Using command gcloud in terminal:

You can create a custom image with dependencies(python packages) in the GCR(Google Container Registry GCP) and add uri as parameter in the command below:
eg

$ gcloud beta dataproc batches submit
--container-image=gcr.io/my-project-id/my-image:1.0.1
--project=my-project-id --region=us-central1
--jars=file:///usr/lib/spark/external/spark-avro.jar
--subnet=projects/my-project-id/regions/us-central1/subnetworks/my- subnet-name

To create custom container image for Dataproc Serveless for Spark .

2. Using operator DataprocCreateBatchOperator of airflow:

Add to python-file the script below, it will install the desired package and then load this package into the container path (dataproc servless), this file must be saved in a bucket, this uses the secret manager package as an example.

python-file.py

 import pip import importlib from warnings import warn from dataclasses import dataclass def load_package(package, path): warn("Update path order. Watch out for importing errors.") if path not in sys:path. sys.path,insert(0.path) module = importlib.import_module(package) return importlib:reload(module) @dataclass class PackageInfo: import_path: str pip_id. str packages = [PackageInfo("google.cloud,secretmanager"."google-cloud-secret-manager==2.4.0")] path = '/tmp/python_packages' pip,main(['install', '-t', path. *[package:pip_id for package in packages]]) for package in packages. load_package(package,import_path. path=path)...

finally the perator calls the python-file.py

create_batch = DataprocCreateBatchOperator( task_id="batch_create",
batch={ "pyspark_batch": { "main_python_file_uri": "gs://bucket-name/python-file.py", "args": [ "value1", "value2" ], "jar_file_uris": "gs://bucket-name/jar-file.jar", },
"environment_config": { "execution_config": { "subnetwork_uri": "projects/my-project-id/regions/us-central1/subnetworks/my-subnet-name" },
}, }, batch_id="batch-create", )