安排 Google Batch 作业在 GCP 上触发（长时间运行 Python 脚本）

Question

By "Google Batch" I'm referring to the new service Google launched about a month or so ago.

https://cloud.google.com/batch

I have a Python script which takes a few minutes to execute at the moment. However with the data it will soon be processing in the next few months this execution time will go from minutes to hours . This is why I am not using Cloud Function or Cloud Run to run this script, both of these have a max 60 minute execution time.

Google Batch came about recently and I wanted to explore this as a possible method to achieve what I'm looking for without just using Compute Engine.

However documentation is sparse across the inte.net and I can't find a method to "trigger" an already created Batch job by using Cloud Scheduler. I've already successfully manually created a batch job which runs my docker image. Now I need something to trigger this batch job 1x a day, thats it . It would be wonderful if Cloud Scheduler could serve this purpose.

I've seen 1 article describing using GCP Workflow to create aa new Batch job on a cron determined by Cloud Scheduler. Issue with this is its creating a new batch job every time, not simply re-running the already existing one. To be honest I can't even re-run an already executed batch job on the GCP website itself so I don't know if its even possible.

https://www.intertec.io/resource/python-script-on-gcp-batch

Lastly, I've even explored the official Google Batch Python library and could not find anywhere in there some built in function which allows me to "call" a previously created batch job and just re-run it.

https://github.com/googleapis/python-batch

Answer 1

There is a misunderstanding. When you use Cloud Run jobs, you create a configuration and you execute a configuration.

BUT, with Batch job, you execute a configuration. That's all, no configuration to create in advance.

Have a look to the APIs : Create, Get, Delete. No more.

Therefore, you have to set in your Cloud Scheduler, the whole Batch configuration to create a new job. Take care to NOT set the jobID in the query parameter.

Answer 2

I wrote this for you this morning as a guide.

It uses Google's example in combination with Cloud Scheduler:

# Used to correctly (!?) form Batch Job
import google.cloud.batch_v1.types

import google.cloud.scheduler_v1
import google.cloud.scheduler_v1.types

import os


project = os.getenv("PROJECT")
number = os.getenv("NUMBER")
location = os.getenv("LOCATION")
job = os.getenv("JOB")

# Batch Job
# Create Batch Job using batch_v1.types
# Alternatively, create this from scratch
batch_job = google.cloud.batch_v1.types.Job(
    priority=0,
    task_groups=[
        google.cloud.batch_v1.types.TaskGroup(
            task_spec=google.cloud.batch_v1.types.TaskSpec(
                runnables=[
                    google.cloud.batch_v1.types.Runnable(
                        container=google.cloud.batch_v1.types.Runnable.Container(
                            image_uri="gcr.io/google-containers/busybox",
                            entrypoint="/bin/sh",
                            commands=[
                                "-c",
                                "echo \"Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.\""
                            ],
                        ),
                    ),
                ],
                compute_resource=google.cloud.batch_v1.types.ComputeResource(
                    cpu_milli=2000,
                    memory_mib=16,
                )
            ),
            task_count=1,
            parallelism=1,
        ),
    ],
    allocation_policy=google.cloud.batch_v1.types.AllocationPolicy(
        location=google.cloud.batch_v1.types.AllocationPolicy.LocationPolicy(
           allowed_locations=[
            f"regions/{location}",
           ], 
        ),
        instances=[
            google.cloud.batch_v1.types.AllocationPolicy.InstancePolicyOrTemplate(
                policy=google.cloud.batch_v1.types.AllocationPolicy.InstancePolicy(
                    machine_type="e2-standard-2",
                ),
            ),
        ],
    ),
    labels={
        "stackoverflow":"73966292",
    },
    logs_policy=google.cloud.batch_v1.types.LogsPolicy(
        destination=google.cloud.batch_v1.types.LogsPolicy.Destination.CLOUD_LOGGING,
    ),
)

# Convert the Google Batch Job into JSON
# Google uses Proto Python
# https://proto-plus-python.readthedocs.io/en/stable/messages.html?highlight=JSON#serialization
batch_json=google.cloud.batch_v1.types.Job.to_json(batch_job)
print(batch_json)

# Convert JSON to bytes as required for body by Cloud Scheduler
body=batch_json.encode("utf-8")

# Run hourly on the hour (HH:00)
schedule = "0 * * * *"

parent = f"projects/{project}/locations/{location}"
name = f"{parent}/jobs/{job}"
uri = f"https://batch.googleapis.com/v1/{parent}/jobs?job_id={job}"

service_account_email = f"{number}-compute@developer.gserviceaccount.com"

scheduler_job = google.cloud.scheduler_v1.types.Job(
    name=name,
    description="description",
    http_target=google.cloud.scheduler_v1.types.HttpTarget(
        uri=uri,
        http_method=google.cloud.scheduler_v1.types.HttpMethod(
            google.cloud.scheduler_v1.types.HttpMethod.POST,
        ),
        oauth_token=google.cloud.scheduler_v1.types.OAuthToken(
            service_account_email=service_account_email,
        ),
        body=body,
    ),
    schedule=schedule,
)

scheduler_json=google.cloud.scheduler_v1.Job.to_json(scheduler_job)
print(scheduler_job)

request = google.cloud.scheduler_v1.CreateJobRequest(
    parent=parent,
    job=scheduler_job,
)

scheduler_client = google.cloud.scheduler_v1.CloudSchedulerClient()
print(
    scheduler_client.create_job(
        request=request
    )
)

You can test using:

BILLING="..."
PROJECT="..."
LOCATION="..." # E.g. us-west1

JOB="tester"

ACCOUNT="tester"
EMAIL="${ACCOUNT}@${PROJECT}.iam.gserviceaccount.com"

# Create Project and enable Billing
gcloud projects create ${PROJECT}
gcloud beta billing projects link ${PROJECT} \
--billing-account=${BILLING}

# Enable Cloud Scheduler and Cloud Run
SERVICES=(
  "batch"
  "cloudscheduler"
  "compute"
)
for SERVICE in ${SERVICES[@]}
do
  gcloud services enable ${SERVICE}.googleapis.com \
  --project=${PROJECT}
done

# Create Service Account
gcloud iam service-accounts create ${ACCOUNT} \
--project=${PROJECT}

gcloud iam service-accounts keys create ${PWD}/${ACCOUNT}.json \
--iam-account=${EMAIL} \
--project=${PROJECT}

# IAM
# https://cloud.google.com/iam/docs/understanding-roles#cloud-scheduler-roles
ROLES=(
  "roles/batch.jobsEditor"
  "roles/cloudscheduler.admin"
)
for ROLE in ${ROLES[@]}
do
  gcloud projects add-iam-policy-binding ${PROJECT} \
  --member=serviceAccount:${EMAIL} \
  --role=${ROLE}
done

# ActAs
NUMBER=$(\
  gcloud projects describe ${PROJECT} \
  --format="value(projectNumber)")
COMPUTE_ENGINE="${NUMBER}-compute@developer.gserviceaccount.com"
gcloud iam service-accounts add-iam-policy-binding ${COMPUTE_ENGINE} \
--member=serviceAccount:${EMAIL} \
--role="roles/iam.serviceAccountUser" \
--project=${PROJECT}

Then:

python3 -m venv venv
source venv/bin/activate

# Or requirements.txt
python3 -m pip install google-cloud-batch
python3 -m pip install google-cloud-scheduler

export JOB
export LOCATION
export NUMBER
export PROJECT

export GOOGLE_APPLICATION_CREDENTIALS=${PWD}/${ACCOUNT}.json

python3 main.py