Pre requisites:

1. Have a gcp project with a linked billing account

2. Open up cloud shell

3. have pip installed

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
sudo apt-get install python3 python3-setuptools
sudo python3 get-pip.py

Set variables

export project="your-gcp-project-id" #change this to your project
export region="your-gcp-region" #for example us-central1
export bq_dataset="dataflow_example"

Create 2 buckets one for the files and one for the template

gsutil mb -p $project -c regional -l $region -b on gs://$project-df-template/
gsutil mb -p $project -c regional -l $region -b on gs://$project-df-files/

Create bigquery dataset

bq mk --location=us --dataset $project:$bq_dataset

Clone the repostiory files

git clone https://github.com/thomas-vl/dataflow-gcs-cf.git

Deploy dataflow template

sudo pip3 install apache-beam[gcp]
cd ~/dataflow-gcs-cf/dataflow
python3 -m main --output $project:$bq_dataset.example --runner DataflowRunner --project $project \
 --staging_location gs://$project-df-template/staging --temp_location gs://$project-df-template/temp \
 --template_location gs://$project-df-template/templates/df-bq

validate if the template file exists:

gsutil ls gs://$project-df-template/templates/

Deploy the function (from cloud-functions folder)

gcloud services enable dataflow.googleapis.com --project $project
cd ~/dataflow-gcs-cf/cloud-functions
gcloud functions deploy start_dataflow --runtime python37 --trigger-resource $project-df-files --trigger-event google.storage.object.finalize --project $project --region $region

##upload the file

cd ~/dataflow-gcs-cf/
gsutil cp titanic.csv gs://$project-df-files