Ethereum ETL Airflow

Read this article: https://cloud.google.com/blog/products/data-analytics/ethereum-bigquery-how-we-built-dataset

Setting up Airflow DAGs using Google Cloud Composer

Create BigQuery Datasets

• Sign in to BigQuery https://bigquery.cloud.google.com/
• Create new datasets called crypto_ethereum, crypto_ethereum_raw, crypto_ethereum_temp

Create Google Cloud Storage bucket

• Create a new Google Storage bucket to store exported files https://console.cloud.google.com/storage/browser

Create Google Cloud Composer environment

Create a new Cloud Composer environment:

export ENVIRONMENT_NAME=ethereum-etl-0
gcloud composer environments create $ENVIRONMENT_NAME --location=us-central1 --zone=us-central1-a \
    --disk-size=100GB --machine-type=n1-standard-4 --node-count=3 --python-version=3 --image-version=composer-1.8.3-airflow-1.10.3 \
    --network=default --subnetwork=default

gcloud composer environments update $ENVIRONMENT_NAME --location=us-central1 --update-pypi-package=ethereum-etl==1.4.1

Create variables in Airflow (Admin > Variables in the UI):

Check other variables in dags/ethereumetl_airflow/variables.py.

Upload DAGs

> ./upload_dags.sh <airflow_bucket>

Running Tests

pip install -r requirements.txt
export PYTHONPATH='dags'
pytest -vv -s

Creating Table Definition Files for Parsing Events and Function Calls

Read this article: https://medium.com/@medvedev1088/query-ens-and-0x-events-with-sql-in-google-bigquery-4d197206e644