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=50GB --machine-type=n1-standard-2 --node-count=3 --python-version=3 --image-version=composer-1.17.6-airflow-1.10.15 \
    --network=default --subnetwork=default

gcloud composer environments update $ENVIRONMENT_NAME --location=us-central1 --update-pypi-package=ethereum-etl==1.7.2

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

More Information

You can follow the instructions here for Polygon DAGs https://github.com/blockchain-etl/polygon-etl. The architecture there is very similar to Ethereum so in most case substituting polygon for ethereum will work. Contributions to this README file for porting documentation from Polygon to Ethereum are welcome.