This is a practice on Airflow, which is building virtual env, installing Airflow and constructing data pipeline (DAGs)

Overview

airflow-test

This is a practice on Airflow, which is

First of all, build virtual env using virtualbox

This is optional but highly recommended

  • It is very important to make sure that development env is independent and has no conflict with other env setting

Next, make python virtual env on proper directory

python3 -m venv sandbox
source ~/sandbox/bin/activate

Let start to install Airflow and initial setting

Install Airflow

pip3 install apache-airflow==2.1.0 \ ## airflow version depends on when you install and constraint 
  --constraint 'git address' ## constraint is ???. It is optional. refer to https://gist.github.com/marclamberti

Airflow Inital Setting

airflow db init ## airflow metadata initializing
airflow users create -u admin -p admin -f jaeyoung -l jang -r Admin -e [email protected] ## create admin user

airflow webserver ## launch web server. after that we can access airflow web server through localhost:8080
airflow scheduler ## activate airfow scheduler to run DAGs

Construct data pipeline with Airflow

One example of data pipeline (one DAGs) - let follow below steps and make data pipeline

  • creating table -> is-api-available -> extending -> processing-use ->
  • what is it? when new user comes in, sense that and process and store user info to destination (?)
  1. create table
  • make python script user_processing.py in dags folder
  • let create table using sqlite operator in user_processing.py
from airflow.models import DAG
from airflow.providers.sqlite.operators.sqlite import SqliteOperator

from datetime import datetime

default_args = {
    'start_date': datetime(2020, 1, 1)
}

with DAG('user_processing', schedule_interval='@daily', default_args=default_args, catchup=False) as dag:
    # Define tasks/operators

    creating_talbe = SqliteOperator(
        task_id='creating_table',
        sqlite_conn_id='db_sqlite',
        sql='''
            CREATE TABLE users (
                firstname TEXT NOT NULL,
                lastname TEXT NOT NULL,
                country TEXT NOT NULL,
                username TEXT NOT NULL,
                password TEXT NOT NULL,
                email TEXT NOT NULL PRIMARY KEY
            );
            '''
    )
  • set sqlite connection on Airflow Web UI
pip install apache-airflow-providers-sqlite ## install airflow provider of sqlite. refer airflow doc. may already be installed from intial installing Airflow..
# next, make a new sqltie connection named 'db_sqlite' in Airflow
  • after that, do test airflow tasks!

airflow tasks test user_processing creating_table 2020-01-01

  • one more things to do just for check again
sqlite3 airflow.db ## connect to sqlite3 in airflow.db
sqlite>.tables; ## see the tables in airflow.dbb
sqlite>select * form users; ## test query
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