1. Installing Airflow via pip 🛠️ Boilerplate Code: pip install apache-airflow Use Case: Install Apache Airflow to automate workflows and tasks. Goal: Set up Airflow for task automation on your local environment. 🎯 Sample Code: pip install apache-a...
Introduction to Data Pipeline 데이터 파이프라인은 원시 데이터 (Raw Data) 를 수집하여 유용한 정보로 변환하는 일련의 프로세스를 말합니다. 데이터의 수집, 저장, 처리, 분석, 그리고 시각화까지의 전 과정을 포함하며, Big Data 환경에서는 대용량 데이터의 효율적인 처리를 위해 필수적인 요소입니다. 데이터 파이프라인의 주요 구성 요소 데이터 수집 (Data Ingestion) 데이터 저장 (Data ...
1. Introduction to Airflow 2. Key Concepts and Terminology 3. Installing and Setting Up Airflow 4. Understanding Directed Acyclic Graphs (DAGs) 5. Creating Your First DAG 6. Operators, Sensors, and Hooks 7. Managing Dependencies 8. Scheduling and Tri...
In the rapidly evolving landscape of data engineering, orchestrating and automating complex workflows has become a fundamental necessity. Businesses are increasingly dependent on data-driven insights, requiring robust systems to manage the seamless f...
Apache Airflow is an open-source platform designed to manage workflows, specifically data pipelines. It was created by Airbnb to handle their increasingly complex workflows and allows users to: Define workflows using Python code. This makes them eas...
Overview: In the era of big data, managing and processing large volumes of data efficiently is a critical challenge for businesses. Data pipelines play a crucial role in this process, allowing organizations to ingest, process, and analyze data from v...
Data pipelines constitute a crucial element in any data project, enabling us to monitor the flow of data from its source to the desired destination. In this context, Apache Airflow emerges as a powerful platform for managing and orchestrating data pi...
In this series, we are going to look at how to dockerize and deploy an Apache airflow pipeline. For this first article, we will learn how to dockerize Apache Airflow. You have your pipeline set up and running locally, now it is time to dockerize the ...
BigQuery has a useful feature which allows the user to create external table with data on Google Sheets. It is very convenient because BigQuery users can query the data from Google Sheets directly. However, as a data engineer, you may need to build p...
I hope you've reached this point, and now we'll begin creating our first microservice application: a books HTTP REST API with a single POST endpoint for adding a book. However, before we proceed, we must establish a migration setup for this service t...
