Data Pipelines
4 articles from official documentation
Mastering Executors in Apache Airflow: What You Need to Know
Executors are the backbone of task execution in Apache Airflow, and understanding them is crucial for efficient data pipelines. With options ranging from LocalExecutor to multi-executor configurations, choosing the right executor can make or break your workflow. Dive in to learn how to configure and optimize executors for your needs.
- →Understand the role of executors in task execution and their pluggable nature.
- →Configure executors in the [core] section of the Airflow configuration file.
Mastering Data Pipelines: Best Practices for Airflow
Data pipelines are the backbone of modern data infrastructure, and mastering them is crucial for any engineer. Learn how to effectively use DAGs, custom operators, and XComs in Airflow to streamline your workflows. Avoid common pitfalls that can derail your data processing tasks.
- →Define `connection_id` and `gcp_conn_id` in `default_args` to avoid mistakes.
- →Avoid storing files in the local filesystem; tasks may run on different servers.
Mastering Airflow Tasks: Relationships, Types, and Configurations
Airflow tasks are the backbone of your data pipelines, dictating execution flow and dependencies. Understanding how to configure them effectively can make or break your workflows.
- →Understand task dependencies by using the '>>' operator to define execution order.
- →Leverage XComs to pass information between tasks effectively.
Mastering Dags in Apache Airflow: The Backbone of Your Data Pipeline
Dags are the heart of Apache Airflow, encapsulating everything needed to execute complex workflows. Understanding how to structure and manage Dags effectively can make or break your data pipeline's reliability and performance.
- →Understand that a Dag encapsulates everything needed to execute a workflow.
- →Utilize task dependencies to control the execution order of tasks effectively.