{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/2"}],"enrichment":{"capability":"Integrates Apache Spark with Apache Airflow, enabling you to orchestrate and monitor Spark jobs as part of Airflow workflows.","skillfed_tags":["airflow-provider","spark-integration","workflow-orchestration"],"use_cases":["Schedule and monitor Spark batch jobs as part of a multi-step Airflow data pipeline.","Orchestrate Spark SQL transformations triggered by upstream Airflow tasks.","Submit Spark jobs to a Kubernetes cluster via Airflow using the cncf.kubernetes extra.","Track data lineage of Spark jobs within Airflow using the openlineage optional dependency.","Coordinate Spark workloads with non-Spark tasks in a unified Airflow workflow."],"what_it_does":"This is an Apache Airflow provider package that adds Spark integration to Airflow's orchestration framework. It allows you to define, schedule, and monitor Apache Spark jobs as tasks within Airflow DAGs, treating Spark workloads as first-class Airflow operators. The package depends on apache-airflow (>=2.11.0), pyspark-client (>=4.0.0), and several supporting libraries (grpcio-status, requests, tenacity) to handle communication, retries, and status reporting.\n\nThe provider is actively maintained by the Apache Airflow project, with production-stable status and support for Python 3.10 through 3.14. It is designed for developers and system administrators who need to integrate Spark batch or streaming jobs into larger Airflow-based data pipelines. Optional dependencies allow integration with Kubernetes clusters and OpenLineage data lineage tracking when needed.","worth_installing":"Yes. This is a production-stable, actively maintained provider with low install friction and no known vulnerabilities. Install it if you run Airflow and need to orchestrate Spark jobs as part of your DAGs. Requires Airflow >=2.11.0 and Python >=3.10; verify your environment meets these minimums before installing."},"id":"apache-airflow-providers-apache-spark","links":{"html":"https://skillfed.io/packages/apache-airflow-providers-apache-spark","md":"https://skillfed.io/packages/apache-airflow-providers-apache-spark.md","pypi":"https://pypi.org/project/apache-airflow-providers-apache-spark/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-08","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"apache-airflow-providers-apache-spark","python_support":"supports_current","summary":"Provider package apache-airflow-providers-apache-spark for Apache Airflow"},"popularity":{"monthly_downloads":1187469,"position":4246,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"6.3.1"}