apache-airflow-providers-apache-pig
Provider package apache-airflow-providers-apache-pig for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Pig scripts in production and use Airflow for orchestration. The package is actively maintained, has no known vulnerabilities, installs cleanly, and is permissively licensed. Install it only if you have Pig workloads to integrate; it adds no value for Airflow users who do not use Pig.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Airflow installation (>=2.11.0) and Python 3.10 or later.
- Pig itself must be available in your environment or cluster.
- Low install friction with a pure-Python wheel.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache License 2.0 (permissive). Safe for commercial and private use with minimal restrictions; you must retain license notices and can modify and distribute freely.
last release 2026-06-07 (68 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 195,318 downloads/mo, #9,818 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-apache-pig
from airflow.providers.apache.pig.operators.pig import PigOperator
from airflow import DAG
with DAG('pig_example') as dag:
pig_task = PigOperator(
task_id='run_pig_script',
pig='script.pig'
)- Whether Pig must be pre-installed on the target system or if the provider handles Pig runtime setup
- Supported Pig versions and any compatibility constraints with specific Hadoop distributions
What it is and what it does
This is an Apache Airflow provider package that adds Pig integration to Airflow's orchestration framework. It supplies operators and hooks that allow you to define and run Apache Pig scripts as tasks within Airflow DAGs, enabling Pig-based data processing to be scheduled, monitored, and coordinated alongside other Airflow tasks.
The package is part of the official Apache Airflow ecosystem and is actively maintained. It depends on apache-airflow (>=2.11.0) and apache-airflow-providers-common-compat (>=1.10.1), and supports Python 3.10 through 3.14. Installation is straightforward via pip, with no compiled dependencies in the package itself, though your Airflow environment and cluster must have Pig available to execute scripts.
Use it for
- Schedule and monitor Apache Pig scripts as part of larger Airflow data pipelines without custom orchestration code.
- Integrate Pig-based ETL jobs with other Airflow operators (SQL, Spark, Python) in a single DAG.
- Manage dependencies and retry logic for Pig scripts using Airflow's native task scheduling and error handling.
- Orchestrate Pig jobs on Hadoop clusters from a centralized Airflow control plane.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Pig scripts in production and use Airflow for orchestration.
The package is actively maintained, has no known vulnerabilities, installs cleanly, and is permissively licensed. Install it only if you have Pig workloads to integrate; it adds no value for Airflow users who do not use Pig.
Install
apache-airflow-providers-apache-pig on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained as part of the Apache Airflow ecosystem, with recent releases and no known vulnerabilities. Requires apache-airflow >=2.11.0 and apache-airflow-providers-common-compat >=1.10.1.
Requires an existing Airflow installation (>=2.11.0) and Python 3.10 or later. Pig itself must be available in your environment or cluster.
License in practice
Licensed under Apache License 2.0 (permissive). Safe for commercial and private use with minimal restrictions; you must retain license notices and can modify and distribute freely.
Quickstart
pip install apache-airflow-providers-apache-pig
from airflow.providers.apache.pig.operators.pig import PigOperator
from airflow import DAG
with DAG('pig_example') as dag:
pig_task = PigOperator(
task_id='run_pig_script',
pig='script.pig'
)Verify before relying
- Whether Pig must be pre-installed on the target system or if the provider handles Pig runtime setup
- Supported Pig versions and any compatibility constraints with specific Hadoop distributions
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesapache-airflowapache-airflow-providers-common-compat |
| Maintenance | Actively maintained 68 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 195,318 / month, #9,818 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_apache_pig-4.8.5-py3-none-any.whl
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See also apache-airflow-providers-apache-pinot · apache-airflow-providers-github · apache-airflow-providers-zendesk · apache-airflow-providers-apache-flink · apache-airflow-providers-standard · apache-airflow-providers-apache-hdfs · apache-airflow-providers-neo4j · apache-airflow-providers-anomalo · apache-airflow-providers-cloudant · apache-airflow-providers-http