Apache Spark Job Manager · diff
git:20260518.471df3d to git:20260710.2925510
14 added, 19 removed. Audit B to B.
---
- name: "Apache Spark Job Manager"
- slug: "apache-spark-job-manager"
- description: ""
- github_stars: 43119
- verification: "listed"
+ title: "Apache Spark Job Manager"
+ description: "Apache Spark Job Manager is built around Apache Spark distributed compute engine. The underlying ecosystem is represented by apache/spark (43,027+ GitHub stars). It gives an agent a more technical and reliable way to work with the tool than a thin one-line wrapper, using stable interfaces like Spark jobs, DataFrames, SQL, executors, stages, Structured Streaming and […]"
+ verification: "security_reviewed"
source: "https://github.com/apache/spark"
author: "apache"
- category: "Data Extraction & Transformation"
- framework: "Custom Agents"
+ category:
+ - "Data Extraction & Transformation"
+ framework:
+ - "Custom Agents"
tool_ecosystem:
github_repo: "apache/spark"
github_stars: 43119
---
# Apache Spark Job Manager
-
+ Apache Spark Job Manager is built around Apache Spark distributed compute engine. The underlying ecosystem is represented by apache/spark (43,027+ GitHub stars). It gives an agent a more technical and reliable way to work with the tool than a thin one-line wrapper, using stable interfaces like Spark jobs, DataFrames, SQL, executors, stages, Structured Streaming and […]
## Prerequisites
Java, Scala, Python
## Installation
- Requirements and caveats from upstream:
- - high-level APIs in Scala, Java, Python, and R (Deprecated), and an optimized engine that
- - ## Interactive Python Shell
- - Alternatively, if you prefer Python, you can use the Python shell:
-
- Basic usage or getting-started notes:
- - To build Spark and its example programs, run:
- - And run the following command, which should also return 1,000,000,000:
- - ## Example Programs
+ Choose whichever fits your setup:
- - Source: https://github.com/apache/spark
- - Extracted from upstream docs: https://raw.githubusercontent.com/apache/spark/HEAD/README.md
+ 1. Copy this skill folder into your local skills directory.
+ 2. Clone the repo and symlink or copy the skill into your agent workspace.
+ 3. Add the repo as a git submodule if you manage shared skills centrally.
+ 4. Install it through your internal provisioning or packaging workflow.
+ 5. Download the folder directly from GitHub and place it in your skills collection.
## Documentation
- https://spark.apache.org/docs/latest/
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/apache-spark-job-manager/)