{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "jddevtime-open-lakehouse-compute-fabric--run-fabric-notebook-on-own-spark",
 "repo": "jddevtime/open-lakehouse-compute-fabric",
 "repo_url": "https://github.com/jddevtime/open-lakehouse-compute-fabric",
 "repo_slug": "jddevtime-open-lakehouse-compute-fabric",
 "title": "Run a Fabric notebook on your own Spark hardware",
 "page_title": "How to run a Fabric notebook on your own Spark hardware with Open Lakehouse Compute Fabric",
 "summary": "Send a Fabric notebook to your own Spark workers with olcf.run_remote() and read OneLake directly.",
 "who": "A Fabric data engineer who wants heavy or sensitive notebook compute to run inside their own network instead of consuming Fabric capacity.",
 "problem": "Large or sensitive Spark jobs in Fabric use Fabric capacity, and some workloads should stay on hardware the team controls.",
 "outcome": "A Fabric notebook cell that runs on your Spark workers, with status, logs and the exit value returned to the cell and to any calling Fabric pipeline.",
 "steps": [
  "Set up a Fabric tenant you control, following the Fabric integration guide.",
  "Attach the olcf_fabric wheel to a Fabric Environment and attach that environment to the notebook.",
  "Enroll at least one worker with `olcf worker enroll-token`, then start it on the machine with `olcf-worker run`.",
  "Call `olcf.run_remote()` in a notebook cell and review the status and logs it returns.",
  "Check the OneLake output table to confirm the write happened."
 ],
 "agent_prompt": "Use the open-lakehouse-compute-fabric repo (jddevtime/open-lakehouse-compute-fabric) and its Fabric integration guide. Attach the olcf_fabric wheel to a Fabric Environment, call olcf.run_remote() on <notebook name>, and report the returned status and exit value. Verify that the target OneLake table has the expected row count after the run.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "240 minutes",
 "basis": "readme",
 "caveat": "The README says the project is not Microsoft's runtime, claims no parity with Fabric's proprietary optimisations, and is not affiliated with Microsoft, so expect some notebooks to be rejected by the compatibility analyzer.",
 "category": "Data and analytics",
 "tags": [
  "Data and analytics"
 ],
 "lang": "python",
 "requirements": [
  "Python and a Linux machine (the README says it runs end to end on Linux)",
  "Installation of the OLCF package as described in the README Install section",
  "For the multi-machine fabric: a Spark runtime installed with the JDK, and machines that can reach the control plane",
  "For the Fabric extension: a Fabric tenant you control, the olcf_fabric wheel in a Fabric Environment, and Entra and network setup"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "credentials",
   "notice": "Fabric and Entra setup and worker enrollment tokens grant access to your OneLake data, so scope them tightly and keep them out of notebooks."
  }
 ],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/jddevtime-open-lakehouse-compute-fabric/run-fabric-notebook-on-own-spark/",
 "md": "https://dedupedai.com/use-cases/jddevtime-open-lakehouse-compute-fabric/run-fabric-notebook-on-own-spark/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/jddevtime-open-lakehouse-compute-fabric--run-fabric-notebook-on-own-spark.json",
 "api_version": "v1"
}