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How to run a full lakehouse platform on one machine with Open Lakehouse Compute Fabric

Start the console, SQL, notebooks and sample Retail lakehouse on a laptop with Python only.

Who it is forA data analyst or developer who wants to try a lakehouse platform locally, with no cloud account and no Spark install.

The problemSetting up a lakehouse with catalog, SQL, notebooks and dashboards usually means several services and cloud accounts before any data can be queried.

The outcomeA running OLCF console on one machine with SQL on DuckDB, Python notebooks, dashboards, pipelines and a sample Retail lakehouse.

What you need first

  • 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

Steps

  1. Install OLCF using the Install section of the README.
  2. Run olcf quickstart.
  3. Open the console the quickstart reports and open the sample Retail lakehouse.
  4. Run a query in the SQL editor against the sample lakehouse and check that rows come back.

Prompt for your agent

Use the open-lakehouse-compute-fabric repo (jddevtime/open-lakehouse-compute-fabric). Install it from the README Install section, run `olcf quickstart`, and report the console address and whether the sample Retail lakehouse loads. Verify by running one SQL query against the sample lakehouse and returning the row count.

Caveat. The README marks this release as 0.1.0 beta for evaluation on trusted infrastructure, so do not point it at production data yet.

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