A simple wrapper process around cloud service providers to run tools for the RAPIDS Accelerator for Apache Spark.
Project description
spark-rapids-user-tools
User tools to help with the adoption, installation, execution, and tuning of RAPIDS Accelerator for Apache Spark.
The wrapper improves end-user experience within the following dimensions:
- Qualification: Educate the CPU customer on the cost savings and acceleration potential of RAPIDS Accelerator for Apache Spark. The output shows a list of apps recommended for RAPIDS Accelerator for Apache Spark with estimated savings and speed-up.
- Bootstrap: Provide optimized RAPIDS Accelerator for Apache Spark configs based on GPU cluster shape. The output shows updated Spark config settings on driver node.
- Tuning: Tune RAPIDS Accelerator for Apache Spark configs based on initial job run leveraging Spark event logs. The output shows recommended per-app RAPIDS Accelerator for Apache Spark config settings.
- Diagnostics: Run diagnostic functions to validate the Dataproc with RAPIDS Accelerator for Apache Spark environment to make sure the cluster is healthy and ready for Spark jobs.
Getting started
set python environment to version [3.8, 3.10]
- Run the project in a virtual environment.
$ python -m venv .venv $ source .venv/bin/activate
- Install spark-rapids-user-tools
-
Using released package.
$ pip install spark-rapids-user-tools
-
Using local version from the repo
$ pip install -e .
-
Using wheel package built from the repo
$ pip install build $ python -m build --wheel $ pip install <wheel-file>
-
- Make sure to install CSP SDK if you plan to run the tool wrapper.
Usage and supported platforms
Please refer to spark-rapids-user-tools guide for details on how to use the tools and the platform.
Changelog
[22.10.2] - 10-28-2022
- Support to handle tools jar arguments in the user tools wrapper
[22.10.1] - 10-26-2022
- Initialize this project
Release history Release notifications | RSS feed
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