aws / aws/amazon-sagemaker-examples

inference pipeline sparkml xgboost notebooks issues

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Dominant language
Jupyter Notebook
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Description

Similar notebooks:

1. [xgboost/spark abalone](https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/inference_pipeline_sparkml_xgboost_abalone/inference_pipeline_sparkml_xgboost_abalone.ipynb)
1. [xgboost/spark car evaluation](https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/inference_pipeline_sparkml_xgboost_car_evaluation/inference_pipeline_sparkml_xgboost_car_evaluation.ipynb)

Issues:
1. Requires manual addition of role for Glue access
- Has user paste in json to add this permission
- How can we programmatically add this permission?
- How to set this up w/ CI?

Contributor guide

Open the contributing guide

Research direction

Start with the linked notebooks in advanced_functionality/inference_pipeline_sparkml_xgboost_abalone and advanced_functionality/inference_pipeline_sparkml_xgboost_car_evaluation. Review how the Glue permission is currently added and how the notebooks are intended to run in CI. Done means the required permission setup no longer depends on manual JSON pasting and the CI approach is documented or implemented.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, jupyter-notebook, spark
Domain
ci-cd, cloud, machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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