Added notebook for running Simple Model with large data

[hsubbaraj-spiral]

Describe your changes and why you are making these changes

This notebook takes a set of data (currently "LARGE_HOTEL_REVIEWS") and generates rows of data based on the parameter provided.

Ran this with a ~400GiB sized dataset and it ran in about 40 minutes including cluster spin up time. Most of this time is reading/writing the data to the views of the SparkSession and spin up/teardown of executors. This is expected behavior, but will try and understand more deeply what is happening under the hood.

Related issue number (if any)

Loom demo (if any)

Checklist before requesting a review

• I have created a descriptive PR title. The PR title should complete the sentence "This PR...".
• I have performed a self-review of my code.
• I have included a small demo of the changes. For the UI, this would be a screenshot or a Loom video.
• If this is a new feature, I have added unit tests and integration tests.
• I have run the integration tests locally and they are passing.
• I have run the linter script locally (See python3 scripts/run_linters.py -h for usage).
• All features on the UI continue to work correctly.
• Added one of the following CI labels:
  • run_integration_test: Runs integration tests
  • skip_integration_test: Skips integration tests (Should be used when changes are ONLY documentation/UI)

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[saurav-c]

Would be good to add comment in the notebook itself about the size of the data we are fetching