Question

Part I: Clustering Models with Spark’s ML Library . In this part, you will build a clustering model using Spark’s ML library and Databricks community edition to run Spark. Steps: We will work with the colon cancer dataset that we used in previous labs. It should be already uploaded to your Databricks account. Go to your Community Edition Databricks account and create a new workspace named Clustering. The colon cancer dataset file should be already uploaded to your account. You can copy the link to the dataset from the previous labs’ worksheets

Answer 1

The student is asked to build a clustering model using Spark's ML library and Databricks community edition with the colon cancer dataset.

Step-by-step explanation:

In this question, the student is asked to build a clustering model using Spark's ML library and Databricks community edition to run Spark with the colon cancer dataset. The steps involve creating a new workspace named Clustering, and the dataset should already be uploaded to the student's Databricks account. This task involves using Spark's ML library and working with a specific dataset.

It looks like you've provided the introduction and context for a task related to building a clustering model using Spark's ML library on Databricks. To proceed with the steps you've outlined, follow these general guidelines:

Access Databricks Community Edition:

Log in to your Databricks Community Edition account.

Create a New Workspace:

In the Databricks workspace, create a new workspace named "Clustering."

Access the Colon Cancer Dataset:

Ensure that the colon cancer dataset is already uploaded to your Databricks account. If not, you may need to upload it. You can use the link from previous labs' worksheets or upload it directly to your Databricks workspace.

Open a New Notebook:

Create a new notebook in your "Clustering" workspace for building the clustering model.