Load Data from an S3 Bucket to Amazon Neptune's Gremlin Environment
In this lab, you'll practice creating Gremlin data files and loading those files into Neptune using the bulk loader. When you're finished with this lab, you'll have a base workflow to build your production process.
Terms and conditions apply.
Challenge
Create the Gremlin Vertex and Edge CSV Files
You'll create the vertex and edge CSV files to be loaded into the Neptune instance. These files will be created using the Gremlin Data Format.
Challenge
Upload the Gremlin CSV Files to S3
You'll upload the created Gremlin CSV files to the S3 bucket.
Challenge
Verify That Neptune Has Access to the S3 Bucket
You'll verify that the IAM role was created correctly. Then you will attach that role to the Neptune cluster to allow the cluster to read files from the S3 bucket.
Challenge
Load the Gremlin CSV Data Files From the S3 Bucket
You'll initiate the Neptune bulk load request using the %load line magic command within the connected Sagemaker notebook.
Challenge
Query the Loaded Gremlin Data
You'll run several Gremlin queries to verify that the vertices and edges were loaded correctly.
Provided environment for hands-on practice
We will provide the credentials and environment necessary for you to practice right within your browser.
Guided walkthrough
Follow along with the author’s guided walkthrough and build something new in your provided environment!
Did you know?
On average, you retain 75% more of your learning if you get time for practice.
Recommended prerequisites
- Gremlin Terminology
- Jupyter Notebooks