LABLoad Data from an S3 Bucket to Amazon Neptune's SPARQL Environment
In this lab, you'll practice creating a SPARQL Data file and loading that file 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 RDF Data File
You'll create the Terse RDF Triple (Turtle) data file to be loaded into the Neptune instance.
Challenge
Upload the SPARQL Data File to S3
You'll upload the SPARQL data file–the RDF file created in the first challenge--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 SPARQL Data File 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 RDF Data Using SPARQL
You'll run several SPARQL queries to verify that the RDF triples 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
- Jupyter Notebooks
- Resource Description Framework (RDF)
- SPARQL Language Fundamentals
