Analyzing Chromia blockchain data with PySpark

Course objectives

After finishing this course, you can:

• Connect the Chromia blockchain to PySpark.
• Fetch data stored on the Chromia blockchain.
• Transform and aggregate that data with PySpark.
• Analyze and visualize the results to draw useful conclusions.

Key features

• Asynchronous execution: Blockchain transactions run through asyncio, so operations don't block.
• Blockchain interaction: You build and sign transactions with postchain-client-py.
• Environment variables: Private keys, configuration values and other sensitive data live in a .env file.
• Randomized data generation: Product quantities and prices are produced at random.

Potential enhancements

• Add pagination so you can pull large data sets from the node's database.
• Handle specific blockchain-related errors explicitly.
• Write transactions to a log file for debugging or auditing.
• Check environment variables and inputs before the code runs.

Links

• Rell documentation.
• Full source code for this course: project repository.