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Big data analysis with Chromia blockchain and PySpark

Course objectives​

By the end of this course, you will be able to:

  • Understand how to integrate the Chromia blockchain with PySpark.
  • Query data from the Chromia blockchain.
  • Perform data transformations and aggregations using PySpark.
  • Analyze and visualize data to extract meaningful insights.

Key features​

  • Asynchronous execution: Utilizes asyncio to handle blockchain transactions asynchronously, ensuring non-blocking operations.
  • Blockchain interaction: Facilitates transaction creation and signing with postchain-client-py.
  • Environment variables: Employs a .env file for managing sensitive data, such as private keys and configuration values.
  • Randomized data generation: Generates random quantities and prices for products.

Potential enhancements​

  • Implement pagination to retrieve large amounts of data from the node's database.
  • Incorporate error handling for specific blockchain-related errors.
  • Log transactions to a file for debugging or auditing purposes.
  • Validate environment variables and inputs before execution.