Hyperion is a robust full history API solution designed to manage and interact with Antelope-based blockchains efficiently. In this blog, we’ll walk you through the essential components and setup necessary to harness the power of Hyperion for your projects.
Overview of Hyperion
Hyperion has been crafted to address the vast data requirements of the Antelope protocol, which can handle tens of thousands of transactions per second. This high-performance system enables block producers, infrastructure providers, and dApp developers to index, store, and retrieve historical blockchain data effectively.
By improving data structure and flattening actions storage, Hyperion ensures faster search times, less bandwidth use, and enhanced usability. Notably, only the block header index is stored, keeping the system lean and efficient.
Architecture: The Components of Hyperion
To run a fully functional Hyperion API deployment, several components must be in play. Here’s a breakdown:
- Elasticsearch Cluster: This cluster stores all indexed data and requires nodes with at least 32 GB of RAM and 8 CPU cores.
- Hyperion Indexer: A Node.js application that processes data from the state history plugin for indexing purposes.
- Hyperion API: Provides V2 and V1 endpoints, operational through PM2 with cluster capabilities.
- RabbitMQ: Handles messaging and data transport between indexer stages.
- Redis: Utilized for transient data storage and caching transactions.
- Leap State History: Collects action traces via websockets for the indexer.
- Hyperion Stream Client: (Optional) For real-time streaming on enabled providers.
- Hyperion Plugins: (Optional) Allows for customization through the hpm tool.
How to Get Started with Hyperion
Now that you know the different components, here’s how to set up and start using Hyperion:
- For Providers: Follow the steps provided in the manual installation guide.
- For Developers: Learn how to utilize Hyperion for your development needs through the official documentation.
- Also, consider using the Hyperion Lightweight Explorer for easier interface and navigation.
Explaining the Code Setup
To make sense of how Hyperion functions, let’s use an analogy:
Imagine Hyperion as a library and the blockchain as a vast, ever-expanding collection of books. Each time a new transaction occurs, it’s like acquiring a new book that contains various details, including action traces (characters) and state deltas (plot twists). The Hyperion Indexer organizes this collection, ensuring the latest releases (transactions) are readily accessible without cluttering the shelves (database) with every single page from each book (full block or transaction data).
The Elasticsearch cluster acts like a sophisticated catalog system that allows readers (users) to quickly find the books (data) they need, while RabbitMQ is akin to a robust courier system that delivers new arrivals to the shelves efficiently. Redis acts as a temporary storage room for popular titles, where frequent visitors can find their favorite reads quickly.
Troubleshooting Tips
As you explore Hyperion, you may run into some hurdles. Here are a few troubleshooting ideas:
- Ensure that your Elasticsearch nodes have the recommended memory and processing power.
- Check the connectivity between your Hyperion Indexer and the Elasticsearch cluster to avoid communication errors.
- Verify that RabbitMQ is set up correctly; issues here can disrupt data transport.
- For persistent problems, examine your configuration settings in the PM2 process manager.
For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.
Conclusion
At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.