Learning DuneSQL and Our Engines

The video provides an introduction to Dune SQL and the engines used on the Dune platform for running queries. Key points include:

  1. Dune SQL Overview: Dune SQL is a fork of Trino SQL, and users can refer to Dune's documentation or Trino's for detailed functions and operators. For beginners, it is recommended to take Kaggle’s SQL courses and practice with Dune's SQL and Ethereum guide.
  2. Learning and Practicing SQL: The video emphasizes the importance of hands-on learning, suggesting users practice basic SQL concepts through the provided guide, focusing on difficult topics like joins and window functions.
  3. Working with Binary/Hex Functions: Users dealing with Ethereum addresses (hexadecimal) should become familiar with functions for converting and handling binary data.
  4. Calling APIs in SQL: Dune SQL supports HTTP GET and POST functions, allowing users to pull external data (e.g., from DeFi Llama) directly into their queries.
  5. Optimizing Queries: The video discusses query optimization, especially when working with large datasets. Key tips include filtering by block time and block number, and understanding the use of partitions instead of indexes in Dune SQL.
  6. Engine Tiers: Dune offers three shared engines (Free, Medium, Large) for running queries. The Free tier allows up to 2-minute queries without costing credits, while the Medium and Large tiers offer faster execution but with a 30-minute timeout and credit usage.
  7. Credits and Plans: Users receive 2,500 free credits each month, with the option to upgrade for more. On the Free plan, only three queries can run simultaneously, whereas other plans allow unlimited concurrent queries.
  8. Becoming a Better Analyst: For users looking to advance their skills, the video suggests exploring Dune's roadmap and related resources to deepen their understanding of crypto concepts and improve as data analysts.

Overall, the video is aimed at helping users understand how to effectively use Dune SQL, optimize queries, and leverage the platform's engine tiers for their data analysis needs.

Transcript