Полный курс по Trino для Data Engineer: Разбор от А до Я (теория + практика)

🔥 Want to understand what Trino (formerly PrestoSQL) is, how to use it to run federated queries across multiple data sources simultaneously, and why it's so popular in data engineering? In this video, we'll break down Trino from the ground up using live examples: from running locally in Docker to fully integrated with PostgreSQL, Apache Kafka, Apache Iceberg, Airflow, and Superset. 🗂️ GitHub repository with code: https://github.com/k0rsakov/pet_proje... ✉️ Questions, training, and consultations on Data Engineering – PM me: https://korsak0v.notion.site/Data-Eng... 💥 Notion alternative (if the link above doesn't work) – https://www.dataengineers.pro/mentors... 💡 At the end of the video – practical recommendations: we'll cover the specifics and subtleties of working with Trino so you can effectively use it for analytics and avoid common mistakes when designing a data platform. Links: Data Engineering Mentoring/Consulting — https://korsak0v.notion.site/Data-Eng... TG Channel — https://t.me/DataLikeQWERTY Instagram —   / i__korsakov   Habr — https://habr.com/ru/users/k0rsakov/pu... Timecodes: 00:00 — Start 00:52 — Trino Theory 04:31 — Simple Trino Launch in Docker Without Configuration 06:35 — Simple Trino Launch in Docker Using Configuration 08:00 — Simple Trino Launch in Docker Using Configuration and a Custom Connector 10:56 — Simple Trino Cluster Launch in Docker 16:59 — Simple Federated Query in Trino in Docker 20:31 — Integrating Trino into Data Engineering: Python 25:28 — Integrating Trino into Data Engineering: Kafka 29:42 — Integrating Trino into Data Engineering: Apache Iceberg 33:30 — Integrating Trino into Data Engineering: Apache Airflow 39:55 — Integrating Trino into Data Engineering: Apache Superset 46:20 — Trino Subtleties and Conclusion #trino #presto #dataengineering #bigdata #apacheairflow #superset #apachekafka #apacheiceberg #python #sql #etl #elt #dwh #dataengineer #junior #middle #pipeline