# Using Trino with Apache Airflow for (almost) all your data problems

DevFeed: [Using Trino with Apache Airflow for (almost) all your data problems](<https://devfeed.tech/articles/using-trino-with-apache-airflow-for-almost-all-your-data-problems-8706.md>)

Original publisher: [Read original article](<https://trino.io/blog/2022/12/21/trino-summit-2022-astronomer-recap.html>)

Author: Philippe Gagnon, Brian Olsen

Published: 2022-12-21T00:00:00Z

Content type: article

Language: en

Sources: [Trino Blog](<https://devfeed.tech/sources/trino-blog.md>)

Topics: [airflow](<https://devfeed.tech/topics/airflow.md>), [data](<https://devfeed.tech/topics/data.md>), [Data Infrastructure](<https://devfeed.tech/topics/data-infrastructure.md>), [Scalability](<https://devfeed.tech/topics/scalability.md>), [Availability](<https://devfeed.tech/topics/availability.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Software as a service](<https://devfeed.tech/topics/saas.md>)

Tags: [airflow](<https://devfeed.tech/tags/airflow.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [apache](<https://devfeed.tech/tags/apache.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [availability](<https://devfeed.tech/tags/availability.md>), [batch](<https://devfeed.tech/tags/batch.md>), [data](<https://devfeed.tech/tags/data.md>), [data-infrastructure](<https://devfeed.tech/tags/data-infrastructure.md>), [databases](<https://devfeed.tech/tags/databases.md>), [integration](<https://devfeed.tech/tags/integration.md>), [saas](<https://devfeed.tech/tags/saas.md>), [scalability](<https://devfeed.tech/tags/scalability.md>), [summit](<https://devfeed.tech/tags/summit.md>), [trading](<https://devfeed.tech/tags/trading.md>), [warehouse](<https://devfeed.tech/tags/warehouse.md>), [workflow](<https://devfeed.tech/tags/workflow.md>)

## AI overview

The article recaps a Trino Summit 2022 talk about using Apache Airflow to orchestrate Trino batch queries. It explains Trino's fault-tolerant execution mode and discusses moving queries closer to federated data sources to improve data availability, performance, scalability, and collaboration.

## Source excerpt

As we close in on the final talks from Trino Summit 2022, this next talk dives into how to set up Trino for batch processing. Trino has historically been well-known for facilitating fast adhoc analytics queries as opposed to long-running, resource intensive batch/ETL queries. This is due to the fact that Trino kills queries that run out of resources in order to prioritize faster query execution. Earlier this year, Trino added features to better support batch queries with a new fault-tolerant execution mode. This mode backs up intermediate data during execution time, allowing Trino to restart individual query tasks on failure rather than a query stage or the query itself. Batch queries don't typically involve human intervention and run asynchronously. These tasks may depend on each other and have a complex workflow. This talk describes how to orchestrate this complexity using Airflow's new Trino integration to run Trino batch queries to solve (almost) all your data problems.