How does Trino process a query? | Starburst Academy скачать в хорошем качестве

How does Trino process a query? | Starburst Academy

Excited to learn more about Starburst? Starburst Academy has a whole course on the topic: https://academy.starburst.io/page/sta... If you want to get hands-on with Starburst, get up and running in seconds with our Starburst Galaxy: Getting started tutorial: https://www.starburst.io/tutorials/st... In this video, you'll discover how the Trino query engine processes SQL queries efficiently. Starburst uses the Trino engine at its core and both Starburst Galaxy and Starburst Enterprise are the best way to use Trino in your data workloads. This is particularly effective when combined with an open data lakehouse architecture using Apache Iceberg. Trino, formerly known as PrestoSQL, employs a distributed architecture to process SQL queries. Clusters of nodes collaborate to handle large datasets in parallel. Each cluster comprises a coordinator node responsible for managing query execution and one or more worker nodes tasked with executing query-related operations. Learn how clusters can scale to accommodate increased processing demands by adding more workers or enhancing the processing power of existing ones. Explore the essential components of clusters, including connectors and catalogs, enabling communication with diverse data sources. Join us as we dive into the intricacies of processing a query spanning multiple data sources. Follow along with a detailed diagram illustrating the roles of coordinators, workers, connectors, clients, and data sources in the query execution process. You'll see how the coordinator parses queries, gathers metadata from data sources, and assigns tasks to workers based on optimal query execution strategies. Understand how workers leverage connectors to access data sources, exchange information, and collaborate to complete tasks efficiently. Explore how Trino's innovative architecture empowers organizations to query any data source and federate data from multiple sources effectively, especially on the data lakehouse. #data #datalakehouse #opendatalakehouse #clouddatalakehouse #datavirtualization #trino #massivelyparallelprocessing #mpp #starburst #enterprisedata #etl #etlpipeline #dataindexing #datacaching #datagovernance #dataobservability #datastrategy #datariskmanagement #dataanalytics #dataengineering #dataoptimization #datalake #datawarehouse #bigdata #dataleddecisions