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Identify Presto Query Patterns and Outliers | varada.io

In this video Guy Mast, Varada's Product Manager, explains how you can use the Presto Analyzer to identify query patterns and outliers. It’s critical to identify patterns in queries executions and spot problematic queries, identify fraction of queries that are memory, i/o intensive, and fraction of queries that are not interactive. The Presto Analyzer enables copying Presto query id to investigate further the root cause and check whether filters are not optimally pushed down or if joins are executed effectively. In addition you can implement partitioning or indexing to reduce the amount of data scanned. Varada recently released a new open source tool that enables data platform teams to easily analyze, monitor and optimize presto clusters, both PrestoDB and Trino. The Presto Analyzer offers workload-level insights on how clusters perform, and enables to instantly identify heavy users and bottlenecks, and effectively optimize performance and concurrency. Go to github: https://github.com/varadaio/presto-wo... Learn more: https://varada.io/blog/presto/presto-... ✿ Social Links: LinkedIn:   / varadaio   Twitter:   / varadaio   🌐Check Out Our Website! https://varada.io 🔔 SUBSCRIBE IF YOU ARE NEW AND TURN THE BELL ON Watch More Videos: ▶️ Identify Resource-Heavy Presto Operators    • Identify Resource-Heavy Presto Operat...   ▶️Optimize Presto Joins    • Optimize Presto Joins | varada.io   ▶️ The State of Data Virtualization Survey, Q1'2021    • The State of Data Virtualization Surv...   Thanks for being with us! 👍 Like the video 💬 Comment if you made it till the end! 🔗 Share the video with anyone you think it might help :)