Presto Performance Best Practices—Get Visibility Into Your Presto Queries

Presto is the go-to query engine of many big data customers for interactive and reporting use cases due to its excellent performance and ability to join unstructured and structured data in seconds. Many Pepperdata customers get visibility into their Presto queries to explore data and run queries in one place with continuous, automated application and infrastructure tuning. The complexity of managing cluster performance to meet business requirements and performance SLAs is complex. You want best-in-class performance to meet the short deadlines of interactive workloads while reducing and/or controlling costs. If a single query fails to complete because of query-level inefficiencies, data skew, missing or old statistics, or resource configurations—that single resource-consuming query can negatively impact the entire application stack on that cluster. Join Pepperdata Field Engineer Alex Pierce for this webinar on Presto performance management best practices to learn: —When to use Presto versus other engines —Key criteria to look for in a query engine for interactive analytics —Visibility into all of your queries in one place with continuous, automated application and infrastructure tuning —How to enable self-service access to your data lake —How to Immediately improve and scale application performance through automated tuning —How to Improve query performance through job-specific recommendations, query run comparisons, and IT chargeback reports