{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/698ca41d993f47519568b06188ed1b1e\" frameborder=\"0\" width=\"1662\" height=\"1246\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1246,"width":1662,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1246,"thumbnail_width":1662,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/698ca41d993f47519568b06188ed1b1e-db99a122ea9841c7.gif","duration":185.392,"title":"Optimizing Database Queries for Better Performance 🚀","description":"In this video, I discuss the performance issues I encountered with my content queries, which were too slow due to inefficient function calls. I implemented a new approach using distinct queries and outer joins, which significantly improved execution time by utilizing indices effectively. The previous method resulted in a prohibitive sequential scan, while the new method shows a drastic reduction in execution time to milliseconds, although the database was empty during testing. I encourage you to review the changes I've made to the resource access for my contents, documents, concepts, and file references, as they should enhance our overall efficiency."}