&gt; doesn’t end here. BigQuery has background processes that constantly look at all the stored data and check if it can be optimized even further. Perhaps initially data was loaded in small chunks, and without seeing all the data, some decisions were not globally optimal. Or perhaps some parameters of the system have changed, and there are new opportunities for storage restructuring. Or perhaps, Capacitor models got more trained and tuned, and it possible to enhance existing data. Whatever the case might be, when the system detects an opportunity to improve storage, it kickstarts data conversion tasks. These tasks do not compete with queries for resources, they run completely in parallel, and don’t degrade query performance. Once the new, optimized storage is complete, it atomically replaces old storage data — without interfering with running queries. Old data will be garbage-collected later.<p>I wonder if they could share more details on how this is handled.