You have daily BigQuery tables named LOGS_yyyymmdd and wildcard queries over long ranges exceed the 1,000-table limit. How should you resolve this?

Converting sharded daily tables into a single partitioned table is the most effective solution. BigQuery's 1,000-table limit for wildcard queries is a hard constraint. Date-partitioned tables allow you to store all data in a single table while still enabling efficient querying by date, eliminating the need for wildcard tables and bypassing the limit. Converting all daily log tables into date-partitioned tables is essentially the same solution. Enabling query caching might help with repeated queries but won't resolve the underlying issue of exceeding the table limit for new or varied queries. Creating monthly views would still likely hit the 1,000-table limit if the underlying daily tables are queried, or it would require pre-aggregating data, which might not suit all use cases.