You created an external Hive-partitioned table over many files in Cloud Storage and queries are slow. How do you improve query performance?

Upgrading to a BigLake table and enabling metadata caching significantly improves query performance for external Hive-partitioned tables on Cloud Storage. BigLake tables optimize access to data lakes by providing a high-performance storage API and fine-grained security. Metadata caching reduces the need to list and inspect every file in Cloud Storage for each query, which is a major bottleneck for tables with many small files or partitions. Changing the storage class (Coldline to Standard) might slightly reduce access latency but won't address the fundamental issue of metadata scanning. Creating individual external tables for each partition and using wildcard queries adds complexity without solving the underlying metadata performance problem. Migrating to a multi-region bucket offers higher availability and geo-redundancy but doesn't inherently speed up queries against a large number of files or partitions.