A BigQuery workload frequently filters large tables by customer identifier within broad date partitions. Which approach best fits?

1. Evaluate clustering on the frequently filtered identifier and measure the effect.
2. Filter on the relevant partition column using a pruning-compatible predicate.
3. Perform a dry run and set an appropriate maximum bytes billed where supported.
4. Evaluate a compatible materialized view.