According to the Snowflake documentation1, clustering keys are most effective when the data is evenly distributed across the key values. If the data is skewed, such as in this case where most sales come from only 20 stores out of 1000, then the micro-partitions will not be well-clustered and the pruning will be poor. This means that more bytes will be scanned by queries, even if they filter by STORE_ID. Option A is incorrect because the data type of the clustering key does not affect the pruning. Option B is incorrect because the table is large enough to benefit from clustering, if the data was more balanced. Option D is incorrect because the cardinality of the clustering key is not relevant for pruning, as long as the key values are distinct.
1: Considerations for Choosing Clustering for a Table | Snowflake Documentation