As per the very short review session of the available source code and the SPIP itself, I think the answer is YES.

It is especially clear for spark.sql.sources.v2.bucketing.partiallyClusteredDistribution.enabled that says:

This is an optimization on skew join and can help to reduce data skewness when certain partitions are assigned large amount of data.

Yes, storage-partitioned joins can be optimized for data skewness. Techniques like adaptive query processing and dynamic repartitioning help distribute the workload evenly across nodes. clipping path service provider By identifying and addressing data hotspots, these methods enhance performance and efficiency, ensuring that no single node becomes a bottleneck, thus effectively managing data skew in distributed databases.