  Different types of data skew can result in load imbalance in the context of
parallel joins under the shared nothing architecture. We study one important
type of skew, join product skew (JPS). A static approach based on frequency
classes is proposed which takes for granted the data distribution of join
attribute values. It comes from the observation that the join selectivity can
be expressed as a sum of products of frequencies of the join attribute values.
As a consequence, an appropriate assignment of join sub-tasks, that takes into
consideration the magnitude of the frequency products can alleviate the join
product skew. Motivated by the aforementioned remark, we propose an algorithm,
called Handling Join Product Skew (HJPS), to handle join product skew.
