The distance join is a spatial join that finds pairs of closest objects in the order of distance by associating two spatial data sets. The distance join stores node pairs in a priority queue, from which node pairs are retrieved while traversing R-trees in top-down manners in the order of distance. This paper first shows that a priority strategy for the tied pairs in the priority queue during distance join processing greatly affects its performance. Then it proposes a probabilistic tie-breaking priority method. The experiments show that the proposed method is always better than alternative methods in the performance perspectives.