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We investigate the problem of efficiently computing a multi-way spatial join without spatial indexes. We propose a novel and effective filtering algorithm based on a two phase partitioning technique. To avoid missing hits due to an inherent difficulty in multi-way spatial joins, we propose to firstly partition a join graph into sub-graphs whenever necessary. In the second phase, we partition the spatial data sets; and then the sub-joins will be executed simultaneously in each partition to minimise the I/O costs. Finally, a multi-way relational join is applied to merge together the sub-join results. Our experiment results demonstrate the effectiveness and efficiency of the proposed algorithm.