  In this work, we study the problem of co-optimize communication,
pre-computing, and computation cost in one-round multi-way join evaluation. We
propose a multi-way join approach ADJ (Adaptive Distributed Join) for complex
join which finds one optimal query plan to process by exploring cost-effective
partial results in terms of the trade-off between pre-computing, communication,
and computation.We analyze the input relations for a given join query and find
one optimal over a set of query plans in some specific form, with high-quality
cost estimation by sampling. Our extensive experiments confirm that ADJ
outperforms the existing multi-way join methods by up to orders of magnitude.
