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For join processing, it is important to minimize the communication cost since it is the main consumer of battery power.
This work is our attempt to go beyond worst-case analysis for join algorithms.
The development of scalable parallel database systems requires the design of efficient algorithms, especially for join, which is the most frequent and expensive operation in relational database systems.
Performance analysis and simulation results demonstrate that HJET is efficient in key establishment and update, and achieves the asymptotic time cost of O(1) for join event and nearly O(1)for leave events when group dynamics are known a priori.
Here, time complexity to generate candidate set is the sum of total time for join and prune task.
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