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The increased availability of massive datasets provides a unique opportunity to discover subtle patterns in their distributions,but also imposes overwhelming computational challenges.To fully utilize the information contained in big data,we propose a two-step procedure:(ⅰ)estimate conditional quantile functions at different levels in a parallel computing environment;(ⅱ)construct quantile process through projection based on these estimated quantile curves.