The high quality decision-making depends on high quality data, hence data preprocessing is an essential phase for data analytics applications. In the big data area, traditional data preprocessing systems cannot be directly applied. To handle the large-scale data, enterprises adopt Hadoop/Hive as a popular solution at the present stage. However, it brings many defects, such as poor performance, the lack of interaction and so on. To fill this gap, this paper proposes and implements an interactive data preprocessing system based on Spark. This system provides a series of common preprocessing logics as basic components and supports flexible user-defined extensions. To get an interactive interface, the system presents data to users in the form of spreadsheets, while it can automatically records users operations to provide undo and redo support. In this paper, we introduce the architecture of this system with four aspects:data model, data preprocessing operations, interactive execution engine and interactive GUI. In the end, we conduct experiments with real stroke data and the result shows that the system can meet interactive demands in most big data scenarios.