Abstract: Frequent pattern mining can find frequent pattern in data, and iYs an important step in the association rules mining. Parallel frequent pattern(PFP) algorithms apply it into parallel environment, which is suitable for massive data.Based on the implementation of Apache Mahout, this paper proposed a design for optimizing the counting and sorting parts of PFP using distributed coordination system. This design takes advantage of distributed coordination system and reduces the consumption on HDFS and memory of data node. Another benefit is that the counting procedure and sorting procedure start parallclly. At last this paper analyzed the experimental result and the difficulties for implementation for further study.

Key words: Frequent pattern growth algorithm, Parallel data mining, Distributed coordination system, Performance tuning