HDFS provides the underlying storage for Hadoop, however, the HDFS deals with massive small files inefficiently and decreases system performance seriously. To solve this problem, we designed a file merging, indexing and retrieval solution. Then through a series of experiments compared to the original HDFS and HAR solution, it can be shown that our scheme can effectively reduce the memory usage of Namenode and improve the I/O performance of HDFS.