To solve the problem that the existing distributed database based on Log Structured Merge-Tree (LSM-Tree) only supports efficient primary key query and cannot allow users to quickly apply it in their own clusters, a light-weight distributed index implementation method based on LSM-Tree, called SIBL (Secondary Index Based LSM-Tree), was proposed. Firstly, the query efficiency of the non-primary key attributes was improved by indexing the primary key attribute columns. Then, a distributed index construction algorithm and an index interval division algorithm based on equidistant sampling were proposed to ensure the even distribution of indexes in the system. And the query algorithm of the traditional index was optimized, and the index file was regarded as a special data file and stored in the system in a distributed manner, ensuring the load balance and scalability of the system. Finally, experiments of the proposed method with Huawei's secondary index scheme HIndex were carried out on the HBase database to compare performances such as time and space overhead of index construction, index query performance and system load balance, verifying that the proposed method improves query performance by 50 to 200 times.