FIMIBase： An Hierarchical Indexing System for Storing and Querying Big Data

Relational database management systems are usually deployed on singlenode machines and have strict limitations in terms of da ta structure. This means they do not work well with big data, and NoSQL has been proposed as a solution. To make data querying more efficient, indexes and memory cache techniques are used in NoSQL databases. In this paper, we propose a hierarchical in dexing mechanism and a prototype distributed datastorage system, called HMIBase, which has hierarchical indexes for nonprima ry keys in tables and makes data querying more efficient. HMIBase uses HBase as the lower data storage and creates a memory cache for more efficient data transmission. HMIBase supports coprocessortoprocess update requests. It also provides a client with query and update APIs and a server to support RPCs from the client and finish jobs. To improve the cache hit ratio, we propose a memory cache replacement strategy, called Hot Score algorithm, in HMIBase. The experimental results show that Hot Score algo rithm is better than other cachereplacement strategies.