The status monitoring data of substation equipment have the characteristics of big volume and low value density

since the traditional data processing method have some limitations in fast query for status monitoring

evaluation and diagnosis. By analyzing the characteristics of status monitoring data and the distributed data storage method

a big data processing framework for the status monitoring of the substation equipment is presented. By combing data attributes such as acquisition time

device code and linked device code

three kinds of status monitoring row key are designed to improve the flexibility of row key query. In order to solve the low efficiency of full table scan problem when the row key is unknown

a secondary index method based on coprocessor is proposed to achieve fast query under non-row key constraint conditions. The experimental results show that

the secondary index based on coprocessor has an obvious improvement on the query efficiency compared with the non-index and the IHBase secondary index

the impact of writing speed on the status monitoring data is insignificant

and it can better meet the needs of fast and flexible query of status monitoring data in big data environment. This work is supported by National Natural Science Foundation of China(No. 61074078).