A block chain system data processing method based on compressed sensing and a sparse reconstruction algorithm, comprising the following steps: (1) converting block chain system transaction data into multi-temporal-spatial and multi-dimensional data, and performing compression and sparse representation on the converted data; (2) constructing an M*N sparse calculation matrix not related to a sparse transformation matrix and performing linear projection on the multi-temporal-spatial and multi-dimensional data to obtain a sensing data calculated value; and (3) reconstructing the transaction information: accurately reconstructing multi-temporal-spatial and multi-dimensional original transaction data by using low-dimensional transaction data obtained by compressed sensing and by using a sparse algorithm. The data processing method resolves the technical problems of data redundancy and a waste of resources caused by a low block chain data processing speed.
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