In order to solve the problem of uneven data distribution or confusion of characteristics in material supply chain under multi-source data, a data balance processing method of material supply chain based on multi-source data was proposed. The data distribution space of material supply chain was established, non-boundary and boundary areas were set, the center of the area was calibrated, the distances between different characteristic data and the center point were calculated respectively, the unbalanced data was searched in advance by using the edge mixed sampling algorithm, and the boundary area to which it belongs was determined according to the data distance characteristics. The unbalanced data was regarded as the working nodes in the supply chain cluster. When the number of working nodes in the cluster changes, the load generated by each cycle execution node was obtained by flow calculation, and the load value was converted into the execution thread score. The unbalanced data was obtained by comparing the scores, the threshold of data memory and CPU resource consumption in the material supply chain was calculated, and the parallel task thread was established. The scheduler was used to transfer the execution thread in the working node to the next node to achieve the purpose of load balancing. The experimental results show that the proposed method has the advantages of short response time, large data throughput, good processing effect and strong stability, and has good practical application value.