A table data simulation generating algorithm is proposed based on not-temporal attribute correlation. This algorithm can overcome the difficulty in building not-temporal attribute correlation in the development of big data simulation generator, and play an important role in the field of measurement of the big data simulation generated. Firstly, we extract the two key not-temporal attributes from the data set, and make the statistics of twofold frequency. Then, based on the statistical results, we calculate the maximal information coefficient (MIC) value to measure dependence for two-variable relationships. We use the stretched exponential (SE) distribution to fit the relationship, and build the correlation model. Finally, we generate data in a two-dimensional matrix with this model. The experimental results show that this algorithm can effectively describe the data characteristics of the real data set.