Adapting to rank address the problem of insufficient domain-specific labeled training data in learning to rank. However, the initial study show that adaptation is not always effective. In this paper, we investigate the relationship between the domain similarity and the effectiveness of domain adaptation with the help of two domain similarity measures: relevance correlation and sample distribution correlation.