With the rapid development of Internet and the coming of big data, resource management system, a thin resource sharing layer that enables sharing cluster across diverse cluster computing frameworks, by giving frameworks a common interface for accessing cluster resources. For powering both large Internet services and a growing number of dataintensive scientific applications, cluster computing framework will continue emerge, and no framework will be optimal for all applications. Therefore, multiplexing a cluster between frameworks makes significant difference. Deploying and running multiple frameworks in the same cluster, improves utilization and allowing applications to share access to large datasets that may be costly to replicate across clusters. This paper is aimed to illustrate current major techniques of resource management and scheduling in cluster, including resource representation model, resource allocation model and scheduling policy. Finally, current prominent solutions, which have been developed and used by many companies, will be demonstrated, and we then summary and contrast these solutions used in recent years.