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The data warehouse is a centralized repository for analyzing and storing huge amounts of data. In distributed data warehouse, data can be shared across multiple data repositories which belong to one or more organizations. In general, clients expect short response times for their queries. The scheduling algorithms are used to resolve the issues and to accomplish the task with quick manner. In this paper, we are dealing grid based scheduling algorithms for query scheduling and resource management in distributed data warehouses. The algorithms are Optimal Resource Constraints (ORC), Grouping based Fine-grained Job Scheduling (GFJS), Research on Novel Dynamic Resource Management (RNDRM) and New Resource Mechanism with Negotiate Solution (NRMNS). When we are combining both job and resource scheduling algorithms, the query processing time and memory size performances are lower than individual scheduling responses.