IReS(Intelligent Multi-Engine Resource Scheduler) is an integrated, open source platform for managing, executing and monitoring complex analytics workflows. IReS is a core component of the ASAP system architecture and its main task is to “mix-and-match” diverse execution engines and data stores in order to optimize a workflow with respect to multiple, user-defined criteria.

To that end, IReS incorporates a modeling framework that constantly evaluates the cost and performance of data and computational resources under various configuration setups in order to decide on the most advantageous store, indexing and execution pattern. A tree-based metadata language that describes operators in abstract and instantiated forms enables the search and matching of operators that perform a similar task in the planning phase. Afterwards, a decision making module chooses among the different equivalent execution plans (i.e., on different engines, resulting in equivalent output) the one that best fits the given policy based on cost and performance models. The chosen plan is scheduled and enforced, taking into account the available resources.