Online aggregation query space optimization technology for streaming data

Abstract We present a novel subspace segment tree data structure designed for online aggregation queries on streaming data, addressing the challenge of efficient query processing under limited storage space in embedded systems. Traditional segment tree structures require several times the storage space of the original data, making them impractical for resource-constrained embedded devices. The proposed Subspace Segment Tree optimizes space utilization by partitioning the tree structure into three hierarchical layers, namely the solid, dynamic, and imaginary layers, and implementing a dynamic memory allocation and reclamation strategy based on a memory pool. This approach allocates memory only when nodes are actively used, significantly reducing space overhead. Experimental results demonstrate that the proposed method achieves over 90% space optimization compared to traditional segment trees while maintaining comparable time complexity, effectively resolving the space efficiency issue for aggregation queries in embedded systems.