Improved Concurrency Control Techniques For Multi-Dimensional Index Structures

Multi-dimensional index structures such as R-trees enable fast searching in high-dimensional spaces. They differ from uni-dimensional structures in the following aspects: (1) index regions in the tree may be modified during ordinary insert and delete operations, and (2) node splits during inserts are quite expensive. Both these characteristics may lead to reduced concurrency of update and query operations. In this paper, we examine how to achieve high concurrency for multi-dimensional structures. First, we develop a new technique for efficiently handling index region modifications. Then, we extend it to reduce/eliminate query blocking overheads during node-splits. We examine two variants of this extended scheme – one that reduces the blocking overhead for queries, and another that completely eliminates it. Experiments on image data on a shared-memory multiprocessor show that these schemes achieve up to 2 times higher throughput than existing techniques, and scale well with the number of processors.