As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems （MMDBs）. Indexing technique is a key component of MMDBs. Unfo...As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems （MMDBs）. Indexing technique is a key component of MMDBs. Unfortunately, the predominant indexes -B^＋-trees and T-trees -- have been shown to utilize cache poorly, which triggers the development of many cache-conscious indexes, such as CSB^＋-trees and pB^＋-trees. Most of these cache-conscious indexes are variants of conventional B^＋-trees, and have better cache performance than B^＋-trees. In this paper, we develop a novel J^＋-tree index, inspired by the Judy structure which is an associative array data structure, and propose a more cacheoptimized index -- Prefetching J^＋-tree （pJ^＋-tree）, which applies prefetching to J^＋-tree to accelerate range scan operations. The J^＋-tree stores all the keys in its leaf nodes and keeps the reference values of leaf nodes in a Judy structure, which makes J^＋-tree not only hold the advantages of Judy （such as fast single value search） but also outperform it in other aspects. For example, J^＋-trees can achieve better performance on range queries than Judy. The pJ^＋-tree index exploits prefetching techniques to further improve the cache behavior of J^＋-trees and yields a speedup of 2.0 on range scans. Compared with B^＋-trees, CSB^＋-trees, pB^＋-trees and T-trees, our extensive experimental Study shows that pJ^＋-trees can provide better performance on both time （search, scan, update） and space aspects.展开更多
With the rapid increasing capacity of flash memory, flash-aware indexing techniques are highly desirable for flash devices. The unique features of flash memory, such as the erase-before-write constraint and the asymme...With the rapid increasing capacity of flash memory, flash-aware indexing techniques are highly desirable for flash devices. The unique features of flash memory, such as the erase-before-write constraint and the asymmetric read/write cost, severely deteriorate the performance of the traditional B＋-tree algorithm. In this paper, we propose an optimized indexing method, called lazy-update B＋-tree, to overcome the limitations of flash memory. The basic idea is to defer the committing of update requests to the B^-tree by buffering them in a segment of main memory. They are later committed in groups so that the cost of each write operation can be amortized by a bunch of update requests. We identify a victim selection problem for the lazy-update B＋-tree and develop two heuristic-based commit policies to address this problem. Simulation results show that the proposed lazy-update method, along with a well-designed commit policy, greatly improves the update performance of the traditional B＋-tree while preserving the query efficiency.展开更多
基金supported by a grant from HP Lab China,and the National Natural Science Foundation of China under Grant Nos.60496325 and 60573092
文摘As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems （MMDBs）. Indexing technique is a key component of MMDBs. Unfortunately, the predominant indexes -B^＋-trees and T-trees -- have been shown to utilize cache poorly, which triggers the development of many cache-conscious indexes, such as CSB^＋-trees and pB^＋-trees. Most of these cache-conscious indexes are variants of conventional B^＋-trees, and have better cache performance than B^＋-trees. In this paper, we develop a novel J^＋-tree index, inspired by the Judy structure which is an associative array data structure, and propose a more cacheoptimized index -- Prefetching J^＋-tree （pJ^＋-tree）, which applies prefetching to J^＋-tree to accelerate range scan operations. The J^＋-tree stores all the keys in its leaf nodes and keeps the reference values of leaf nodes in a Judy structure, which makes J^＋-tree not only hold the advantages of Judy （such as fast single value search） but also outperform it in other aspects. For example, J^＋-trees can achieve better performance on range queries than Judy. The pJ^＋-tree index exploits prefetching techniques to further improve the cache behavior of J^＋-trees and yields a speedup of 2.0 on range scans. Compared with B^＋-trees, CSB^＋-trees, pB^＋-trees and T-trees, our extensive experimental Study shows that pJ^＋-trees can provide better performance on both time （search, scan, update） and space aspects.
基金supported by the Research Grants Council of Hong Kong under Grant No. HKBU210808the National Natural Science Foundation of China under Grant No. 60833005
文摘With the rapid increasing capacity of flash memory, flash-aware indexing techniques are highly desirable for flash devices. The unique features of flash memory, such as the erase-before-write constraint and the asymmetric read/write cost, severely deteriorate the performance of the traditional B＋-tree algorithm. In this paper, we propose an optimized indexing method, called lazy-update B＋-tree, to overcome the limitations of flash memory. The basic idea is to defer the committing of update requests to the B^-tree by buffering them in a segment of main memory. They are later committed in groups so that the cost of each write operation can be amortized by a bunch of update requests. We identify a victim selection problem for the lazy-update B＋-tree and develop two heuristic-based commit policies to address this problem. Simulation results show that the proposed lazy-update method, along with a well-designed commit policy, greatly improves the update performance of the traditional B＋-tree while preserving the query efficiency.
