HashTree: A New Hybrid Index for Flash Disks

Cui, Kai; Jin, Peiquan; Yue, Lihua

doi:10.1109/apweb.2010.67

Cited by 3 publications

(3 citation statements)

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“…Therefore, when we implement the B+-tree for SSD, the updates on the tree will cause many random writes and in turn worsen the overall time performance and shorten the lifetime of SSD. In order to reduce random writes on the B+-tree for SSD, some work utilizes the asymmetric I/O property of SSD and employs the policy of using more reads for less writes [11,18,19]. The work in [18] uses overflow nodes to delay the updates on leaf nodes.…”

Section: Related Workmentioning

confidence: 99%

“…Then, based on the method in [18], researchers propose an improved method in [19] to reduce the reading costs by keeping the records orderly in leaf nodes. In the literature [11], the authors propose a hash index with each bucket organized as a B+-tree. This method decreases the number of splits/merges by distributing the keys into the B+-trees in different buckets.…”

Section: Related Workmentioning

confidence: 99%

“…So far, there are many SSD-aware tree indices proposed, such as Hash-tree [11], LATree [12], FD-tree [13,14], FlashDB [15], etc. However, these SSD-aware indices are not suitable for the hybrid storage systems involving both SSD and HDD.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing B+-tree for hybrid storage systems

Jin

Yang

Yue

2014

Distrib Parallel Databases

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Flash-memory-based solid state drives (SSD) have been widely used in computer systems. Due to the high price and some specific features of SSD such as asymmetric read/write speeds and limited erasure endurance, it has been a very common solution, e.g., in modern data centers, to use hybrid storage systems involving SSD and traditional hard disks (HDD). However, the SSD/HDD-based hybrid storage systems introduce some new problems in the indexing schemes for data management. In this paper, we propose a new B+-tree-based index for such hybrid storage systems, which is called HybridB tree. The HybridB tree aims to reduce the random writes to SSD while keeping high time performance and low buffer costs. Particularly, we introduce a new design called huge leaf to avoid the splits and merges on B+-tree. A huge leaf node contains two or more leaf nodes in different states. We place the leaf nodes on HDD or SSD according to their current states, and dynamically adapt the states of leaf nodes when they are read or updated. After a detailed explanation on the structure and operations of the HybridB tree, we give a theoretical analysis on the costs of the HybridB tree. Then, we conduct experiments on two TPC-C traces, using a real hybrid storage system including one HDD and two SSDs, and compare the performance of our proposal with two implementations of B+-tree, namely the B+-tree on HDD and the B+-tree on SSD/HDD. The results show that our proposal has the best time performance and the fewest buffer costs. Moreover, our proposal is able to effectively reduce the random writes to SSD.

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