Lazy-Update B+-Tree for Flash Devices

On, Sai Tung; Hu, Haibo; Liu, Yu; Xu, Jianliang

doi:10.1109/mdm.2009.48

Cited by 19 publications

(7 citation statements)

References 8 publications

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“…For NVM, the large number of writes caused by index updates not only reduces their lifespan but also degrades their performance. To reduce frequent updates and writes of small amounts of data, merge updates [64] or late updates [65], which are frequently used on flash indexes, are typical approaches. Future indexing technologies for NVM should be more effective in controlling the read and write paths and impact areas that result from index updates, as well as enabling layered indexing techniques for the NVM storage hierarchies.…”

Section: Storage and Indexing Techniques In Platforms With New Hardwarementioning

confidence: 99%

The New Hardware Development Trend and the Challenges in Data Management and Analysis

Pan

Zhang

et al. 2018

Data Sci. Eng.

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Hardware techniques and environments underwent significant transformations in the field of information technology, represented by high-performance processors and hardware accelerators characterized by abundant heterogeneous parallelism, nonvolatile memory with hybrid storage hierarchies, and RDMA-enabled high-speed network. Recent hardware trends in these areas deeply affect data management and analysis applications. In this paper, we first introduce the development trend of the new hardware in computation, storage, and network dimensions. Then, the related research techniques which affect the upper data management system design are reviewed. Finally, challenges and opportunities are addressed for the key technologies of data management and analysis in new hardware environments.

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Section: Storage and Indexing Techniques In Platforms With New Hardwarementioning

confidence: 99%

The New Hardware Development Trend and the Challenges in Data Management and Analysis

Pan

Zhang

et al. 2018

Data Sci. Eng.

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“…The entries for old data items are deleted by a garbage cleaner inside the RUMtree. In the lazy-update B + -tree [17], which was designed for flash-based databases, whenever an update arrives, it is temporarily stored in a lazy-update pool. The updates are committed in groups so that each write operation can be amortized by a bunch of updates.…”

Section: Related Workmentioning

confidence: 99%

“…The asymmetric performance in reading and writing a page in flash memory makes it highly important to have an efficient method for managing the index such that the number of writes to flash memory can be minimized. Otherwise, the index management cost could be very expensive [9,[16][17][18][19], especially in CPSes as most of them are write intensive. Furthermore, frequent updates to index nodes also create the wear-out problem requiring a garbage collection mechanism to reclaim invalid pages to be free pages.…”

Section: Introductionmentioning

confidence: 99%

“…Although, in recent years, the design of efficient indexing structures, in particular based on the B + -tree, for flashbased databases has received growing interests [16,17,19], the research on multi-version indexing for flash-based embedded databases has been greatly ignored. Most of the proposed index structures for flash-based databases are concentrated on database systems supporting singleversion of data, i.e., if a data item is updated, the old version of the data item will become non-retrievable.…”

Section: Introductionmentioning

confidence: 99%

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Block-Based Multi-Version B$^+$-Tree for Flash-Based Embedded Database Systems

Wang

Lam

Chang

et al. 2015

IEEE Trans. Comput.

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In this paper, we propose a novel multi-version B + -tree index structure, called block-based multi-version B + -tree (BbMVBT ), for indexing multi-versions of data items in an embedded multi-version database (EMVDB) on flash memory. An EMVDB needs to support streams of update transactions and version-range queries to access different versions of data items maintained in the database. In BbMVBT, the index is divided into two levels. At the higher level, a multi-version index is maintained for keeping successive versions of each data item. These versions are allocated consecutively in a version block. At the lower level, a version array is used to search for a specific data version within a version block. With the reduced index structure of BbMVBT, the overhead for managing the index in processing update operations can be greatly reduced. At the same time, BbMVBT can also greatly reduce the number of accesses to the index in processing versionrange queries. To ensure sufficient free blocks for creating version blocks for efficient execution of BbMVBT, in this paper, we also discuss how to perform garbage collection using the purging-range queries for reclaiming "old" versions of data items and their associated entries in the index nodes. Analysis of the performance of BbMVBT is presented and verified with performance studies using both synthetic and real workloads. The performance results illustrate that BbMVBT can significantly improve the read and write performance to the multi-version index as compared with MVBT even though the sizes of the version blocks are not large.

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“…Transactions over the multiversion B + -tree have also been well investigated [5]. Meanwhile, the management of (single-version) B + -trees over flash memory are extensively discussed in [7,12]. Although these excellent works perform very well on block devices such as hard disks and NAND flash memory, they are not designed to best fit the distinct characteristics of PCM.…”

Section: Introductionmentioning

confidence: 99%

Space-Efficient Multiversion Index Scheme for PCM-based Embedded Database Systems

Kuan

Chang

Huang

et al. 2014

Proceedings of the 51st Annual Design Automation Conference

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Embedded database systems are widely adopted in various control and motoring systems, e.g., cyber-physical systems (CPSes). To support the functionality to access the historical data, a multiversion index is adopted to maintain multiple versions of data items and their index information. However, CPSes are usually batterypowered embedded systems that have limited energy, computing power, and storage space. In this work, we consider the systems with phase-change memory (PCM) as their storage due to its nonvolatility and low energy consumption. In order to resolve the problem of the limited storage space and the fact that existing multiversion index designs are lack of space efficiency, we propose a spaceefficient multiversion index scheme to enhance the space utilization and access performance of embedded multiversion database systems on PCM by utilizing the byte-addressability and write asymmetry of PCM. A series of experiments was conducted to evaluate the efficacy of the proposed scheme. The results show that the proposed scheme achieves very high space utilization and has good performance on serving update transactions and range queries.

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Lazy-Update B+-Tree for Flash Devices

Cited by 19 publications

References 8 publications

The New Hardware Development Trend and the Challenges in Data Management and Analysis

The New Hardware Development Trend and the Challenges in Data Management and Analysis

Block-Based Multi-Version B$^+$-Tree for Flash-Based Embedded Database Systems

Space-Efficient Multiversion Index Scheme for PCM-based Embedded Database Systems

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