• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Bloom Filter Based Associative Deletion
【24h】

Bloom Filter Based Associative Deletion

机译：基于Bloom过滤的关联删除

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Bloom filters are widely-used powerful tools for processing set membership queries. However, they are not entirely suitable for many new applications, such as deleting one attribute value according to another attribute value for a set of data objects/items with two correlated attributes. In this paper, we introduce a concept for such an operation, called the associative deletion. To realize this operation, we propose a new Bloom filter data structure, named IABF (Improved Associative deletion Bloom Filter), which keeps the association information on the two correlated attributes of items in the given data set. Based on IABF, we present an algorithm to perform associative deletions, which can be applied to both normal data and streaming data. To further accelerate the operation, we also illustrate a hardware coprocessor implementation for a crucial component of the algorithm. Detailed theoretical analysis and experimental results demonstrate that the presented IABF technique can accurately process associative deletions with controlled false positive and negative rates.
机译：Bloom筛选器是用于处理集合成员资格查询的广泛使用的强大工具。但是，它们并不完全适合于许多新应用程序，例如针对具有两个相关属性的一组数据对象/项目，根据另一个属性值删除一个属性值。在本文中，我们介绍了这种操作的概念，称为关联删除。为了实现此操作，我们提出了一种新的Bloom过滤器数据结构，称为IABF（改进的关联删除Bloom过滤器），该结构将关联信息保留在给定数据集中项目的两个相关属性上。基于IABF，我们提出了一种执行关联删除的算法，该算法可应用于普通数据和流数据。为了进一步加快操作速度，我们还说明了算法关键部分的硬件协处理器实现。详细的理论分析和实验结果表明，所提出的IABF技术可以准确地处理关联删除，且假阳性率和阴性率受控。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号