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公开(公告)号：US07937428B2
公开(公告)日：2011-05-03
申请号：US11614844
申请日：2006-12-21
IPC分类号： G06F17/10
CPC分类号： G06F12/0864
摘要： A dynamic Bloom filter comprises a cascaded set of Bloom filters. The system estimates or guesses a cardinality of input items, selects a number of hash functions based on the desired false positive rate, and allocates memory for an initial Bloom filter based on the estimated cardinality and desired false positive rate. The system inserts items into the initial Bloom filter and counts the bits set as they are inserted. If the number of bits set in the current Bloom filter reaches a predetermined target, the system declares the current Bloom filter full. The system recursively generates additional Bloom filters as needed for items remaining after the initial Bloom filter is filled; items are checked to eliminate duplicates. Each of the set of Bloom filters is individually queried to identify a positive or negative in response to a query. When the system is configured such that the false positive rate of each successive Bloom filter is decreased by one half, the system guarantees a false positive rate of at most twice the desired false positive rate.
摘要翻译： 一个动态的Bloom过滤器包括一个级联的Bloom过滤器。 系统估计或猜测输入项的基数，基于所需的假阳性率选择多个散列函数，并且基于估计的基数和期望的假阳性率为初始布隆过滤器分配存储器。 系统将项目插入到初始布隆过滤器中，并对插入的位进行计数。 如果当前布隆过滤器中设置的位数达到预定目标，则系统将声明当前布隆过滤器已满。 系统会根据需要在初始布隆过滤器填充后剩余的项目递归地生成其他布隆过滤器; 检查项目以消除重复。 每一组Bloom过滤器都被单独查询以识别响应于查询的正或负值。 当系统被配置为使得每个连续的Bloom过滤器的假阳性率减少一半时，系统保证假阳性率为期望假阳性率的两倍。
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公开(公告)号：US20080154852A1
公开(公告)日：2008-06-26
申请号：US11614844
申请日：2006-12-21
CPC分类号： G06F12/0864
摘要： A dynamic Bloom filter comprises a cascaded set of Bloom filters. The system estimates or guesses a cardinality of input items, selects a number of hash functions based on the desired false positive rate, and allocates memory for an initial Bloom filter based on the estimated cardinality and desired false positive rate. The system inserts items into the initial Bloom filter and counts the bits set as they are inserted. If the number of bits set in the current Bloom filter reaches a predetermined target, the system declares the current Bloom filter full. The system recursively generates additional Bloom filters as needed for items remaining after the initial Bloom filter is filled; items are checked to eliminate duplicates. Each of the set of Bloom filters is individually queried to identify a positive or negative in response to a query. When the system is configured such that the false positive rate of each successive Bloom filter is decreased by one half, the system guarantees a false positive rate of at most twice the desired false positive rate.
摘要翻译： 一个动态的Bloom过滤器包括一个级联的Bloom过滤器。 系统估计或猜测输入项的基数，基于所需的假阳性率选择多个散列函数，并且基于估计的基数和期望的假阳性率为初始布隆过滤器分配存储器。 系统将项目插入到初始布隆过滤器中，并对插入的位进行计数。 如果当前布隆过滤器中设置的位数达到预定目标，则系统将声明当前布隆过滤器已满。 系统会根据需要在初始布隆过滤器填充后剩余的项目递归地生成其他布隆过滤器; 检查项目以消除重复。 每一组Bloom过滤器都被单独查询以识别响应于查询的正或负值。 当系统被配置为使得每个连续的Bloom过滤器的假阳性率减少一半时，系统保证假阳性率为期望假阳性率的两倍。
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公开(公告)号：US08209368B2
公开(公告)日：2012-06-26
申请号：US12134148
申请日：2008-06-05
IPC分类号： G06F17/10
CPC分类号： G06F12/0864
摘要： A dynamic Bloom filter comprises a cascaded set of Bloom filters. The system estimates or guesses a cardinality of input items, selects a number of hash functions based on the desired false positive rate, and allocates memory for an initial Bloom filter based on the estimated cardinality and desired false positive rate. The system inserts items into the initial Bloom filter and counts the bits set as they are inserted. If the number of bits set in the current Bloom filter reaches a predetermined target, the system declares the current Bloom filter full. The system recursively generates additional Bloom filters as needed for items remaining after the initial Bloom filter is filled; items are checked to eliminate duplicates. Each of the set of Bloom filters is individually queried to identify a positive or negative in response to a query. When the system is configured such that the false positive rate of each successive Bloom filter is decreased by one half, the system guarantees a false positive rate of at most twice the desired false positive rate.
摘要翻译： 一个动态的Bloom过滤器包括一个级联的Bloom过滤器。 系统估计或猜测输入项的基数，基于所需的假阳性率选择多个散列函数，并且基于估计的基数和期望的假阳性率为初始布隆过滤器分配存储器。 系统将项目插入到初始布隆过滤器中，并对插入的位进行计数。 如果当前布隆过滤器中设置的位数达到预定目标，则系统将声明当前布隆过滤器已满。 系统会根据需要在初始布隆过滤器填充后剩余的项目递归地生成其他布隆过滤器; 检查项目以消除重复。 每一组Bloom过滤器都被单独查询以识别响应于查询的正或负。 当系统被配置为使得每个连续的Bloom过滤器的假阳性率减少一半时，系统保证假阳性率为期望假阳性率的两倍。
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公开(公告)号：US08032732B2
公开(公告)日：2011-10-04
申请号：US12134125
申请日：2008-06-05
IPC分类号： G06F12/00
CPC分类号： G06F17/10
摘要： A cache-aware Bloom filter system segments a bit vector of a cache-aware Bloom filter into fixed-size blocks. The system hashes an item to be inserted into the cache-aware Bloom filter to identify one of the fixed-size blocks as a selected block for receiving the item and hashes the item k times to generate k hashed values for encoding the item for insertion in the in the selected block. The system sets bits within the selected block with addresses corresponding to the k hashed values such that accessing the item in the cache-aware Bloom filter requires accessing only the selected block to check the k hashed values. The size of the fixed-size block corresponds to a cache-line size of an associated computer architecture on which the cache-aware Bloom filter is installed.
摘要翻译： 一个缓存感知的Bloom过滤器系统将缓存感知的Bloom过滤器的位向量分成固定大小的块。 系统将要插入到缓存感知的布隆过滤器中的项目进行散列，以将固定大小块之一识别为用于接收项目的选定块，并将项目k次哈希，以产生用于编码项目以插入的k个哈希值 在所选的块中。 系统在所选择的块内设置与k个哈希值相对应的地址的位，使得访问缓存感知的Bloom过滤器中的项目只需要访问所选择的块来检查k个哈希值。 固定大小块的大小对应于其上安装有缓存感知布隆过滤器的关联计算机体系结构的高速缓存行大小。
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公开(公告)号：US20080155229A1
公开(公告)日：2008-06-26
申请号：US11614790
申请日：2006-12-21
IPC分类号： G06F9/34
CPC分类号： G06F17/10
摘要： A cache-aware Bloom filter system segments a bit vector of a cache-aware Bloom filter into fixed-size blocks. The system hashes an item to be inserted into the cache-aware Bloom filter to identify one of the fixed-size blocks as a selected block for receiving the item and hashes the item k times to generate k hashed values for encoding the item for insertion in the in the selected block. The system sets bits within the selected block with addresses corresponding to the k hashed values such that accessing the item in the cache-aware Bloom filter requires accessing only the selected block to check the k hashed values. The size of the fixed-size block corresponds to a cache-line size of an associated computer architecture on which the cache-aware Bloom filter is installed.
摘要翻译： 一个缓存感知的Bloom过滤器系统将缓存感知的Bloom过滤器的位向量分成固定大小的块。 系统将要插入到缓存感知的布隆过滤器中的项目进行散列，以将固定大小块之一识别为用于接收项目的选定块，并将项目k次哈希，以产生用于编码项目以插入的k个哈希值 在所选的块中。 系统在所选择的块内设置与k个哈希值相对应的地址的位，使得访问缓存感知的Bloom过滤器中的项目只需要访问所选择的块来检查k个哈希值。 固定大小块的大小对应于其上安装有缓存感知布隆过滤器的关联计算机体系结构的高速缓存行大小。
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6.发明授权公开(公告)号：US07991771B2
公开(公告)日：2011-08-02
申请号：US11561949
申请日：2006-11-21
IPC分类号： G06F17/30
CPC分类号： G06F17/30672
摘要： Disclosed is an evaluation technique for text search with black-box scoring functions, where it is unnecessary for the evaluation engine to maintain details of the scoring function. Included is a description of a system for dealing with blackbox searching, proofs of correctness, as well experimental evidence showing that the performance of the technique is comparable in efficiency to those techniques used in custom-built engines.
摘要翻译： 公开了一种用于具有黑匣子评分功能的文本搜索的评估技术，其中评估引擎不需要保持评分功能的细节。 包括处理黑箱搜索的系统的描述，正确性的证明，以及实验证据表明该技术的性能与定制引擎中使用的技术的效率相当。
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公开(公告)号：US20080243941A1
公开(公告)日：2008-10-02
申请号：US12134125
申请日：2008-06-05
IPC分类号： G06F12/00
CPC分类号： G06F17/10
摘要： A cache-aware Bloom filter system segments a bit vector of a cache-aware Bloom filter into fixed-size blocks. The system hashes an item to be inserted into the cache-aware Bloom filter to identify one of the fixed-size blocks as a selected block for receiving the item and hashes the item k times to generate k hashed values for encoding the item for insertion in the in the selected block. The system sets bits within the selected block with addresses corresponding to the k hashed values such that accessing the item in the cache-aware Bloom filter requires accessing only the selected block to check the k hashed values. The size of the fixed-size block corresponds to a cache-line size of an associated computer architecture on which the cache-aware Bloom filter is installed.
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公开(公告)号：US20110113010A1
公开(公告)日：2011-05-12
申请号：US12616679
申请日：2009-11-11
申请人： Ronald J. Barber , Harish Deshmukh , Ning Li , Bruce G. Lindsay , Sridhar Rajagopalan , Roger C. Raphael , Eugene J. Shekita
发明人： Ronald J. Barber , Harish Deshmukh , Ning Li , Bruce G. Lindsay , Sridhar Rajagopalan , Roger C. Raphael , Eugene J. Shekita
CPC分类号： G06F17/30578 , G06F17/30545
摘要： Systems, methods and articles of manufacture are disclosed for synchronizing a primary data system with an auxiliary data system that processes data for the primary data system. In one embodiment, how current the primary data system and the auxiliary data system are may be determined. Requests sent from the primary data system that were not processed by the auxiliary data system may be determined. The requests may be resent to the auxiliary data system for processing.
摘要翻译： 公开了用于使主数据系统与处理主数据系统的数据的辅助数据系统同步的系统，方法和制品。 在一个实施例中，可以确定主数据系统和辅助数据系统的当前时间。 可以确定从主数据系统发送的未被辅助数据系统处理的请求。 请求可以重新发送到辅助数据系统进行处理。
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9.发明申请Adaptive Evaluation of Text Search Queries With Blackbox Scoring Functions 失效使用Blackbox评分函数自适应评估文本搜索查询公开(公告)号：US20070150467A1
公开(公告)日：2007-06-28
申请号：US11561949
申请日：2006-11-21
申请人： Kevin Beyer , Robert Lyle , Sridhar Rajagopalan , Eugene Shekita
发明人： Kevin Beyer , Robert Lyle , Sridhar Rajagopalan , Eugene Shekita
IPC分类号： G06F17/30
CPC分类号： G06F17/30672
摘要： Disclosed is an evaluation technique for text search with black-box scoring functions, where it is unnecessary for the evaluation engine to maintain details of the scoring function. Included is a description of a system for dealing with blackbox searching, proofs of correctness, as well experimental evidence showing that the performance of the technique is comparable in efficiency to those techniques used in custom-built engines.
摘要翻译： 公开了一种用于具有黑匣子评分功能的文本搜索的评估技术，其中评估引擎不需要保持评分功能的细节。 包括处理黑箱搜索的系统的描述，正确性的证明，以及实验证据表明该技术的性能与定制引擎中使用的技术的效率相当。
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公开(公告)号：US20050165718A1
公开(公告)日：2005-07-28
申请号：US10764772
申请日：2004-01-26
申请人： Marcus Fontoura , Reiner Kraft , Tony Leung , John McPherson , Andreas Neumann , Runping Qi , Sridhar Rajagopalan , Eugene Shekita , Jason Zien
发明人： Marcus Fontoura , Reiner Kraft , Tony Leung , John McPherson , Andreas Neumann , Runping Qi , Sridhar Rajagopalan , Eugene Shekita , Jason Zien
CPC分类号： G06F17/30864 , Y10S707/99931 , Y10S707/99943
摘要： Disclosed is a technique for building an index in which global analysis computations and index creation are pipelined, wherein the global analysis computations share intermediate results.
摘要翻译： 公开了一种用于构建其中全局分析计算和索引创建被流水线的索引的技术，其中全局分析计算共享中间结果。
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