公开(公告)号：US08997109B2

公开(公告)日：2015-03-31

申请号：US13585252

申请日：2012-08-14

Applicant: Myung-Cheol Lee ,  Hyun-Hwa Choi ,  Hun-Soon Lee ,  Byoung-Seob Kim ,  Mi-Young Lee

Inventor： Myung-Cheol Lee ,  Hyun-Hwa Choi ,  Hun-Soon Lee ,  Byoung-Seob Kim ,  Mi-Young Lee

IPC: G06F9/46 ,  G06F9/50

CPC classification number: G06F9/5038 ,  G06F9/505

Abstract: Disclosed herein are an apparatus and method for managing a data stream distributed parallel processing service. The apparatus includes a service management unit, a Quality of Service (QoS) monitoring unit, and a scheduling unit. The service management unit registers a plurality of tasks constituting the data stream distributed parallel processing service. The QoS monitoring unit gathers information about the load of the plurality of tasks and information about the load of a plurality of nodes constituting a cluster which provides the data stream distributed parallel processing service. The scheduling unit arranges the plurality of tasks by distributing the plurality of tasks among the plurality of nodes based on the information about the load of the plurality of tasks and the information about the load of the plurality of nodes.

Abstract translation: 这里公开了一种用于管理分布式并行处理服务的数据流的装置和方法。 该装置包括服务管理单元，服务质量（QoS）监视单元和调度单元。 服务管理单元登记构成数据流分散并行处理服务的多个任务。 QoS监视单元收集关于多个任务的负载的信息和关于构成提供数据流分布式并行处理服务的集群的多个节点的负载的信息。 调度单元基于关于多个任务的负载的信息和关于多个节点的负载的信息，在多个节点之间分配多个任务来配置多个任务。

公开(公告)号：US20100161565A1

公开(公告)日：2010-06-24

申请号：US12543208

申请日：2009-08-18

Applicant: Hun Soon LEE ,  Byoung Seob Kim ,  Mi Young Lee

Inventor： Hun Soon LEE ,  Byoung Seob Kim ,  Mi Young Lee

IPC: G06F17/30

CPC classification number: G06F11/2028 ,  G06F11/1469 ,  G06F11/1471 ,  G06F11/2025 ,  G06F11/203 ,  G06F11/2035 ,  G06F11/2046

Abstract: Provided are a cluster data management system and a method for data restoration using a shared redo log in the cluster data management system. The data restoration method includes collecting service information of a partition served by a failed partition server, dividing redo log files written by the partition server by columns of a table including the partition, restoring data of the partition on the basis of the collected service information and log records of the divided redo log files, and selecting a new partition server that will serve the data-restored partition, and allocating the partition to the selected partition server.

Abstract translation: 提供了一种集群数据管理系统和使用群集数据管理系统中的共享重做日志进行数据恢复的方法。 所述数据恢复方法包括：收集由故障分区服务器服务的分区的服务信息，将由所述分区服务器写入的重做日志文件划分为包括所述分区的表的列，基于所收集的服务信息恢复所述分区的数据;以及 分割重做日志文件的日志记录，并选择一个新的分区服务器，将服务于数据恢复的分区，并将分区分配给所选分区服务器。

公开(公告)号：US06484172B1

公开(公告)日：2002-11-19

申请号：US09497345

申请日：2000-02-03

Applicant: Jang Sun Lee ,  Jin Soo Lee ,  Hun Soon Lee ,  Myung Joon Kim ,  Jae Soo Yoo ,  Seok Il Song ,  Seok Hee Lee

Inventor： Jang Sun Lee ,  Jin Soo Lee ,  Hun Soon Lee ,  Myung Joon Kim ,  Jae Soo Yoo ,  Seok Il Song ,  Seok Hee Lee

IPC: G06F1730

CPC classification number: G06F17/30327 ,  G06F17/30362 ,  Y10S707/99933 ,  Y10S707/99938

Abstract: A concurrency control method for searching the high-dimensional index tree of a database is disclosed. The concurrency control includes: a) adding a root node to the queue and acquiring the shared lock for reinsertion node; b) determining whether the queue is empty or not, fetching a node from the queue and assigning the fetched node as a current node if queue is not empty, releasing the shared lock and terminating the search process if queue is empty; c) acquiring the shared latch in the current node, selecting the lower nodes which are within the query range and adding the selected nodes to the queue if current node is not leaf or to the result set if current node is leaf; and d) returning to the step b).

Abstract translation: 公开了一种用于搜索数据库的高维索引树的并发控制方法。 并发控制包括：a）将根节点添加到队列并获取重新插入节点的共享锁; b）确定队列是否为空，如果队列不为空，则从队列中获取节点并将获取的节点分配为当前节点，如果队列为空，则释放共享锁并终止搜索进程; c）获取当前节点中的共享锁存器，选择查询范围内的下级节点，如果当前节点不为叶，则将所选节点添加到队列中，如果当前节点为叶，则将其添加到队列中; 和d）返回步骤b）。

公开(公告)号：US20110153650A1

公开(公告)日：2011-06-23

申请号：US12838917

申请日：2010-07-19

Applicant: Hun Soon Lee ,  Mi Young Lee

Inventor： Hun Soon Lee ,  Mi Young Lee

IPC: G06F12/06 ,  G06F17/30

CPC classification number: G06F16/10

Abstract: Disclosed are a column-based data managing method and apparatus, and a column-based data searching method. The column-based data managing method includes determining whether the size of the column-group data file exceeds a partitioning threshold, dividing the column-group data if the size exceeds the partitioning threshold, and generating divided column-group data files.

Abstract translation: 公开了一种基于列的数据管理方法和装置以及基于列的数据搜索方法。 基于列的数据管理方法包括：确定列组数据文件的大小是否超过分区阈值，如果大小超过分区阈值，则划分列组数据，并且生成分割的列组数据文件。

公开(公告)号：US20090157624A1

公开(公告)日：2009-06-18

申请号：US12207180

申请日：2008-09-09

Applicant: Kyu-Woong LEE ,  Mi-Young Lee ,  Hun-Soon Lee ,  Myung-Joon Kim

Inventor： Kyu-Woong LEE ,  Mi-Young Lee ,  Hun-Soon Lee ,  Myung-Joon Kim

IPC: G06F17/30 ,  G06F7/06

CPC classification number: G06F16/2264 ,  G06F16/2246

Abstract: Provided are a system and a method for indexing high-dimensional data in parallel in a cluster environment. The system for indexing high-dimensional data in parallel in a cluster environment includes a Spill-tree creation means for creating a Spill-tree using an sampled N-dimensional feature vector, a feature vector division storage means for distributedly storing the N-dimensional feature vector in a terminal node of the Spill-tree, and a local signature creation means for creating and managing a local signature for the N-dimensional feature vector dispersed into each node of the Spill-tree.

Abstract translation: 提供了一种用于在集群环境中并行索引高维数据的系统和方法。 用于在群集环境中并行索引高维数据的系统包括：使用采样的N维特征向量创建溢出树的溢出树创建装置，用于分布式地存储N维特征的特征向量分割存储装置 向量，以及本地签名创建装置，用于创建和管理分散到溢出树的每个节点中的N维特征向量的本地签名。

公开(公告)号：US20080133465A1

公开(公告)日：2008-06-05

申请号：US11949740

申请日：2007-12-03

Applicant: Hun-Soon LEE ,  Jun-KI MIN ,  MI-Young LEE ,  Myung-Joon KIM

Inventor： Hun-Soon LEE ,  Jun-KI MIN ,  MI-Young LEE ,  Myung-Joon KIM

IPC: G06F17/30

CPC classification number: G06F16/835

Abstract: Provided is a continuous query processing apparatus and method using operation sharable among multiple queries on an Extensible Markup Language (XML) data stream. The apparatus, includes: a storing unit for storing a sharable operation result; a syntactic analyzation unit for performing a syntactic analysis on the registered continuous query; a semantic analyzation unit for analyzing the meaning upon receiving a syntactic analysis result from the syntactic analyzation unit; a sharable operation extracting unit for extracting a sharable operation upon receiving a semantic analysis result from the semantic analyzation unit; and a query execution unit for storing the result of the extracted sharable operation in the storing unit and performing the continuous queries on an XML data stream based on the result of the semantic analysis and the result of the sharable operation stored in the storing unit.

Abstract translation: 提供了一种使用在可扩展标记语言（XML）数据流上的多个查询之间可共享的操作的连续查询处理装置和方法。 该装置包括：存储单元，用于存储可共享的运算结果; 句法分析单元，用于对所登记的连续查询进行句法分析; 语义分析单元，用于在从语法分析单元接收到句法分析结果时分析该含义; 共享操作提取单元，用于在从所述语义分析单元接收到语义分析结果时提取可共享操作; 以及查询执行单元，用于将提取的可共享操作的结果存储在存储单元中，并且基于存储在存储单元中的语义分析的结果和可共享操作的结果对XML数据流执行连续查询。

公开(公告)号：US20070136239A1

公开(公告)日：2007-06-14

申请号：US11607279

申请日：2006-11-29

Applicant: Hun-Soon Lee ,  Mi-Young Lee ,  Myung-Joon Kim

Inventor： Hun-Soon Lee ,  Mi-Young Lee ,  Myung-Joon Kim

IPC: G06F17/30

CPC classification number: G06F17/30548 ,  G06F17/30923 ,  Y10S707/99931 ,  Y10S707/99934

Abstract: Provided is a stream data processing system and method for avoiding duplication of data process. The system including: an evaluation result storing unit for updating and storing a query condition evaluation result; a window evaluating unit for performing window evaluation; a data separating unit for separating data into new data and duplication input data; a reuse result extracting unit for receiving duplication input data from the data separating unit and extracting a query condition evaluation result; a query condition evaluating unit for receiving new data from the data separating unit, performing query condition evaluation and creating a query condition evaluation result; and a result organizing unit for receiving the query condition evaluation result, merging, outputting and transmitting the query condition evaluation result to the evaluation result storing unit.

Abstract translation: 提供了一种用于避免数据处理重复的流数据处理系统和方法。 该系统包括：评估结果存储单元，用于更新和存储查询条件评估结果; 用于执行窗口评估的窗口评估单元; 用于将数据分离成新数据和复制输入数据的数据分离单元; 重用结果提取单元，用于从数据分离单元接收复制输入数据并提取查询条件评估结果; 查询条件评估单元，用于从数据分离单元接收新数据，执行查询条件评估和创建查询条件评估结果; 以及结果组织单元，用于接收查询条件评估结果，合并，输出并将查询条件评估结果发送到评估结果存储单元。

公开(公告)号：US07174417B2

公开(公告)日：2007-02-06

申请号：US10706933

申请日：2003-11-14

Applicant: Hong Yeon Kim ,  Hun Soon Lee ,  June Kim ,  Myung-Joon Kim

Inventor： Hong Yeon Kim ,  Hun Soon Lee ,  June Kim ,  Myung-Joon Kim

IPC: G06F12/00

CPC classification number: G06F12/0815

Abstract: A cache consistency maintenance procedure to select one of a detection-based cache consistency maintenance procedure optimized for record-based locking and an avoidance-based consistency-based maintenance procedure optimized for table and block-based locking. To support the characteristic of DBMS in which table locking and record locking are consistent to access the same table, the two kinds of the consistency maintenance policies for the same block are processed by a single buffer load process and the two kinds of the consistency maintenance policies are consistent with each other to provide better configuration and performance.

Abstract translation: 缓存一致性维护程序，用于选择针对基于记录的锁定优化的基于检测的缓存一致性维护过程之一，以及针对基于表和块的锁定优化的基于回避的基于一致性的维护过程。 为了支持DBMS的特征，表锁定和记录锁定与访问相同的表一致，同一块的两种一致性维护策略由单个缓冲区加载过程和两种一致性维护策略 相互一致，提供更好的配置和性能。

公开(公告)号：US06631385B2

公开(公告)日：2003-10-07

申请号：US09497136

申请日：2000-02-03

Applicant: Jang Sun Lee ,  June Kim ,  Hun Soon Lee ,  Myung Joon Kim ,  Gil Rok Oh ,  Jae Soo Yoo ,  Seok Il Song

Inventor： Jang Sun Lee ,  June Kim ,  Hun Soon Lee ,  Myung Joon Kim ,  Gil Rok Oh ,  Jae Soo Yoo ,  Seok Il Song

IPC: G06F1730

CPC classification number: G06F11/1474 ,  Y10S707/99933 ,  Y10S707/99953

Abstract: A recovery method for a high-dimensional index structure is disclosed, in which a reinsert operation is employed based on ARIES (algorithm for recovery and isolation exploiting semantics) and a page-oriented redo and a logical undo. Further, a recording medium on which a program for carrying out the above method is recorded is disclosed, the program being readable by a computer. The recovery method for a high-dimensional index structure employing a reinsert operation according to the present invention includes the following steps. At a first step, an entry is inserted into a node, a minimum bounding region is adjusted, an overflow is processed, and a log record is stored. At a second step, the log record thus stored is recovered.

Abstract translation: 公开了一种高维度索引结构的恢复方法，其中基于ARIES（用于恢复和隔离开发语义的算法）和面向页面的重做和逻辑撤销来采用重新插入操作。 此外，公开了记录有用于执行上述方法的程序的记录介质，该程序可由计算机读取。 根据本发明的采用重新插入操作的高维索引结构的恢复方法包括以下步骤。 在第一步，将条目插入节点，调整最小边界区域，处理溢出，并存储日志记录。 在第二步，恢复如此存储的日志记录。

公开(公告)号：US06622141B2

公开(公告)日：2003-09-16

申请号：US09865362

申请日：2001-05-25

Applicant: Hun-Soon Lee ,  June Kim ,  Jae-Soo Yoo ,  Seok-Il Song ,  June-Il Pee

Inventor： Hun-Soon Lee ,  June Kim ,  Jae-Soo Yoo ,  Seok-Il Song ,  June-Il Pee

IPC: G06F1730

CPC classification number: G06F17/30333 ,  Y10S707/99934 ,  Y10S707/99935

Abstract: A bulk loading method, for use in a high-dimensional index structure using some parts of dimensions based on an unbalanced binarization scheme, accelerates an index construction and improves a search performance. For the purpose, the bulk loading method calculates a topology of the index by recognizing information for the index to be constructed using a given data set, splits the given data set into sub-sets of data by repeatedly performing an establishment of a split strategy and a binarization based on the calculated topology of the index, if a leaf node is derived from the sub-sets of data divided through a top-down recursive split process, reflects a minimum bounding region of the leaf node on a higher node, and, if a non-leaf node is generated, repeatedly performing the above processes for another sub-set of data to thereby produce a final root node.