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    • 1. 发明申请
    • Parallel partition-wise aggregation
    • 并行分区聚合
    • US20060182046A1
    • 2006-08-17
    • US11060260
    • 2005-02-16
    • Benoit DagevilleBhaskar GhoshRushan ChenThierry CruanesMohamed Zait
    • Benoit DagevilleBhaskar GhoshRushan ChenThierry CruanesMohamed Zait
    • H04L12/16H04Q11/00
    • G06F9/4494
    • Techniques are provided for performing a parallel aggregation operation on data that resides in a container, such as a relational table. During generation of the execution plan for the operation, it is determined whether partition-wise aggregation should be performed, based on the grouping keys involved in the aggregation and the partition keys used to partition the container. If partition-wise aggregation is to be performed, then the assignments given to the slave processes that are assigned to scan a container are made on a partition-wise basis. The scan slaves themselves may perform full or partial aggregation (depending on whether they are the only scan slaves assigned to the partition). If the scan slaves perform no aggregation, or only partial aggregation, then the scan slaves redistribute the data items to aggregation slaves that are local to the scan slaves.
    • 提供了用于对驻留在诸如关系表的容器中的数据执行并行聚合操作的技术。 在生成操作的执行计划时,基于聚合中涉及的分组密钥和用于分区容器的分区密钥,确定是否应该执行分区聚合。 如果要执行分区聚合,则分配给分配给扫描容器的从属进程的分配是以分区方式进行的。 扫描从站本身可以执行完全或部分聚合(取决于它们是否是分配给分区的唯一扫描从站)。 如果扫描从站不执行聚合或仅执行部分聚合,则扫描从站将数据项重新分配到扫描从站本地的聚合从站。
    • 5. 发明授权
    • Parallel partition-wise aggregation
    • 并行分区聚合
    • US07779008B2
    • 2010-08-17
    • US11060260
    • 2005-02-16
    • Benoit DagevilleBhaskar GhoshRushan ChenThierry CruanesMohamed Zait
    • Benoit DagevilleBhaskar GhoshRushan ChenThierry CruanesMohamed Zait
    • G06F17/30
    • G06F9/4494
    • Techniques are provided for performing a parallel aggregation operation on data that resides in a container, such as a relational table. During generation of the execution plan for the operation, it is determined whether partition-wise aggregation should be performed, based on the grouping keys involved in the aggregation and the partition keys used to partition the container. If partition-wise aggregation is to be performed, then the assignments given to the slave processes that are assigned to scan a container are made on a partition-wise basis. The scan slaves themselves may perform full or partial aggregation (depending on whether they are the only scan slaves assigned to the partition). If the scan slaves perform no aggregation, or only partial aggregation, then the scan slaves redistribute the data items to aggregation slaves that are local to the scan slaves.
    • 提供了用于对驻留在诸如关系表的容器中的数据执行并行聚合操作的技术。 在生成操作的执行计划时,基于聚合中涉及的分组密钥和用于分区容器的分区密钥,确定是否应该执行分区聚合。 如果要执行分区聚合,则分配给分配给扫描容器的从属进程的分配是以分区方式进行的。 扫描从站本身可以执行完全或部分聚合(取决于它们是否是分配给分区的唯一扫描从站)。 如果扫描从站不执行聚合或仅执行部分聚合,则扫描从站将数据项重新分配到扫描从站本地的聚合从站。
    • 7. 发明授权
    • Executing filter subqueries using a parallel single cursor model
    • 使用并行单光标模型执行过滤器子查询
    • US07958160B2
    • 2011-06-07
    • US10841991
    • 2004-05-06
    • Bhaskar GhoshThierry CruanesRushan ChenShrikanth Shankar
    • Bhaskar GhoshThierry CruanesRushan ChenShrikanth Shankar
    • G06F17/30
    • G06F17/30445
    • Techniques are provided for generating execution plans for, and executing, database statements that contain filter subqueries. Upon receiving a database statement that contains a filter subquery, the database server builds an execution plan that includes a filter operation that is fed by a subtree that corresponds to the subquery. The database server performs a cost analysis to determine whether (1) the filter operation should be parallelized, and (2) the subquery tree should be parallelized. Techniques are also described for generating plans and executing queries where (1) both the filter operation and the subquery subtree are parallelized, (2) the filter operation is parallelized but the subquery subtree operation is performed serially, and (3) the filter operation is performed serially but the subquery subtree operation is parallelized.
    • 提供了技术来生成包含过滤器子查询的数据库语句的执行计划和执行。 在收到包含过滤器子查询的数据库语句之后,数据库服务器构建一个执行计划,其中包含由子查询对应的子树进行的过滤操作。 数据库服务器执行成本分析来确定(1)是否应该并行化过滤器操作,以及(2)子查询树应该并行化。 还描述了用于生成计划和执行查询的技术,其中(1)过滤器操作和子查询子树都被并行化,(2)过滤操作并行化,但是子查询子树操作被串行执行,并且(3)过滤器操作 串行执行子查询子树操作并行化。
    • 8. 发明申请
    • Executing filter subqueries using a parallel single cursor model
    • 使用并行单光标模型执行过滤器子查询
    • US20050131877A1
    • 2005-06-16
    • US10841991
    • 2004-05-06
    • Bhaskar GhoshThierry CruanesRushan ChenShrikanth Shankar
    • Bhaskar GhoshThierry CruanesRushan ChenShrikanth Shankar
    • G06F7/00G06F17/30
    • G06F17/30445
    • Techniques are provided for generating execution plans for, and executing, database statements that contain filter subqueries. Upon receiving a database statement that contains a filter subquery, the database server builds an execution plan that includes a filter operation that is fed by a subtree that corresponds to the subquery. The database server performs a cost analysis to determine whether (1) the filter operation should be parallelized, and (2) the subquery tree should be parallelized. Techniques are also described for generating plans and executing queries where (1) both the filter operation and the subquery subtree are parallelized, (2) the filter operation is parallelized but the subquery subtree operation is performed serially, and (3) the filter operation is performed serially but the subquery subtree operation is parallelized.
    • 提供了技术来生成包含过滤器子查询的数据库语句的执行计划和执行。 在收到包含过滤器子查询的数据库语句之后,数据库服务器构建一个执行计划,其中包含由子查询对应的子树进行的过滤操作。 数据库服务器执行成本分析来确定(1)是否应该并行化过滤器操作,以及(2)子查询树应该并行化。 还描述了用于生成计划和执行查询的技术,其中(1)过滤器操作和子查询子树都被并行化,(2)过滤操作并行化,但是子查询子树操作被串行执行,并且(3)过滤器操作 串行执行子查询子树操作并行化。
    • 9. 发明授权
    • Dynamic and scalable parallel processing of sequence operations
    • 动态和可扩展的并行处理序列操作
    • US07089356B1
    • 2006-08-08
    • US10302207
    • 2002-11-21
    • Rushan ChenBhaskar Ghosh
    • Rushan ChenBhaskar Ghosh
    • G06F12/06
    • G06F17/30445
    • A method is described for parallel processing of sequence operations, in which contention for the sequence operation is reduced among multiple parallel processes. Contention is reduced by caching sequence values locally for each parallel process. Each process accesses the sequence operation, or an instance level cache of sequence values, in a batched manner, thereby returning a block of unique sequence values instead of a single sequence value. The block of sequence values, or at least information that indicates a range of sequence values that define the block, is then cached locally in association with a given process of the multiple processes. Hence, future requests for sequence values from the given process are serviced from the local cache, rather than having to access the sequence operation and risk contention for the operation with other processes.
    • 描述了用于并行处理序列操作的方法,其中在多个并行进程中减少了对顺序操作的争用。 通过为每个并行进程本地缓存序列值来减少争用。 每个进程以批量方式访问序列操作或序列值的实例级高速缓存,从而返回唯一序列值的块而不是单个序列值。 序列值块或至少指示定义块的序列值范围的信息随后与多个进程的给定进程相关联地本地缓存。 因此,来自给定进程的对序列值的未来请求从本地缓存服务,而不是必须访问序列操作和与其他进程的操作的风险争用。
    • 10. 发明申请
    • REAL TIME ANALYTICS VIA STREAM PROCESSING
    • 实时分析通过流程处理
    • US20130339473A1
    • 2013-12-19
    • US13829119
    • 2013-03-14
    • Daniel McCaffreyMichael FanRushan Chen
    • Daniel McCaffreyMichael FanRushan Chen
    • H04L12/863
    • H04L47/62H04L49/90H04L67/22
    • Real time analytics via stream processing is described. A stream reader receives a stream of messages and batches the messages in a message queue. A stream writer accesses the messages from the message queue, aggregates the messages from a time window based on a hierarchy of an attribute to generate a set of event data for the time window, stores the set of event data in a memory cache cluster, and stores a key corresponding to the set of event data in a key buffer queue. A stream aggregator accesses the key from the key buffer queue, retrieves the set of data in the time window corresponding to the key from the memory cache cluster, and performs a process on the retrieved set of data.
    • 描述通过流处理的实时分析。 流读取器接收消息流并在消息队列中分批消息。 流写入器从消息队列访问消息,基于属性的层次结构从时间窗口聚合消息以生成时间窗口的事件数据集,将事件数据集存储在存储器高速缓存集群中,以及 将与该组事件数据相对应的密钥存储在密钥缓冲器队列中。 流聚合器从密钥缓冲区队列中访问密钥,从存储器缓存集群中检索对应于密钥的时间窗口中的数据集,并对检索到的数据集进行处理。