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1. 发明授权

US07433886B2 SQL language extensions for modifying collection-valued and scalar valued columns in a single statement 有权
标题翻译：用于在单个语句中修改集合值和标量值的SQL语言扩展
公开(公告)号：US07433886B2
公开(公告)日：2008-10-07
申请号：US10693302
申请日：2003-10-24
申请人： Balaji Rathakrishnan , Stefano Stefani , Aleksandras Surna , Jose A. Blakeley , Oliver Nicholas Seeliger
发明人： Balaji Rathakrishnan , Stefano Stefani , Aleksandras Surna , Jose A. Blakeley , Oliver Nicholas Seeliger
IPC分类号： G06F17/30
CPC分类号： G06F17/30365 , G06F17/30342 , G06F17/30607 , Y10S707/99931 , Y10S707/99932 , Y10S707/99934 , Y10S707/99944
摘要： A system and method for updating collection-valued and other complex structured columns in a nested table using a nested extension of an UPDATE statement that is analogous to the syntax and semantics of the UPDATE statement that is used to modify scalar-valued columns of the table (called the outer UPDATE). Using the same syntactic and semantic constructs as the table at the outer level allows an existing implementation that processes modifications to relational tables to reuse its implementation techniques for processing outer updates to modify collection-valued columns as well. The UPDATE extensions enable the specification of updates to nested collections embedded at arbitrary levels of depth in the object model. The new syntax is embedded inside the outer UPDATE statement in a way that parallels the structure of the data itself and thus maps more directly to the user's conceptual model of the data.
摘要翻译：用于使用类似于用于修改表的标量值列的UPDATE语句的语法和语义的UPDATE语句的嵌套扩展来更新嵌套表中的集合值和其他复杂结构化列的系统和方法（称为外部UPDATE）。使用与外层相同的句法和语义结构允许处理对关系表的修改的现有实现，以重用其实现技术来处理外部更新以修改集合值列。 UPDATE扩展使得能够对对象模型中嵌套在任意深度深度的嵌套集合进行更新。新的语法以外部UPDATE语句的方式嵌入到数据本身的结构中，从而更直接地映射到用户的数据概念模型。

2. 发明申请

US20050091256A1 SQL language extensions for modifying collection-valued and scalar valued columns in a single statement 有权
标题翻译：用于在单个语句中修改集合值和标量值的SQL语言扩展
公开(公告)号：US20050091256A1
公开(公告)日：2005-04-28
申请号：US10693302
申请日：2003-10-24
申请人： Balaji Rathakrishnan , Stefano Stefani , Aleksandras Surna , Jose Blakeley , Oliver Seeliger
发明人： Balaji Rathakrishnan , Stefano Stefani , Aleksandras Surna , Jose Blakeley , Oliver Seeliger
IPC分类号： G06F20060101 , G06F1/00 , G06F17/00
CPC分类号： G06F17/30365 , G06F17/30342 , G06F17/30607 , Y10S707/99931 , Y10S707/99932 , Y10S707/99934 , Y10S707/99944
摘要： A technique for updating collection-valued and other complex structured columns in a nested table using a nested extension of an UPDATE statement that uses syntax and semantics to modify collection-valued columns in a way that is analogous to the syntax and semantics of the UPDATE statement that is used to modify scalar-valued columns of the table (called the outer UPDATE). Using the same syntactic and semantic constructs as the table at the outer level allows an existing implementation that processes modifications to relational tables to reuse its implementation techniques for processing outer updates to modify collection-valued columns as well. The UPDATE extensions enable the specification of updates to nested collections embedded at arbitrary levels of depth in the object model. The new syntax is embedded inside the outer UPDATE statement in a way that parallels the structure of the data itself and thus maps more directly to the user's conceptual model of the data. The method for implementing the UPDATE extensions uses a change descriptor, which is a data structure that aggregates substantially all changes, both scalar and collection-valued into a single value that can be applied to the changed collection-valued column. This technique can also be used for modifications to other kinds of complex-structured columns such as objects or xml. The change descriptor includes hierarchical information for the cell, thereby enabling efficient application of multiple updates at various granularity levels in a single operation and enabling the implementation of efficient index maintenance algorithms by updating only the indexes affected by the UPDATE operation and updating only those index rows that were affected by the UPDATE operation.
摘要翻译：一种用于使用UPDATE语句的嵌套扩展来更新嵌套表中的集合值和其他复杂结构化列的技术，该语法使用语法和语义来以类似于UPDATE语句的语法和语义的方式修改集合值列用于修改表的标量值列（称为外部UPDATE）。使用与外层相同的句法和语义结构允许处理对关系表的修改的现有实现，以重用其实现技术来处理外部更新以修改集合值列。 UPDATE扩展使得能够对对象模型中嵌套在任意深度深度的嵌套集合进行更新。新的语法以外部UPDATE语句的方式嵌入到数据本身的结构中，从而更直接地映射到用户的数据概念模型。实现UPDATE扩展的方法使用一个更改描述符，该描述符是一个数据结构，它将基本上所有的变量（标量和收集值）聚合成一个可以应用到更改的收集值列的值。此技术也可用于修改其他类型的复杂结构列（如对象或xml）。更改描述符包括小区的分层信息，从而能够在单个操作中在各种粒度级别高效地应用多个更新，并且通过仅更新受UPDATE操作影响的索引并仅更新那些索引行，从而实现高效的索引维护算法受UPDATE操作的影响。

3. 发明授权

US07437346B2 Systems and methods for a large object infrastructure in a database system 有权
标题翻译：数据库系统中大对象基础架构的系统和方法
公开(公告)号：US07437346B2
公开(公告)日：2008-10-14
申请号：US10776664
申请日：2004-02-10
申请人： Shrinivas Ashwin , Jose A. Blakeley , Peter Carlin , Jun Fang , Ajay Kalhan , Christian Kleinerman , Stefano Stefani , Aleksandras Surna , Honggang Zhang
发明人： Shrinivas Ashwin , Jose A. Blakeley , Peter Carlin , Jun Fang , Ajay Kalhan , Christian Kleinerman , Stefano Stefani , Aleksandras Surna , Honggang Zhang
IPC分类号： G06F7/00
CPC分类号： G06F17/30504 , Y10S707/99931 , Y10S707/99936 , Y10S707/99943
摘要： Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) which are an internal representation of a large value. BHs are immutable and stateless references to a large data object. The structure of a BH contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.
摘要翻译：本发明的各种实施例直接利用作为大值的内部表示的Blob句柄（BH）。 BH是不可变的和无状态的引用大型数据对象。 BH的结构包含足够的信息来返回ILockBytes接口，以便提供对相应的大数据块的访问，并且BH还可以返回关于其自身寿命描述的信息。可以使用（a）指向BH数据的开始的指针和（b）BH的字节长度来完全描述BH。

4. 发明申请

US20050187893A1 Systems and methods for a large object infrastructure in a database system 有权
标题翻译：数据库系统中大对象基础架构的系统和方法
公开(公告)号：US20050187893A1
公开(公告)日：2005-08-25
申请号：US10776664
申请日：2004-02-10
申请人： Shrinivas Ashwin , Jose Blakeley , Peter Carlin , Jun Fang , Ajay Kalhan , Christian Kleinerman , Stefano Stefani , Aleksandras Surna , Honggang Zhang
发明人： Shrinivas Ashwin , Jose Blakeley , Peter Carlin , Jun Fang , Ajay Kalhan , Christian Kleinerman , Stefano Stefani , Aleksandras Surna , Honggang Zhang
IPC分类号： G06F7/00
CPC分类号： G06F17/30504 , Y10S707/99931 , Y10S707/99936 , Y10S707/99943
摘要： Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) which are an internal representation of a large value. BHs are immutable and stateless references to a large data object. The structure of a BH contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.
摘要翻译：本发明的各种实施例直接利用作为大值的内部表示的Blob句柄（BH）。 BH是不可变的和无状态的引用大型数据对象。 BH的结构包含足够的信息来返回ILockBytes接口，以便提供对相应的大数据块的访问，并且BH还可以返回关于其自身寿命描述的信息。可以使用（a）指向BH数据的开始的指针和（b）BH的字节长度来完全描述BH。

5. 发明申请

US20110276607A1 NORMALIZING DATA FOR FAST SUPERSCALAR PROCESSING 有权
标题翻译：正规化数据进行快速超级处理
公开(公告)号：US20110276607A1
公开(公告)日：2011-11-10
申请号：US12773889
申请日：2010-05-05
申请人： Aleksandras Surna , Erik Ismert , Srikumar Rangarajan , Nimish S. Khanolkar
发明人： Aleksandras Surna , Erik Ismert , Srikumar Rangarajan , Nimish S. Khanolkar
IPC分类号： G06F17/30
CPC分类号： G06F17/30303 , G06F9/30192 , G06F9/3885 , G06F15/82 , G06F17/30292 , G06F17/30315 , G06F17/30569
摘要： A data normalization system is described herein that represents multiple data types that are common within database systems in a normalized form that can be processed uniformly to achieve faster processing of data on superscalar CPU architectures. The data normalization system includes changes to internal data representations of a database system as well as functional processing changes that leverage normalized internal data representations for a high density of independently executable CPU instructions. Because most data in a database is small, a majority of data can be represented by the normalized format. Thus, the data normalization system allows for fast superscalar processing in a database system in a variety of common cases, while maintaining compatibility with existing data sets.
摘要翻译：这里描述了一种数据归一化系统，其表示以规范化形式在数据库系统中通用的多个数据类型，其可以被均匀地处理以实现对超标量CPU架构的数据的更快处理。数据归一化系统包括对数据库系统的内部数据表示的更改以及利用高密度独立可执行CPU指令的规范化内部数据表示的功能处理变化。因为数据库中的大多数数据很小，所以大部分数据可以用归一化格式表示。因此，数据归一化系统允许在各种常见情况下在数据库系统中进行快速超标量处理，同时保持与现有数据集的兼容性。

6. 发明申请

US20080209428A1 RESOURCE GOVERNOR CONFIGURATION MODEL 有权
标题翻译：资源总监配置模式
公开(公告)号：US20080209428A1
公开(公告)日：2008-08-28
申请号：US11679520
申请日：2007-02-27
申请人： Boris Baryshnikov , Aleksandras Surna , In-Jerng Choe , Alexandre Verbitski , Ravishankar Rajamani
发明人： Boris Baryshnikov , Aleksandras Surna , In-Jerng Choe , Alexandre Verbitski , Ravishankar Rajamani
IPC分类号： G06F9/46
CPC分类号： G06F9/5027 , G06F17/30286 , G06F2209/5011
摘要： A database can have multiple requests applied at one time. Each of these requests requires a specific amount of server resources. There can be a differentiation of user-submitted workloads between each other. These workloads are a set of queries submitted by different users. Each query can have specific resource limits. In addition, each set can have specific resource limits.
摘要翻译：数据库可以同时应用多个请求。这些请求中的每一个都需要特定数量的服务器资源。可以区分用户提交的工作负载。这些工作负载是由不同用户提交的一组查询。每个查询可以具有特定的资源限制。此外，每组可以具有特定的资源限制。

7. 发明授权

US08065682B2 Enforcing system resource usage limits on query requests based on grouping query requests into workgroups and assigning workload groups to resource pools 有权
标题翻译：基于将查询请求分组到工作组并将工作负载组分配给资源池，来对查询请求执行系统资源使用限制
公开(公告)号：US08065682B2
公开(公告)日：2011-11-22
申请号：US11679520
申请日：2007-02-27
申请人： Boris Baryshnikov , Aleksandras Surna , In-Jerng Choe , Alexandre Verbitski , Ravishankar Rajamani
发明人： Boris Baryshnikov , Aleksandras Surna , In-Jerng Choe , Alexandre Verbitski , Ravishankar Rajamani
IPC分类号： G06F9/46
CPC分类号： G06F9/5027 , G06F17/30286 , G06F2209/5011
摘要： A database can have multiple requests applied at one time. Each of these requests requires a specific amount of server resources. There can be a differentiation of user-submitted workloads between each other. These workloads are a set of queries submitted by different users. Each query can have specific resource limits. In addition, each set can have specific resource limits.
摘要翻译：数据库可以同时应用多个请求。这些请求中的每一个都需要特定数量的服务器资源。可以区分用户提交的工作负载。这些工作负载是由不同用户提交的一组查询。每个查询可以具有特定的资源限制。此外，每组可以具有特定的资源限制。

8. 发明申请

US20110231403A1 SCALABLE INDEX BUILD TECHNIQUES FOR COLUMN STORES 有权
标题翻译：可扩展索引建筑柱子技术
公开(公告)号：US20110231403A1
公开(公告)日：2011-09-22
申请号：US12727266
申请日：2010-03-19
申请人： Artem Oks , Qingqing Zhou , Srikumar Rangarajan , Aleksandras Surna , Wey Guy , Cipri Clinciu , Ashit Gosalia
发明人： Artem Oks , Qingqing Zhou , Srikumar Rangarajan , Aleksandras Surna , Wey Guy , Cipri Clinciu , Ashit Gosalia
IPC分类号： G06F17/30 , G06F9/46
CPC分类号： G06F17/30315 , G06F9/5083 , G06F17/30321 , G06F17/30474 , H04L47/82
摘要： Architecture that includes an index creation algorithm that utilizes available resources and dynamically adjusts to successfully scale with increased resources and be able to do so for any data distribution. The resources can be processing resources, memory, and/or input/output, for example. A finer level of granularity, called a segment, is utilized to process tuples in a partition while creating an index. The segment also aligns with compression techniques for the index. By choosing an appropriate size for a segment and using load balancing the overall time for index creation can be reduced. Each segment can then be processed by a single thread thereby limiting segment skew. Skew is further limited by breaking down the work done by a thread into parallelizable stages.
摘要翻译：体系结构包括利用可用资源并动态调整的索引创建算法，以便通过增加的资源成功扩展，并能够为任何数据分配做到这一点。资源可以是例如处理资源，存储器和/或输入/输出。使用更精细的粒度级别（称为段）来处理分区中的元组，同时创建索引。该段也与索引的压缩技术保持一致。通过为段选择适当的大小并使用负载平衡，可以减少创建索引的总时间。然后可以通过单个线程处理每个段，从而限制段偏移。通过将线程完成的工作分解成可并行化阶段来进一步限制倾斜。

9. 发明授权

US08631039B2 Normalizing data for fast superscalar processing 有权
标题翻译：归一化数据进行快速超标量处理
公开(公告)号：US08631039B2
公开(公告)日：2014-01-14
申请号：US12773889
申请日：2010-05-05
申请人： Aleksandras Surna , Erik Ismert , Srikumar Rangarajan , Nimish S. Khanolkar
发明人： Aleksandras Surna , Erik Ismert , Srikumar Rangarajan , Nimish S. Khanolkar
IPC分类号： G06F17/30
CPC分类号： G06F17/30303 , G06F9/30192 , G06F9/3885 , G06F15/82 , G06F17/30292 , G06F17/30315 , G06F17/30569
摘要： A data normalization system is described herein that represents multiple data types that are common within database systems in a normalized form that can be processed uniformly to achieve faster processing of data on superscalar CPU architectures. The data normalization system includes changes to internal data representations of a database system as well as functional processing changes that leverage normalized internal data representations for a high density of independently executable CPU instructions. Because most data in a database is small, a majority of data can be represented by the normalized format. Thus, the data normalization system allows for fast superscalar processing in a database system in a variety of common cases, while maintaining compatibility with existing data sets.
摘要翻译：这里描述了一种数据归一化系统，其表示以规范化形式在数据库系统中通用的多个数据类型，其可以被均匀地处理以实现对超标量CPU架构的数据的更快处理。数据归一化系统包括对数据库系统的内部数据表示的更改以及利用高密度独立可执行CPU指令的规范化内部数据表示的功能处理变化。因为数据库中的大多数数据很小，所以大部分数据可以用归一化格式表示。因此，数据归一化系统允许在各种常见情况下在数据库系统中进行快速超标量处理，同时保持与现有数据集的兼容性。

10. 发明授权

US08548986B2 Adaptive row-batch processing of database data 有权
标题翻译：自适应行批处理数据库数据
公开(公告)号：US08548986B2
公开(公告)日：2013-10-01
申请号：US12727235
申请日：2010-03-19
申请人： Aleksandras Surna , Per-Ake Larson , Srikumar Rangarajan
发明人： Aleksandras Surna , Per-Ake Larson , Srikumar Rangarajan
IPC分类号： G06F17/30
CPC分类号： G06F17/30492
摘要： Architecture that provides for greater interoperability between column stores and row stores by leveraging the advantages both have to offer. The architecture operates automatically (e.g., dynamically) to move between row oriented processing mode and batch processing mode, and the combination thereof, when it is more beneficial to run in one mode relative to the other mode, or both modes. The auto-switching of data processing between batch and row oriented mode occurs during the execution of a single query. The architecture can automatically modify an operator in the query tree and/or remove an operator if desired at runtime for more efficient processing. This approach also accounts for memory constraints for either of row or column processing.
摘要翻译：架构通过利用两者必须提供的优点，提供列存储和行存储之间的更大的互操作性。当相对于其他模式或两种模式运行在一种模式中更有利时，架构在行面向处理模式和批处理模式之间自动运行（例如，动态地）移动，以及其组合。批处理和行向模式之间的数据处理自动切换在执行单个查询期间发生。架构可以在运行时自动修改查询树中的运算符和/或删除运算符，以便更有效的处理。这种方法也解决了行或列处理中的任何一个的内存限制。

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