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    • 52. 发明申请
    • Hybrid optimization strategies in automatic SQL tuning
    • 自动SQL调优中的混合优化策略
    • US20100030758A1
    • 2010-02-04
    • US12221131
    • 2008-07-30
    • Peter BelknapKhaled YagoubKarl DiasBenoit DagevilleThierry CruanesAnupam Singh
    • Peter BelknapKhaled YagoubKarl DiasBenoit DagevilleThierry CruanesAnupam Singh
    • G06F17/30
    • G06F17/30463G06F17/30306G06F17/30471
    • Systems, methods, and other embodiments associated with hybrid optimization strategies in automatic SQL tuning are described. One example method includes receiving a first (e.g., cost-based) execution plan for a user structured query language statement (User SQL) from a first (e.g., cost-based) optimizer. The example method may also include receiving a second (e.g., rules-based) execution plan for the User SQL from a second, different (e.g., rules-based) query optimizer. The method may include identifying a preferred execution plan based on data produced by test executing the execution plans in a reproduced execution environment that reproduces at least a portion of an execution environment in which the user SQL runs. The method may also include controlling a database to execute the User SQL using the preferred execution plan.
    • 描述了与自动SQL调优中的混合优化策略相关联的系统,方法和其他实施例。 一个示例性方法包括从第一(例如基于成本的)优化器接收用户结构化查询语言语句(User SQL)的第一(例如基于成本的)执行计划。 示例性方法还可以包括从第二不同(例如,基于规则的)查询优化器接收针对用户SQL的第二(例如基于规则的)执行计划。 该方法可以包括基于在再现执行用户SQL运行的执行环境的至少一部分的再现执行环境中执行执行计划的测试产生的数据来识别优选执行计划。 该方法还可以包括控制数据库以使用优选的执行计划来执行User SQL。
    • 53. 发明申请
    • SQL Execution Plan Verification
    • SQL执行计划验证
    • US20090106219A1
    • 2009-04-23
    • US12188683
    • 2008-08-08
    • Peter BelknapBenoit DagevilleDinesh DasKhaled YagoubMohamed ZaitMohamed Ziauddin
    • Peter BelknapBenoit DagevilleDinesh DasKhaled YagoubMohamed ZaitMohamed Ziauddin
    • G06F17/30
    • G06F17/30469G06F17/30463
    • Approaches, techniques, and mechanisms are disclosed for ensuring that a database command is executed according to a query plan that has been verified to be actually optimal. Except in rare circumstances, a database server does not execute a query plan unless it is first verified by the database server. The database server receives a request to execute a database command. The database server determines an unverified plan is the best plan for satisfying the request. Rather than risk the unknown behavior of an unverified plan, the database server instead satisfies the request according to a verified plan. Subsequently—for example as part of a scheduled job—the database server executes the unverified plan to determine performance statistics. Based at least on the performance statistics, the database server determines whether or not to verify the unverified plan. Techniques for concurrent and optimistic verifications are also disclosed.
    • 公开了方法,技术和机制,以确保根据已被验证为实际最佳的查询计划来执行数据库命令。 除非在极少数情况下,数据库服务器不执行查询计划,除非数据库服务器首先进行了验证。 数据库服务器接收执行数据库命令的请求。 数据库服务器确定未验证的计划是满足请求的最佳方案。 而不是冒险未验证的计划的未知行为,数据库服务器而是根据验证的计划满足请求。 随后 - 例如作为计划作业的一部分 - 数据库服务器执行未验证的计划以确定性能统计信息。 至少基于性能统计,数据库服务器确定是否验证未验证的计划。 还公开了并发和乐观验证的技术。
    • 54. 发明授权
    • Efficient data aggregation operations using hash tables
    • 使用哈希表进行有效的数据聚合操作
    • US07469241B2
    • 2008-12-23
    • US11156068
    • 2005-06-17
    • Srikanth BellamkondaBenoit Dageville
    • Srikanth BellamkondaBenoit Dageville
    • G06F7/00G06F17/30
    • G06F17/30489Y10S707/99932Y10S707/99933Y10S707/99942
    • Hash aggregation operates in two phases. In the first phase, data read from underlying row source is partitioned on GROUP BY keys with on-the-fly aggregation. It is determined into which partition an entry corresponding to the incoming record should be grouped, and whether a matching entry is already present in the partition, using a hash function and a hash table built for the partition. For aggregation operations, if a match is found, then a measure value from the incoming record is aggregated with a measure value for the entry existing in the partition. If there is not enough system volatile memory to complete the first phase, then a partition is selected for storing persistently. Thus, only one partition at a time is stored persistently, as necessary. In the second phase, one persistently stored partition is processed at a time, whereby aggregation of the data in that partition is completed and results are returned.
    • 哈希聚合分为两个阶段。 在第一阶段,从基础行源读取的数据在具有即时聚合的GROUP BY密钥上进行分区。 确定哪个分区对应于输入记录的条目应该被分组,以及使用为该分区构建的散列函数和哈希表是否已经存在分区中的匹配条目。 对于聚合操作,如果找到匹配项,则来自记录的度量值将与分区中存在的条目的度量值进行聚合。 如果没有足够的系统易失性存储器来完成第一阶段,则选择一个分区来持久存储。 因此,必要时,一次只能存储一个分区。 在第二阶段,一次处理一个持久存储的分区,从而完成该分区中的数据的聚合,并返回结果。
    • 56. 发明授权
    • Performing recursive database operations
    • 执行递归数据库操作
    • US07155446B2
    • 2006-12-26
    • US10867923
    • 2004-06-14
    • Thierry CruanesWei LiAri MozesBenoit Dageville
    • Thierry CruanesWei LiAri MozesBenoit Dageville
    • G06F17/00
    • G06F17/3056G06F17/30513Y10S707/99942
    • A method and apparatus for performing recursive database operations is provided. According to one aspect, a plurality of first-stage slaves and a plurality of second-stage slaves are established in a database server. During one or more iterations of a recursive database operation, the first-stage slaves concurrently process data items stored in a data repository and send results to the second-stage slaves. The second-stage slaves receive the results and concurrently process those results. The second-stage slaves store the results of the second-stage slaves' processing in the data repository. Subsequent iterations of the recursive database operation proceed in this manner until the recursive database operation has been completed. In each iteration, the first-stage slaves consume the product of the second-stage slaves' previous iteration's processing, and the second-stage slaves consume the product of the first-stage slaves' current iteration's processing.
    • 提供了一种用于执行递归数据库操作的方法和装置。 根据一个方面,在数据库服务器中建立多个第一级从站和多个第二级从站。 在递归数据库操作的一个或多个迭代期间,第一级从站同时处理存储在数据存储库中的数据项,并将结果发送到第二级从站。 第二阶段的奴隶收到结果并同时处理这些结果。 第二级从站将数据存储库中的第二级从站处理的结果存储起来。 递归数据库操作的后续迭代以这种方式进行,直到递归数据库操作完成。 在每次迭代中,第一级从站消耗第二级从站先前迭代处理的乘积,第二级从站消耗第一级从站当前迭代处理的乘积。
    • 57. 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。
    • 58. 发明申请
    • Efficient data aggregation operations using hash tables
    • 使用哈希表进行有效的数据聚合操作
    • US20060116989A1
    • 2006-06-01
    • US11156068
    • 2005-06-17
    • Srikanth BellamkondaBenoit Dageville
    • Srikanth BellamkondaBenoit Dageville
    • G06F17/30
    • G06F17/30489Y10S707/99932Y10S707/99933Y10S707/99942
    • Hash aggregation operates in two phases. In the first phase, data read from underlying row source is partitioned on GROUP BY keys with on-the-fly aggregation. It is determined into which partition an entry corresponding to the incoming record should be grouped, and whether a matching entry is already present in the partition, using a hash function and a hash table built for the partition. For aggregation operations, if a match is found, then a measure value from the incoming record is aggregated with a measure value for the entry existing in the partition. If there is not enough system volatile memory to complete the first phase, then a partition is selected for storing persistently. Thus, only one partition at a time is stored persistently, as necessary. In the second phase, one persistently stored partition is processed at a time, whereby aggregation of the data in that partition is completed and results are returned.
    • 哈希聚合分为两个阶段。 在第一阶段,从基础行源读取的数据在具有即时聚合的GROUP BY密钥上进行分区。 确定哪个分区对应于输入记录的条目应该被分组,以及使用为该分区构建的散列函数和哈希表是否已经存在分区中的匹配条目。 对于聚合操作,如果找到匹配项,则来自记录的度量值将与分区中存在的条目的度量值进行聚合。 如果没有足够的系统易失性存储器来完成第一阶段,则选择一个分区来持久存储。 因此,必要时,一次只能存储一个分区。 在第二阶段,一次处理一个持久存储的分区,从而完成该分区中的数据的聚合,并返回结果。