公开(公告)号：US20160378824A1

公开(公告)日：2016-12-29

申请号：US14749098

申请日：2015-06-24

Applicant: Futurewei Technologies, Inc.

Inventor： Huaizhi Li ,  Guogen Zhang ,  Jason Yang Sun

IPC: G06F17/30

CPC classification number: G06F16/24532 ,  G06F16/2255

Abstract: A system and method for parallelizing hash-based operators in symmetric multiprocessing (SMP) databases is provided. In an embodiment, a method in a device for performing hash based database operations includes receiving at the device an database query; creating a plurality of execution workers to process the query; and building by the execution workers a hash table from a database table, the database table comprising one of a plurality of partitions and a plurality of scan units, the hash table shared by the execution workers, each execution worker scanning a corresponding partition and adding entries to the hash table if the database table is partitioned, each execution worker scanning an unprocessed scan unit and adding entries to the hash table according to the scan unit if the database table comprises scan units, and the workers performing the scanning and the adding in a parallel manner.

Abstract translation: 提供了一种用于在对称多处理（SMP）数据库中并行化基于散列算子的系统和方法。 在一个实施例中，用于执行基于散列的数据库操作的设备中的方法包括在所述设备处接收数据库查询; 创建多个执行人员来处理查询; 并且由执行工作者构建来自数据库表的散列表，所述数据库表包括多个分区和多个扫描单元之一，所述散列表由执行工作者共享，每个执行工作人员扫描相应的分区并添加条目 如果数据库表被分区，则每个执行人员扫描未处理的扫描单元，并且如果数据库表包括扫描单元，则根据扫描单元将条目添加到散列表，并且执行扫描和添加的工作人员 并行方式

公开(公告)号：US09311354B2

公开(公告)日：2016-04-12

申请号：US13730872

申请日：2012-12-29

Applicant: FutureWei Technologies, Inc.

Inventor： Jason Yang Sun ,  Qingqing Zhou ,  Mohan Singamshetty

IPC: G06F17/30

CPC classification number: G06F17/30445 ,  G06F17/30483

Abstract: Queries may be processed more efficiently in an massively parallel processing (MPP) database by locally optimizing the global execution plan. The global execution plan and a semantic tree may be provided to MPP data nodes by an MPP coordinator. The MPP data nodes may then use the global execution plan and the semantic tree to generate a local execution plan. Thereafter, the MPP data nodes may select either the global execution plan or the local execution plan is accordance with a cost evaluation.

Abstract translation: 在大规模并行处理（MPP）数据库中，可以通过局部优化全局执行计划，更有效地处理查询。 全局执行计划和语义树可以由MPP协调器提供给MPP数据节点。 然后，MPP数据节点可以使用全局执行计划和语义树来生成本地执行计划。 此后，MPP数据节点可以选择全局执行计划，或者本地执行计划根据成本评估。