公开(公告)号：US11797509B2

公开(公告)日：2023-10-24

申请号：US17266080

申请日：2020-01-14

Applicant: Renmin University of China

Inventor： Yansong Zhang ,  Yu Zhang ,  Shan Wang

IPC: G06F16/22 ,  G06F16/2453 ,  G06F16/242 ,  G06F16/2455 ,  G06F16/28

CPC classification number: G06F16/2237 ,  G06F16/244 ,  G06F16/2456 ,  G06F16/24544 ,  G06F16/283

Abstract: The disclosure includes aspects of a system and/or method including a hash multi-table joining implementation method based on a grouping vector, which includes the following steps: 1) rewriting an SQL query command, and dividing a complete OLAP query command into a subtask of selecting-projecting-grouping-joining operation and an subtask of aggregating operation; 2) creating and generating grouping vector metadata corresponding to a GROUP-BY statement in an SQL command through the subtask of selecting-projecting-grouping-joining operation, and creating a vector index as an output result of the subtask of selecting-projecting-grouping-joining operation; 3) executing aggregation computation based on the vector index through the subtask of aggregating operation, and storing an aggregation computation result in a corresponding unit of a grouping vector aggregator with the same length as the grouping vector; and 4) merging the aggregation computation result in the grouping vector aggregator with the grouping vector metadata created in the joining operation subtask, and outputting the merged data as a result set of the SQL query command. The disclosure can be widely applied to the field of OLAP data query.

公开(公告)号：US20210256006A1

公开(公告)日：2021-08-19

申请号：US17266080

申请日：2020-01-14

Applicant: Renmin University of China

Inventor： Yansong Zhang ,  Yu Zhang ,  Shan Wang

IPC: G06F16/22 ,  G06F16/2455 ,  G06F16/2453 ,  G06F16/28 ,  G06F16/242

Abstract: The disclosure includes aspects of a system and/or method including a hash multi-table joining implementation method based on a grouping vector, which includes the following steps: 1) rewriting an SQL query command, and dividing a complete OLAP query command into a subtask of selecting-projecting-grouping-joining operation and an subtask of aggregating operation; 2) creating and generating grouping vector metadata corresponding to a GROUP-BY statement in an SQL command through the subtask of selecting-projecting-grouping-joining operation, and creating a vector index as an output result of the subtask of selecting-projecting-grouping-joining operation; 3) executing aggregation computation based on the vector index through the subtask of aggregating operation, and storing an aggregation computation result in a corresponding unit of a grouping vector aggregator with the same length as the grouping vector; and 4) merging the aggregation computation result in the grouping vector aggregator with the grouping vector metadata created in the joining operation subtask, and outputting the merged data as a result set of the SQL query command. The disclosure can be widely applied to the field of OLAP data query.