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US 10,540,352 B2Granted
Remote query optimization in multi data sources
AssigneeInternational Business Machines Corporation
InventorsLei Cui, Yi Dai, Ya Qiong Liu, Xing Xing Shen
Life of this patent
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Abstract
Embodiments of the present invention provide systems and methods for remote query optimization in multi data sources. The method includes receiving a database query from a remote source requesting data-points from multiple data sources. The method further includes receiving and analyzing the data-points, creating a data set based on the analysis, and transmitting the data set to the remote source.
Claims6
A method for remote query optimization in multi data sources, the method comprising:
- receiving, by one or more processors, a database query from a remote source, wherein the query requests one or more groupings of data-points from each of two or more data sources;
- receiving, by one or more processors, the one or more groupings of data-points from each of the two or more data sources;
- analyzing, by one or more processors, the one or more groupings of data-points from each of the two or more data sources;
- creating, by one or more processors, a data set, wherein the data set comprises the analyzed one or more groupings of data-points;
- transmitting, by one or more processors, the data set to the remote source;
- mapping, by one or more processors, functions for each of the one or more groupings of data-points, wherein mapping functions of each of the one or more groupings of data-points comprises;
- mapping, by one or more processes, a real number for each of the one or more groupings of data-points;
- comparing, by one or more processes, each of the groupings from the two or more data sources;
- converting, by one or more processes, non-integer data-points to integer values;
- and
- computing, by one or more processes, the mapping function using a recursive equation G(C1)=g(C1), G(C1,C2)=g(C1)+F(G(C2,C3, . . . ,CN)), . . . ,G(C1,C2, . . . ,Cn)=g(C1)+F(G(C2,C3,. . . ,Cn)), where C1, C2, . . . , CN are the groupings for a join, g(Ci) is a mapping function for column Ci to convert Ci to integer values, F(x) is the probability distribution function, and G( ) is the final mapping function for each grouping.
8 more elements
Dependencies are inferred from the claim text.