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Many-to-many psj aggregation query method based on tuple-level uncertainty model

A technology of uncertainty and aggregation query, applied in the fields of instrumentation, computing, electrical digital data processing, etc., can solve the problem of missing information, regardless of mapping constraints, etc.

Active Publication Date: 2020-07-17
ZHEJIANG UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Some methods reduce the number of possible worlds by limiting the number of connections or setting a probability threshold, but these methods not only lose a lot of information, but also do not consider the mapping constraints

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  • Many-to-many psj aggregation query method based on tuple-level uncertainty model
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  • Many-to-many psj aggregation query method based on tuple-level uncertainty model

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Embodiment Construction

[0051] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0052] figure 1 It is a flow chart of the many-to-many PSJ aggregation query method based on the tuple-level uncertainty model provided by the embodiment. The method is divided into three stages: preprocessing, initializing the recursive basis and recursive, which can solve the COUNT query and SUM query of many-to-many PSJ.

[0053] Preprocessing stage: This stage is mainly to model the many-to-many PSJ as tuple-level uncertain tuples. This stage can be divided into two steps: constructing uncertain tuples and processing predicate conditions. The specific content of ea...

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Abstract

The invention discloses a PSJ aggregation query method based on a tuple-level uncertainty model. The method includes the steps of 1, connecting and modeling each many-to-many PSJ as an uncertainty tuple by using the tuple-level uncertainty mode to form a complete PSJ set; 2, based on the modeling result of the step 1, adding marker attributes to the tuples satisfying the conditions of a COUNT query predicate, and adding summation attributes to the tuples satisfying the conditions of a SUM query predicate; 3, on the basis of the step 2, calculating the probability distribution of aggregated values of PSJ subsets by using a dynamic programming idea, and calculating the probability distribution of an aggregated values of the complete PSJ set on the basis of the result of the probability distribution of the aggregated values of the PSJ subsets. The method solves the problem that it is difficult to execute COUNT queries and SUM queries on the many-to-many PSJs, and has broad application prospects in databases, online analytical processing and data warehouses.

Description

technical field [0001] The invention relates to the field of probabilistic similarity join (Probabilistic Similarity Join, PSJ) aggregation query, in particular to a many-to-many PSJ aggregation query method based on a tuple-level uncertainty model. Background technique [0002] Join aggregation queries are widely used in databases, online analytical processing, and data warehouses. Such queries usually use join operations to combine multiple relational tables first, and then perform aggregation operations. However, due to the explosive growth of data in the information age, the uncertainty of the data itself and the uncertainty introduced in the process of data collection and integration lead to a large amount of data with incompleteness and ambiguity. The existence of uncertain data often makes it impossible to join between multiple tables, which in turn leads to the failure of aggregation queries based on join operations. [0003] PSJ query is based on the similarity mea...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2455
CPCG06F16/2456
Inventor 陈岭王俊凯
Owner ZHEJIANG UNIV