Connection sequence inquiry optimizing method based on column-storage model

A query optimization and connection sequence technology, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as seldom considering column storage characteristics, costing overhead, and complicated connection operations

Inactive Publication Date: 2012-07-25
DONGHUA UNIV
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AI Technical Summary

Problems solved by technology

The more related columns are queried, the more complicated the connection operation between columns will be, which will consume a lot of overhead
Query optimization has always played an important role in the database field. However, most of the existing column storage systems adapt to upper-level queries by optimizing the underlying data organization structure or establishing auxiliary physical structures. In the early query optimization stage, the characteristics of column storage are rarely considered, so it is difficult to Guaranteed "best" optimization results

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  • Connection sequence inquiry optimizing method based on column-storage model
  • Connection sequence inquiry optimizing method based on column-storage model
  • Connection sequence inquiry optimizing method based on column-storage model

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Embodiment Construction

[0024] In order to make the present invention more comprehensible, a preferred embodiment is described in detail as follows.

[0025] The present invention provides a query optimization method based on a column storage model, the steps of which are:

[0026] Step 1. Receive the user's SQL query input according to the relational table, which is recorded as select L from R 1 ,...,R m where ∧ / ∨(A 1 ,...A n ). where R i is a relational table, L is the attribute set of the relation, A 1 ,...,A n is the predicate that is connected with the node or the node

[0027] Step 2: Convert the above SQL statement into a query based on a binary table, recorded as select L from(K 1 × K 2 ×......)where ∧ / ∨(A 1 ,...A n ), where K i is the query related column. If K i and K j is an attribute of the same relational table R, it is called the same table column.

[0028] Step 3, generating an initial logical plan tree;

[0029] 1) Use the equivalent transformation rules of relationa...

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Abstract

The invention provides an inquiry optimizing method based on a column-storage model. The inquiry optimizing method is characterized by comprising steps: receiving input inquiry according to relationship tables from a user; converting into inquiry according to an attribute binary table; generating an initial logic plan tree; optimizing same-table connection sequence for the logic inquiry plan tree generated in the last step; registering a relationship set J for each relationship table according to connection information stored in the logic plan tree; judging the type of the relationship tables according to the set J; optimizing connection sequence of single-event tables; and optimizing connection sequence of multi-event tables. Event tables have relationship with multiple tables, and rest tables are dimension tables. The inquiry optimizing method based on the column-storage model has the advantages that the method is implemented according to characteristics of column-storage data and characteristics of an analytical inquiry request, the quantity of extracted data and intermediate result generated during connection of each step are reduced to the greatest extent, and an inquiry execution strategy with high efficiency is obtained.

Description

technical field [0001] The invention relates to a connection sequence query optimization method based on column storage. Background technique [0002] With the explosive growth of data volume in the information age, driven by the demand for massive data analysis and processing, analytical applications such as data warehouse, data mining, and decision support have developed rapidly. Such applications are characterized by large amounts of data, intensive queries, and focus more on attributes rather than entities. The column storage technology physically splits the data table in units of columns, and stores the data of the same column continuously. During the query process, it only needs to read in the query-related columns, avoiding the reading of irrelevant data, so as to maximize the improve the efficiency of analytical queries. [0003] However, the change of the data organization structure enables the column storage system to avoid operating irrelevant column data, and a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 王梅夏小玲乐嘉锦陆戌辰
Owner DONGHUA UNIV
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