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Column-storage-oriented B+ tree index method for DWMS (data warehouse management system)

A B+ tree and column storage technology, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve the problems of increasing the B+ tree index height, no data insertion and modification, reducing data query efficiency, etc. The effect of group reconstruction and multi-table join, reducing the number of searches, and keeping data in order

Inactive Publication Date: 2012-07-25
DONGHUA UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But in the data warehouse system, there are almost no data insertion and modification operations
Applying the traditional B+ tree to the data warehouse system for massive data storage will cause a waste of space
At the same time, since the nodes are not completely filled, data storage requires more nodes, which will increase the height of the B+ tree index and reduce the query efficiency of data

Method used

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  • Column-storage-oriented B+ tree index method for DWMS (data warehouse management system)
  • Column-storage-oriented B+ tree index method for DWMS (data warehouse management system)
  • Column-storage-oriented B+ tree index method for DWMS (data warehouse management system)

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Embodiment Construction

[0028] In order to make the present invention more comprehensible, a preferred embodiment is described in detail as follows.

[0029] The invention provides a B+ tree index method for column storage DWMS, the steps of which are as follows:

[0030] Step 1. Column data generation: import user data, divide the original data stored by row vertically into single columns, add row number items for tuple reconstruction to each item of data in each column according to the row number where it is located, and form Two-tuple (row number, column value), apply for a data segment, and save the newly generated data of each column value in a data segment;

[0031] Step 2. If the B+ tree key is row number data, go to step 4 to create it; if the B+ tree key is column value data, go to step 3 to sort the column values ​​first;

[0032] Step 3. Combining multi-way merge and heap sorting to perform key-value sorting on column-valued data. This step includes:

[0033] Step 3.1. Initialization: Ap...

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Abstract

The invention relates to a column-storage-oriented B+ tree index method for a DWMS (data warehouse management system). The column-storage-oriented B+ tree index method is characterized by comprising a first step, generating column data; a second step, turning to a fourth step for building if a B+ tree keyword is a row number, and turning to a third step for sorting if the B+ tree keyword is not the row number; the third step, sorting column value data by means of using multi-line merging with heapsort; the fourth step, initiating a B+ tree index; a fifth step, creating leaf nodes; and a sixth step, generating a middle nodes an a bottom-up manner. The column-storage-oriented B+ tree index method for the DWMS is used for column storage, and has the advantages that 1), the number of layers of a B+ tree is the smallest, and the number of searching is reduced; and 2), a traditional plug-in method for building the B+ tree is abandoned, and the bottom-up B+ tree creating method is utilized. When the method is used, division operation is omitted, and a lot of expense is reduced.

Description

technical field [0001] The invention relates to a B+ tree index technology for column storage DWMS (Data Warehouse Management System). Background technique [0002] With the rapid development of Internet applications, high throughput and large storage capacity have become the necessary features of today's database products, and the requirements for high performance in transaction processing and query analysis are increasingly urgent. Traditional row storage databases cannot provide efficient query analysis for enterprise decision-making like processing transaction applications. In recent years, the database architecture of column storage has been re-examined. out has significantly more performance than row storage. Since relational tables are still logical rows externally, tuple reconstruction and multi-table joins are important factors affecting query performance in column storage. Indexing is one of the important technologies to improve query efficiency. The B+ tree ind...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 夏小玲乐嘉锦王梅李晔锋
Owner DONGHUA UNIV
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