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Effective index for two-dimensional data table, and method for creating and querying effective index

A technology of data tables and two-dimensional tables, which is applied in the field of efficient indexing, creation and query, and can solve problems such as the inability to improve query performance, the inability to filter data, and the easy failure of data

Inactive Publication Date: 2013-04-03
TIANJIN NANKAI UNIV GENERAL DATA TECH
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AI Technical Summary

Problems solved by technology

However, it is very easy to fail for data with a relatively discrete distribution (in extreme cases, coarse-grained indexes may not be able to filter out any data, and query performance cannot be improved)
Furthermore, the coarse-grained index cannot precisely locate the query results, and for data blocks that cannot be precisely excluded, the original data still needs to be opened for scanning

Method used

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  • Effective index for two-dimensional data table, and method for creating and querying effective index
  • Effective index for two-dimensional data table, and method for creating and querying effective index
  • Effective index for two-dimensional data table, and method for creating and querying effective index

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Embodiment Construction

[0033] Depend on figure 1 It can be seen that the flow of the method for creating an efficient index for a two-dimensional data table according to the present invention is as follows

[0034] 1) Divide the two-dimensional data table into several data blocks;

[0035] 2) Create block coarse-grained indexes for data blocks;

[0036] 3) Create a block local index for the data block; use the above three steps to create an efficient index for the two-dimensional data table. figure 1 Split according to the horizontal split granularity of n (that is, the number of data rows in each data block is n).

[0037] In addition, it is generally used as image 3 As shown, the two-dimensional table is cut horizontally and vertically by a certain number of rows and columns.

[0038] figure 2 In order to be a schematic flow chart of the query method of the present invention for efficient indexing of two-dimensional data tables, according to figure 2 The set steps perform block-by-block e...

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Abstract

The invention provides an effective index for a two-dimensional data table, which comprises a block coarse-grained index used for excluding target data which definitely can not be hit by a block, and a cell exact index used for accurately positioning the hit data in the data block which cannot be accurately determined by the block coarse-grained index. Besides, the invention also provides a method for creating and querying an effective index for a two-dimensional data table. The invention has the benefits that the indexes for the two-dimensional data table can be created and maintained with lower creation and maintenance cost, meanwhile, the expansion ratio of index data is smaller, the I / O cost is low, and the efficiency is effectively improved.

Description

technical field [0001] The invention belongs to the field of data storage, and in particular relates to an efficient index, creation and query method for two-dimensional data tables. Background technique [0002] A relational table in a relational database is a typical two-dimensional data. Common data computing systems often use rough indexes or precise indexes to reduce the amount of I / O when searching for fields, thereby improving query performance. Precise index is divided into two types: global index and local index. Take hash index as an example: [0003] Global hash index query performance is very good, but the cost of creation and maintenance is extremely high, and the data expansion rate is very high (often more than 1.5 times or even greater than the original data expansion). [0004] The local hash index creates an index for each data block separately, and the maintenance cost when updating a certain data block is limited to the index data of this data block, so...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 孟祥斌崔维力武新赵伟
Owner TIANJIN NANKAI UNIV GENERAL DATA TECH
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