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Data index establishing system and method as well as data query method

An index and data technology, applied in the field of cloud computing, can solve the problems of affecting global index, maintenance cost, system throughput, and high index maintenance cost, and achieve the effect of reducing invalid scans, reducing index maintenance cost, and improving query performance

Inactive Publication Date: 2013-09-25
NEC (CHINA) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] However, in order to maintain the balance of the tree, the RT-CAN scheme needs to continuously split and adjust the index nodes during the data insertion process (each data insertion will trigger an update of the local index, which in turn affects the global index)
Therefore, the maintenance cost of the index is very high, especially for applications with frequent data insertion, the high maintenance cost of the index will have a great impact on the throughput of the system
Therefore, this solution is not suitable for application in the Internet of Things

Method used

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  • Data index establishing system and method as well as data query method
  • Data index establishing system and method as well as data query method
  • Data index establishing system and method as well as data query method

Examples

Experimental program
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Effect test

no. 1 example

[0040] figure 1 is a block diagram showing a system 10 for indexing data according to a first embodiment of the present invention. Such as figure 1 As shown, the system 10 includes a time segment dividing unit 110 , a first index building unit 120 and a second index building unit 130 . Next, the specific operations of each unit in the system 10 will be described in detail.

[0041]The time period dividing unit 110 is configured to divide a predetermined time range into a plurality of time periods. Since the regional distribution of Internet of Things data often changes with time, the time segment division unit 110 can divide the data into several time segments (TIS) in the time dimension, namely

[0042] TIS = {[t 1 , t 2 ), [t 2 , t 3 ), ..., [t i-1 , t i ),...},

[0043] where [t i-1 , t i ) is a time interval that is left closed and right open, and all these time intervals are non-overlapping. Of course, those skilled in the art can understand that each time pe...

no. 2 example

[0062] image 3 is a block diagram showing a system 30 for indexing data according to a second embodiment of the present invention. Such as image 3 As shown, the system 30 includes a time segment dividing unit 310 , a first index building unit 320 , a second index building unit 330 and a data storage unit 340 . It should be pointed out that image 3 The time segment dividing unit 310, the first index building unit 320, the second index building unit 330 and the figure 1 The time segment dividing unit 110, the first index building unit 120, and the second index building unit 130 shown in are similar. For simplicity, only the data storage unit 340 is described in detail below.

[0063] The data storage unit 340 is configured to store temporally and spatially adjacent data in the same or adjacent storage areas. In this way, the number of storage areas to be scanned during the query process can be reduced, thereby improving query efficiency.

[0064] specifically, Figure ...

no. 3 example

[0068] Figure 5 is a flowchart illustrating a method 50 for indexing data according to a third embodiment of the present invention. Such as Figure 5 As shown, the method 50 starts at step S510.

[0069]In step S520, the predetermined time range is divided into multiple time periods. The time period can be divided according to prior knowledge, or the predetermined time range can be divided into multiple time periods, so that the data is evenly distributed in the multiple time periods. Preferably, the division strategy can also be dynamically adjusted according to whether the division result is reasonable.

[0070] In step S530, a first-level index (coarse-grained level index) is established for data in the current time period, and the first-level index includes a time period index and a subspace index. Various data structures may be employed to index time segments and subspaces, respectively. For example, a B+ tree may be used to establish indexes of each time period, an...

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Abstract

The invention provides a data index establishing system, which includes a time period dividing unit, a first index establishing unit, and a second index establishing unit, wherein the time period dividing unit is configured to divide a preset time range into multiple time periods; the first index establishing unit is configured to establish first grade indexes for data in a present time period, and each first grade index comprises a time period index and a subspace index; the second index establishing unit is configured to establish second grade indexes for data in the present time period during the time periods after the present time period; moreover, the second grade indexes have finer granularity than the first grade indexes. The invention further provides a data index establishing method and a data query method. With adoption of the system and methods, index maintenance cost under the circumstance of high frequency update is reduced, invalid scanning during the query process can be reduced, and thus query performance is improved.

Description

technical field [0001] The present invention relates to cloud computing technology, in particular to a system and method for indexing data and a corresponding data query method. Background technique [0002] With the development of RFID, GPS and other technologies, the Internet of Things has been rapidly popularized and widely used. In the Internet of Things environment, millions of detection objects will periodically generate data, causing traditional relational databases to encounter bottlenecks in terms of scalability, and their system throughput cannot meet the requirements. [0003] The cloud data management system has good scalability and supports high concurrency at the same time. It is an effective solution for IoT data management. The cloud data management system supports efficient point query and range query on the primary key (rowkey). However, for non-primary key queries, a full table scan is required. Although Map-Reduce technology can be used to improve quer...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/2264G06F16/2477G06F16/322
Inventor 饶佳胡卫松
Owner NEC (CHINA) CO LTD
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