Data storing, managing and inquiring method and system for distributed key-value storage system

A technology of data storage and data storage system, applied in the field of data storage, management and query mechanism, can solve the problems of reducing the application scope of text-based distributed databases, unable to realize multi-attribute retrieval of structured data, numerical statistics and analysis, etc. Achieve the effect of rich data query methods
CN102332030AInactive Publication Date: 2012-01-25INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
INST OF COMPUTING TECH CHINESE ACAD OF SCI
Publication Date
2012-01-25
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention provides a data storing, managing and inquiring method and system for a distributed key-value storage system. The method comprises the following steps: before storing data, respectively converting data into ordered character strings according to different data classifications and then storing the ordered character strings into the distributed key-value storage system, wherein storage sequences of the converted character strings sequenced according a dictionary sequence are consistent with numerical value sequences before conversion; and during data retrieval, the same conversion is carried out on the numerical values in retrieval conditions. The method provided by the invention supports storage and retrieval of complex data classifications and includes complex data inquiring methods, such as multi-field attribute inquiring, multi-data classification inquiring, numerical value statistic analysis and the like.
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Description

technical field

[0001] The invention belongs to the field of information security, and in particular relates to a data storage, management and query mechanism in a distributed key-value (KEY-VALUE) text data storage system. Background technique

[0002] At present, e-commerce, system operation logs, and web applications have accumulated a large amount of text data, which is huge in scale. Even small enterprises have collected terabytes of data. For the application background of such large data sets, traditional databases is no longer applicable. At present, the successful solution for such scenarios is to use distributed KEY-VALUE type NO-SQL databases to improve data compression efficiency and storage scale by establishing a column storage structure and combining technologies such as compression and partitioning. Because the text data type is simple and intuitive, it is easy to migrate in heterogeneous cluster systems. At present, typical large-scale distributed mass data ...

Claims

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