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CN-121996819-A - Unlimited storage database system and method based on function calculation mapping

CN121996819ACN 121996819 ACN121996819 ACN 121996819ACN-121996819-A

Abstract

The invention discloses an infinite storage database system and method based on function calculation mapping, and belongs to the technical field of database storage. The core of the system is that the physical storage requirement is converted into the calculation requirement through the unique mapping relation from the data value to the compound function, so that infinite logic storage in the fixed physical space is realized. The system comprises a data mapping layer, a function calculation layer and a physical storage layer. When data is written, the data value is mapped to the unique compound function through the deterministic algorithm, only the identifier of the function is stored instead of the original data, and when the data is queried, the original data value is calculated reversely through the function identifier. The composite function is a predefined mathematical transformation function that ensures a one-to-one correspondence of input data values to output function identifiers. The invention breaks through the limitation of physical storage space through the innovative architecture of computing power storage, and realizes infinite data storage capacity under the limited storage capacity.

Inventors

  • WANG CHUANGYE

Assignees

  • 许昌禾下梦农业科技有限公司

Dates

Publication Date
20260508
Application Date
20260128

Claims (10)

  1. 1. An infinitely stored database system based on a function computation map, comprising: the data mapping module is used for converting the input data value into a unique function identifier through a deterministic mapping algorithm; a function calculation module comprising a plurality of predefined composite functions, each composite function having a unique function identifier; The physical storage module is only used for storing the function identifier and the necessary metadata; The query calculation module is used for reversely calculating to obtain an original data value through a corresponding composite function according to the stored function identifier; Wherein the mapping algorithm in the data mapping module ensures that different data values are mapped to different function identifiers, each function identifier corresponding to a unique composite function in the function calculation module.
  2. 2. The database system of claim 1, wherein the complex functions are mathematical transformation functions including, but not limited to, polynomial functions, trigonometric function combinations, exponential logarithmic functions, or combinations thereof, each complex function having a fixed mathematical expression and adjustable parameters.
  3. 3. The database system of claim 1, wherein the mapping algorithm is a one-way hash function or a cryptographic hash function, and the output space is larger than the input space, so that the mapping relation between the data value and the function identifier is ensured.
  4. 4. The database system of claim 1, wherein the metadata stored by the physical storage module comprises a data access frequency, a storage time stamp, and function parameter configuration information, wherein the storage space requirement of the function identifier is substantially smaller than the storage space requirement of the original data value.
  5. 5. The database system of claim 1, wherein the query computing module comprises a computational effort scheduling unit that dynamically allocates computing resources based on query complexity, supports parallel computing acceleration, and wherein computational effort consumption is proportional to data complexity and independent of data size.
  6. 6. The database system of claim 1, further comprising a function optimization module for analyzing the data access patterns and dynamically adjusting the parameter configuration of the composite function to optimize the computational efficiency and maintain the physical storage space constant.
  7. 7. A method for implementing an infinitely stored database based on a function computation map, comprising the steps of: Step S1, a composite function library is established, a group of mathematical transformation functions are defined, and unique identifiers are allocated to each function; S2, inputting the original data value into a mapping function to generate a corresponding function identifier when writing data; step S3, only the generated function identifier and related metadata are stored, and the original data value is not stored; s4, reading the stored function identifier during data query; step S5, finding out a corresponding compound function according to the function identifier; S6, restoring the original data value through inverse function calculation or numerical approximation algorithm of the composite function; and step S7, returning the calculated data value to the query requester.
  8. 8. The method of claim 7, wherein the step S1 of creating a library of composite functions includes designing a family of matched mathematical transformation functions based on the statistical distribution characteristics of the data values, and setting adjustable parameters for each function, the parameter adjustment not changing the function identifier.
  9. 9. The method of claim 7, wherein the method of calculating the inverse function in the step S6 comprises the steps of analyzing the inverse function, solving the inverse function through numerical iteration and approximating the inverse function through machine learning, wherein the calculation accuracy can be controlled through iteration times, and the calculation force consumption is in direct proportion to the accuracy requirement.
  10. 10. A computer readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements the method according to any of claims 7-9, the system supporting unlimited data storage under fixed physical storage space by exchanging power consumption for unlimited expansion of the storage space.

Description

Unlimited storage database system and method based on function calculation mapping Technical Field The invention relates to the technical field of database storage, in particular to a database system and a method for realizing infinite storage of a fixed physical space through function calculation mapping. Technical Field As data explosively grows, traditional databases face severe storage space pressures. The prior art storage technology is primarily optimized around the following aspects: data compression technology, which is to reduce data storage space through an algorithm, but has a limited compression rate, generally only reduces 50% -90% of storage requirements, and can not realize infinite compression. And the repeated data is deleted, namely the repeated data blocks are identified and eliminated, and the repeated data blocks have obvious effect under specific scenes, but are invalid to non-repeated data. Hierarchical storage-migration of cold data to low cost storage media, but only cost optimization, not space optimization. Cloud storage expansion, namely expanding capacity by increasing storage nodes, but requiring corresponding hardware investment. The prior patent document CN201810123356. X discloses a database storage optimization method based on a compression algorithm, which reduces storage space through multistage compression, but has theoretical limit on compression rate. Another document, infinite storage systems research, proposes a storage reclamation mechanism based on the lifecycle of data, but cannot solve the problem of continuous growth of new data. Conventional storage technologies are fundamentally limited by physical storage capacity, and expansion of storage space is necessarily accompanied by an increase in hardware cost. Therefore, a new storage architecture capable of breaking through the limitation of physical storage space is needed. Disclosure of Invention The invention aims to provide an infinite storage database system and method based on function calculation mapping, which are used for realizing infinite logic storage in a fixed physical space by converting storage requirements into calculation requirements. The core idea of the invention is to map data values to a function space by mathematical transformations, storing only the identifiers of the functions and not the data itself. Since the mathematical description space of a function is much larger than the data value space, it is theoretically possible to represent infinite data in a limited physical storage. The technical proposal is as follows: The system architecture: And the data mapping module is used for receiving the original data value and generating a unique function identifier through a deterministic mapping algorithm. The mapping algorithm ensures that different data values are mapped to different identifiers. The function calculation module maintains a predefined composite function library, each function having a unique identifier and a mathematical definition. The library of functions can be extended but the number of functions is much smaller than the representable amount of data. And the physical storage module only stores the function identifier and a small amount of metadata, and does not store the original data value. The storage space requirement is constant irrespective of the amount of data. And the query calculation module finds out the corresponding function according to the function identifier and restores the original data value through calculation. The computing process consumes computational effort, and the computational effort requirements are related to data complexity. Mathematical principles: let the original data value be D, the mapping function be M, the complex function be F, then there are: storage phase id=m (D), storing only ID The inquiry phase D' =F-1 (ID), where F-1 is the inverse or approximation function of F The key point is that the stored ID is fixed in length and much smaller than D, while the computational complexity of F is acceptable. By careful design of the family of functions F, the ID space is enabled to cover all possible D values. Example 1 digital data storage For numerical data, a polynomial function is selected as the complex function: F(x) = a0 + a1x + a2x² + ... + anxn parameter vector a= [ a 0, a1, ..., an ] uniquely identifies a function The data value D is mapped to the parameter vector A, storing the code of A as ID Recovery D by polynomial root computing at query time Storage costs O (n) parameters, n typically being 5-10 Calculation cost polynomial root, complexity O (n 2) Example 2 text data storage For text data, strings are encoded into a digital sequence using trigonometric function combinations: F(x) = Σi(bi·sin(cix + di)) Parameter set B, C, D encodes text information Storing only parametric codes when stored Recovering text by inverse fourier transform at query time Example 3 image data storage For image data, a combination of wavelet transform