Data storage optimization method and system

Abstract

The invention discloses a data storage optimization method and system, and belongs to the technical field of data storage, and the method comprises the steps: obtaining a data storage state, and generating a data storage state index; wherein the data storage state comprises a data volume change value, a data storage total amount and an uncompressed data access frequency; judging whether the storage state of the data meets the storage requirement or not according to the data storage state index; if the storage state of the data does not meet the storage requirement, acquiring data quality data, and generating a data quality evaluation index; wherein the data quality data comprises a data repetition rate, a data processing step number and a data error rate; obtaining a current data processing cycle, and generating a data processing cycle adjustment value; according to the method, the data processing period is adjusted through the data storage state and the data quality, and the storage efficiency is remarkably improved by flexibly adjusting the data processing period and optimizing the data storage strategy, so that the utilization rate of the storage space is optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of data storage, and particularly relates to an optimization method and system for data storage. Background Art

[0002] With the advent of the information age, the explosive growth of data volume has brought unprecedented challenges to data storage and processing systems. In traditional data storage systems, either too high or too low data processing frequency may lead to overloaded system or wasted resources, thus affecting the timeliness of data processing and the rational use of storage resources.

[0003] Existing storage optimization technologies usually focus on aspects such as the selection of storage media, data compression, and deduplication, but there is no effective solution for the reasonable adjustment of the data processing cycle, resulting in the need to improve the data processing efficiency and storage space utilization rate. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides an optimization method and system for data storage, which solves the above problems.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: An optimization method for data storage includes the following steps: Obtain the state of data storage and generate a data storage state index; wherein, the state of data storage includes the data volume change value, the total data storage volume, and the uncompressed data access frequency; the data volume change value refers to the difference between the data storage volume before and after the change; the total data storage volume refers to the total amount of data stored in the storage medium; Judge whether the storage state of the data meets the storage requirements according to the data storage state index; If the storage state of the data does not meet the storage requirements, obtain data quality data and generate a data quality evaluation index; wherein, the data quality data includes the data duplication rate, the number of data processing steps, and the data error rate; Obtain the current data processing cycle and generate a data processing cycle adjustment value.

[0006] Based on the above technical solutions, the present invention also provides the following optional technical solutions: A further technical solution, the step of obtaining the state of data storage and generating a data storage state index specifically includes the following steps: Obtain the data volume change value and the total data storage volume, and perform a ratio process on the data volume change value and the historical total data storage volume to generate a data volume change index; wherein, the historical total data storage volume refers to the total data storage volume before the data volume change; Obtain the total data storage volume and the maximum storage capacity of the storage medium to generate a data storage volume evaluation index; Among them, the generation method of the data storage volume evaluation index is specifically as follows: Perform a difference operation on the total data storage volume and the maximum storage volume of the storage medium to generate a storage volume difference; Perform a ratio operation on the storage volume difference and the maximum storage volume of the storage medium to generate a data storage volume evaluation index; Obtain the uncompressed data access frequency and generate an uncompressed data evaluation index; Among them, the generation method of the uncompressed data evaluation index is specifically as follows: Perform a difference operation on the uncompressed data access frequency and the uncompressed data access frequency threshold to generate an uncompressed data access frequency difference; the uncompressed data access frequency threshold refers to the maximum access frequency when data needs to be compressed; Perform a ratio operation on the uncompressed data access frequency difference and the uncompressed data access frequency threshold to generate an uncompressed data evaluation index; Through the formula , generate the data storage status index Ds; In the formula, Tp represents the data storage volume evaluation index, Af represents the uncompressed data evaluation index, Rc represents the data volume change index, and α, β, and γ are all weight coefficients, and α + β + γ = 1.

[0007] For a further technical solution, to determine whether the storage status of the data meets the storage requirements according to the data storage status index, the determination method is specifically as follows: Compare the data storage status index with the data storage status index threshold; the data storage status index threshold refers to the maximum value of the data storage status index under normal conditions; If the data storage status index is greater than the data storage status index threshold, it means that the larger the data storage status index, the more abnormal the storage status of the data, then it is determined that the data storage status does not meet the storage requirements.

[0008] For a further technical solution, if the storage status of the data does not meet the storage requirements, obtain data quality data and generate a data quality evaluation index, which specifically includes the following steps: If the storage status of the data does not meet the storage requirements, obtain the data duplication rate and generate a data duplication rate evaluation index; the data duplication rate refers to the proportion of the content or entries that appear repeatedly in the dataset; Among them, the generation method of the data duplication rate evaluation index is specifically as follows: Obtain the data duplication rate, perform a difference operation on the data duplication rate and the data duplication rate threshold to generate a data duplication rate difference; the data duplication rate threshold refers to the maximum duplication rate that the storage medium can withstand without affecting the computing performance; Ratio the difference in data duplication rate with the data duplication rate threshold to generate a data duplication rate evaluation index; Obtain the number of data processing steps to generate a data processing steps evaluation index; Among them, the specific method for generating the data processing steps evaluation index is as follows: Obtain the number of data processing steps, perform a difference process on the number of data processing steps and the data processing steps threshold to generate a difference in the number of data processing steps; Ratio the difference in the number of data processing steps with the data processing steps threshold to generate a data processing steps evaluation index; Obtain the data error rate to generate a data error rate evaluation index; among them, the data error rate refers to the ratio of the number of error data to the total number of data; Among them, the specific method for generating the data error rate evaluation index is as follows: Obtain the data error rate, perform a difference process on the data error rate and the data error rate threshold to generate a data error rate difference; the data error rate threshold refers to the maximum error rate that the storage medium can tolerate without affecting the computing performance; Ratio the data error rate difference with the data error rate threshold to generate a data error rate evaluation index; Through the formula , generate a data quality evaluation index Mp; In the formula, Da represents the data duplication rate evaluation index, Dp represents the data processing steps evaluation index, De represents the data error rate evaluation index, and a1, a2, and a3 are all proportionality coefficients.

[0009] In a further technical solution, the obtaining of the current data processing cycle and generating a data processing cycle adjustment value specifically includes the following steps: Obtain the current data processing cycle; Establish a data processing cycle evaluation model; Obtain the temperature factor of the storage medium, substitute the temperature factor of the storage medium, the data quality index, the current data processing cycle, and the data storage status index into the data processing cycle evaluation model to generate a data processing cycle adjustment value Sv; Among them, the expression of the data processing cycle evaluation model is: ; In the expression, Pv represents the current data processing cycle, Ds represents the data storage status index, Mp represents the data quality index, and Tf represents the temperature factor of the storage medium.

[0010] In a further technical solution, the specific method for obtaining the temperature factor of the storage medium is as follows: Obtain the temperature value of the current storage medium, and compare the temperature value of the storage medium with the standard temperature value of the storage medium; If the temperature value of the storage medium is greater than the standard temperature value of the storage medium, mark the temperature as a high-temperature value; Perform a difference process on the high-temperature value and the standard temperature value of the storage medium to generate a temperature difference; Perform a ratio process on the temperature difference and the standard temperature value of the storage medium to generate a temperature factor of the storage medium.

[0011] An optimization system for data storage, the system includes: A data storage status analysis unit, used to obtain the status of data storage and generate a data storage status index; wherein, the status of data storage includes the data volume change value, the total data storage volume, and the uncompressed data access frequency; the data volume change value refers to the difference between the data storage volume before and after the change; the total data storage volume refers to the total amount of data stored in the storage medium; A data storage status judgment unit, used to judge whether the storage status of the data meets the storage requirements according to the data storage status index; A data quality evaluation unit. If the storage status of the data does not meet the storage requirements, the data quality evaluation unit is used to obtain data quality data and generate a data quality evaluation index; wherein, the data quality data includes the data duplication rate, the number of data processing steps, and the data error rate; A data processing cycle analysis unit, used to obtain the current data processing cycle and generate a data processing cycle adjustment value.

[0012] A further technical solution, the data storage status analysis unit specifically includes: A data volume change index generation module, used to obtain the data volume change value and the total data storage volume, perform a ratio process on the data volume change value and the total historical data storage volume, and generate a data volume change index; wherein, the total historical data storage volume refers to the total data storage volume before the data volume change; A data storage volume evaluation index generation module, used to obtain the total data storage volume and the maximum storage volume of the storage medium, and generate a data storage volume evaluation index; An uncompressed data evaluation index generation module, used to obtain the uncompressed data access frequency and generate an uncompressed data evaluation index; A data storage status index generation module, used to perform a weighted process on the data volume change index, the data storage volume evaluation index, and the uncompressed data evaluation index to generate a data storage status index.

[0013] A further technical solution, the data quality evaluation unit specifically includes: The data duplication rate evaluation index generation module is used to obtain the data duplication rate and generate a data duplication rate evaluation index if the storage status of the data does not meet the storage requirements; the data duplication rate refers to the proportion of the content or entries that appear repeatedly in the dataset. The data processing step evaluation index generation module is used to obtain the number of data processing steps and generate a data processing step evaluation index. The data error rate evaluation index generation module is used to obtain the data error rate and generate a data error rate evaluation index. The data quality evaluation index generation module is used to perform weighted processing on the data duplication rate evaluation index, the data processing step evaluation index, and the data error rate evaluation index to generate a data quality evaluation index.

[0014] A further technical solution is that the data processing cycle analysis unit specifically includes: The data acquisition module is used to acquire the current data processing cycle. The model establishment module is used to establish a data processing cycle evaluation model. The data processing cycle adjustment value generation module is used to obtain the temperature factor of the storage medium, substitute the temperature factor of the storage medium, the data quality index, the current data processing cycle, and the data storage status index into the data processing cycle evaluation model, and generate a data processing cycle adjustment value.

[0015] The present invention provides an optimization method and system for data storage, and has the following beneficial effects compared with the prior art: The present invention adjusts the data processing cycle according to the storage status and data quality of the data. By flexibly adjusting the data processing cycle, optimizing the data storage strategy, significantly improving the storage efficiency, and thus optimizing the utilization rate of the storage space. Description of the Drawings

[0016] Figure 1 It is a flow block diagram of an optimization method for data storage provided by the present invention.

[0017] Figure 2 It is a flow block diagram of step S10 provided by the present invention.

[0018] Figure 3 It is a flow block diagram of step S20 provided by the present invention.

[0019] Figure 4 It is a flow block diagram of step S30 provided by the present invention.

[0020] Figure 5 It is a flow block diagram of step S40 provided by the present invention.

[0021] Figure 6Block diagram of an optimization system for data storage provided by the present invention.

[0022] Figure 7 Block diagram of the data storage status analysis unit 10 provided by the present invention.

[0023] Figure 8 Block diagram of the data quality assessment unit 30 provided by the present invention.

[0024] Figure 9 Block diagram of the data processing cycle analysis unit 40 provided by the present invention. Detailed implementation manners

[0025] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0026] The following describes in detail the specific implementation of the present invention with reference to specific embodiments.

[0027] Please refer to Figure 1 , an optimization method for data storage provided by an embodiment of the present invention, includes the following steps: Step S10: Obtain the status of data storage and generate a data storage status index; wherein, the status of data storage includes the data volume change value, the total data storage volume, and the uncompressed data access frequency; the data volume change value refers to the difference between the data storage volume before and after the change; the total data storage volume refers to the total amount of data stored in the storage medium; Step S20: Determine whether the storage status of the data meets the storage requirements according to the data storage status index; Step S30: If the storage status of the data does not meet the storage requirements, obtain data quality data and generate a data quality assessment index; wherein, the data quality data includes the data duplication rate, the number of data processing steps, and the data error rate; Step S40: Obtain the current data processing cycle and generate a data processing cycle adjustment value.

[0028] Please refer to Figure 2 , as a preferred embodiment of the present invention, the step S10 specifically includes the following steps: Step S11: Obtain the data volume change value and the total data storage volume, perform a ratio process on the data volume change value and the total historical data storage volume, and generate a data volume change index; wherein, the total historical data storage volume refers to the total data storage volume before the data volume change; Step S12: Obtain the total data storage volume and the maximum storage capacity of the storage medium, and generate a data storage volume assessment index; Among them, the generation method of the data storage capacity evaluation index is specifically as follows: Perform a difference operation on the total data storage amount and the maximum storage amount of the storage medium to generate a storage amount difference; Perform a ratio operation on the storage amount difference and the maximum storage amount of the storage medium to generate a data storage capacity evaluation index; Step S13: Obtain the uncompressed data access frequency and generate an uncompressed data evaluation index; Among them, the generation method of the uncompressed data evaluation index is specifically as follows: Perform a difference operation on the uncompressed data access frequency and the uncompressed data access frequency threshold to generate an uncompressed data access frequency difference; the uncompressed data access frequency threshold refers to the maximum access frequency when data needs to be compressed; Perform a ratio operation on the uncompressed data access frequency difference and the uncompressed data access frequency threshold to generate an uncompressed data evaluation index; Step S14: Perform a weighted operation on the data volume change index, the data storage capacity evaluation index, and the uncompressed data evaluation index to generate a data storage state index; Exemplarily, through the formula , generate the data storage state index Ds; In the formula, Tp represents the data storage capacity evaluation index, Af represents the uncompressed data evaluation index, Rc represents the data volume change index, and α, β, and γ are all weight coefficients, and α + β + γ = 1.

[0029] Please refer to Figure 3 , as a preferred embodiment of the present invention, the judgment method of step S20 is specifically as follows: Compare the data storage state index with the data storage state index threshold; the data storage state index threshold refers to the maximum value of the data storage state index under normal conditions; If the data storage state index is less than or equal to the data storage state index threshold, it means that the smaller the data storage state index, the more normal the data storage state, and it is determined that the data storage state meets the storage requirements; If the data storage state index is greater than the data storage state index threshold, it means that the larger the data storage state index, the more abnormal the data storage state, and it is determined that the data storage state does not meet the storage requirements.

[0030] Please refer to Figure 4 , as a preferred embodiment of the present invention, step S30 specifically includes the following steps: Step S31: If the data storage state does not meet the storage requirements, obtain the data duplication rate and generate a data duplication rate evaluation index; the data duplication rate refers to the proportion of the content or entries that repeatedly appear in the dataset.

[0031] Among them, the specific generation method of the data duplication rate evaluation index is as follows: Obtain the data duplication rate, perform a difference operation on the data duplication rate and the data duplication rate threshold to generate a data duplication rate difference; the data duplication rate threshold refers to the maximum duplication rate that the storage medium can withstand without affecting the computing performance. It should be noted that the value of the data duplication rate threshold is set by relevant personnel in the field. Perform a ratio operation on the data duplication rate difference and the data duplication rate threshold to generate a data duplication rate evaluation index. It should be noted that the data duplication rate can be obtained by processing the data through a hashing algorithm (such as MD5, SHA256, etc.) to convert the data into a hash value of a fixed length; for the same data, the hash value will be the same, and if the hash values are the same, it is considered that the data is duplicated; this algorithm is an existing technology and will not be elaborated here.

[0032] Step S32: Obtain the number of data processing steps and generate a data processing step evaluation index. Among them, the specific generation method of the data processing step evaluation index is as follows: Obtain the number of data processing steps, perform a difference operation on the number of data processing steps and the data processing step number threshold to generate a difference in the number of data processing steps. Perform a ratio operation on the difference in the number of data processing steps and the data processing step number threshold to generate a data processing step evaluation index.

[0033] Step S33: Obtain the data error rate and generate a data error rate evaluation index; among them, the data error rate refers to the ratio of the number of error data to the total number of data. Among them, the specific generation method of the data error rate evaluation index is as follows: Obtain the data error rate, perform a difference operation on the data error rate and the data error rate threshold to generate a data error rate difference; the data error rate threshold refers to the maximum error rate that the storage medium can withstand without affecting the computing performance. It should be noted that the value of the data error rate threshold is set by relevant personnel in the field. Perform a ratio operation on the data error rate difference and the data error rate threshold to generate a data error rate evaluation index. It should be noted that the number of error data can be obtained through parity check, CRC (Cyclic Redundancy Check), etc.

[0034] Step S34: Perform a weighted operation on the data duplication rate evaluation index, the data processing step evaluation index, and the data error rate evaluation index to generate a data quality evaluation index. Exemplarily, through the formula , the data quality evaluation index Mp is generated; In the formula, Da represents the data duplication rate evaluation index, Dp represents the data processing step evaluation index, De represents the data error rate evaluation index, and a1, a2, and a3 are all proportionality coefficients.

[0035] Please refer to Figure 5 , as a preferred embodiment of the present invention, the step S40 specifically includes the following steps: Step S41: Obtain the current data processing cycle; Step S42: Establish a data processing cycle evaluation model; Step S43: Obtain the temperature factor of the storage medium, substitute the temperature factor of the storage medium, the data quality index, the current data processing cycle, and the data storage status index into the data processing cycle evaluation model, and generate a data processing cycle adjustment value Sv; Among them, the expression of the data processing cycle evaluation model is: ; In the expression, Pv represents the current data processing cycle, Ds represents the data storage status index, Mp represents the data quality index, and Tf represents the temperature factor of the storage medium; Among them, the specific method for obtaining the temperature factor of the storage medium is: Obtain the current temperature value of the storage medium, and compare the temperature value of the storage medium with the standard temperature value of the storage medium; If the temperature value of the storage medium is less than or equal to the standard temperature value of the storage medium, mark this temperature as the normal temperature value; If the temperature value of the storage medium is greater than the standard temperature value of the storage medium, mark this temperature as the high temperature value; Perform a difference processing on the high temperature value and the standard temperature value of the storage medium to generate a temperature difference; Perform a ratio processing on the temperature difference and the standard temperature value of the storage medium to generate the temperature factor of the storage medium; Exemplarily, through the formula , the temperature factor Tf of the storage medium is generated; In the formula, T i represents the high temperature value, and T0 represents the standard temperature value of the storage medium.

[0036] As a preferred embodiment of the present invention, when receiving the data processing cycle adjustment value Sv, adjust the data processing cycle of the storage medium according to the data processing cycle adjustment value Sv.

[0037] Please refer to Figure 6, the present invention also provides an optimization system for data storage, and the system includes: A data storage status analysis unit 10, configured to obtain the status of data storage and generate a data storage status index; wherein, the status of data storage includes the data volume change value, the total data storage volume, and the uncompressed data access frequency; the data volume change value refers to the difference between the data storage volume before and after the change; the total data storage volume refers to the total amount of data stored in the storage medium; A data storage status judgment unit 20, configured to judge whether the storage status of the data meets the storage requirements according to the data storage status index; A data quality evaluation unit 30, if the storage status of the data does not meet the storage requirements, the data quality evaluation unit is configured to obtain data quality data and generate a data quality evaluation index; wherein, the data quality data includes the data duplication rate, the number of data processing steps, and the data error rate; A data processing cycle analysis unit 40, configured to obtain the current data processing cycle and generate a data processing cycle adjustment value.

[0038] Please refer to Figure 7 , as a preferred embodiment of the present invention, the data storage status analysis unit 10 specifically includes: A data volume change index generation module 11, configured to obtain the data volume change value and the total data storage volume, perform a ratio process on the data volume change value and the total historical data storage volume, and generate a data volume change index; wherein, the total historical data storage volume refers to the total data storage volume before the data volume change; A data storage volume evaluation index generation module 12, configured to obtain the total data storage volume and the maximum storage volume of the storage medium, and generate a data storage volume evaluation index; An uncompressed data evaluation index generation module 13, configured to obtain the uncompressed data access frequency and generate an uncompressed data evaluation index; A data storage status index generation module 14, configured to perform a weighted process on the data volume change index, the data storage volume evaluation index, and the uncompressed data evaluation index, and generate a data storage status index.

[0039] Please refer to Figure 8 , as a preferred embodiment of the present invention, the data quality evaluation unit 30 specifically includes: A data duplication rate evaluation index generation module 31, if the storage status of the data does not meet the storage requirements, the data duplication rate evaluation index generation module 31 is configured to obtain the data duplication rate and generate a data duplication rate evaluation index; the data duplication rate refers to the proportion of the content or entries that appear repeatedly in the data set; A data processing step evaluation index generation module 32, configured to obtain the number of data processing steps and generate a data processing step evaluation index; A data error rate evaluation index generation module 33 is configured to obtain a data error rate and generate a data error rate evaluation index; A data quality evaluation index generation module 34 is configured to perform weighted processing on the data duplication rate evaluation index, the data processing step evaluation index, and the data error rate evaluation index to generate a data quality evaluation index.

[0040] Please refer to Figure 9 , as a preferred embodiment of the present invention, the data processing cycle analysis unit 40 specifically includes: A data acquisition module 41 is configured to acquire the current data processing cycle; A model establishment module 42 is configured to establish a data processing cycle evaluation model; A data processing cycle adjustment value generation module 43 is configured to obtain the temperature factor of the storage medium, substitute the temperature factor of the storage medium, the data quality index, the current data processing cycle, and the data storage status index into the data processing cycle evaluation model to generate a data processing cycle adjustment value.

[0041] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An optimization method for data storage, characterized in that, It includes the following steps: Obtain the state of data storage and generate a data storage state index; wherein, the state of data storage includes the data volume change value, the total data storage volume, and the uncompressed data access frequency; the data volume change value refers to the difference between the data storage volume before and after the change; the total data storage volume refers to the total amount of data stored in the storage medium; Judge whether the storage state of the data meets the storage requirements according to the data storage state index; If the storage state of the data does not meet the storage requirements, obtain data quality data and generate a data quality evaluation index; wherein, the data quality data includes the data duplication rate, the number of data processing steps, and the data error rate; Obtain the current data processing cycle and generate a data processing cycle adjustment value.

2. An optimization method for data storage according to claim 1, characterized in that, The step of obtaining the state of data storage and generating a data storage state index specifically includes the following steps: Obtain the data volume change value and the total data storage volume, perform a ratio process on the data volume change value and the historical total data storage volume, and generate a data volume change index; wherein, the historical total data storage volume refers to the total data storage volume before the data volume change; Obtain the total data storage volume and the maximum storage capacity of the storage medium, and generate a data storage volume evaluation index; Among them, the generation method of the data storage volume evaluation index is specifically: Perform a difference process on the total data storage volume and the maximum storage capacity of the storage medium to generate a storage volume difference; Perform a ratio process on the storage volume difference and the maximum storage capacity of the storage medium to generate a data storage volume evaluation index; Obtain the uncompressed data access frequency and generate an uncompressed data evaluation index; Among them, the generation method of the uncompressed data evaluation index is specifically: Perform a difference process on the uncompressed data access frequency and the uncompressed data access frequency threshold to generate an uncompressed data access frequency difference; the uncompressed data access frequency threshold refers to the maximum access frequency when the data needs to be compressed; Perform a ratio process on the uncompressed data access frequency difference and the uncompressed data access frequency threshold to generate an uncompressed data evaluation index; Generate the data storage status index Ds through the formula , and generate the data storage status index Ds; In the formula, Tp represents the data storage volume evaluation index, Af represents the uncompressed data evaluation index, Rc represents the data volume change index, α, β, and γ are all weight coefficients, and α + β + γ = 1.

3. The optimization method for data storage according to claim 2, wherein, The method of judging whether the storage state of the data meets the storage requirements according to the data storage state index is specifically: Compare the data storage state index with the data storage state index threshold; The data storage state index threshold refers to the maximum value of the data storage state index under normal conditions; If the data storage state index is greater than the data storage state index threshold, it means that the larger the data storage state index, the more abnormal the storage state of the data, then it is determined that the data storage state does not meet the storage requirements.

4. An optimization method for data storage according to claim 1, characterized in that, The step of obtaining data quality data and generating a data quality evaluation index if the storage state of the data does not meet the storage requirements specifically includes the following steps: If the storage state of the data does not meet the storage requirements, obtain the data duplication rate and generate a data duplication rate evaluation index; the data duplication rate refers to the proportion of the content or entries that appear repeatedly in the dataset; Among them, the generation method of the data duplication rate evaluation index is specifically: Obtain the data duplication rate, perform a difference operation on the data duplication rate and the data duplication rate threshold to generate a data duplication rate difference; the data duplication rate threshold refers to the maximum duplication rate that the storage medium can withstand without affecting the computing performance; Perform a ratio operation on the data duplication rate difference and the data duplication rate threshold to generate a data duplication rate evaluation index; Obtain the number of data processing steps and generate a data processing steps evaluation index; Among them, the specific generation method of the data processing steps evaluation index is as follows: Obtain the number of data processing steps, perform a difference operation on the number of data processing steps and the data processing steps threshold to generate a difference in the number of data processing steps; Perform a ratio operation on the difference in the number of data processing steps and the data processing steps threshold to generate a data processing steps evaluation index; Obtain the data error rate and generate a data error rate evaluation index; among them, the data error rate refers to the ratio of the number of error data to the total number of data; Among them, the specific generation method of the data error rate evaluation index is as follows: Obtain the data error rate, perform a difference operation on the data error rate and the data error rate threshold to generate a data error rate difference; the data error rate threshold refers to the maximum error rate that the storage medium can withstand without affecting the computing performance; Perform a ratio operation on the data error rate difference and the data error rate threshold to generate a data error rate evaluation index; Through the formula , generate the data quality evaluation index Mp; In the formula, Da represents the data duplication rate evaluation index, Dp represents the data processing steps evaluation index, De represents the data error rate evaluation index, and a1, a2, and a3 are all proportionality coefficients.

5. An optimization method for data storage according to claim 1, characterized in that The obtaining of the current data processing cycle and generating a data processing cycle adjustment value specifically includes the following steps: Obtain the current data processing cycle; Establish a data processing cycle evaluation model; Obtain the temperature factor of the storage medium, substitute the temperature factor of the storage medium, the data quality index, the current data processing cycle, and the data storage status index into the data processing cycle evaluation model to generate a data processing cycle adjustment value Sv; Among them, the expression of the data processing cycle evaluation model is: ； In the expression, Pv represents the current data processing cycle, Ds represents the data storage status index, Mp represents the data quality index, and Tf represents the temperature factor of the storage medium.

6. An optimization method for data storage according to claim 5, characterized in that, The specific obtaining method of the temperature factor of the storage medium is as follows: Obtain the current temperature value of the storage medium and compare the temperature value of the storage medium with the standard temperature value of the storage medium; If the temperature value of the storage medium is greater than the standard temperature value of the storage medium, mark this temperature as the high temperature value; Perform a difference operation on the high temperature value and the standard temperature value of the storage medium to generate a temperature difference; Perform a ratio operation on the temperature difference and the standard temperature value of the storage medium to generate the temperature factor of the storage medium.

7. An optimized system for data storage, characterized in that, This system is used to execute the method described in any one of the above claims 1-6. This system includes: A data storage status analysis unit for obtaining the status of data storage and generating a data storage status index; wherein, the status of data storage includes the data volume change value, the total data storage volume, and the uncompressed data access frequency; the data volume change value refers to the difference between the data storage volume before and after the change; the total data storage volume refers to the total amount of data stored in the storage medium; A data storage status judgment unit for judging whether the storage status of data meets the storage requirements according to the data storage status index; A data quality evaluation unit. If the storage status of the data does not meet the storage requirements, the data quality evaluation unit is used to obtain data quality data and generate a data quality evaluation index; wherein, the data quality data includes the data duplication rate, the number of data processing steps, and the data error rate; A data processing cycle analysis unit for obtaining the current data processing cycle and generating a data processing cycle adjustment value.

8. An optimized system for data storage according to claim 7, characterized in that, The data storage status analysis unit specifically includes: A data volume change index generation module for obtaining the data volume change value and the total data storage volume, performing a ratio process on the data volume change value and the historical total data storage volume, and generating a data volume change index; wherein, the historical total data storage volume refers to the total data storage volume before the data volume change; A data storage volume evaluation index generation module for obtaining the total data storage volume and the maximum storage volume of the storage medium, and generating a data storage volume evaluation index; An uncompressed data evaluation index generation module for obtaining the uncompressed data access frequency and generating an uncompressed data evaluation index; A data storage status index generation module for performing a weighted process on the data volume change index, the data storage volume evaluation index, and the uncompressed data evaluation index to generate a data storage status index.

9. An optimization system for data storage according to claim 7, characterized in that, The data quality evaluation unit specifically includes: A data duplication rate evaluation index generation module. If the storage status of the data does not meet the storage requirements, the data duplication rate evaluation index generation module is used to obtain the data duplication rate and generate a data duplication rate evaluation index; the data duplication rate refers to the proportion of the content or entries that appear repeatedly in the data set; A data processing step evaluation index generation module for obtaining the number of data processing steps and generating a data processing step evaluation index; A data error rate evaluation index generation module for obtaining the data error rate and generating a data error rate evaluation index; A data quality evaluation index generation module for performing a weighted process on the data duplication rate evaluation index, the data processing step evaluation index, and the data error rate evaluation index to generate a data quality evaluation index.

10. An optimized system for data storage according to claim 7, characterized in that, The data processing cycle analysis unit specifically includes: A data acquisition module for obtaining the current data processing cycle; A model establishment module for establishing a data processing cycle evaluation model; A data processing cycle adjustment value generation module for obtaining the temperature factor of the storage medium, substituting the temperature factor of the storage medium, the data quality index, the current data processing cycle, and the data storage status index into the data processing cycle evaluation model, and generating a data processing cycle adjustment value.

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