An optimization method and system for data storage

Abstract

The present invention discloses a data storage optimization method and system, which belongs to the field of data storage technology, including obtaining the state of data storage and generating a data storage state index; wherein the state of data storage includes a data volume change value, a total amount of data stored and an access frequency of uncompressed data; according to the data storage state index, judging whether the storage state of the data meets the storage requirements; if the storage state of the data does not meet the storage requirements, obtaining data quality data and generating a data quality assessment index; wherein the data quality data includes a data repetition rate, a number of data processing steps and a data error rate; obtaining a current data processing cycle and generating a data processing cycle adjustment value; the present invention adjusts the data processing cycle according to the data storage state and data quality, optimizes the data storage strategy by flexibly adjusting the data processing cycle, significantly improves the storage efficiency, and thus optimizes the utilization of the storage space.

Description

TECHNICAL FIELD

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

[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, data processing frequency that is too high or too low can lead to excessive system load or resource waste, thereby affecting the timeliness of data processing and the rational use of storage resources.

[0003] Existing storage optimization techniques usually focus on the selection of storage media, data compression and deduplication, etc., but there is no effective solution for the rational adjustment of data processing period, resulting in the need to improve the processing efficiency of data and the utilization rate of storage space. SUMMARY

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

[0005] To achieve the above purpose, the present application is implemented by the following technical scheme: an optimization method for data storage, comprising the following steps:

[0006] Obtain the state of data storage to generate a data storage state index; wherein the state of data storage includes data volume change value, total data storage volume and uncompressed data access frequency; the data volume change value refers to the difference between before and after the change of data storage volume; the total data storage volume refers to the total amount of data storage in the storage medium;

[0007] According to the data storage state index, determine whether the data storage state meets the storage requirements;

[0008] If the data storage state does not meet the storage requirements, obtain data quality data to generate a data quality evaluation index; wherein the data quality data includes data duplication rate, data processing step number and data error rate;

[0009] Obtain the current data processing period to generate a data processing period adjustment value.

[0010] On the basis of the above technical scheme, the present application further provides the following optional technical schemes:

[0011] Further technical scheme, the step of obtaining the state of data storage to generate a data storage state index specifically includes the following steps:

[0012] Obtaining the data amount change value and the total data storage amount, and performing ratio processing on the data amount change value and the total data storage history amount to generate a data amount change index; wherein the total data storage history amount refers to the total data storage amount before the data amount change;

[0013] Obtaining the total data storage amount and the maximum storage amount of the storage medium to generate a data storage amount evaluation index;

[0014] The generation method of the data storage amount evaluation index is specifically as follows:

[0015] Performing difference processing on the total data storage amount and the maximum storage amount of the storage medium to generate a storage amount difference;

[0016] Performing ratio processing on the storage amount difference and the maximum storage amount of the storage medium to generate the data storage amount evaluation index;

[0017] Obtaining the uncompressed data access frequency to generate an uncompressed data evaluation index;

[0018] The generation method of the uncompressed data evaluation index is specifically as follows:

[0019] Performing difference processing 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;

[0020] Performing ratio processing on the uncompressed data access frequency difference and the uncompressed data access frequency threshold to generate the uncompressed data evaluation index;

[0021] The data storage state index Ds is generated through the formula .

[0022] In the formula, Tp represents the data storage amount evaluation index, Af represents the uncompressed data evaluation index, Rc represents the data amount change index, and α, β, and γ are weight coefficients, and α+β+γ=1.

[0023] Further, according to the data storage state index, the data storage state is determined whether to meet the storage requirement, and the determination method is specifically as follows:

[0024] Comparing the data storage state index with a data storage state index threshold; the data storage state index threshold refers to the maximum value of the data storage state index in a normal state;

[0025] If the data storage state index is greater than the data storage state index threshold, it indicates that the larger the data storage state index is, the more abnormal the data storage state is, and it is determined that the data storage state does not meet the storage requirement.

[0026] Further technical solutions, if the storage state of the data does not meet the storage requirements, obtain data quality data, generate a data quality evaluation index, specifically including the following steps:

[0027] 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 repeated content or entries in the data set;

[0028] Among them, the generation method of the data duplication rate evaluation index is specifically:

[0029] Obtain the data duplication rate, and perform difference processing 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;

[0030] Perform ratio processing on the data duplication rate difference and the data duplication rate threshold to generate the data duplication rate evaluation index;

[0031] Obtain the data processing step number, and generate a data processing step evaluation index;

[0032] Among them, the generation method of the data processing step evaluation index is specifically:

[0033] Obtain the data processing step number, and perform difference processing on the data processing step number and the data processing step number threshold to generate a data processing step number difference;

[0034] Perform ratio processing on the data processing step number difference and the data processing step number threshold to generate the data processing step evaluation index;

[0035] Obtain the data error rate, and generate a data error rate evaluation index; wherein the data error rate refers to the ratio of the number of error data to the total number of data;

[0036] Among them, the generation method of the data error rate evaluation index is specifically:

[0037] Obtain the data error rate, and perform difference processing 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;

[0038] Perform ratio processing on the data error rate difference and the data error rate threshold to generate the data error rate evaluation index;

[0039] Generate the data quality evaluation index Mp through the formula

[0040] ​In the formula, Da represents a data repetition rate evaluation index, Dp represents a data processing step evaluation index, De represents a data error rate evaluation index, a1, a2, and a3 are proportional coefficients.

[0041] Further technical solutions, the current data processing period is obtained, and a data processing period adjustment value is generated, and the specific steps include the following steps:

[0042] The current data processing period is obtained.

[0043] A data processing period evaluation model is established.

[0044] A temperature factor of the storage medium is obtained, and the temperature factor of the storage medium, the data quality index, the current data processing period, and the data storage state index are substituted into the data processing period evaluation model to generate a data processing period adjustment value Sv.

[0045] The expression of the data processing period evaluation model is as follows:

[0046]

[0047] In the expression, Pv represents the current data processing period, Ds represents the data storage state index, Mp represents the data quality index, and Tf represents the temperature factor of the storage medium.

[0048] Further technical solutions, the temperature factor of the storage medium is obtained in the following manner:

[0049] The temperature value of the current storage medium is obtained, and the temperature value of the storage medium is compared with a standard temperature value of the storage medium.

[0050] If the temperature value of the storage medium is greater than the standard temperature value of the storage medium, the temperature is marked as a high-temperature temperature value.

[0051] The high-temperature temperature value is processed by difference with the standard temperature value of the storage medium to generate a temperature difference value.

[0052] The temperature difference value is processed by ratio with the standard temperature value of the storage medium to generate the temperature factor of the storage medium.

[0053] An optimization system for data storage, the system comprising:

[0054] A data storage state analysis unit is configured to obtain a state of data storage and generate a data storage state index, wherein the state of data storage includes a data amount change value, a total data storage amount, and an uncompressed data access frequency; the data amount change value refers to a difference between before and after a change in the data storage amount; and the total data storage amount refers to a total amount of data storage in the storage medium. ​

[0055] a data storage state judging unit configured to judge whether the storage state of the data meets the storage requirement according to the data storage state index;

[0056] a data quality evaluation unit configured to obtain data quality data and generate a data quality evaluation index if the storage state of the data does not meet the storage requirement, wherein the data quality data comprises a data repetition rate, a number of data processing steps and a data error rate;

[0057] a data processing cycle analysis unit configured to obtain a current data processing cycle and generate a data processing cycle adjustment value.

[0058] In a further aspect, the data storage state analysis unit specifically comprises:

[0059] a data volume change index generation module configured to obtain a data volume change value and a total data storage amount, perform ratio processing on the data volume change value and the total data storage amount, and generate a data volume change index, wherein the total data storage amount refers to a total data storage amount before the data volume change;

[0060] a data storage amount evaluation index generation module configured to obtain the total data storage amount and a maximum storage amount of the storage medium, and generate a data storage amount evaluation index;

[0061] an uncompressed data evaluation index generation module configured to obtain an uncompressed data access frequency, and generate an uncompressed data evaluation index;

[0062] a data storage state index generation module configured to perform weighted processing on the data volume change index, the data storage amount evaluation index and the uncompressed data evaluation index, and generate a data storage state index.

[0063] In a further aspect, the data quality evaluation unit specifically comprises:

[0064] a data repetition rate evaluation index generation module configured to obtain a data repetition rate and generate a data repetition rate evaluation index if the storage state of the data does not meet the storage requirement, wherein the data repetition rate refers to a proportion of contents or entries that repeatedly appear in the data set;

[0065] a data processing step evaluation index generation module configured to obtain a number of data processing steps and generate a data processing step evaluation index;

[0066] a data error rate evaluation index generation module configured to obtain a data error rate and generate a data error rate evaluation index;

[0067] The data quality evaluation index generation module is configured to generate a data quality evaluation index by weighting the data duplication rate evaluation index, the data processing step evaluation index and the data error rate evaluation index.

[0068] Further, the data processing period analysis unit specifically comprises:

[0069] The data acquisition module is configured to acquire a current data processing period.

[0070] The model establishment module is configured to establish a data processing period evaluation model.

[0071] The data processing period adjustment value generation module is configured to acquire a temperature factor of the storage medium, and generate a data processing period adjustment value by substituting the temperature factor of the storage medium, the data quality index, the current data processing period and the data storage state index into the data processing period evaluation model.

[0072] The present application provides a data storage optimization method and system, which has the following advantages compared with the prior art:

[0073] The present application adjusts the data processing period according to the data storage state and the data quality, optimizes the data storage strategy by flexibly adjusting the data processing period, and significantly improves the storage efficiency, thereby optimizing the utilization rate of the storage space. BRIEF DESCRIPTION OF DRAWINGS

[0074] Figure 1 A flowchart of the data storage optimization method provided by the present application is provided.

[0075] Figure 2 A flowchart of step S10 provided by the present application is provided.

[0076] Figure 3 A flowchart of step S20 provided by the present application is provided.

[0077] Figure 4 A flowchart of step S30 provided by the present application is provided.

[0078] Figure 5 A flowchart of step S40 provided by the present application is provided.

[0079] Figure 6 A module block diagram of the data storage optimization system provided by the present application is provided.

[0080] Figure 7 A module block diagram of the data storage state analysis unit 10 provided by the present application is provided.

[0081] Figure 8 A module block diagram of the data quality evaluation unit 30 provided by the present application is provided.

[0082] Figure 9 A module block diagram of the data processing cycle analysis unit 40 provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0083] In order to make the objects, technical solutions and advantages of the present application clearer, the present application 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 application and should not be used to limit the present application.

[0084] The specific implementation of the present application will be described in detail below with reference to specific embodiments.

[0085] Please refer to Figure 1 An optimization method of data storage provided by an embodiment of the present application comprises the following steps:

[0086] Step S10: obtaining the state of data storage and generating a data storage state index; wherein the state of data storage comprises a data amount change value, a total data storage amount and an uncompressed data access frequency; the data amount change value refers to the difference between before and after the change of data storage amount; the total data storage amount refers to the total amount of data storage in the storage medium;

[0087] Step S20: judging whether the storage state of data meets the storage requirement according to the data storage state index;

[0088] Step S30: if the storage state of data does not meet the storage requirement, obtaining 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;

[0089] Step S40: obtaining the current data processing cycle and generating a data processing cycle adjustment value.

[0090] Please refer to Figure 2 As a preferred embodiment of the present application, the step S10 specifically comprises the following steps:

[0091] Step S11: obtaining the data amount change value and the total data storage amount, performing ratio processing on the data amount change value and the total data storage history amount to generate a data amount change index; wherein the total data storage history amount refers to the total data storage amount before the change of data amount;

[0092] Step S12: obtaining the total data storage amount and the maximum storage amount of the storage medium and generating a data storage amount evaluation index;

[0093] The generation mode of the data storage amount evaluation index is specifically as follows:

[0094] Performing a difference processing on the total amount of data storage and the maximum storage capacity of the storage medium to generate a storage capacity difference;

[0095] The storage capacity difference is compared with the maximum storage capacity of the storage medium to generate a data storage capacity evaluation index;

[0096] Step S13: Obtaining the uncompressed data access frequency and generating an uncompressed data evaluation index;

[0097] The uncompressed data evaluation index is generated in the following manner:

[0098] The uncompressed data access frequency is subtracted from the uncompressed data access frequency threshold to generate the uncompressed data access frequency difference; the uncompressed data access frequency threshold refers to the maximum access frequency when the data needs to be compressed;

[0099] The uncompressed data access frequency difference is compared with the uncompressed data access frequency threshold to generate an uncompressed data evaluation index;

[0100] Step S14: performing weighted processing 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;

[0101] For example, by formula , generate data storage status index Ds;

[0102] In the formula, Tp represents the data storage capacity evaluation index, Af represents the uncompressed data evaluation index, Rc represents the data capacity change index, α, β, and γ are all weight coefficients, and α+β+γ=1.

[0103] See also Figure 3 As a preferred embodiment of the present invention, the determination method of step S20 is specifically as follows:

[0104] Comparing the data storage status index with a 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;

[0105] If the data storage status index is less than or equal to the data storage status index threshold, it means that the smaller the data storage status index is, the more normal the data storage status is, and it is determined that the data storage status meets the storage requirements;

[0106] 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 is, the more abnormal the data storage status is, and it is determined that the data storage status does not meet the storage requirements.

[0107] See also Figure 4As a preferred embodiment of the present application, the step S30 specifically comprises the following steps:

[0108] Step S31: If the storage state of the data does not meet the storage requirement, obtain the data repetition rate, and generate a data repetition rate evaluation index; the data repetition rate refers to the proportion of the repeated contents or entries in the data set.

[0109] The data repetition rate evaluation index is generated in the following manner:

[0110] Obtain the data repetition rate, and perform difference processing on the data repetition rate and a data repetition rate threshold value to generate a data repetition rate difference; the data repetition rate threshold value refers to the maximum repetition rate that the storage medium can withstand without affecting the computing performance.

[0111] It should be explained that the value of the data repetition rate threshold value is set by the relevant personnel in the field;

[0112] Perform ratio processing on the data repetition rate difference and the data repetition rate threshold value to generate the data repetition rate evaluation index.

[0113] It should be explained that the data repetition rate can be processed by a hash algorithm (such as MD5, SHA256, etc.) to convert the data into a fixed-length hash value; for the same data, the hash values will be the same, and if the hash values are the same, the data is considered to be repeated; this algorithm is prior art, and will not be described here.

[0114] Step S32: Obtain the number of data processing steps, and generate a data processing step evaluation index.

[0115] The data processing step evaluation index is generated in the following manner:

[0116] Obtain the number of data processing steps, and perform difference processing on the number of data processing steps and a data processing step number threshold value to generate a data processing step number difference.

[0117] Perform ratio processing on the data processing step number difference and the data processing step number threshold value to generate the data processing step evaluation index.

[0118] Step S33: Obtain the data error rate, and generate a data error rate evaluation index; wherein the data error rate refers to the ratio of the number of error data to the total number of data.

[0119] The data error rate evaluation index is generated in the following manner:

[0120] Obtaining a data error rate, and performing difference processing on the data error rate and a 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;

[0121] It should be explained that the value of the data error rate threshold is set by the relevant personnel in the field;

[0122] Performing ratio processing on the data error rate difference and the data error rate threshold to generate a data error rate evaluation index;

[0123] It should be explained that the data error number can be obtained through parity check, CRC (Cyclic Redundancy Check) and the like.

[0124] Step S34: performing weighted processing on the data repetition rate evaluation index, the data processing step evaluation index and the data error rate evaluation index to generate a data quality evaluation index;

[0125] For example, the data quality evaluation index Mp is generated through the formula

[0126] In the formula, Da represents the data repetition 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 proportional coefficients.

[0127] Please refer to Figure 5 As a preferred embodiment of the present application, the step S40 specifically comprises the following steps:

[0128] Step S41: obtaining a current data processing period;

[0129] Step S42: establishing a data processing period evaluation model;

[0130] Step S43: obtaining a temperature factor of the storage medium, and substituting the temperature factor of the storage medium, a data quality index, the current data processing period and a data storage state index into the data processing period evaluation model to generate a data processing period adjustment value Sv;

[0131] The expression of the data processing period evaluation model is as follows:

[0132] ;

[0133] In the expression, Pv represents the current data processing period, Ds represents the data storage state index, Mp represents the data quality index, and Tf represents the temperature factor of the storage medium;

[0134] The temperature factor of the storage medium is obtained in the following manner:​

[0135] obtaining a temperature value of the current storage medium, comparing the temperature value of the storage medium with a standard temperature value of the storage medium;

[0136] if the temperature value of the storage medium is less than or equal to the standard temperature value of the storage medium, marking the temperature as a normal temperature value;

[0137] if the temperature value of the storage medium is greater than the standard temperature value of the storage medium, marking the temperature as a high temperature value;

[0138] differencing the high temperature value and the standard temperature value of the storage medium to generate a temperature difference value;

[0139] ratio processing the temperature difference value and the standard temperature value of the storage medium to generate a temperature factor of the storage medium;

[0140] For example, the temperature factor Tf of the storage medium is generated by the formula

[0141] In the formula, T i represents the high temperature value, and T0 represents the standard temperature value of the storage medium.

[0142] As a preferred embodiment of the present application, when the data processing period adjustment value Sv is received, the data processing period of the storage medium is adjusted according to the data processing period adjustment value Sv.

[0143] Referring to Figure 6 , the present application also provides an optimization system for data storage, which comprises:

[0144] a data storage state analysis unit 10 for obtaining a state of data storage and generating a data storage state index; wherein the state of data storage comprises a data amount change value, a total data storage amount, and an uncompressed data access frequency; the data amount change value refers to a difference between before and after a change in the data storage amount; and the total data storage amount refers to a total amount of data storage in the storage medium;

[0145] a data storage state judgment unit 20 for judging whether the storage state of data meets storage requirements according to the data storage state index;

[0146] a data quality evaluation unit 30 for obtaining data quality data and generating a data quality evaluation index if the storage state of data does not meet the storage requirements; wherein the data quality data comprises a data repetition rate, a data processing step number, and a data error rate;

[0147] a data processing period analysis unit 40 for obtaining a current data processing period and generating a data processing period adjustment value. ​

[0148] Referring to Figure 7 , as a preferred embodiment of the present application, the data storage state analysis unit 10 specifically comprises:

[0149] a data volume change index generation module 11 for obtaining a data volume change value and a data storage total volume, performing ratio processing on the data volume change value and the data storage history total volume, and generating a data volume change index; wherein the data storage history total volume refers to the data storage total volume before the data volume change;

[0150] a data storage volume evaluation index generation module 12 for obtaining the data storage total volume and the maximum storage volume of the storage medium, and generating a data storage volume evaluation index;

[0151] an uncompressed data evaluation index generation module 13 for obtaining an uncompressed data access frequency, and generating an uncompressed data evaluation index;

[0152] a data storage state index generation module 14 for performing weighted processing on the data volume change index, the data storage volume evaluation index, and the uncompressed data evaluation index, and generating a data storage state index.

[0153] Referring to Figure 8 , as a preferred embodiment of the present application, the data quality evaluation unit 30 specifically comprises:

[0154] a data repetition rate evaluation index generation module 31 for obtaining a data repetition rate and generating a data repetition rate evaluation index, if the data storage state does not meet the storage requirement; the data repetition rate refers to the proportion of the contents or entries that repeatedly appear in the data set;

[0155] a data processing step evaluation index generation module 32 for obtaining a data processing step number and generating a data processing step evaluation index;

[0156] a data error rate evaluation index generation module 33 for obtaining a data error rate and generating a data error rate evaluation index;

[0157] a data quality evaluation index generation module 34 for performing weighted processing on the data repetition rate evaluation index, the data processing step evaluation index, and the data error rate evaluation index, and generating a data quality evaluation index.

[0158] Referring to Figure 9 , as a preferred embodiment of the present application, the data processing cycle analysis unit 40 specifically comprises:

[0159] a data acquisition module 41 for obtaining a current data processing cycle;

[0160] The model establishing module 42 is configured to establish a data processing period evaluation model;

[0161] The data processing period adjustment value generating module 43 is configured to obtain a temperature factor of the storage medium, and substitute the temperature factor of the storage medium, the data quality index, the current data processing period and the data storage state index into the data processing period evaluation model to generate a data processing period adjustment value.

[0162] Although the embodiments of the present application have been shown and described, it is to be understood that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A data storage optimization method, characterized in that: The following steps are involved: Obtaining the state of data storage and generating a data storage state index; wherein the state of data storage includes a data volume change value, a total amount of data stored, and an 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 amount of data stored refers to the total amount of data stored in the storage medium; According to the data storage status index, determine whether the storage status of the data meets the storage requirements; 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 data duplication rate, number of data processing steps and data error rate; Obtain the current data processing cycle and generate a data processing cycle adjustment value; Wherein, if the storage state of the data does not meet the storage requirements, obtaining data quality data and generating a data quality assessment index specifically include the following steps: If the storage status of the data does not meet the storage requirements, obtain the data repetition rate and generate a data repetition rate evaluation index; the data repetition rate refers to the proportion of repeated content or items in the data set; The data repetition rate evaluation index is generated in the following manner: Obtaining a data repetition rate, performing subtraction processing on the data repetition rate and a data repetition rate threshold to generate a data repetition rate difference; the data repetition rate threshold refers to the maximum repetition rate that the storage medium can withstand without affecting computing performance; The data repetition rate difference is compared with the data repetition rate threshold to generate a data repetition rate evaluation index; Obtain the number of data processing steps and generate a data processing step evaluation index; The data processing step evaluation index is generated in the following manner: Obtaining the number of data processing steps, performing difference processing on the number of data processing steps and a threshold value of the number of data processing steps to generate a difference in the number of data processing steps; The data processing step number difference is compared with the data processing step number threshold to generate a data processing step evaluation index; Obtaining the data error rate and generating a data error rate evaluation index; wherein the data error rate refers to the ratio of the number of erroneous data to the total number of data; The data error rate evaluation index is generated in the following manner: Obtaining a data error rate, performing a subtraction process between the data error rate and a 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 computing performance; The data error rate difference is compared with the data error rate threshold to generate a data error rate evaluation index; By formula , generate the data quality assessment index Mp; In the formula, Da represents the data repetition 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 proportional coefficients.

2. The data storage optimization method according to claim 1, characterized in that: The obtaining of the data storage status and generating of the data storage status index specifically includes the following steps: Obtain the data volume change value and the total amount of data stored, perform a ratio processing on the data volume change value and the historical total amount of data stored, and generate a data volume change index; wherein the historical total amount of data stored refers to the total amount of data stored before the data volume change; Obtaining the total amount of data storage and the maximum storage capacity of the storage medium, and generating a data storage capacity evaluation index; The data storage capacity evaluation index is generated in the following manner: Performing a difference processing on the total amount of data storage and the maximum storage capacity of the storage medium to generate a storage capacity difference; The storage capacity difference is compared with the maximum storage capacity of the storage medium to generate a data storage capacity evaluation index; Obtaining the access frequency of uncompressed data and generating an uncompressed data evaluation index; The uncompressed data evaluation index is generated in the following manner: The uncompressed data access frequency is subtracted from the uncompressed data access frequency threshold to generate the uncompressed data access frequency difference; the uncompressed data access frequency threshold refers to the maximum access frequency when the data needs to be compressed; The uncompressed data access frequency difference is compared with the uncompressed data access frequency threshold to generate an uncompressed data evaluation index; By formula , generate data storage status index Ds; In the formula, Tp represents the data storage capacity evaluation index, Af represents the uncompressed data evaluation index, Rc represents the data capacity change index, α, β, and γ are all weight coefficients, and α+β+γ=1.

3. The data storage optimization method according to claim 2, characterized in that: The method of judging whether the storage status of the data meets the storage requirements is as follows: comparing the data storage status index with a 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 is, the more abnormal the data storage status is, and it is determined that the data storage status does not meet the storage requirements.

4. The data storage optimization method according to claim 1, characterized in that: The method of obtaining the current data processing cycle and generating the data processing cycle adjustment value specifically includes the following steps: Get the current data processing cycle; Establish a data processing cycle evaluation model; Obtaining a 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 a data processing cycle evaluation model to generate a data processing cycle adjustment value Sv; 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.

5. The data storage optimization method according to claim 4, characterized in that: The temperature factor of the storage medium is obtained in the following manner: Obtaining the current temperature value of the storage medium and comparing 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, the temperature value is marked as a high temperature value; Performing difference processing on the high temperature value and the standard temperature value of the storage medium to generate a temperature difference value; The temperature difference is compared with the standard temperature value of the storage medium to generate the temperature factor of the storage medium.

6. A data storage optimization system, characterized in that: The system is used to execute the method according to any one of claims 1 to 5, and the system comprises: a data storage status analysis unit, configured to obtain the data storage status and generate a data storage status index; wherein the data storage status includes a data volume change value, a total amount of data stored, and an 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 amount of data stored refers to the total amount of data stored in the storage medium; a data storage status judgment unit, configured to judge whether the storage status of the data meets the storage requirements based on the data storage status index; a data quality assessment unit, wherein if the storage state of the data does not meet the storage requirements, the data quality assessment unit is used to obtain data quality data and generate a data quality assessment index; wherein the data quality data includes data repetition rate, number of data processing steps and data error rate; The data processing cycle analysis unit is used to obtain the current data processing cycle and generate a data processing cycle adjustment value.

7. The data storage optimization system according to claim 6, characterized in that: The data storage status analysis unit specifically includes: The data volume change index generation module is used to obtain the data volume change value and the total amount of data storage, and compare the data volume change value with the historical total amount of data storage to generate the data volume change index; wherein the historical total amount of data storage refers to the total amount of data storage before the data volume change; A data storage capacity evaluation index generation module is used to obtain the total amount of data storage and the maximum storage capacity of the storage medium and generate a data storage capacity evaluation index; An uncompressed data evaluation index generation module is used to obtain the uncompressed data access frequency and generate an uncompressed data evaluation index; The data storage status index generation module is used to perform weighted processing on the data volume change index, the data storage volume evaluation index and the uncompressed data evaluation index to generate the data storage status index.

8. The data storage optimization system according to claim 6, characterized in that: The data quality assessment unit specifically includes: A data repetition rate evaluation index generation module is used to obtain the data repetition rate and generate a data repetition rate evaluation index if the storage status of the data does not meet the storage requirements; the data repetition rate refers to the proportion of content or items that appear repeatedly in the data set; A 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; A 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 assessment index generation module is used to perform weighted processing on the data repetition rate assessment index, the data processing step assessment index and the data error rate assessment index to generate a data quality assessment index.

9. The data storage optimization system according to claim 6, characterized in that: The data processing cycle analysis unit specifically includes: Data acquisition module, used to obtain the current data processing cycle; Model building module, used to build 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 to generate the data processing cycle adjustment value.

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