A migration method based on data platform

Abstract

The present invention relates to the technical field of data migration, and in particular to a migration method based on a data platform, comprising: step S1, determining a data platform to be migrated and a target migration data platform, determining the type of data stored in the data platform to be migrated and data migration demand information; step S2, determining migration difference characteristics according to the data migration demand, and calculating the data migration difference parameters of this migration according to the migration difference characteristics; step S3, determining the data migration type according to the data migration difference parameters; step S4, migrating the damageable data after lossy compression and migrating the non-destructive data after lossless compression, and determining the analysis process of this migration according to the data migration type; the present invention provides data security protection for data migration by considering the compatibility issues between different data platform versions and setting different analysis methods in a targeted manner.

Description

Technical Field

[0001] The present invention relates to the technical field of data migration, and in particular to a migration method based on a data platform. Background Art

[0002] Data migration is a critical operation in the field of information technology. It involves transferring data from one system, platform, or location to another to support system upgrades, expand business needs, improve data security and performance, or comply with regulatory requirements. This process not only ensures the integrity and availability of data, but also helps maintain business continuity and avoid service interruptions during technology iterations. Data migration can also promote data integration, break down information silos, and improve data consistency and accuracy, thereby providing a solid foundation for data analysis and decision-making. In addition, with the popularity of cloud computing, data migration has also become an important step in achieving digital transformation and utilizing cloud services.

[0003] Chinese Patent Publication No.: CN117931767A, discloses a database migration platform and a database migration method, the platform includes: a flop library module, a management end and an engine end; the flop library module stores a table, the table includes a flop parameter field; the management end includes a configuration module and a query module; the configuration module divides the source table data into multiple blocks for serial transmission when configuring the migration task; a piece of data is stored in the flop library module, and the flop parameter field stores the current flop parameter; an incremental extraction statement is configured in the migration task; the query module queries the current flop parameter before each migration task is executed and submits it to the engine end; the configuration module also modifies the flop parameter of this migration task when the migration task is successfully executed; the query module submits the modified flop parameter to the engine end to execute the next migration task; the engine end executes the migration task according to the incremental extraction statement and the current flop parameter; it can be seen that the database migration platform and the database migration method have the following problems: the migration is directly performed without analyzing the difference between the two migration data platforms, which leads to abnormalities after data migration. Summary of the invention

[0004] To this end, the present invention provides a migration method based on a data platform to overcome the problem in the prior art that migration is performed directly without analyzing the differences between two migration data platforms, resulting in abnormalities that are prone to occur after data migration.

[0005] To achieve the above object, the present invention provides a migration method based on a data platform, comprising:

[0006] Step S1, determining a data platform to be migrated and a target migration data platform, determining the data type stored in the data platform to be migrated and data migration requirement information, wherein the data type includes destructible data and non-destructible data;

[0007] Step S2, determining migration difference characteristics according to the data migration requirements, and calculating data migration difference parameters of this migration according to the migration difference characteristics;

[0008] Step S3, determining the data migration type according to the data migration difference parameter;

[0009] Step S4, performing lossy compression on the lossy data and then migrating it, performing lossless compression on the non-lossy data and then migrating it, and analyzing this migration according to the data migration type, including:

[0010] After the data content of each data type is migrated, a sample search is performed on the data in the target migration data platform, and the search response time is recorded to determine the compatible characterization parameter, and whether there is an abnormality in the migration result according to the compatible characterization parameter;

[0011] Alternatively, the hash value of each segment of data in the data platform to be migrated is compared with the hash value of the corresponding data segment in the target migration data platform to determine the accurate parameters of data migration, and whether there is an abnormality in the migration result is determined based on the accurate parameters of data migration, and the data segment that needs to be re-migrated is determined based on the abnormal hash value.

[0012] Furthermore, in the step S2, the process of determining migration difference characteristics according to the data migration requirements includes:

[0013] Determine the amount of data to be migrated to the target migration data platform in the data migration requirements;

[0014] Performing simulated migration for the migration data volume to obtain the migration data volume of the target migration data platform under the simulated migration;

[0015] Calculate the difference between the migration amount of the data platform to be migrated and the migration amount of the target migration data platform;

[0016] Determine the difference in the number of indexes between the migration data indexes of the data platform to be migrated and the migration data indexes of the target migration data platform;

[0017] The migration amount difference and the index quantity difference are determined as a migration difference feature.

[0018] Furthermore, in step S2, the data migration difference parameter is determined according to formula (1):

[0019]

[0020] In formula (1), G is the data migration difference parameter, C1 is the migration difference, C0 is the standard migration difference, M1 is the index quantity difference, and M0 is the standard index quantity difference.

[0021] Furthermore, in the step S3, determining the data migration type of this migration according to the data migration difference parameter includes:

[0022] If the data migration difference parameter is greater than or equal to the standard migration difference parameter, the data migration type is a direct migration type;

[0023] If the data migration difference parameter is less than the standard migration difference parameter, the data migration type is an indirect migration type.

[0024] Furthermore, in the step S4, the migration is analyzed according to the data migration type, including:

[0025] If the data migration type is an indirect migration type, after the data content of each data type is migrated, a sample search is performed on the data in the target migration data platform, and the search response time is recorded to determine the compatible characterization parameter, and whether there is an abnormality in the migration result is determined according to the compatible characterization parameter;

[0026] If the data migration type is a direct migration type, the hash value of each segment of data on the data platform to be migrated is compared with the hash value of the corresponding data segment in the target migration data platform to determine the accurate parameters of the data migration, and whether there is any abnormality in the migration result is determined based on the accurate parameters of the data migration, and the data segment that needs to be re-migrated is determined based on the abnormal hash value.

[0027] Furthermore, the process of determining the compatible characterization parameter includes:

[0028] Randomly searching for a number of data segments in the to-be-migrated data platform, and adding marks to the searched data segments;

[0029] Recording the first search response time used for searching each marked data segment;

[0030] Retrieving each marked data segment in the target migration data platform to obtain a second retrieval response time corresponding to each marked data segment;

[0031] The compatible characterization parameter is determined according to the first search response time and the second search response time.

[0032] Furthermore, the compatibility characterization parameter is determined according to formula (2):

[0033]

[0034] In formula (2), K is a compatible characterization parameter, m is the total number of retrieved data segments, Tj is the first retrieval response time of the j-th data segment in the data platform to be migrated, tj is the second retrieval response time of the j-th data segment in the target migration data platform, and j is an integer greater than 0.

[0035] Further, determining whether there is an abnormality in the migration result according to the compatible characterization parameter includes:

[0036] If the compatible characterization parameter is greater than or equal to the standard compatible characterization parameter, it is determined that there is an abnormality in the migration result;

[0037] If the compatible characterization parameter is smaller than the standard compatible characterization parameter, it is determined that there is no abnormality in the migration result.

[0038] Further, determining the accurate parameters of the data migration and determining the data segments that need to be re-migrated includes:

[0039] Determine the abnormal hash value and the corresponding data segment according to the comparison result of the hash value of each segment of the data platform to be migrated and the hash value of the corresponding data segment in the target migration data platform;

[0040] Determine the data segment corresponding to the abnormal hash value as the data segment that needs to be re-migrated;

[0041] Determine the exact parameters for data migration based on the number of abnormal hash values

[0042] Further, determining whether there is an abnormality in the migration result according to the accurate parameters of the data migration includes:

[0043] If the data migration accuracy parameter is greater than or equal to the standard accuracy parameter, it is determined that the migration result is abnormal;

[0044] If the data migration accuracy parameter is less than the standard accuracy parameter, it is determined that there is no abnormality in the migration result.

[0045] Compared with the prior art, the beneficial effect of the present invention lies in that it fully obtains the version information of the platforms of both migration parties and the migration demand information, lays the foundation for subsequent compatibility analysis and migration strategy formulation, determines the migration type by calculating the data migration difference parameters, so that the determined migration process can solve the differences between different versions in a targeted manner, and adaptively selects the analysis method according to the different migration types to adapt to different migration scenarios and ensure the accuracy of data migration, and can timely discover anomalies in the migration process by retrieving response time or hash value comparison; the present invention provides data security protection for data migration by considering the compatibility issues between different data platform versions and setting different analysis methods in a targeted manner.

[0046] Furthermore, in the present invention, since the data migration difference parameter is determined based on the version information and the migration difference characteristics, the larger the data migration difference parameter is, the greater the difference between the two data platforms is, resulting in a large difference in the storage method and index of the same data segment before and after migration. The more data is processed during the data migration process, the direct comparison method cannot be used to determine whether there is an abnormality in the migration, and other methods need to be used for judgment, thereby improving the analysis accuracy of the present invention.

[0047] Furthermore, in the invention, for indirect migration type of data migration, since there is a large difference between the data platform to be migrated and the target migration data platform, after the same data enters the target migration data platform after various processes in the data migration process, there is a change in the retrieval index, which leads to a large difference in the second retrieval response time of the data retrieval process. For direct migration type of data migration, since the migration process hardly performs any processing other than compression and decompression on the data, most of the data is exactly the same before and after migration. Therefore, the hash value can be used to more simply and intuitively determine whether the migration is abnormal. The present invention can adaptively select a more reasonable analysis method according to different migration types, thereby improving the quality of the data after the final migration.

[0048] Furthermore, the larger the compatibility characterization parameter is, the longer the second search response time used to retrieve the data in the target migration data platform after the migration is completed, indicating poor compatibility, which further indicates that the adaptive processing of data to solve version compatibility issues during the data migration process cannot achieve the effect of solving the compatibility problem, and further processing is required.

[0049] Furthermore, since hash values ​​have an avalanche effect, even tiny data changes will cause significant changes in hash values. Therefore, for the data migration process between two data platforms with basically consistent data before and after migration, using hash values ​​to determine whether there are any anomalies in the data segments during the migration process is both simple and intuitive. That is, when the hash values ​​are different, it can be determined that the data segment corresponding to the current hash value is abnormal. Therefore, using hash values ​​to analyze the migration process can not only determine whether the data accuracy is qualified, but also directly determine the data segments with migration abnormalities, avoiding wasting time on repeated retrieval and positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of a migration method based on a data platform according to an embodiment of the present invention;

[0051] Figure 2 A logical diagram for determining data migration types for an embodiment of the present invention;

[0052] Figure 3 A logic diagram for determining whether an abnormality exists according to compatible characterization parameters in an embodiment of the present invention;

[0053] Figure 4 A logic diagram for determining whether an abnormality exists based on accurate parameters of data migration according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with 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.

[0055] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0056] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0057] See also Figure 1 As shown, it is a flow chart of a migration method based on a data platform according to an embodiment of the present invention; the present invention provides a migration method based on a data platform, including:

[0058] Step S1, determining a data platform to be migrated and a target migration data platform, determining the data type stored in the data platform to be migrated and data migration requirement information, wherein the data type includes destructible data and non-destructible data;

[0059] Step S2, determining migration difference characteristics according to the data migration requirements, and calculating data migration difference parameters of this migration according to the migration difference characteristics;

[0060] Step S3, determining the data migration type according to the data migration difference parameter;

[0061] Step S4, performing lossy compression on the lossy data and then migrating it, performing lossless compression on the non-lossy data and then migrating it, and analyzing this migration according to the data migration type, including:

[0062] After the data content of each data type is migrated, a sample search is performed on the data in the target migration data platform, and the search response time is recorded to determine the compatible characterization parameter, and whether there is an abnormality in the migration result according to the compatible characterization parameter;

[0063] Alternatively, the hash value of each segment of data in the data platform to be migrated is compared with the hash value of the corresponding data segment in the target migration data platform to determine the accurate parameters of data migration, and whether there is an abnormality in the migration result is determined based on the accurate parameters of data migration, and the data segment that needs to be re-migrated is determined based on the abnormal hash value.

[0064] In implementation, the version information includes the major version number and minor version number of the data platform and all indexes used by the current version of the data platform;

[0065] Lossable data refers to audio data, video data, and image data, and all other data types excluding lossable data are non-lossable data;

[0066] The migration requirement information includes the data to be migrated and its data volume in the data platform to be migrated, the data type of each data segment in the data to be migrated, the migration data volume after the migration is completed in the target migration data platform, the indexes included in the data to be migrated, and the indexes included in the data after the migration is completed;

[0067] Among them, the amount of migrated data after the migration is completed in the target migration data platform and the indexes contained in the data after the migration are completed can be obtained through migration simulation, which is a prior art and will not be described in detail.

[0068] It can be understood that lossy compression reduces the file size by removing the part of the data that has less impact on human perception, and the compression degree of lossy compression is determined according to the reserved memory of the target migration data platform.

[0069] Fully obtain the version information of the platforms of both migration parties and the migration requirement information, lay the foundation for subsequent compatibility analysis and migration strategy formulation, determine the migration type by calculating the data migration difference parameters, so that the determined migration process can solve the differences between different versions in a targeted manner, and adaptively select the analysis method according to the different migration types to adapt to different migration scenarios and ensure the accuracy of data migration. By retrieving response time or hash value comparison, anomalies in the migration process can be discovered in time. The present invention provides data security protection for data migration by considering the compatibility issues between different data platform versions and setting different analysis methods in a targeted manner.

[0070] Specifically, in step S2, the process of determining migration difference characteristics according to the data migration requirements includes:

[0071] Determine the amount of data to be migrated to the target migration data platform in the data migration requirements;

[0072] Performing simulated migration for the migration data volume to obtain the migration data volume of the target migration data platform under the simulated migration;

[0073] Calculate the difference between the migration amount of the data platform to be migrated and the migration amount of the target migration data platform;

[0074] Determine the difference in the number of indexes between the migration data indexes of the data platform to be migrated and the migration data indexes of the target migration data platform;

[0075] The migration amount difference and the index quantity difference are determined as a migration difference feature.

[0076] It is understandable that for different data platforms, the same data is stored in different encoding methods such as ASCII, UTF-8, UTF-16, etc., which determines the storage method of characters in memory. The different storage methods lead to differences in the total amount of data before and after the migration of the same data. For example, UTF-8 uses one to four bytes to represent a character, while UTF-16 uses two bytes or four bytes. In addition, the type and number of indexes corresponding to the same data in different data platforms may be different, which affects the data platform's additional memory for data retrieval.

[0077] In implementation, simulated migration is to migrate simulated data with the same migration data volume to the target migration data platform, so as to obtain the migration data volume of the target migration data platform after migration. The index of the simulated data can be the same as that of the data to be migrated.

[0078] See also Figure 2 As shown, it is a logic diagram for determining the data migration type according to an embodiment of the present invention. In step S2, the data migration difference parameter is determined according to formula (1):

[0079]

[0080] In formula (1), G is the data migration difference parameter, C1 is the migration difference, C0 is the standard migration difference, M1 is the index quantity difference, and M0 is the standard index quantity difference.

[0081] In implementation, the standard migration amount difference is 0.2 to 0.3 times the amount of data to be migrated, and the standard index quantity difference is 0.3 to 0.4 times the amount of indexes contained in the data to be migrated.

[0082] Specifically, in step S4, determining the data migration type of this migration according to the data migration difference parameter includes:

[0083] If the data migration difference parameter is greater than or equal to the standard migration difference parameter, the data migration type is a direct migration type;

[0084] If the data migration difference parameter is less than the standard migration difference parameter, the data migration type is an indirect migration type.

[0085] In practice, the standard migration difference parameter is selected in the interval [1.15,1.35].

[0086] In the present invention, since the data migration difference parameter is determined based on the version information and the migration difference characteristics, the larger the data migration difference parameter is, the greater the difference between the two data platforms is, resulting in a large difference in the storage method and index of the same data segment before and after migration. The more data is processed during the data migration process, the direct comparison method cannot be used to determine whether there is an abnormality in the migration, and other methods need to be used for judgment, thereby improving the analysis accuracy of the present invention.

[0087] Specifically, in step S4, the migration is analyzed according to the data migration type, including:

[0088] If the data migration type is an indirect migration type, after the data content of each data type is migrated, a sample search is performed on the data in the target migration data platform, and the search response time is recorded to determine the compatible characterization parameter, and whether there is an abnormality in the migration result is determined according to the compatible characterization parameter;

[0089] If the data migration type is a direct migration type, the hash value of each segment of data on the data platform to be migrated is compared with the hash value of the corresponding data segment in the target migration data platform to determine the accurate parameters of the data migration, and whether there is any abnormality in the migration result is determined based on the accurate parameters of the data migration, and the data segment that needs to be re-migrated is determined based on the abnormal hash value.

[0090] It is understandable that due to the differences between the two data platforms, during the data migration process, in order to make the data compatible, the data on the migration platform will be adaptively processed during the migration process. For example, for incompatible data types, mapping rules are created to convert the data types of the source database into data types supported by the target database. This is a prior art and is not specifically limited.

[0091] In the invention, for indirect migration type of data migration, because the difference between the data platform to be migrated and the target migration data platform is relatively large, after the same data enters the target migration data platform after various processing in the data migration process, there is a change in the retrieval index, which leads to a large difference in the retrieval response time used in the data retrieval process on different data platforms. For direct migration type of data migration, because the migration process hardly performs any processing other than compression and decompression on the data, most of the data is exactly the same before and after migration, so the hash value can be used to more simply and intuitively determine whether the migration is abnormal. The present invention can adaptively select a more reasonable analysis method according to different migration types, thereby improving the quality of the data after the final migration.

[0092] See also Figure 3 As shown, it is a logic diagram of determining whether there is an abnormality according to the compatible characterization parameters according to an embodiment of the present invention. The process of determining the compatible characterization parameters includes:

[0093] Randomly searching for a number of data segments in the to-be-migrated data platform, and adding marks to the searched data segments;

[0094] Recording the first search response time used for searching each marked data segment;

[0095] Retrieving each marked data segment in the target migration data platform to obtain a second retrieval response time corresponding to each marked data segment;

[0096] The compatible characterization parameter is determined according to the first search response time and the second search response time.

[0097] In implementation, the number of retrieved data segments should not be too small. Too few retrievals will result in analysis results that are not sufficiently representative. Preferably, the proportion of retrieved data segments should be greater than 30% of the total number of data segments. A marked data segment corresponds to a first retrieval response time and a second retrieval response time.

[0098] It can be understood that the retrieval response time is the time taken to retrieve the corresponding data segment.

[0099] Specifically, the compatibility characterization parameter is determined according to formula (2):

[0100]

[0101] In formula (2), K is a compatible characterization parameter, m is the total number of retrieved data segments, Tj is the first retrieval response time of the j-th data segment in the data platform to be migrated, tj is the second retrieval response time of the j-th data segment in the target migration data platform, and j is an integer greater than 0.

[0102] Specifically, determining whether the migration result is abnormal according to the compatible characterization parameter includes:

[0103] If the compatible characterization parameter is greater than or equal to the standard compatible characterization parameter, it is determined that there is an abnormality in the migration result;

[0104] If the compatible characterization parameter is smaller than the standard compatible characterization parameter, it is determined that there is no abnormality in the migration result.

[0105] In implementation, the ratio of the second retrieval response time to the first retrieval response time is greater than or equal to 1, that is, the larger the compatibility characterization parameter is, the longer the second retrieval response time used to retrieve the data after the migration is completed in the target migration data platform, indicating poor compatibility, and further indicating that the adaptive processing of data in the data migration process to solve the version compatibility problem cannot achieve the effect of solving the compatibility problem, and further processing is required.

[0106] See also Figure 4 As shown, it is a logic diagram of determining whether there is an abnormality according to the accurate parameters of data migration according to an embodiment of the present invention. Determining the accurate parameters of data migration and determining the data segments that need to be re-migrated includes:

[0107] Determine the abnormal hash value and the corresponding data segment according to the comparison result of the hash value of each segment of the data platform to be migrated and the hash value of the corresponding data segment in the target migration data platform;

[0108] Determine the data segment corresponding to the abnormal hash value as the data segment that needs to be re-migrated;

[0109] Determine the accurate parameters for data migration based on the number of abnormal hash values.

[0110] In practice, the exact parameters of data migration are determined according to formula (3):

[0111] K2=H1 / H0 (3)

[0112] In formula (3), K2 is the accurate parameter of data migration, H1 is the number of abnormal hash values, and H0 is the total number of hash values.

[0113] It is understandable that due to the avalanche effect of hash values, even small data changes will cause significant changes in hash values. Therefore, for the data migration process between two data platforms with basically consistent data before and after migration, using hash values ​​to determine whether there are any anomalies in the data segments during the migration process is both simple and intuitive. That is, when the hash values ​​are different, it can be determined that the data segment corresponding to the current hash value is abnormal. Therefore, using hash values ​​to analyze the migration process can not only determine whether the data accuracy is qualified, but also directly determine the data segments with migration abnormalities, avoiding wasting time on repeated retrieval and positioning.

[0114] Specifically, determining whether there is an abnormality in the migration result according to the accurate parameters of the data migration includes:

[0115] If the data migration accuracy parameter is greater than or equal to the standard accuracy parameter, it is determined that the migration result is abnormal;

[0116] If the data migration accuracy parameter is less than the standard accuracy parameter, it is determined that there is no abnormality in the migration result.

[0117] In implementation, the standard accuracy parameter is selected in the interval [0.02, 0.05]. The smaller the data migration difference parameter is, the smaller the standard accuracy parameter is.

[0118] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0119] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A migration method based on a data platform, characterized in that: include: Step S1, determining a data platform to be migrated and a target migration data platform, determining the data type stored in the data platform to be migrated and data migration requirement information, wherein the data type includes destructible data and non-destructible data; Step S2, determining migration difference characteristics according to the data migration requirements, and calculating data migration difference parameters of this migration according to the migration difference characteristics; In step S2, the process of determining migration difference characteristics according to the data migration requirements includes: Determine the amount of data to be migrated to the target migration data platform in the data migration requirements; Performing simulated migration for the migration data volume to obtain the migration data volume of the target migration data platform under the simulated migration; Calculate the difference between the migration amount of the data platform to be migrated and the migration amount of the target migration data platform; Determine the difference in the number of indexes between the migration data indexes of the data platform to be migrated and the migration data indexes of the target migration data platform; Determining the migration amount difference and the index quantity difference as a migration difference feature; In step S2, the data migration difference parameter is determined according to formula (1): ， In formula (1), G is the data migration difference parameter, C1 is the migration difference, C0 is the standard migration difference, M1 is the index quantity difference, and M0 is the standard index quantity difference; Step S3, determining the data migration type according to the data migration difference parameter; Step S4, performing lossy compression on the lossy data and then migrating it, performing lossless compression on the non-lossy data and then migrating it, and analyzing this migration according to the data migration type, including: If the data migration type is an indirect migration type, after the data content of each data type is migrated, a sample search is performed on the data in the target migration data platform, and the search response time is recorded to determine the compatible characterization parameter, and whether there is an abnormality in the migration result is determined according to the compatible characterization parameter; If the data migration type is a direct migration type, the hash value of each segment of data on the to-be-migrated data platform is compared with the hash value of the corresponding data segment in the target migration data platform to determine the accurate parameters of data migration, and whether there is an abnormality in the migration result according to the accurate parameters of data migration, and the data segment that needs to be re-migrated is determined according to the abnormal hash value; The process of determining the compatible characterization parameter includes: Randomly searching for a number of data segments in the to-be-migrated data platform, and adding marks to the searched data segments; Recording the first search response time used for searching each marked data segment; Retrieving each marked data segment in the target migration data platform to obtain a second retrieval response time corresponding to each marked data segment; Determining the compatible characterization parameter according to the first search response time and the second search response time; The compatibility characterization parameter is determined according to formula (2): ， In formula (2), K is a compatible characterization parameter, m is the total number of retrieved data segments, Tj is the first retrieval response time of the jth data segment in the data platform to be migrated, tj is the second retrieval response time of the jth data segment in the target migration data platform, and j is an integer greater than 0; Determining the accurate parameters of the data migration and determining the data segments that need to be re-migrated includes: Determine the abnormal hash value and the corresponding data segment according to the comparison result of the hash value of each segment of the data platform to be migrated and the hash value of the corresponding data segment in the target migration data platform; Determine the data segment corresponding to the abnormal hash value as the data segment that needs to be re-migrated; Determine the accurate parameters of data migration based on the number of abnormal hash values; The accurate parameters of data migration are determined according to formula (3): K2=H1 / H0 (3) In formula (3), K2 is the accurate parameter of data migration, H1 is the number of abnormal hash values, and H0 is the total number of hash values.

2. The data platform-based migration method according to claim 1, characterized in that: In the step S3, determining the data migration type of this migration according to the data migration difference parameter includes: If the data migration difference parameter is greater than or equal to the standard migration difference parameter, the data migration type is a direct migration type; If the data migration difference parameter is less than the standard migration difference parameter, the data migration type is an indirect migration type.

3. The data platform-based migration method according to claim 2, characterized in that: The determining whether the migration result is abnormal according to the compatible characterization parameter includes: If the compatible characterization parameter is greater than or equal to the standard compatible characterization parameter, it is determined that there is an abnormality in the migration result; If the compatible characterization parameter is smaller than the standard compatible characterization parameter, it is determined that there is no abnormality in the migration result.

4. The data platform-based migration method according to claim 3, characterized in that: Determining whether there is an abnormality in the migration result based on the accurate parameters of the data migration includes: If the data migration accuracy parameter is greater than or equal to the standard accuracy parameter, it is determined that the migration result is abnormal; If the data migration accuracy parameter is less than the standard accuracy parameter, it is determined that there is no abnormality in the migration result.

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