A heterogeneous database data type rapid comparison method

Abstract

The application provides a kind of heterogeneous database data type fast comparison method, comprising the following steps: first establish a cloud server based on middle end;IP address tracking module is set on the cloud server;There are several groups of processing modules on the cloud server;Each comparison group in the processing module is stored with the data type comparison relationship between two different heterogeneous databases;According to its IP address, its data type can be known, and their signals are separately allocated to specific comparison groups for processing and identification by signal distributor;After comparison, the result information is returned to the access database by transcoding or correction, and the comparison result can be quickly obtained.The application uses cloud server as a medium as the transfer station of heterogeneous database, improves the sharing efficiency;According to the data type of heterogeneous database and the data type of target database, the two data types are isolated and processed by corresponding processing module, and the comparison efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of database, in particular to a heterogeneous database data type rapid comparison method. BACKGROUND

[0002] The heterogeneous database system is a collection of related database systems, which can realize data sharing and transparent access. Several database systems exist before joining the heterogeneous database system and have their own database management systems. Each component of the external database has its own autonomy. While realizing data sharing, each database system still has its own application characteristics, integrity control and security control.

[0003] The data type refers to a set of values and a set of operations defined on the value set. It appears to divide data into different sizes of memory required for program operation. Generally, data can be divided into different types according to the characteristics of the data type, such as primitive type, multivariate group, record unit, algebraic data type, abstract data type, reference type and function type. There are different data types in each programming language and database. Common data types mainly include: numerical type, date type, time type, string type, logical type and text type.

[0004] The heterogeneous database system should achieve two points to realize data sharing: one is to realize database conversion; the other is to realize transparent access of data; to achieve the above two points, the data definition model of the source database needs to be converted into the data definition model of the target database, and then the data is reorganized, that is, the data in the source database system is loaded into the destination database. However, it is difficult to achieve strict equivalent conversion in the conversion process. First, the conflicts in syntax and semantics existing in the two models need to be determined. These conflicts may include: naming conflicts, format conflicts, structure conflicts, etc.

[0005] Because many heterogeneous databases have many data types, a large amount of data type comparison needs to be performed during conversion. Often, only the server itself is relied on to process comparison and conversion when sharing, which is slow and occupies a large amount of computing resources. A large data flow is formed between access and being accessed, and the server itself cannot bear the heavy burden, affecting the sharing efficiency. SUMMARY

[0006] The purpose of the present disclosure is to provide a heterogeneous database data type rapid comparison method, which can use a cloud server as a medium as a transfer station of a heterogeneous database, improve the sharing efficiency, and can isolate the data types of the heterogeneous database and the target database according to the data types of the heterogeneous database and the target database, and process them with corresponding processing modules, thereby improving the comparison efficiency.

[0007] To achieve this objective, the present disclosure adopts the following technical solution:

[0008] A method for fast comparison of data types in heterogeneous databases includes the following steps:

[0009] S1. Establish a mid-range cloud server that can communicate with multiple heterogeneous databases via network.

[0010] S2. Set up an IP address tracking module on the cloud server. This IP address tracking module can track the IP address of the database accessing the database and the IP address of the target database.

[0011] S3. The data types of each heterogeneous database connected to the cloud server are known and are entered into the cloud server for storage;

[0012] S4. Several processing modules are set up on the cloud server; the number of comparison groups in the processing modules is set according to the number of heterogeneous databases, and the number of heterogeneous databases is set to X.

[0013] The number of comparison groups is: X*(X-1) / 2;

[0014] S5. Each comparison group in the processing module stores the data type comparison relationship between two different heterogeneous databases.

[0015] S6. After identifying the IP address of the access database and the IP address of the target database, the data type can be determined based on the IP address. Then, the signal distributor assigns the signals between them to a specific comparison group for processing and identification. The specific comparison group stores the data type comparison relationship between the two heterogeneous databases.

[0016] S7. The comparison group is also equipped with a transcoding module and a correction module. After the comparison is completed, the result information is returned to the access database through transcoding or correction, which can quickly obtain the comparison result.

[0017] Preferably, the cloud server described above is equipped with multiple network interfaces, each of which can only communicate with one heterogeneous database. The IP address of the heterogeneous database can be directly determined through the network interface.

[0018] Preferably, databases with the same data type among the aforementioned heterogeneous databases share a single network interface when communicating with the cloud server.

[0019] Preferably, the IP address tracking module described above includes a network port identification module.

[0020] Preferably, the processing modules on the cloud server are configured with 32, 48, or 64 groups, of which the groups in use are comparison groups and the groups in standby are blank groups; the blank groups are reserved for use when the number of heterogeneous databases increases in the future.

[0021] Preferably, each of the above processing modules is equipped with a memory, which is used to store data type comparison relationships.

[0022] Preferably, each of the above processing modules is configured as a separate integrated module, and the two ends of the surface of the integrated module are engraved with two data type marks corresponding to the data type comparison relationship stored in the memory.

[0023] Preferably, the above also includes a permission module, which is set at the front end of the signal distributor. By restricting access through the permission module, one-way access permissions can be formed between multiple databases, thus preventing the leakage of data from the superior database.

[0024] Preferably, the heterogeneous database types mentioned above include at least three of the following: MySQL, SQL Server, Oracle, PostgreSQL, DB2, BigTable, Cassandra, MongoDB, Apache Cassandra, Dynamo, and LevelDB.

[0025] Preferably, the above also includes a back-end control center, which is used to control and manage the cloud server, and can call the processing modules, delete their working data, load data type comparison relationships, and communicate with the back-end of various heterogeneous databases through an independent network.

[0026] The beneficial effects of this disclosure are as follows:

[0027] This invention, by setting up a cloud server and using the cloud server as a medium to act as a relay station for heterogeneous databases, does not consume the processing resources of its own server when processing comparisons, thus improving sharing efficiency.

[0028] This invention sets up an IP address tracking module on a cloud server, which can isolate the data types of the heterogeneous database and the target database separately and process them with corresponding processing modules, thus rationally allocating and utilizing the resources of the cloud server and improving comparison efficiency.

[0029] In this invention, each processing module is configured as a separate integrated module on a cloud server, which facilitates maintenance, management, and expansion.

[0030] This invention sets up a permission module on a cloud server, which can ensure the security of its own database information during sharing. Attached Figure Description

[0031] Figure 1 This is a diagram showing the connection relationships between the cloud server and multiple heterogeneous databases in the publicly provided method for fast comparison of heterogeneous database data types.

[0032] Figure 2 This is a connection diagram of the IP address tracking module in the heterogeneous database data type fast comparison method provided in this publication;

[0033] Figure 3 This is a diagram showing the backend connection relationship between the backend management center and multiple databases in the publicly provided method for fast comparison of heterogeneous database data types.

[0034] Figure 4 This is a schematic diagram of the access process when sharing databases in the fast comparison method for heterogeneous database data types provided in this publication;

[0035] Figure 5 This is a partial data type comparison diagram between MySQL and Oracle databases during the implementation of the publicly provided method for fast comparison of heterogeneous database data types. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1

[0038] A method for fast comparison of data types in heterogeneous databases includes the following steps:

[0039] S1. Establish a mid-range cloud server that can communicate with multiple heterogeneous databases via network.

[0040] S2. Set up an IP address tracking module on the cloud server. This IP address tracking module can track the IP address of the database accessing the database and the IP address of the target database.

[0041] S3. The data types of each heterogeneous database connected to the cloud server are known and are entered into the cloud server for storage;

[0042] S4. Several processing modules are set up on the cloud server; the number of comparison groups in the processing modules is set according to the number of heterogeneous databases, and the number of heterogeneous databases is set to X.

[0043] The number of comparison groups is: X*(X-1) / 2;

[0044] S5. Each comparison group in the processing module stores the data type comparison relationship between two different heterogeneous databases.

[0045] S6. After identifying the IP address of the access database and the IP address of the target database, the data type can be determined based on the IP address. Then, the signal distributor assigns the signals between them to a specific comparison group for processing and identification. The specific comparison group stores the data type comparison relationship between the two heterogeneous databases.

[0046] S7. The comparison group is also equipped with a transcoding module and a correction module. After the comparison is completed, the result information is returned to the access database through transcoding or correction, which can quickly obtain the comparison result.

[0047] Specifically, the processing modules on the cloud server are configured with 32, 48, or 64 groups, of which the groups in use are comparison groups, and the groups in standby are blank groups; the blank groups are reserved for future use when the number of heterogeneous databases increases. Each processing module is equipped with a memory to store data type comparison relationships.

[0048] In implementation, such as Figure 1 As shown, the processing module is configured with 32 groups, of which 6 databases (A, B, C, I, J, K) constitute the entire heterogeneous database system. The number of comparison groups is 6*(6-1) / 2 = 15, namely (AB), (AC), (AI), (AJ), (AK), (BC), (BI), (BJ), (BK), (CI), (CJ), (CK), (IJ), (IK), and (JK). The remaining 17 groups are blank. In the comparison groups, A, B, ... represent the data types of their respective databases.

[0049] Example 2

[0050] Unlike Example 1, as Figure 2 As shown, the cloud server is equipped with multiple network interfaces, each of which can only communicate with one heterogeneous database. The IP address of the heterogeneous database can be directly determined through the network interface. Databases with the same data type in the heterogeneous databases share a single network interface when communicating with the cloud server. The IP address tracking module includes a network port identification module. In this embodiment, the IP address tracking module is directly implemented using network port identification; this design simplifies data flow and allows databases of the same type in the heterogeneous databases to share a single network port, thus saving resources.

[0051] Example 3

[0052] Unlike Example 1, as Figure 1 As shown, each processing module is configured as a separate integrated module, and two data type markers corresponding to the data type comparison relationships stored in the memory are engraved on both ends of the surface of the integrated module. In this embodiment, the processing modules are physically isolated, which facilitates maintenance and expansion.

[0053] Example 4

[0054] Unlike Embodiment 1, this embodiment also includes a permission module. This permission module is located at the front end of the signal distributor. By restricting access through the permission module, one-way access permissions can be established between multiple databases, preventing the leakage of data from higher-level databases. Figure 4 As shown in the example, this embodiment is designed for databases with hierarchical relationships. To prevent the leakage of the upper-level database, access permissions are set to prevent the lower-level database from directly accessing the upper-level database, thereby improving security during sharing.

[0055] Example 5

[0056] In implementation, unlike Example 1, the heterogeneous database types include at least three of the following: MySQL, SQL Server, Oracle, PostgreSQL, DB2, BigTable, Cassandra, MongoDB, Apache Cassandra, Dynamo, and LevelDB. Figure 5 As shown in the figure, this embodiment discloses a comparison diagram of some data types of MySQL and Oracle databases.

[0057] Example 6

[0058] like Figure 3 As shown, unlike Embodiment 1, it also includes a backend control center, which is used to control and manage the cloud server. This center can call processing modules, delete their working data, load data type comparison relationships, and communicate with the backends of various heterogeneous databases via an independent network. The backend control center enables real-time communication, timely handling of problems encountered during the sharing process, and improves sharing efficiency.

[0059] In summary, this invention uses a cloud server as a relay station for heterogeneous databases, which does not consume the processing resources of its own server during comparison, thus improving sharing efficiency. It can isolate the data types of the heterogeneous database and the target database separately and process them using corresponding processing modules, rationally allocating and utilizing cloud server resources, thereby improving comparison efficiency. On the cloud server, each processing module is set up as a separate integrated module, facilitating maintenance, management, and expansion. The inclusion of a permission module ensures the security of the database information during sharing.

[0060] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for fast comparison of data types in heterogeneous databases, characterized in that, Includes the following steps: S1. Establish a mid-range cloud server that can communicate with multiple heterogeneous databases via network. S2. Set up an IP address tracking module on the cloud server. This IP address tracking module can track the IP address of the database accessing the database and the IP address of the target database. S3. The data types of each heterogeneous database connected to the cloud server are known and are entered into the cloud server for storage; S4. Several processing modules are set up on the cloud server; the number of comparison groups in the processing modules is set according to the number of heterogeneous databases, and the number of heterogeneous databases is set to X. The number of comparison groups is: X*(X-1) / 2; S5. Each comparison group in the processing module stores the data type comparison relationship between two different heterogeneous databases. S6. After identifying the IP address of the access database and the IP address of the target database, the data type can be determined based on the IP address. Then, the signal distributor assigns the signals between them to a specific comparison group for processing and identification. The specific comparison group stores the data type comparison relationship between the two heterogeneous databases. S7. The comparison group is also equipped with a transcoding module and a correction module. After the comparison is completed, the result information is returned to the access database through transcoding or correction, which can quickly obtain the comparison result. The cloud server is equipped with multiple network interfaces, each of which can only communicate with one heterogeneous database. The IP address of the heterogeneous database can be directly determined through the network interface. Databases with the same data type in heterogeneous databases share a single network interface when communicating with the cloud server.

2. The method for fast comparison of heterogeneous database data types according to claim 1, characterized in that, The IP address tracking module includes a network port identification module.

3. The method for fast comparison of heterogeneous database data types according to claim 1, characterized in that, The processing modules on the cloud server are configured with 32, 48, or 64 groups, of which the groups in use are comparison groups, and the groups in standby are blank groups; the blank groups are reserved for use when the number of heterogeneous databases increases in the future.

4. The method for fast comparison of heterogeneous database data types according to claim 1, characterized in that, Each processing module is equipped with a memory, which is used to store data type comparison relationships.

5. The method for fast comparison of heterogeneous database data types according to claim 4, characterized in that, Each processing module is set up as a separate integrated module, and two data type markers corresponding to the data type comparison relationship stored in the memory are engraved on both ends of the surface of the integrated module.

6. The method for fast comparison of heterogeneous database data types according to claim 1, characterized in that, It also includes a permission module, which is set at the front end of the signal distributor. By restricting access through the permission module, one-way access permissions can be formed between multiple databases, preventing the leakage of data from the superior database.

7. The method for fast comparison of heterogeneous database data types according to claim 1, characterized in that, Heterogeneous databases include at least three of the following types: MySQL, SQL Server, Oracle, PostgreSQL, DB2, BigTable, Cassandra, MongoDB, Apache Cassandra, Dynamo, and LevelDB.

8. The method for fast comparison of heterogeneous database data types according to claim 1, characterized in that, It also includes a back-end control center, which is used to control and manage cloud servers. It can call processing modules, delete their working data, load data type comparison relationships, and communicate with the back-end of various heterogeneous databases through an independent network.

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