CN114706850B - Warehouse-in method of distributed heterogeneous relational database - Google Patents
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Abstract
The invention discloses a method for warehousing a distributed heterogeneous relational database, which comprises the steps that a warehousing submission service program on an application server loads a corresponding relational database driver according to the type of a database node in a database node list and the link information of the database node, and links the database nodes in the database node list; and scanning the normalized operation log file copy cached for the database node by a warehousing submission service program on the application server, analyzing a key value pair with a key value rep in the operation log file copy, reversely converting the value of the key value pair into a series of warehousing operations of the database node, and performing the warehousing operation on the data object to be operated. The invention solves the problem of transverse expansion of relational data storage and is suitable for storing infinite mass data; by supporting the heterogeneous relational database, the safety and the economy of data storage are improved.
Description
Technical Field
The invention relates to a method for warehousing a distributed heterogeneous relational database, and belongs to the technical field of computer data storage.
Background
In the age of coming in 5G silently, along with the improvement of the performance of the Internet of things and the data acquisition terminal, more and more data are acquired and stored, and mass data are generated in the process. However, the data read-write of the traditional relational database is required to be analyzed by sql, so that the read-write performance is insufficient under the conditions of large amount of data and high concurrency, and a large amount of data is concentrated in a service area for processing, so that the server is overwhelmed.
At present, aiming at the requirement of massive relational data storage, the storage capacity can be effectively improved only by carrying out partition processing on data objects to be stored, however, in order to improve the safety and the economy, the conventional various relational databases are operated in parallel. The inconsistency of the operation interfaces of the relational databases of different types and the supported sql language standard, when a plurality of types of relational database software are selected as data storage carriers, how to solve the problem of relational data storage and improve the storage capacity becomes a technical problem which needs to be solved by the technicians in the field.
Disclosure of Invention
The purpose is as follows: in order to overcome the defects in the prior art, the invention provides a method for warehousing a distributed heterogeneous relational database.
The technical scheme is as follows: in order to solve the technical problems, the invention adopts the following technical scheme:
A method for warehousing a distributed heterogeneous relational database comprises the following steps:
When the application program on the application server performs data object warehousing operation, the data storage grouping of the warehousing operation is obtained according to the data partition corresponding to the data object to be operated.
And obtaining a database node list in the data storage group according to the data storage group of the warehousing operation.
And loading a corresponding relational database driver according to the database node types and the database node linking information in the database node list by a warehouse-in submitting service program on the application server, and linking the database nodes in the database node list.
And scanning the normalized operation log file copy cached for the database node by a warehousing submission service program on the application server, analyzing a key value pair with a key value rep in the operation log file copy, reversely converting the value of the key value pair into a series of warehousing operations of the database node, and performing the warehousing operation on the data object to be operated.
Preferably, the method further comprises: and for the database nodes which are not online, entering a delay retry mode, and continuing to carry out warehousing operation after access recovery.
As a preferred scheme, the number of the data storage packets is a plurality of, no master-slave division exists among the data storage packets, no core packet exists, and the plurality of data storage packets form a data storage cluster; each data storage group includes a master plurality of backup heterogeneous relational database nodes.
Preferably, each data storage packet has a globally unique data storage packet code.
Preferably, the heterogeneous relational database node comprises at least one of Oracle, mysql, daphne and PostgreSQL.
Preferably, the obtaining the data storage packet of the binning operation according to the data partition corresponding to the data object to be operated includes:
and obtaining the data partition codes according to the data object codes of the data objects to be operated.
And obtaining the data partition and the corresponding data storage block code according to the data partition code.
The data storage packets are obtained from the data storage packet encoding.
Preferably, the data partition is divided according to at least one of geographic location, administrative area, object number and data importance.
Preferably, each data partition maps at least one data storage packet; each data storage packet may map multiple data partitions.
As a preferred solution, the normalized operation log file copy obtaining method includes the following steps:
And caching a series of warehousing operations of the data objects of the same data partition into a normalized JSON format operation log file.
And storing a copy of the normalized JSON format operation log file in all database nodes in a database node list of the data storage group corresponding to the data partition.
The JSON-format operation log file includes: the time of log file generation is manipulated, JSON array.
The JSON array includes: a SqlJson object normalized by static SQL statement operations, a BindJson object normalized by dynamic SQL statement binding variable operations, and a ProcedureJson object normalized by stored procedure operations.
The object of SqlJson normalized by the static SQL statement operation comprises two groups of key value pairs, which are respectively:
1) "type" = "DIRECTSQL" means that SqlJson object records a static SQL statement operation.
2) "SQL" = "static SQL statement" means that a static SQL statement operates on a specific SQL statement, which is recorded in the value of the key-value pair.
The BindJson object for dynamic SQL statement binding variable operation normalization comprises three groups of key value pairs, which are respectively:
1) "type" = "bindSql" means that BindJson object records dynamic SQL statement binding variable operations.
2) "SQL" = "dynamic SQL statement" means an SQL statement of a dynamic SQL statement bind variable operation, which is recorded in the value of the key value pair.
3) "Bind" = [ ] represents the data to be bound of the dynamic SQL statement bind variable operation, the value of the key value pair is a JSON array type, each element of the array is also an array, the value of a group of bind variables is recorded in the array, and the array formed by a plurality of elements records a plurality of groups of bind variable values.
The storage process operates the normalized ProcedureJson object, including four sets of key-value pairs, respectively:
1) "type" = "procedure" means ProcedureJson that the object records is a stored procedure operation.
2) "Pack" = "packet name" means the packet name of the stored procedure that stores the procedure operation call.
3) "Proc" = "procedure name" means a procedure name of a stored procedure storing a procedure operation call.
4) "Pram" = "parameter name" indicates a parameter of the stored procedure that stores the procedure operation call, and indicates that there is no parameter when the value of the key-value pair is null.
Preferably, the method for resolving a key value pair with a key value rep in the operation log file copy and reversely converting the value of the key value pair into a series of warehousing operations of the database node comprises the following steps:
acquiring a JSON array in a key value pair with a key value rep.
Traversing each binning operation JSON object in the JSON array.
Look up JSON object key-value pair is a value of type,
When the value of the type is DIRECTSQL, searching for the value of the key value pair sql in the JSON object, calling a direct sql execution interface in the loaded relational database driver, and completing execution of the warehousing operation.
When the value of the type is bindSql, searching for the value of the key value pair in the JSON object as SQL, calling an SQL statement preprocessing interface in the loaded relational database drive to process SQL statements, analyzing the SQL statements to obtain the number and the type of binding parameters, searching for the value of the key value pair in the JSON object as bind to obtain a binding parameter array, calling the binding parameter interface in the loaded relational database drive to complete the binding of data, and completing the execution of the warehousing operation.
When the value of the type is procedure, searching a value of a key value pair in the JSON object as pack to obtain a package name, searching a value of a key value pair in the JSON object as proc to obtain a process name, searching a value of a key value pair in the JSON object as pram to obtain a parameter name, calling a storage process interface in a loaded relational database driver, and completing execution of a warehousing operation.
The beneficial effects are that: according to the method for warehousing the distributed heterogeneous relational database, on one hand, the problem of transverse expansion of relational data storage is solved, and the method for warehousing can be suitable for storing infinite mass data in technical principle; on the other hand, through supporting the heterogeneous relational database, the safety and the economy of data storage are improved.
Drawings
FIG. 1 is a schematic diagram of a distributed heterogeneous relational database network architecture.
FIG. 2 is a map of data partitions and storage packets.
FIG. 3 is a flowchart of a normalized cache operation log file for a binning operation.
Detailed Description
The following detailed description of the preferred embodiments of the invention is provided to enable those skilled in the art to more readily understand the advantages and features of the invention and to make a clear and concise definition of the scope of the invention.
A method for warehousing a distributed heterogeneous relational database comprises the following steps:
1) The data storage nodes can run different types of relational database software, the data storage nodes run in groups, the storage nodes of the same group finish redundant storage of data, no master-slave division exists among the data storage groups, no core group exists, and a plurality of data storage groups form a data storage cluster; there is a globally unique data storage block code for each data storage block.
2) Each data object to be stored has a globally unique data object code, and a part of the data object code is used as a data partition code of the data object, and the partition code of the data object of a partition is identical.
3) And constructing a data partition coding and data storage block coding mapping table, and storing the data partition coding and data storage block coding mapping table in a local shared memory.
The data partition coding and data storage block coding mapping table stored in the local shared memory comprises: the data storage group comprises a data storage group number, a data storage group code, a data partition number, a data partition code, a mapping relation between the data partition code and the data storage group code, and a database node list contained in the data storage group, wherein the database node list comprises database nodes, database node types and database node link information.
4) When an application program on an application server performs warehousing operation, firstly, acquiring a data partition code of a data object to be operated according to the data object code of the data object, then, inquiring a data partition code and a data storage block code mapping table to acquire a data storage block code corresponding to the data object, and finally, acquiring a database node list of a data storage block according to the data storage block code.
5) According to the type of the warehousing operation, a series of warehousing operations of the data objects of the same data partition are cached into normalized JSON format operation log files, and one copy of the operation log files is stored in all database nodes in a database node list corresponding to the data partition.
Types of binning operations include: the method particularly needs to be explained that if the static SQL statement operation and the dynamic SQL statement binding variable operation cannot be compatible with the SQL statement of different types of relational databases, the stored procedure operation is required to be created in the relational databases to replace the static SQL statement operation and the dynamic SQL statement binding variable operation so as to shield the inconsistency of SQL language standards of the different types of relational databases.
Caching a series of binning operations into normalized caches includes converting each binning operation into a JSON object and merging the JSON objects into a JSON array.
The static SQL sentence operation is normalized to SqlJson objects, and the objects comprise two groups of key value pairs, which are respectively:
1) "type" = "DIRECTSQL" indicates that the object records a static SQL statement operation.
2) "SQL" = "static SQL statement" means that the static SQL statement operates a specific SQL statement, which is recorded in the value of the key-value pair.
The dynamic SQL statement binding variable operation is normalized to BindJson objects, which contain three sets of key value pairs, respectively:
1) "type" = "bindSql" indicates that the object records a dynamic SQL statement bind variable operation.
2) "SQL" = "dynamic SQL statement" means an SQL statement that the dynamic SQL statement binds variable operations, which statement is recorded in the value of the key-value pair.
3) "Bind" = [ ] represents the data to be bound of the dynamic SQL statement bind variable operation, the value of the key value pair is a JSON array type, each element of the array is also an array, the value of a group of bind variables is recorded in the array, and the array formed by a plurality of elements records a plurality of groups of bind variable values.
The stored procedure operation is normalized to ProcedureJson object, which contains four sets of key-value pairs, respectively:
1) "type" = "procedure" means that the object records is a stored procedure operation.
2) "Pack" = "packet name" means the packet name of the stored procedure called by the stored procedure operation.
3) "Proc" = "procedure name" means the procedure name of the stored procedure called by the stored procedure operation.
4) "Pram" = "parameter name" indicates a parameter of the stored procedure called by the stored procedure operation, and indicates no parameter when the value of the key-value pair is null.
The JSON-format operation log file records a series of warehousing operations of the data objects of the same data partition, and comprises two key value pairs, which are respectively:
1) "time" = "" indicates the time when the file was generated.
2) "Rep" = "[ ]" represents a JSON array converted by a series of binning operations.
6) Each application server node deploys a warehouse-in submitting service program, loads a corresponding relational database driver according to the database node types and the database node linking information in the database node list, and tries to link the database nodes. Periodically scanning a normalized operation log file copy cached for the node by a database node capable of being linked, analyzing a key value pair with a key value rep in the operation log file, reversely converting the value of the key value pair into a series of warehousing operations on an actual database, and submitting to warehousing after the operations are completed; and for the database nodes which are not online, entering a delay retry mode, and continuing to submit and warehouse-in after access recovery.
The key value of the key value pair with rep is a JSON array, each element in the array is a JSON object, and each JSON object corresponds to one warehousing operation.
The reverse conversion of the key value pair value into a series of binning operations on the actual database includes traversing each binning operation JSON object of the value array, for each binning operation JSON object, first searching for a value of the object key type, one of the value DIRECTSQL, BINDSQL and procedure representing a static SQL statement operation, a dynamic SQL statement binding variable operation, and a stored procedure operation, respectively.
When the value of the key type is DIRECTSQL, searching for the value of the object key as sql, and then calling a direct sql execution interface in the loaded relational database driver to finish the execution of the operation.
When the value of the key type is bindSql, searching for the value of the JSON object key as SQL, then calling an SQL statement preprocessing interface in the loaded relational database driver to process the SQL statement, then analyzing the SQL statement to obtain the number and the type of binding parameters, finally searching for the value of the JSON object key as bind to obtain a binding parameter array, calling a binding parameter interface in the loaded relational database driver to complete the binding of data, and completing the execution of the operation.
When the value of the key type is procedure, searching the value obtained package name of the JSON object key pack, searching the value obtained process name of the JSON object key proc, searching the value obtained parameter name of the JSON object key pram, and calling a storage process interface in the loaded relational database driver to finish execution of the operation.
Further, the step 1 data storage packet includes:
1) A master and a plurality of N heterogeneous relational database nodes.
2) Heterogeneous relational databases include Oracle, mysql, dalberg, and PostgreSQL.
Further, the rule set in the partition in the step 2 is as follows: the division is performed according to geographic location, administrative area, number of objects or degree of importance of data.
Further, the mapping relationship between the data object partition and the data storage packet in the step 3 includes:
1) Each data partition maps at least one storage packet.
2) Each storage packet may map multiple data partitions.
Example 1:
As shown in fig. 1, the distributed heterogeneous relational database includes: and 3 storage groups, wherein each storage group comprises 2 relational database nodes of the same type, and relational database instances of different types are installed among the storage groups. The 3 storage packets are respectively connected with 2 application servers in the network.
According to the importance degree of the data object to be stored, 3 data partitions are set to be general, common and important respectively, and p1, p2 and p3 are used for coding the data partitions respectively, wherein the data partition p1 is general, only one storage packet is needed to be selected as a storage carrier of the data partition p3, and three storage packets are needed to be selected as the storage carriers of the data partition p3, and the three storage carriers are redundant.
And setting a globally unique code for each data object according to the data partition to which the data object to be stored belongs, and ensuring that the data partition code can be acquired from the codes.
And establishing a warehouse-in operation log cache folder for each database node on the application server. When the application program needs to perform the warehousing operation, converting the operation of the data object belonging to the same data partition into a unified normalized operation log file, and caching the warehousing operation into an operation log file flow as shown in fig. 3. And then the data partition codes of the data object are obtained according to the codes of the data object, as shown in fig. 2, the target relational database nodes of the warehousing operation are determined according to the mapping relation between the data partition codes and the storage groups, and finally an operation log file copy is saved for each target relational database node according to the normalized operation log format. The warehousing and submitting service program scans the normalized operation log file copy cached by each database node, loads the corresponding relational database driver according to the relational database type operated by the database node, analyzes the operation in the operation log file and converts the operation into the operation on the actual database, and merges all the operations in one operation log file into one transaction for submitting.
If the application program needs to delete the data object coded as p100000001 on the home data partition p1, storing the data object in a table named as table1, wherein the primary key name is id, the value is p100000001, and normalizing the operation into SQLJson objects { type: sql, sql: delete from table table1 sphere id=p 100000001}; inquiring a data partition coding and data storage block coding mapping table to confirm that a storage partition corresponding to a data partition p1 is a storage partition 1, wherein the storage partition is provided with two relational database nodes, and corresponding cache folders are respectively folder1 and folder2; one oplog file is cached in folders folder1 and folder2, respectively. After the warehouse-in submitting service program scans the operation log files in the folders folder1 and folder2, loading the corresponding dream-reaching database driver according to the type of the relational database operated by the database node, analyzing the deleting operation in the operation log file to be converted into the operation on the actual database, deleting and submitting the record with the main key p100000001 in the table1 in the two relational database nodes, and deleting the corresponding file in the cache folder after the submitting is successful.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (10)
1. A method for warehousing a distributed heterogeneous relational database is characterized by comprising the following steps of: the method comprises the following steps:
When an application program on an application server performs data object warehousing operation, acquiring a data storage group of the warehousing operation according to a data partition corresponding to a data object to be operated;
according to the data storage grouping of the warehousing operation, a database node list in the data storage grouping is obtained;
The warehouse-in submitting service program on the application server loads the corresponding relational database driver according to the database node types and the database node linking information in the database node list and links the database nodes in the database node list;
And scanning the normalized operation log file copy cached for the database node by a warehousing submission service program on the application server, analyzing a key value pair with a key value rep in the operation log file copy, reversely converting the value of the key value pair into a series of warehousing operations of the database node, and performing the warehousing operation on the data object to be operated.
2. The method for warehousing a distributed heterogeneous relational database according to claim 1, wherein: further comprises: and for the database nodes which are not online, entering a delay retry mode, and continuing to carry out warehousing operation after access recovery.
3. A method for warehousing a distributed heterogeneous relational database according to claim 1 or 2, wherein: the number of the data storage groups is multiple, no master-slave division exists among the data storage groups, no core group exists, and the data storage groups form a data storage cluster; each data storage group includes a master plurality of backup heterogeneous relational database nodes.
4. A method of warehousing a distributed heterogeneous relational database according to claim 3, wherein: each data storage packet has a globally unique data storage packet code.
5. A method of warehousing a distributed heterogeneous relational database according to claim 3, wherein: the heterogeneous relational database node comprises at least one of Oracle, mysql, daphne, and PostgreSQL.
6. A method for warehousing a distributed heterogeneous relational database according to claim 1 or 2, wherein: the data storage grouping of the warehousing operation is obtained according to the data partition corresponding to the data object to be operated, and the method comprises the following steps:
obtaining data partition codes according to the data object codes of the data objects to be operated;
Obtaining a data partition and a corresponding data storage block code according to the data partition code;
The data storage packets are obtained from the data storage packet encoding.
7. The method for warehousing the distributed heterogeneous relational database according to claim 6, wherein the method comprises the following steps: the data partitions are partitioned according to at least one of geographic location, administrative area, number of objects, and degree of importance of the data.
8. The method for warehousing the distributed heterogeneous relational database according to claim 6, wherein the method comprises the following steps: mapping at least one data storage packet per data partition; each data storage packet may map multiple data partitions.
9. A method for warehousing a distributed heterogeneous relational database according to claim 1 or 2, wherein: the normalized operation log file copy acquisition method comprises the following steps:
caching a series of warehousing operations of the data objects of the same data partition into a normalized JSON format operation log file;
Storing a copy of the normalized JSON format operation log file in all database nodes in a database node list of a data storage group corresponding to the data partition;
The JSON-format operation log file includes: time of operation log file generation, JSON array;
The JSON array includes: a SqlJson object normalized by static SQL statement operation, a BindJson object normalized by dynamic SQL statement binding variable operation and a ProcedureJson object normalized by storage process operation;
The object of SqlJson normalized by the static SQL statement operation comprises two groups of key value pairs, which are respectively:
1) "type" = "DIRECTSQL" means that SqlJson object records a static SQL statement operation;
2) "SQL" = "static SQL statement" means that a static SQL statement operates a specific SQL statement, which is recorded in the value of the key value pair;
The BindJson object for dynamic SQL statement binding variable operation normalization comprises three groups of key value pairs, which are respectively:
1) "type" = "bindSql" means that BindJson object records dynamic SQL statement binding variable operations;
2) "SQL" = "dynamic SQL statement" means an SQL statement of a dynamic SQL statement bind variable operation, which statement is recorded in the value of the key value pair;
3) "bind" = [ ] represents the data to be bound of the dynamic SQL statement binding variable operation, the value of the key value pair is a JSON array type, each element of the array is also an array, the value of a group of binding variables is recorded in the array, and the array formed by a plurality of elements records a plurality of groups of binding variable values;
The storage process operates the normalized ProcedureJson object, including four sets of key-value pairs, respectively:
1) "type" = "procedure" means ProcedureJson that the object record is a store procedure operation;
2) "pack" = "package name" means the package name of the stored procedure that stores the procedure operation call;
3) "proc" = "procedure name" means a procedure name of a stored procedure that stores a procedure operation call;
4) "pram" = "parameter name" indicates a parameter of the stored procedure that stores the procedure operation call, and indicates that there is no parameter when the value of the key-value pair is null.
10. The method for warehousing a distributed heterogeneous relational database according to claim 9, wherein: the method for resolving the key value pair with the key value rep in the operation log file copy and reversely converting the value of the key value pair into a series of warehousing operations of the database node comprises the following steps:
acquiring a JSON array in a key value pair with a key value rep;
Traversing each warehousing operation JSON object in the JSON array;
Look up JSON object key-value pair is a value of type,
When the value of the type is DIRECTSQL, searching for the value of the key value pair sql in the JSON object, calling a direct sql execution interface in the loaded relational database drive, and completing execution of the warehousing operation;
When the value of the type is bindSql, searching for the value of the key value pair in the JSON object as SQL, calling an SQL statement preprocessing interface in the loaded relational database drive to process SQL statements, analyzing the SQL statements to obtain the number and the type of binding parameters, searching for the value of the key value pair in the JSON object as bind to obtain a binding parameter array, calling a binding parameter interface in the loaded relational database drive to complete the binding of data, and completing the execution of warehousing operation;
When the value of the type is procedure, searching a value of a key value pair in the JSON object as pack to obtain a package name, searching a value of a key value pair in the JSON object as proc to obtain a process name, searching a value of a key value pair in the JSON object as pram to obtain a parameter name, calling a storage process interface in a loaded relational database driver, and completing execution of a warehousing operation.
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