Data conversion method of heterogeneous data source and middleware
A technology of heterogeneous data sources and conversion methods, applied in structured data retrieval, electronic digital data processing, database management systems, etc., can solve the problems of insufficient types of heterogeneous data sources, difficulty in automatic conversion, and failure to support domestic databases, etc.
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Embodiment 1
[0084] image 3 Embodiment 1 of the present invention provides a flow chart of a data conversion method for heterogeneous data sources. This example takes the core data conversion function as an example. The method specifically includes the following:
[0085] Step 101, configure the access data source, and obtain the technical metadata of the access data source.
[0086] According to the different types of different access data sources, the configuration information is different, as follows:
[0087] Database-type data sources need to configure the specific type of database, database address, user name, password, database instance name (can be empty), and driver package. The specific type of database such as Dameng, Oracle, MySQL, MongoDB, etc.; the database address such as the IP address or domain name address of the database server; the user name and password are the authorization to access the database; if there are multiple instances of the database, one needs to be spe...
Embodiment 2
[0115] In this embodiment, on the basis of the first embodiment above, a process engine is introduced to streamline the data conversion process.
[0116] The data conversion process includes six core nodes: access-exit source configuration, data access adaptation, data acquisition, processing conversion, data access adaptation, and data loading, such as Figure 4 shown.
[0117] Node 201, access-access source configuration.
[0118] The main task of this node is to select the access data source and the access data source, and configure the access-exit mapping relationship. The content of the configuration is the same as step 103 in the first embodiment. If the access data source and the output data source have not been registered as data sources, they need to be registered in advance. The content of the registration information is the same as that in steps 101-102 of the first embodiment.
[0119] Node 202, data access adaptation.
[0120] The main task of this node is to ...
Embodiment 3
[0130] On the basis of the second embodiment above, this embodiment introduces task scheduling to automate the data conversion process.
[0131] Configurable scheduling strategy, supports real-time task scheduling, scheduled task scheduling, and supports setting priorities. Scheduling tasks can be associated with one or more data conversion processes, and support parallel and sequential execution of multiple data conversion processes, such as Figure 5 a, 5b, 5c.
[0132] Figure 5 a indicates the sequential scheduling of multiple data conversion processes, that is, the combined scheduling of some data conversion processes has a sequence, and the input of the latter conversion process depends on the output of the previous conversion process, and must be executed in a certain order.
[0133] Figure 5 b indicates parallel scheduling of multiple data conversion processes, that is, the input of a certain conversion process depends on the output of multiple conversion processes...
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