Have you actually read the apidoc of javax. What is unclear about that? Add a comment. Active Oldest Votes. Improve this answer. Mark Rotteveel 86k gold badges silver badges bronze badges. Shubh Sharma Shubh Sharma 59 7 7 bronze badges. Pooja Arora Pooja Arora 7 7 silver badges 19 19 bronze badges. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Applications such as relational database management systems and even websites use databases as primary data sources.
Hardware such as input devices and sensors use the environment as the primary data source. A good example is a temperature and pressure control system for a fluid circulation system such as the ones used in factories and oil refineries, which take all related data from the environment or whatever they are monitoring; so the data source here is the environment. Data such as temperature and pressure of the fluid are taken by sensors regularly and then stored in a database, which then becomes the primary data source for another computer application that manipulates and presents this data.
A data source is most commonly used in context with databases and database management systems or any system that primarily deals with data, and is referred to as a data source name DSN , which is defined in the application so that it can find the location of the data. It simply means what the words mean: where data is coming from. Share this Term. Tech moves fast! You must identify databases to the applications that access them. You can distribute databases across a network and involve various servers and database management systems.
A database data source identifies the database information that the software needs to connect to a database. A logic machine is the machine on which batch applications and master business functions run. You must identify logic machines using a data source definition. The data source definition must include the network information about the machine, such as a server name - HP, for example. When mapping logic objects for distributed processing, the software uses the machine data source distributed processing data source as the target location for processing logic objects.
Data source names that you define are names used to identify the data source. You should use a meaningful name for the data sources. For example, to indicate that you are storing business data for production users, the data source name could be Business Data - Prod.
JD Edwards EnterpriseOne provides demonstration data source names at installation; you can use these for your own data sources. The data source definition must contain information about the database and the server in which it is located.
Different database management systems identify the databases in different ways. Two of the required data sources define machines that process logic in the enterprise. The other data sources define various databases used in the enterprise. The installation software provides samples of these required data sources to build your system configuration:. This data source points to the Object Librarian tables you use for custom development.
You should have only one set of Object Librarian tables for each software release, regardless of how many path codes sets of central objects you maintain. This data source can reside on any supported platform. The Object Librarian data source is named by base release number; for example, Object Librarian - This data source consists of the technical tables you use to run all JD Edwards EnterpriseOne applications.
You must set up one system data source per release. All workstations use a central set of system tables usually stored on the enterprise server but not on the deployment server. Each logic server requires its own subset of system tables. These server system tables are stored in the server map data source. This data source enables you to store data dictionary master tables in a central location to enable easier administration of changes.
Group these master tables together to form a data dictionary database. You should share one data dictionary between the production such as PD and development such as DV path codes. The software allows one data dictionary per path code, but multiple data dictionaries are not recommended or supported. Use this data source to override the process location of a batch application that you mapped in the Object Configuration Manager to run on the server.
This data source is used when you divide the business data into multiple owners or libraries, which can reside on the same enterprise server or on different ones. Each group of data requires a separate data source. The installation software provides demonstration data that you can copy to supported host databases. Each file stores a connection string for a single data source. File data sources, unlike machine sources, are editable and copyable like any other computer file.
This allows users and systems to share a common connection by moving the data source between individual machines or servers , and for the streamlining of data connection processes for example by keeping a source file on a shared resource so it may be used simultaneously by multiple applications and users.
These are the same type of file as described above, but they exist on a single machine and cannot be moved or copied. These files point directly to machine data sources. This means that unshareable file data sources are wrappers for machine data sources, serving as a proxy for applications which expect only files but also need to connect to machine data.
Data sources are used in a variety of ways. Many platforms use data sources with FTP addresses to specify the location of data needed to be imported. For example, in the Adobe Analytics platform, a file data source is uploaded to a server using an FTP client, then a service utilizes this source to move and process the relevant data automatically. Meanwhile, many and diverse APIs are now provided to manage data sources and how they are used in applications.
APIs are used to programmatically link applications to data sources, and typically provide more customization and a more versatile collection of access methods.
For example, Spark provides an API with abstract implementations for representing and connecting to data sources, from barebones but extensible classes for generic relational sources, to detailed implementations for hard-coded JDBC connections.
These protocols are often used within APIs and some APIs themselves make use of other APIs internally , within fully featured data applications, or as standalone transfer processes.
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