Overview
When a service system needs turned on for its users, the cluster administrator can define service models on the RTD GUI, including service tenant information, service event sources, formats of event source data packets, information dimensions that you need to pay attention to (such as card holders and merchants), service database modeling information, event variables, and metadata of batch variables.
You can directly customize the system environment on the platform for the O&M of the entire service application. The customization includes the following operations:
- IT system initialization: Initialize the system, perform database modeling, specify event sources and information dimensions, establish the mapping between event sources and the information dimensions, and turn the system on or off for users.
- Basic service configuration: Service personnel define event variables for event sources, blacklist and whitelist for each event source, take batch variables offline under each dimension, and turn the service on or off for users.
- Customer service configuration: Your users can create and turn real-time query variables to obtain real-time data query results from MOTService; create model variables and perform data analysis and calculation using trained models; create prediction variables and perform inference and analysis on event data through deep learning; and create and use PL/SQL stored procedure rules to check whether data matches the rules.
- Database tool: Perform data definition and data manipulation operations, including adding, deleting, querying, and modifying tables, views, and stored procedures in MOTService.
- Template management: Create templates for rules and modify the templates to create new services, simplifying the creation process.
Type |
Operation |
Description |
---|---|---|
IT system initialization |
Configure analysis dimensions |
Classify data by dimension, for example, card holder and merchant dimensions. |
Add event sources |
Define data sources, including the dimensions used by an event source and the data source fields to be saved. |
|
Basic service configuration |
Configure event variables |
Configure event variables to specify the message fields that variables and rules can use in an even source. |
Configure batch variables |
Configure batch variables to specify the computation results to be used. The computation results are calculated and imported by the offline big data cluster. |
|
Add a blacklist and whitelist |
Add blacklist and whitelist based on which SQL statements check the event sources. |
|
Customer service configuration |
Add real-time query variables |
Use the real-time query variables in SQL statements to to query real-time data in MOTService. |
Add model variables |
Use the variables in a scoring model trained offline based on historical user data to predict scores based on real-time data. |
|
Add prediction variables |
Connect prediction variables to the inference platform for event type prediction. |
|
Add stored procedures |
A store procedure is a prepared SQL code that contains a set of conditions and returns 0 or 1. |
|
Configure window variables |
Use window variables in Flink for streaming process and batch process. |
|
Decision engine |
Configure the decision engine |
The decision engine calculates data and generates decision scores for decision-making. |
Database tools |
Perform database operations |
Run DDL, DML, and DQL commands in MOTService, including table creation, query, and indexing. |
Manage scheduled data clearing tasks |
Set scheduled tasks for clearing data tables. |
|
Template management |
Manage templates |
Manage templates for creating event sources, and blacklists and whitelists. |
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