Bank task allocation method and device

Abstract

The invention relates to a bank task allocation method and device. The method comprises the following steps: reading task message data from an MQ queue, and processing the task message data to obtain task information; storing legal task information in a redis cache database, converting the legal task information into message data which is consistent with a DB2 database storage format, and putting the message data into a local MQ queue; reading the message data which is consistent with the DB2 database storage format with local multiple threads, and storing the read message data in a DB2 database; publishing a corresponding notification message to a socket IO server subscribing for the notification message with a redis pub / sub queue; and transmitting notification information to a business end by the socket IO server, and judging whether or not the operating authorization for executing corresponding task information is available by the business end according to the notification information.

Description

technical field [0001] The invention relates to the technical field of bank system data processing, in particular to a bank task allocation method and device. Background technique [0002] As the scale of the bank gradually increases, the fields that the bank is engaged in are also expanding. In this case, how to assign tasks to designated employees has become an important step in the informatization of banking business. The efficiency and accuracy of task assignment will be greatly improved. Have a huge impact on the bank's operating costs. [0003] At present, the common way to complete task allocation is that each business system sends tasks to designated employees. Usually, the task data is stored in the DB2 database. After the task is sent, the employee usually obtains it by periodically polling the background database. own task list. [0004] Above technical scheme has following shortcoming: [0005] 1) Each task will have dozens or even hundreds of matching relatio...

AI Technical Summary

Problems solved by technology

DB2 database is a single point, and there is a certain bottleneck in terms of large data storage and high concurrent query performance

[0007] 3) Employees usually obtain their own task lists by regularly polling the background database, which causes a large number of query requests to bring huge pressure on the server; moreover, there are a large number of invalid query requests, wasting server resources

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