Data change message notification method and device

Abstract

The invention belongs to the technical field of big data, and provides a data change message notification method and device, and the method comprises the steps: generating a data relation graph according to metadata in a database where a to-be-notified data change message is located; determining all target nodes of the to-be-notified data change message according to a data relationship graph; andsending the to-be-notified data change message to all the target nodes. According to the method, a task calling relationship and a table dependency relationship are fused to construct a complete'datadependency graph '. Based on the data dependence graph, a traversal algorithm of the graph is utilized to carry out change notification, and the effects of accurately notifying without omitting any person in charge and controlling a notification level to notify in place at one time are achieved.

Description

technical field [0001] The invention relates to the technical field of computer software, in particular to a method and device for notifying a data change message. Background technique [0002] As we all know, the data processing of the data warehouse uses the production data of the transaction system. When production data changes, business development leads to data offline, and data warehouse processing logic changes, etc., it is necessary to notify the downstream data user in time so that the downstream user can make corresponding processing. In the prior art, the flexible notification scheme is as follows: the changer initiates a change notification application, describes the content of the change, and sends it to the direct downstream user according to the invocation dependency of the data processing task. [0003] The above scheme is applicable to the notification of changes in the general trading system, and there are two problems with changes in the data warehouse fi...

AI Technical Summary

Problems solved by technology

In the data warehouse, in order to improve the timeliness of data output, or the data source used has not been updated for a long time, there may be cases where the processing task has no upstream and downstream call relationship, but the data of the table produced by the processing task is actually used; according to the data processing The task calls the relationship notification, that is, the situation of missing notification will occur

[0005] (2) Notification level control is not in place

In-depth data warehouse processing often has dozens of layers of scheduling dependencies. For data offline, it will affect all downstream data users, and layer-by-layer notifications consume human resources.

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