How to efficiently realize mass message transmission and status tracking of millions of users?

Strategies for mass message sending and status tracking of million-level users

This article explains how to build an efficient message mass sending system to meet the needs of batch sending, interrupted sending and reading status tracking under the scale of millions of users.

First, database design is crucial. Faced with massive data, we need to optimize the data structure. It is recommended to use two table structures:

• Message table: stores the message content and overall sending status (0: not started, 1: sending, 2: interrupted, 3: completed). This table is used to monitor the overall progress of each message.
• Message item table (message_items): Stores the delivery results of each message to each user (read, unread, failed to send, etc.). In order to improve efficiency, especially for millions of users, it is recommended to use adjacency tables or link table structures to avoid performance bottlenecks caused by simple row recording methods.

In order to achieve efficient mass transmission, we will adopt the message queue mechanism. The queue triggers the sending task based on the preset sending time in the message table. The sending item by item is inefficient, so a batch sending strategy is adopted, for example, 500 user data are processed at a time (chunk size = 500).

The sending progress bar on the front end of the system can be dynamically updated through the data in the statistical message item table. If the user requests interrupt sending, the status of the corresponding message in the update message table is "Interrupted" (status value 2). The message queue continuously monitors the status changes of the message table, checking the status before processing each data block, thereby realizing the interrupted transmission function.

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