A stream rendering method and related apparatus

By breaking down the query task into multiple subtasks for parallel execution and streaming data transmission, the problems of high response latency and low resource utilization in existing technologies are solved, enabling real-time updates of the terminal interface and efficient data processing.

CN122332014APending Publication Date: 2026-07-03KINGDEE SOFTWARE(CHINA) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
KINGDEE SOFTWARE(CHINA) CO LTD
Filing Date
2026-04-09
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

In existing technologies, data analysis and generation processes suffer from high response latency and low utilization of computing resources. Especially in high-concurrency scenarios, users need to wait several minutes to see the results, and the system throughput is low with serious resource idleness.

Method used

The query task is broken down into multiple subtasks using a streaming rendering method. Each subtask is executed in parallel by multiple intelligent agents. Execution data is sent to the terminal in real time for dynamic rendering. Communication is achieved through an event bus, shared memory, and middleware, along with concurrency control and data buffer management.

Benefits of technology

It enables real-time updates of the terminal interface and progressive rendering of results, improving response speed and resource utilization, reducing user waiting time, and enhancing the system's processing capabilities in high-concurrency scenarios.

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Abstract

This invention discloses a streaming rendering method and related apparatus to improve the response speed of a terminal to query tasks. The method includes: performing semantic parsing on a query task received by the terminal to obtain multiple subtasks; selecting multiple agents from an agent resource pool to execute the multiple subtasks based on the multiple subtasks; and streaming the execution data of each subtask to the terminal when each agent outputs the execution data of each subtask, so that the terminal performs interface rendering based on the execution data of each subtask.
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