Resource management method and system

Abstract

The embodiment of the invention provides a resource management method and system. The resource management method comprises the following steps: receiving a first operation task submitting message, wherein the first operation task submitting message comprises an operation to be processed, first resource demand information for processing the operation, and a first resource management framework for processing the operation; converting the first resource demand information into second resource demand information corresponding to the first resource management framework; transmitting the second resource demand information and the operation to the first resource management framework, so that the first resource management framework distributes a first resource which is required for operating the operation according to the second resource demand information, and operates the operation according to the distributed first resource. Through the resource management method which is provided by the embodiment of the invention, the resource management cost is reduced, and the resource managing and scheduling complexity is reduced.

Description

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AI Technical Summary

Benefits of technology

This technology allows organizations with diverse sources of data (such as databases) to efficiently manage their own storage space without having manual adjustments that increase costly manpower efforts. It also simplifies how these systems work together effectively across heterogeneous environments such as those containing both physical servers and virtual machines. Overall this results in improved efficiency and reduced maintenance expenses compared to existing methods.

Problems solved by technology

The technical problem addressed in this patented text relates to improving the efficiency and effectiveness of large-scale software applications that involve processing massive amounts of data (Big Data). Current solutions rely heavily upon manual adaptation or customization from various sources like databases with specific configurations, leading to increased costs associated with managing resource requests across diverse hardware platforms.

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