Financial data query method based on cloud computing

Abstract

The invention provides a financial data query method based on cloud computing. The financial data query method comprises the steps of receiving a query request which is submitted by a user by a user node; analyzing the query request and verifying the query request; decomposing the query request into multiple sub-queries; respectively converting the multiple sub-queries into multiple query languages which aim at multiple data sources based on the multiple data sources which need to be accessed by the multiple sub-queries; respectively executing the multiple query languages and obtaining multiple intermediate results; composing the multiple intermediate results into a query result. According to the financial data query method based on the cloud computing, provided by the invention, a more comprehensive query result can be obtained in a could computing network, unnecessary query operation is avoided, the computing resource is more reasonably utilized, and the data transmission cost is reduced.

Description

technical field [0001] The present invention relates to cloud computing technology, in particular to a query method based on cloud computing, in particular to a financial data query method based on cloud computing. Background technique [0002] Since the emergence of cloud computing, through the continuous development of science and technology, through the continuous advancement of academia and industry, the application of cloud computing is constantly developing and deepening, and cloud computing is also moving from theory to practice. With the continuous maturity of cloud computing technology, the data center also develops accordingly. Today's data center is no longer just a place where servers are hosted and maintained in a unified manner. It has evolved into a centralized place for high-performance computers that integrate large-scale data computing and storage. The cloud computing data center involves hundreds of millions of servers or PCs, etc., with a large number of...

AI Technical Summary

Problems solved by technology

On the one hand, if you only perform data query on a certain computing node, you will not be able to get the expected goal

On the second hand, many users are not familiar with the business in actual operation, it is easy to make wrong requests, so the expected results cannot be obtained without verification

In the third aspect, the data query request is decomposed in real time. If the decomposition granularity is too small, resources will be wasted, and if the decomposition granularity is too large, resources will not be fully utilized.

The fourth aspect is the utilization of resources. For example, the selection of computing nodes is often randomly selected, which may occupy remote resources, but there are corresponding resources in the vicinity of user nodes, which increases the cost of data transmission.

[0004] For the above-mentioned problems existing in related technologies, effective solutions have not yet been proposed

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