Method and system for implementing data sandbox based on mongoDB

Abstract

The invention relates to a method and system for implementing a data sandbox based on mongoDB. The method comprises the steps that a server receives a data sandbox creation application sent by a user side; the server creates an independent data sandbox on the mongoDB according to the application; the server stores the data sandbox and manages operation resource quotas; the server leads data warehouse data or external data into the data sandbox and performs data processing in a data sandbox environment; and after the data processing, the server leads processed data out of the data sandbox, destroys the data sandbox and recycles system resources. An elastic data operating environment is provided for users, and the request on local installation and transaction database management is omitted; through an isolated environment, data risks caused by misoperation by users are effectively avoided, the conditions that a data warehouse is retarded due to a centralized mode are reduced, environmental availability is improved, and efficient data access is achieved while the overhead of the data warehouse is reduced.

Description

Technical field [0001] The invention relates to the field of computer software, in particular to a method and system for implementing a data sandbox based on mongoDB. Background technique [0002] In order to meet the needs of analysis and decision-making, enterprises provide a data analysis environment for analysts by establishing a centralized data warehouse. With the continuous accumulation of data, the centralized method has led to an increasingly large data warehouse; business development has increased the demand for data analysis. More and more people need to rely on the data warehouse, and more personalized analysis needs require the support of the data environment; the increase in the amount of data and the increase in accessing users, in this case, the centralized model easily leads to the data warehouse being overtaken Slow: Distributed database or big data solves some of the problems in terms of performance, but it still cannot meet the changing business needs and pers...

AI Technical Summary

Problems solved by technology

[0002] In order to meet the needs of analysis and decision-making, enterprises provide analysts with a data analysis environment by establishing a centralized data warehouse. With the continuous accumulation of data, the centralized method leads to an increasingly large data warehouse; business development increases the demand for data analysis. More and more people need to rely on the data warehouse, and more personalized analysis requirements require the support of the data environment; the increase in the amount of data and the increase in access users, in this case, the centralized model is likely to cause the data warehouse to be dragged more and more Slow; distributed databases or big data have solved some problems in terms of performance, but still cannot meet the changing business needs and personalized analysis needs in the case of increasing data complexity and data volume

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