Cloud Server SQL Query Parsing for Data Transfer Reduction
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Solution Overview
Problem
In cloud computing, existing methods for big data analysis in cloud storage require enterprises to download all data from a cloud server to a terminal, consuming large amounts of network resources and resulting in inefficient data retrieval due to manual screening of data.
Innovation Solution
A method and apparatus that parse a SQL query statement to generate an abstract structured syntax tree, allowing the cloud server to selectively send only the target data to the client, reducing network resource consumption by screening data at the storage layer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all data is downloaded from cloud server to terminal, then data completeness is ensured, but network resource consumption increases significantly
Solution Approach 1:
The patent extracts only the necessary data fields and records that match the query conditions from the complete dataset, rather than transferring all data. The SQL query statement is parsed to identify specific data elements needed, and only those elements are retrieved from cloud storage, significantly reducing network bandwidth consumption while maintaining data completeness for the analysis purpose.
Solution Approach 2:
The system performs preliminary data filtering and screening at the cloud server before data transfer. By parsing the SQL query statement and generating an abstract syntax tree, the system pre-determines which data should be transferred, enabling the cloud server to screen and prepare only the necessary data for transmission, thus reducing the quantity of data over the network.
2Productivity
If all data is manually screened at terminal, then data analysis flexibility is maintained, but processing time and efficiency decrease
Solution Approach 1:
The patent introduces a SQL query parser and abstract syntax tree generator as intermediaries between the user's data analysis needs and the cloud storage system. This intermediary layer translates high-level query statements into executable screening operations, enabling efficient data retrieval while maintaining analysis flexibility through standardized query processing.
Solution Approach 2:
The system replaces manual mechanical data screening operations with automated computer-based processing. By using SQL query parsing and abstract syntax tree execution, the system automatically filters and retrieves data based on query conditions, eliminating time-consuming manual screening while maintaining the flexibility to perform various data analysis operations.
Data Source
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AI summary
A target data obtaining method and an apparatus provided by embodiments of the present application relate to the technical field of cloud computing. A specific implementation is that: when a cloud server receives a structured query language SQL query statement, which is sent by a client and used to indicate target data that needs to be obtained, the cloud server does not directly issue all data to the client, but first generates an abstract structured syntax tree corresponding to the SQL query statement; and screens all stored data according to the abstract structured syntax tree to obtain the target data; and then sends the target data to the client. Compared with the prior art, in which all data are issued to client, the amount of issued data is effectively reduced, thereby reducing network resources consumed by the cloud server. In addition, for the client, compared with the prior art, in which all data need to be downloaded to the client, the amount of downloaded data is effectively reduced and network resources consumed by the client can also be reduced.