Data query method, system, device and medium based on index query platform

Abstract

This invention discloses a data query method, system, device, and medium based on an indicator query platform, relating to the field of data processing technology. The method includes: pre-acquiring query SQL and related data from the indicator query platform, and generating target data parameters based on the query SQL and related data; performing data analysis on the target data parameters to find target datasets with the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets; receiving a user's query instruction based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data. This invention solves the problems of low cache hit rate, duplicate data caching, and poor data display timeliness in existing indicator query platforms.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and specifically to a data query method, system, computer device, and non-volatile computer-readable storage medium based on an indicator query platform. Background Technology

[0002] Currently, in the fintech field, financial institutions often need to use indicator query platforms to query and display indicator data due to their business needs. Indicator query platforms serve as a unified platform for financial institutions to manage and apply indicators.

[0003] Currently, there are many application scenarios for industry indicator query platforms, such as open interfaces, BI (Business Intelligence) dashboards, card displays, and mobile displays. When querying data, indicators generate multiple copies of SQL (Structured Query Language) based on the indicator data model. Due to the ever-changing user permissions and query conditions, the cache hit rate during data query is low. At the same time, data is saved repeatedly, making it difficult and untimely to actively cache data when it is updated. This results in poor data timeliness, insufficient flexibility and convenience when displaying data, and also wastes computing resources.

[0004] In summary, how to provide a data query method, system, computer equipment, and non-volatile computer-readable storage medium based on an indicator query platform to avoid the problems of low cache hit rate, duplicate data caching, and poor timeliness of data display in existing indicator query platforms is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a data query method, system, computer device and non-volatile computer-readable storage medium based on an indicator query platform that can be used in financial technology or other related fields. The aim is to solve the problems of low cache hit rate, repeated saving of data cache and poor timeliness of data display when the existing indicator query platform performs data query.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A data query method based on an indicator query platform, comprising:

[0008] The query SQL and related data from the indicator query platform are obtained in advance, and target data parameters are generated based on the query SQL and the related data.

[0009] Data analysis is performed on the target data parameters to find target datasets with the same indicator data model, and parameter fusion is performed on the target datasets to generate the parameter tree corresponding to the target datasets;

[0010] The system receives query instructions from users based on the indicator query platform, performs data queries through the parameter tree, and returns the corresponding query data.

[0011] In a further technical solution, the data query method based on the indicator query platform, wherein the step of pre-acquiring the query SQL and related data of the indicator query platform, and generating target data parameters based on the query SQL and the related data, includes:

[0012] Pre-acquire the query SQL and related data that appear in various application scenarios of the indicator query platform;

[0013] The query SQL is converted into SQL to obtain SqlNode;

[0014] Based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

[0015] In a further technical solution, the data query method based on the indicator query platform includes the step of performing data structure analysis based on the SqlNode and the related data to generate target data parameters for a preset group of the query SQL, wherein the preset group includes a condition group, a permission group, an aggregation group, and a dimension group.

[0016] In a further technical solution, the data query method based on the indicator query platform includes the following steps: performing data analysis on the target data parameters to find target datasets containing the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets.

[0017] Perform data analysis on the target data parameters;

[0018] Find the target dataset that contains the same index data model within the target data parameters;

[0019] Based on the data parameters, parameter comparison is performed, data with the same parameters in the target dataset are aggregated, and data with different parameters are inserted into the dataset to generate the parameter tree corresponding to the target dataset.

[0020] In a further technical solution, the data query method based on the indicator query platform, wherein receiving the user's query instruction based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data includes:

[0021] Receive query instructions from users based on the indicator query platform;

[0022] Traverse the parameter tree to query data and return the corresponding query data.

[0023] In a further technical solution, the data query method based on the indicator query platform, wherein receiving the user's query instruction based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data, further includes:

[0024] If the corresponding query data cannot be found through the parameter tree, then the data query is performed through OLAP;

[0025] The dataset returned by the data query through the OLAP will be fused with parameters.

[0026] In a further technical solution, the data query method based on the indicator query platform is described, wherein the indicator query platform is the Pandora indicator platform.

[0027] A data query system based on an indicator query platform, comprising:

[0028] The data parameter generation module is used to pre-acquire the query SQL and related data from the indicator query platform, and generate target data parameters based on the query SQL and the related data.

[0029] The parameter tree generation module is used to perform data analysis on the target data parameters, find target datasets that have the same indicator data model, and perform parameter fusion on the target datasets to generate the parameter tree corresponding to the target datasets.

[0030] The data query module is used to receive query instructions from users based on the indicator query platform, perform data queries through the parameter tree, and return the corresponding query data.

[0031] In a further technical solution, the data query system based on the indicator query platform, wherein the step of pre-acquiring the query SQL and related data from the indicator query platform, and generating target data parameters based on the query SQL and the related data, includes:

[0032] Pre-acquire the query SQL and related data that appear in various application scenarios of the indicator query platform;

[0033] The query SQL is converted into SQL to obtain SqlNode;

[0034] Based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

[0035] In a further technical solution, the data query system based on the indicator query platform includes a step of performing data structure analysis based on the SqlNode and the relevant data to generate target data parameters for a preset group of the query SQL. The preset group includes a condition group, a permission group, an aggregation group, and a dimension group.

[0036] In a further technical solution, the data query system based on the indicator query platform includes the following steps: performing data analysis on the target data parameters to find target datasets containing the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets.

[0037] Perform data analysis on the target data parameters;

[0038] Find the target dataset that contains the same index data model within the target data parameters;

[0039] Based on the data parameters, parameter comparison is performed, data with the same parameters in the target dataset are aggregated, and data with different parameters are inserted into the dataset to generate the parameter tree corresponding to the target dataset.

[0040] In a further technical solution, the data query system based on the indicator query platform, wherein receiving the user's query instruction based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data includes:

[0041] Receive query instructions from users based on the indicator query platform;

[0042] Traverse the parameter tree to query data and return the corresponding query data.

[0043] In a further technical solution, the data query system based on the indicator query platform, wherein receiving the user's query instruction based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data, further includes:

[0044] If the corresponding query data cannot be found through the parameter tree, then the data query is performed through OLAP;

[0045] The dataset returned by the data query through the OLAP will be fused with parameters.

[0046] In a further technical solution, the data query system based on the indicator query platform is described, wherein the indicator query platform is the Pandora indicator platform.

[0047] A computer device, wherein the computer device includes at least one processor; and,

[0048] A memory communicatively connected to the at least one processor; wherein,

[0049] The memory stores a computer program that can be executed by the at least one processor. When the computer program is executed by the at least one processor, it can implement the data query method based on the indicator query platform as described above.

[0050] A non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, which, when executed by at least one processor, can implement the data query method based on the indicator query platform as described in any of the preceding claims.

[0051] Compared to existing technologies, this invention provides a data query method, system, computer device, and non-volatile computer-readable storage medium based on an indicator query platform. The method includes: pre-acquiring query SQL and related data from the indicator query platform, and generating target data parameters based on the query SQL and related data; performing data analysis on the target data parameters to find target datasets with the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets; receiving a query instruction from a user based on the indicator query platform, performing a data query through the parameter tree, and returning the corresponding query data. This invention solves the problems of low cache hit rate, duplicate data caching, and poor data display timeliness in existing indicator query platforms. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart illustrating the data query method based on an indicator query platform provided in an embodiment of the present invention.

[0054] Figure 2 for Figure 1 A detailed flowchart of step S100 described above.

[0055] Figure 3 for Figure 1 A detailed flowchart of step S200 described above.

[0056] Figure 4 for Figure 1 A detailed flowchart of step S300 described above.

[0057] Figure 5 This is a schematic diagram of the functional modules of a data query system based on an indicator query platform provided in an embodiment of the present invention.

[0058] Figure 6 This is a schematic diagram of the hardware structure of the computer device provided in an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0060] In the description of this invention, the terms "comprising," "including," "having," and "containing" are all open-ended terms, meaning that they include but are not limited to. The terms "one embodiment," "one specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0061] Various non-limiting embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0062] Pandora Indicator Platform is Ping An Bank's unified platform for indicator management and application. Driven by business scenarios, the platform provides fundamental capabilities in AI, BI, and content, and combined with a component-based open platform, offers a one-stop solution for data analysis and application. In terms of content, it provides capabilities for the input, publication, and standardized management of indicators, dimensions, and tags. In terms of BI, it offers functions such as indicator cards, indicator maps, indicator dashboards, and indicator derivation and generation. In terms of AI, it establishes pluggable intelligent alerts, rule-based alerts, intelligent attribution, and indicator recommendations. The platform provides a complete solution for multi-dimensional analysis of billions of data points in the banking industry, solving pain points such as long data development cycles, complex data definitions, difficult data acquisition, and slow query response. Through its unique intelligent query routing and construction technology, the platform can build cubes for Qilin Big Data on demand and automatically manage corresponding task scheduling, batch processing queues, lifecycles, and query pressure, meeting the flexible indicator application needs of business users while effectively reducing development and maintenance costs.

[0063] However, the applicant's research revealed that in the Pandora metrics platform, when querying data, the metrics generate multiple copies of SQL (Structured Query Language) based on the metrics data model. Due to the ever-changing user permissions and query conditions, the cache hit rate during data queries is low. At the same time, data is saved repeatedly, making it difficult and untimely to actively cache data when it is updated. This results in poor data timeliness, insufficient flexibility and convenience when displaying data, and also wastes computing resources.

[0064] To resolve the above issues, please refer to Figure 1 This invention provides a data query method based on an indicator query platform, wherein the indicator query platform is the Pandora indicator platform, and the method includes the following steps:

[0065] S100: Pre-acquire the query SQL and related data from the indicator query platform, and generate target data parameters based on the query SQL and the related data;

[0066] S200. Perform data analysis on the target data parameters, find target datasets with the same indicator data model, and perform parameter fusion on the target datasets to generate a parameter tree corresponding to the target datasets.

[0067] S300: Receive the user's query instruction based on the indicator query platform, perform data query through the parameter tree, and return the corresponding query data.

[0068] Further, please refer to Figure 2The data query method based on the indicator query platform, wherein step S100, which involves pre-acquiring the query SQL and related data from the indicator query platform, and generating target data parameters based on the query SQL and the related data, includes the following steps:

[0069] S101. Pre-acquire the query SQL and related data that appear in various application scenarios of the indicator query platform;

[0070] S102. Convert the query SQL into SQL to obtain SqlNode;

[0071] S103. Based on the SqlNode and the related data, perform data structure analysis to generate target data parameters for the preset group of the query SQL.

[0072] In specific implementation, in this embodiment, the query SQL and related data appearing in various application scenarios of the Pandora indicator platform are obtained in advance, and the query SQL is converted into SQL to obtain SqlNode. Then, based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

[0073] Furthermore, in the data query method based on the indicator query platform, the step of performing data structure analysis based on the SqlNode and the related data to generate target data parameters for a preset group of the query SQL, wherein the preset group includes a condition group, a permission group, an aggregation group, and a dimension group.

[0074] In specific implementation, in this embodiment, the condition group is the field of the fact table and dimension table of the indicator that the user filters; the permission group is a group of root institutions used for filtering on a certain organization; the aggregation group is the aggregation method of the indicator's measurement field, and has a complex calculation method, such as AVG*(sum(a)+count(b))+count(c), etc.; the dimension group is the field group that the user classifies and aggregates in the specified groupby group.

[0075] Further, please refer to Figure 3 The data query method based on the indicator query platform, wherein step S200, involves performing data analysis on the target data parameters, finding target datasets containing the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets, includes the following steps:

[0076] S201. Perform data analysis on the target data parameters;

[0077] S202. Locate the target dataset containing the same index data model within the target data parameters;

[0078] S203. Based on the data parameters, perform parameter comparison, aggregate data with the same parameters in the target dataset, and insert data with different parameters into the dataset to generate the parameter tree corresponding to the target dataset.

[0079] In specific implementation, in this embodiment, data analysis is performed on the target data parameters to find target datasets with the same indicator data models within the target data parameters. Then, parameter comparison is performed based on the data parameters, and data with the same parameters within the target datasets are aggregated, while data with different parameters are inserted into the datasets to generate the parameter tree corresponding to the target dataset.

[0080] Further, please refer to Figure 4 The data query method based on the indicator query platform, wherein step S300, receiving a user's query instruction based on the indicator query platform, performing a data query through the parameter tree, and returning the corresponding query data, includes the following steps:

[0081] S301. Receive the user's query instruction based on the indicator query platform;

[0082] S302. Traverse the parameter tree to query data and return the corresponding query data.

[0083] S303. If the corresponding query data cannot be found through the parameter tree, then data query is performed through OLAP.

[0084] S304. Perform parameter fusion on the dataset returned by the data query through the OLAP.

[0085] In specific implementation, in this embodiment, after generating the parameter tree corresponding to the target dataset, when a user's query instruction based on the Pandora indicator platform is received, the parameter tree is traversed to query the indicator data and the corresponding query data is returned. Secondly, if the corresponding query data cannot be found through the parameter tree, the indicator data can be queried again through OLAP (Online Analytical Processing) to improve query efficiency. At the same time, the dataset returned by the data query through OLAP is fused, that is, data with the same parameters in the dataset returned by the data query through OLAP are aggregated, and data with different parameters are inserted into the dataset to facilitate subsequent query of indicator data.

[0086] As can be seen from the above method embodiments, the data query method based on the indicator query platform provided by the present invention manages, integrates, and queries the dataset in terms of cache management, avoiding problems such as duplicate data caching and low cache hit rate, thereby saving resources, improving the timeliness of data display, and improving the efficiency of data analysis. On this basis, it can quickly display the indicator data that users need to view, efficiently compare data, and help users make faster decisions, etc., which can help enterprises improve data analysis methods and improve data processing efficiency and display capabilities.

[0087] It should be understood that although this application provides the method operation steps as described in the embodiments or flowcharts, conventional or non-inventive labor may include more or fewer operation steps, and these operation steps are not necessarily executed sequentially according to the order of the embodiments or flowcharts. The order of steps listed in the embodiments or flowcharts is merely one way of executing many steps and does not represent the only execution order. It should be noted that there is no necessary sequential order between the above steps. Those skilled in the art can understand from the description of the embodiments of the present invention that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in exchange, etc. Moreover, at least some steps in the embodiments or flowcharts may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn, alternately, or synchronously with other steps or at least a part of the sub-steps or stages of other steps.

[0088] Based on the above embodiments, please refer to Figure 5 Another embodiment of the present invention also provides a data query system based on an indicator query platform, wherein the indicator query platform is the Pandora indicator platform, and the system includes:

[0089] The data parameter generation module 11 is used to pre-acquire the query SQL and related data of the indicator query platform, and generate target data parameters based on the query SQL and the related data.

[0090] The parameter tree generation module 12 is used to perform data analysis on the target data parameters, find target datasets that have the same indicator data model, and perform parameter fusion on the target datasets to generate the parameter tree corresponding to the target datasets.

[0091] The data query module 13 is used to receive query instructions from users based on the indicator query platform, perform data queries through the parameter tree, and return the corresponding query data.

[0092] Furthermore, in the data query system based on the indicator query platform, the step of pre-acquiring the query SQL and related data from the indicator query platform, and generating target data parameters based on the query SQL and the related data, includes:

[0093] Pre-acquire the query SQL and related data that appear in various application scenarios of the indicator query platform;

[0094] The query SQL is converted into SQL to obtain SqlNode;

[0095] Based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

[0096] In specific implementation, in this embodiment, the query SQL and related data appearing in various application scenarios of the Pandora indicator platform are obtained in advance, and the query SQL is converted into SQL to obtain SqlNode. Then, based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

[0097] Furthermore, in the data query system based on the indicator query platform, the process involves performing data structure analysis based on the SqlNode and the relevant data to generate target data parameters for a preset group of the query SQL. The preset group includes a condition group, a permission group, an aggregation group, and a dimension group.

[0098] In specific implementation, in this embodiment, the condition group is the field of the fact table and dimension table of the indicator that the user filters; the permission group is a group of root institutions used for filtering on a certain organization; the aggregation group is the aggregation method of the indicator's measurement field, and has a complex calculation method, such as AVG*(sum(a)+count(b))+count(c), etc.; the dimension group is the field group that the user classifies and aggregates in the specified groupby group.

[0099] Furthermore, in the data query system based on the indicator query platform, the step of performing data analysis on the target data parameters, finding target datasets containing the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets includes:

[0100] Perform data analysis on the target data parameters;

[0101] Find the target dataset that contains the same index data model within the target data parameters;

[0102] Based on the data parameters, parameter comparison is performed, data with the same parameters in the target dataset are aggregated, and data with different parameters are inserted into the dataset to generate the parameter tree corresponding to the target dataset.

[0103] In specific implementation, in this embodiment, data analysis is performed on the target data parameters to find target datasets with the same indicator data models within the target data parameters. Then, parameter comparison is performed based on the data parameters, and data with the same parameters within the target datasets are aggregated, while data with different parameters are inserted into the datasets to generate the parameter tree corresponding to the target dataset.

[0104] Furthermore, in the aforementioned data query system based on the indicator query platform, the step of receiving a user's query instruction based on the indicator query platform, performing a data query through the parameter tree, and returning the corresponding query data includes:

[0105] Receive query instructions from users based on the indicator query platform;

[0106] Traverse the parameter tree to query data and return the corresponding query data.

[0107] If the corresponding query data cannot be found through the parameter tree, then the data query is performed through OLAP;

[0108] The dataset returned by the data query through the OLAP will be fused with parameters.

[0109] In specific implementation, in this embodiment, after generating the parameter tree corresponding to the target dataset, when a user's query instruction based on the Pandora indicator platform is received, the parameter tree is traversed to query the indicator data and the corresponding query data is returned. Secondly, if the corresponding query data cannot be found through the parameter tree, the indicator data can be queried again through OLAP (Online Analytical Processing) to improve query efficiency. At the same time, the dataset returned by the data query through OLAP is fused, that is, data with the same parameters in the dataset returned by the data query through OLAP are aggregated, and data with different parameters are inserted into the dataset to facilitate subsequent query of indicator data.

[0110] As can be seen from the above system embodiments, the data query system based on the indicator query platform provided by the present invention manages, integrates, and queries datasets in terms of cache management, avoiding problems such as duplicate data caching and low cache hit rate, thereby saving resources, improving the timeliness of data display, and improving the efficiency of data analysis. On this basis, it can quickly display the indicator data that users need to view, efficiently compare data, and help users make faster decisions, etc., which can help enterprises improve data analysis methods and improve data processing efficiency and display capabilities.

[0111] Based on the above embodiments, please refer to Figure 6 Another embodiment of the present invention also provides a computer device, wherein the computer device 10 includes:

[0112] Memory 120 and one or more processors 110, Figure 6 The following description uses a processor 110 as an example. The processor 110 and the memory 120 can be connected via a communication bus or other means. Figure 6 Taking the example of China and Israel being connected via a communication bus.

[0113] Processor 110 performs various control logic functions of computer device 10. It can be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), microcontroller, ARM (AcornRISC Cachine) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. Furthermore, processor 110 can also be any conventional processor, microprocessor, or state machine. Processor 110 can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration.

[0114] The memory 120, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the computer program corresponding to the data query method based on the index query platform in this embodiment of the invention. The processor 110 executes various functional applications and data processing of the computer device 10 by running the non-volatile software programs, instructions, and units stored in the memory 120, thereby implementing the data query method based on the index query platform in the above method embodiment.

[0115] The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store application programs required for operating the device and at least one function; and the data storage area may store data created based on the use of the computer device 10. Furthermore, the memory 120 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 120 may optionally include memory remotely located relative to the processor 110, and these remote memories may be connected to the computer device 10 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0116] One or more units are stored in memory 120. When executed by one or more processors 110, they can implement the data query method based on the indicator query platform as described in any of the above method embodiments. For example, they can implement the above-described... Figure 1 The method steps S100 to S300.

[0117] Those skilled in the art will understand that Figure 6 The hardware structure diagram shown is only a schematic diagram of a part of the structure related to the present invention and does not constitute a limitation on the computer device on which the present invention is applied. The specific computer device may include more components than shown in the figure, or combine some components, or have different component arrangements.

[0118] Based on the above embodiments, the present invention also provides a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by at least one processor, it can implement the data query method based on the indicator query platform as described in any of the above method embodiments, for example, it can implement the above-described... Figure 1 The method steps S100 to S300.

[0119] As an example, non-volatile storage media can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) as an external cache memory. By way of illustration and not limitation, RAM can be obtained in many forms such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM). The memory components or memories disclosed in the operating environment described herein are intended to include one or more of these and / or any other suitable types of memory.

[0120] Another embodiment of the present invention provides a computer program product, the computer program product including a computer program stored on a non-volatile computer-readable storage medium, the computer program including program instructions, which, when executed by a processor, can implement the data query method based on an indicator query platform as described in any of the above method embodiments, for example, can implement the above-described... Figure 1 The method steps S100 to S300.

[0121] The embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0122] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a general-purpose hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can exist in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0123] Among other things, conditional language such as “can,” “may,” “may,” or “may,” unless otherwise specifically stated or otherwise understood as in the context in which they are used, is generally intended to convey that a particular implementation may include (but not others) certain features, elements, and / or operations. Therefore, such conditional language is also generally intended to imply that features, elements, and / or operations are necessary for one or more implementations in any way, or that one or more implementations must include logic for determining, with or without input or prompting, whether such features, elements, and / or operations are included or will be performed in any particular implementation.

[0124] The contents already described herein in this specification and accompanying drawings include examples of data query methods, systems, computer devices, and non-volatile computer-readable storage media capable of providing a data query platform based on an index query platform. Of course, not every conceivable combination of elements and / or methods can be described for the purpose of describing the various features of this disclosure, but it will be appreciated that many other combinations and substitutions of the disclosed features are possible. Therefore, it will be apparent that various modifications can be made to this disclosure without departing from the scope or spirit of this disclosure, but all such various modifications should fall within the protection scope of the appended claims. Furthermore, or in alternatives, other embodiments of this disclosure may become apparent from consideration of this specification and accompanying drawings and from practice of this disclosure as presented herein. It is intended that the examples presented in this specification and accompanying drawings be considered illustrative rather than restrictive in all respects. Although specific terminology is used herein, it is used in a general and descriptive sense and is not intended for limiting purposes.

Claims

1. A data query method based on an indicator query platform, characterized in that, include: The query SQL of the indicator query platform and the relevant data when the query SQL is executed are obtained in advance, and target data parameters are generated based on the query SQL and the relevant data; wherein, the relevant data includes user permission data and query condition data; Data analysis is performed on the target data parameters to find target datasets with the same indicator data model, and parameter fusion is performed on the target datasets to generate the parameter tree corresponding to the target datasets; The system receives query instructions from users based on the indicator query platform, performs data queries through the parameter tree, and returns the corresponding query data.

2. The data query method based on an indicator query platform according to claim 1, characterized in that, The process of pre-acquiring the query SQL from the indicator query platform and the relevant data during the execution of the query SQL, and generating target data parameters based on the query SQL and the relevant data, includes: Pre-acquire the query SQL that appears in various application scenarios of the indicator query platform, as well as the relevant data when the query SQL is executed; The query SQL is converted into SQL to obtain SqlNode; Based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

3. The data query method based on the indicator query platform according to claim 2, characterized in that, The data structure analysis is performed based on the SqlNode and the related data to generate target data parameters for the preset groups of the query SQL, wherein the preset groups include condition groups, permission groups, aggregation groups and dimension groups.

4. The data query method based on the indicator query platform according to claim 2, characterized in that, The step of performing data analysis on the target data parameters, finding target datasets with the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets includes: Perform data analysis on the target data parameters; Find the target dataset that contains the same index data model within the target data parameters; Based on the data parameters, parameter comparison is performed, data with the same parameters in the target dataset are aggregated, and data with different parameters are inserted into the dataset to generate the parameter tree corresponding to the target dataset.

5. The data query method based on the indicator query platform according to claim 4, characterized in that, The process of receiving a user's query command based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data includes: Receive query instructions from users based on the indicator query platform; Traverse the parameter tree to query data and return the corresponding query data.

6. The data query method based on an indicator query platform according to claim 5, characterized in that, The step of receiving a user's query command based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data further includes: If the corresponding query data cannot be found through the parameter tree, then the data query is performed through OLAP; The dataset returned by the data query through the OLAP will be fused with parameters.

7. The data query method based on an indicator query platform according to any one of claims 1-6, characterized in that, The indicator query platform mentioned is the Pandora Indicator Platform.

8. A data query system based on an indicator query platform, characterized in that, include: The data parameter generation module is used to pre-acquire the query SQL of the indicator query platform and the relevant data when the query SQL is executed, and generate target data parameters based on the query SQL and the relevant data; wherein, the relevant data includes user permission data and query condition data; The parameter tree generation module is used to perform data analysis on the target data parameters, find target datasets that have the same indicator data model, and perform parameter fusion on the target datasets to generate the parameter tree corresponding to the target datasets. The data query module is used to receive query instructions from users based on the indicator query platform, perform data queries through the parameter tree, and return the corresponding query data.

9. The data query system based on the indicator query platform according to claim 8, characterized in that, The process of pre-acquiring the query SQL from the indicator query platform and the relevant data during the execution of the query SQL, and generating target data parameters based on the query SQL and the relevant data, includes: Pre-acquire the query SQL that appears in various application scenarios of the indicator query platform, as well as the relevant data when the query SQL is executed; The query SQL is converted into SQL to obtain SqlNode; Based on the SqlNode and the related data, data structure analysis is performed to generate target data parameters for the preset group of the query SQL.

10. The data query system based on the indicator query platform according to claim 9, characterized in that, The data structure analysis is performed based on the SqlNode and the related data to generate target data parameters for the preset groups of the query SQL, wherein the preset groups include condition groups, permission groups, aggregation groups and dimension groups.

11. The data query system based on the indicator query platform according to claim 9, characterized in that, The step of performing data analysis on the target data parameters, finding target datasets with the same indicator data model, and fusing parameters of the target datasets to generate a parameter tree corresponding to the target datasets includes: Perform data analysis on the target data parameters; Find the target dataset that contains the same index data model within the target data parameters; Based on the data parameters, parameter comparison is performed, data with the same parameters in the target dataset are aggregated, and data with different parameters are inserted into the dataset to generate the parameter tree corresponding to the target dataset.

12. The data query system based on the indicator query platform according to claim 11, characterized in that, The process of receiving a user's query command based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data includes: Receive query instructions from users based on the indicator query platform; Traverse the parameter tree to query data and return the corresponding query data.

13. The data query system based on the indicator query platform according to claim 12, characterized in that, The step of receiving a user's query command based on the indicator query platform, performing data query through the parameter tree, and returning the corresponding query data further includes: If the corresponding query data cannot be found through the parameter tree, then the data query is performed through OLAP; The dataset returned by the data query through the OLAP will be fused with parameters.

14. The data query system based on an indicator query platform according to any one of claims 8-13, characterized in that, The indicator query platform mentioned is the Pandora Indicator Platform.

15. A computer device, characterized in that, The computer device includes at least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor. When the computer program is executed by the at least one processor, it can implement the data query method based on the indicator query platform as described in any one of claims 1-7.

16. A non-volatile computer-readable storage medium, characterized in that, The non-volatile computer-readable storage medium stores a computer program that, when executed by at least one processor, can implement the data query method based on the index query platform as described in any one of claims 1-7.

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