Data search method and system based on Dores and medium

Abstract

The invention relates to a Dores-based data search method and system and a medium, and the method comprises the steps: searching static attribute data of a preset entity in a Dores database, and obtaining an entity ID meeting a preset condition to generate a first temporary table; based on the event time when the preset entity is in the active state, searching the dynamic trajectory data of the preset entity to generate a second temporary table; and performing Inner join association on the first temporary table and the second temporary table to obtain target data which meets a preset condition and is active in a specified time period. Through the method and the device, data search based on Dores is realized, required static fields such as entity IDs can be searched from the static attribute data of the entities, corresponding dynamic fields can be screened from the dynamic trajectory data associated with the entities, and the data meeting the requirements are matched and associated and then are totally returned, so that the data search efficiency is improved, and the data search efficiency is improved. The problem that an existing database retrieval scheme is poor in retrieval effect is solved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a Doris-based data search method, system and medium. Background Art

[0002] As a high-performance, real-time analytical database based on the current MPP architecture, Doris has efficient query performance and can return query search results under massive data in sub-second response time, which can realize the search of massive data. In the past, most of the data searches were implemented based on the Elasticsearch search engine.

[0003] Elasticsearch can only search for a specific article or field, and directly return a specific number of search results. The response time is slow, and it is impossible to bind the search results to time filtering conditions. It is difficult to search for a certain entity to see if the result match appears in the trajectory table within a certain time period.

[0004] Currently, the existing database retrieval schemes in the relevant technology have the problem of poor retrieval effect, and no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a Doris-based data search method, system and medium to at least solve the problem of poor retrieval effect of existing database retrieval solutions in the related art.

[0006] In a first aspect, an embodiment of the present application provides a data search method based on Doris, the method comprising:

[0007] Searching for static attribute data of preset entities in the Doris database to obtain entity IDs that meet preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes, and satellites;

[0008] Based on the event time when the preset entity is in an active state, searching the dynamic trajectory data of the preset entity in the Doris database to generate a second temporary table;

[0009] An Inner join is performed on the first temporary table and the second temporary table to obtain target data that meets the preset condition and has been active within a specified time period.

[0010] In some embodiments, before searching the data of a preset entity in the Doris database, the method includes:

[0011] Perform field concatenation on the static attribute data of the preset entity to obtain entity field data and;

[0012] Fully aggregating the dynamic trajectory data of the preset entity to obtain first fully aggregated data and second fully aggregated data;

[0013] The static attribute data, the dynamic trajectory data, the entity field data, the first full aggregate data and the second full aggregate data are stored in a Doris database.

[0014] In some embodiments, performing full aggregation on the dynamic trajectory data of the preset entity to obtain first full aggregate data includes:

[0015] The dynamic trajectory data generated by the preset entity every day is fully aggregated every hour to obtain first fully aggregated data, wherein the first fully aggregated data includes the last dynamic trajectory data of each preset entity from 0:00 on the day to the current aggregation time point.

[0016] In some embodiments, performing full aggregation on the dynamic trajectory data of the preset entity to obtain the second full aggregate data includes:

[0017] The dynamic trajectory data generated by the preset entity every year is fully aggregated every day to obtain second fully aggregated data, wherein the second fully aggregated data includes the last dynamic trajectory data of each preset entity from the preset year time point to the current aggregation time point.

[0018] In some embodiments, after searching the dynamic trajectory data of the preset entity in the Doris database based on the event time when the preset entity is in an active state to obtain the second temporary table, the method includes:

[0019] Based on the event time when the preset entity is in an active state, searching the first full aggregated data of the preset entity in the Doris database to generate a third temporary table;

[0020] Based on the event time when the preset entity is in an active state, the second full amount of aggregated data of the preset entity in the Doris database is searched to generate a fourth temporary table.

[0021] In some embodiments, performing an Inner join on the first temporary table and the second temporary table to obtain target data that meets the preset condition and has been active within a specified time period includes:

[0022] Performing a Full Outer Join on the second temporary table, the third temporary table, and the fourth temporary table to generate a fifth temporary table;

[0023] An Inner join is performed on the first temporary table and the fifth temporary table to obtain target data that meets the preset conditions and has been active within a specified time period.

[0024] In some embodiments, field concatenation is performed on the static attribute data of the preset entity to obtain entity field data including:

[0025] Field concatenation is performed on the static attribute data of the preset entity to obtain entity field data, and a corresponding Doris inverted index is created for the entity field data.

[0026] In some embodiments, searching static attribute data of preset entities in the Doris database to obtain entity IDs that meet preset conditions to generate a first temporary table includes:

[0027] Through the Doris inverted index function, the static attribute data of the preset entities in the Doris database are searched to obtain the entity ID that meets the preset conditions to generate the first temporary table.

[0028] In a second aspect, an embodiment of the present application provides a Doris-based data search system, the system being used to execute the method described in any one of the first aspects above, the system comprising a static data retrieval module, a dynamic data retrieval module and a matching association module;

[0029] The static data retrieval module is used to search for static attribute data of preset entities in the Doris database to obtain entity IDs that meet preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes, and satellites;

[0030] The dynamic data retrieval module is used to search the dynamic trajectory data of the preset entity in the Doris database according to the event time when the preset entity is in an active state to generate a second temporary table;

[0031] The matching association module is used to perform an Inner join association on the first temporary table and the second temporary table to obtain target data that meets the preset conditions and has been active within a specified time period.

[0032] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect above.

[0033] Compared with the related art, the embodiment of the present application provides a Doris-based data search method, system and medium, wherein the method searches the static attribute data of the preset entities in the Doris database to obtain the entity ID that meets the preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes and satellites; based on the event time when the preset entities are active, the dynamic trajectory data of the preset entities in the Doris database are searched to generate a second temporary table; the first temporary table and the second temporary table are inner joined to obtain the target data that meets the preset conditions and has been active within the specified time period, thereby realizing the Doris-based data search, which can not only search for the required static fields such as entity ID from the static attribute data of entities such as ships and airplanes, but also filter out the corresponding dynamic fields such as longitude and latitude from the dynamic trajectory data associated with the entity, match and associate the data that meets the requirements and return them in full, thereby solving the problem of poor retrieval effect in the existing database retrieval scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0035] Figure 1 is a flowchart of the steps of the Doris-based data search method according to an embodiment of the present application;

[0036] Figure 2 is a structural block diagram of a Doris-based data search system according to an embodiment of the present application;

[0037] Figure 3 It is a schematic diagram of the internal structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0039] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0040] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0041] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0042] The present application embodiment provides a data search method based on Doris. Figure 1 is a flowchart of the steps of the data search method based on Doris according to an embodiment of the present application, such as Figure 1As shown, the method comprises the following steps:

[0043] Step S102, searching for static attribute data of preset entities in the Doris database, obtaining entity IDs that meet preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes, and satellites;

[0044] Specifically, step S102 searches static attribute data of preset entities in the Doris database through the Doris inverted index function to obtain entity IDs that meet preset conditions to generate a first temporary table.

[0045] It should be noted that when performing data search queries, first perform a data search on the static attribute data (entity table) of the preset entity. You can use any Doris inverted index function (such as match_all, match_any) to perform the required matching search operation to search for the entity ID that meets the preset conditions to form the first temporary table tmp01.

[0046] Before step S102, the method includes step S101, and step S101 specifically includes the following steps:

[0047] Step S1011, performing field concatenation on the static attribute data of the preset entity to obtain the entity field data and;

[0048] Specifically, step S1011 performs field concatenation on the static attribute data of the preset entity to obtain entity field data, and creates a corresponding Doris inverted index for the entity field data.

[0049] It should be noted that the fields to be searched of the static attribute data (entity table) of the preset entity are concatenated into a field search_key, and a Doris inverted index is created for the field, and unicode is selected as the encoding format.

[0050] Step S1012, performing full aggregation on the dynamic trajectory data of the preset entity to obtain first full aggregation data and second full aggregation data;

[0051] Step S1012 specifically:

[0052] ① The dynamic trajectory data generated by the preset entity every day is fully aggregated every hour to obtain the first full aggregated data, wherein the first full aggregated data includes the last dynamic trajectory data of each preset entity from 0:00 on the day to the current aggregation time point.

[0053] It should be noted that the dynamic trajectory data (trajectory table) of the preset entity is fully aggregated by hour on the day, and aggregated once every hour to obtain the first full aggregate data B1. B1 retains the last dynamic trajectory data of each preset entity from 0:00 on the day to the current aggregation time point, and preferably retains the maximum event time of the preset entity as of the current aggregation time point and the aggregation table ID (including the entity ID and the current aggregation time point merge_time).

[0054] ② Perform full daily aggregation on the dynamic trajectory data generated by the preset entity each year to obtain the second full aggregated data, wherein the second full aggregated data includes the last dynamic trajectory data of each preset entity from the preset year time point to the current aggregation time point.

[0055] It should be noted that the dynamic trajectory data (trajectory table) of the preset entity is fully aggregated on a daily basis to obtain the first full aggregate data B2, which retains the last dynamic trajectory data of each preset entity from the preset year time point (such as 1970-1-1 00:00:00) to the current aggregation time point, and preferably retains the maximum event time of the preset entity as of the current aggregation time point and the aggregation table ID (including the entity ID and the current aggregation time point merge_time).

[0056] Step S1013, storing the static attribute data, dynamic trajectory data, entity field data, the first full aggregate data and the second full aggregate data in the Doris database.

[0057] It should be noted that the static attribute data (entity table) and dynamic track data (track table) of the preset entity are stored in the Doris database. In the subsequent data search, the static attribute data (entity table) is searched and it is determined whether these preset entities have been active within the specified startTime-endTime time range. The active data is returned. Furthermore, the entity field data, the first full aggregate data, and the second full aggregate data of the preset entity are also stored in the Doris database, which can improve the accuracy of subsequent data searches.

[0058] Step S104, based on the event time when the preset entity is in an active state, searching the dynamic trajectory data of the preset entity in the Doris database to generate a second temporary table;

[0059] Specifically, step S104 filters the event time field of the dynamic trajectory data (trajectory table), uses doris data retrieval functions (such as hours_sub and date_trunc functions) to operate on endTime, and finally filters out the dynamic trajectory data whose event time is greater than startTime and between hours_sub(date_trunc(endTime,'hour'),1), groups the filtered dynamic trajectory data by entity ID, and uses may_by function to generate the second temporary table tmp02.

[0060] After step S104, the method includes step S105, which specifically includes the following steps:

[0061] Step S1051, based on the event time when the preset entity is in an active state, searching the first full aggregated data of the preset entity in the Doris database to generate a third temporary table;

[0062] Specifically, step S1051 performs a screening operation on the first full aggregate data B1 of the preset entity, formats endTime into the time of the previous hour, and makes the aggregate time field merge_time of the first full aggregate data B1 greater than startTime and equal to hours_sub(date_trunc(endTime,'hour'),1), thereby forming a third temporary table tmp03.

[0063] Step S1052: Based on the event time when the preset entity is in an active state, the second full aggregate data of the preset entity in the Doris database is searched to generate a fourth temporary table.

[0064] Specifically, step S1052 performs a screening operation on the second full aggregate data B2 of the preset entity, formats endTime as 0:00 of the day, and makes the aggregate time field merge_time of the second full aggregate data B2 greater than startTime and equal to date_trunc(endTime,'day'), thereby forming a fourth temporary table tmp04.

[0065] Step S106: perform an Inner join on the first temporary table and the second temporary table to obtain target data that meets preset conditions and has been active within a specified time period.

[0066] Step S106 specifically includes the following steps:

[0067] Step S1061, performing a Full Outer Join on the second temporary table, the third temporary table and the fourth temporary table to generate a fifth temporary table;

[0068] It should be noted that in database query language, Full outer join is a type of join that returns all matching rows in two tables. If no match is found in one of the tables, the columns in the other table are filled with NULL. In other words, the Full outer join result set contains the results of LEFT JOIN and RIGHT JOIN. For the Doris database, Doris supports Full outer join operations, allowing users to merge all records in two tables and return results even if there are no matching keys.

[0069] Step S1062: perform an Inner join on the first temporary table and the fifth temporary table to obtain target data that meets preset conditions and has been active within a specified time period.

[0070] It should be noted that in the database query language, Inner join is a type of join that returns a combination of matching rows in two tables. Only when the key values ​​in the two tables correspond will they appear in the final result set. In other words, Inner join will only select those records that exist in both joined tables. For the Doris database, Inner join is used to extract data from two or more tables. Records are returned only when the specified join condition is true, which usually involves one or more key fields shared between the two tables.

[0071] Through the above steps in the embodiment of the present application, Doris-based data search is realized, which can not only search for the required static fields such as entity ID from the static attribute data of entities such as ships and airplanes, but also filter out the corresponding dynamic fields such as longitude and latitude from the dynamic trajectory data associated with the entity, match and associate the data that meets the requirements and return them in full, solving the problem of poor retrieval effect in existing database retrieval schemes.

[0072] Compared with the existing massive data search method, which can only realize the search of entity tables and return results, it is impossible to associate the entity ID of the search entity table with the track table of hundreds of billions of levels to find out whether the entity has appeared in the track of the entity return in any time period of the track table. The Doris-based data search method proposed in this embodiment can support single-field search and various AND, OR, and NOT searches of multiple fields. This new massive data search method will perform associated filtering searches from the time dimension, space dimension, and conditional dimension, enriching the search function and making the search function no longer single. It can improve the accuracy of the search function and reduce the complexity of various operations.

[0073] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0074] The present application embodiment provides a data search system based on Doris. Figure 2 is a structural block diagram of a Doris-based data search system according to an embodiment of the present application, such as Figure 2 As shown, the system includes a static data retrieval module, a dynamic data retrieval module and a matching association module;

[0075] A static data retrieval module is used to search for static attribute data of preset entities in the Doris database, obtain entity IDs that meet preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes, and satellites;

[0076] A dynamic data retrieval module, used to search the dynamic trajectory data of the preset entity in the Doris database according to the event time when the preset entity is in an active state to generate a second temporary table;

[0077] The matching association module is used to perform an Inner join on the first temporary table and the second temporary table to obtain target data that meets preset conditions and has been active within a specified time period.

[0078] Through the static data retrieval module, dynamic data retrieval module and matching association module in the embodiments of the present application, Doris-based data search is implemented, which can not only search for the required static fields such as entity ID from the static attribute data of entities such as ships and airplanes, but also filter out the corresponding dynamic fields such as longitude and latitude from the dynamic trajectory data associated with the entity, match and associate the data that meets the requirements and return them in full, solving the problem of poor retrieval effect in existing database retrieval schemes.

[0079] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0080] This embodiment further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0081] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0082] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0083] In addition, in combination with the Doris-based data search method in the above embodiment, the present application embodiment can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any one of the Doris-based data search methods in the above embodiment is implemented.

[0084] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a data search method based on Doris is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0085] In one embodiment, Figure 3 is a schematic diagram of the internal structure of an electronic device according to an embodiment of the present application, such as Figure 3 As shown, an electronic device is provided, which may be a server, and its internal structure diagram may be as shown in Figure 3As shown. The electronic device includes a processor, a network interface, an internal memory and a non-volatile memory connected through an internal bus, wherein the non-volatile memory stores an operating system, a computer program and a database. The processor is used to provide computing and control capabilities, the network interface is used to communicate with an external terminal through a network connection, the internal memory is used to provide an environment for the operation of the operating system and the computer program, the computer program is executed by the processor to implement a Doris-based data search method, and the database is used to store data.

[0086] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0087] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0088] Those skilled in the art should understand that the technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0089] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A data search method based on Doris, characterized in that: The method comprises: Searching for static attribute data of preset entities in the Doris database to obtain entity IDs that meet preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes, and satellites; Based on the event time when the preset entity is in an active state, searching the dynamic trajectory data of the preset entity in the Doris database to generate a second temporary table; An Inner join is performed on the first temporary table and the second temporary table to obtain target data that meets the preset condition and has been active within a specified time period.

2. The method according to claim 1, characterized in that Before searching the data of the preset entity in the Doris database, the method includes: Perform field concatenation on the static attribute data of the preset entity to obtain entity field data and; Fully aggregating the dynamic trajectory data of the preset entity to obtain first fully aggregated data and second fully aggregated data; The static attribute data, the dynamic trajectory data, the entity field data, the first full aggregate data and the second full aggregate data are stored in a Doris database.

3. The method according to claim 2, characterized in that The dynamic trajectory data of the preset entity is fully aggregated to obtain first fully aggregated data including: The dynamic trajectory data generated by the preset entity every day is fully aggregated every hour to obtain first fully aggregated data, wherein the first fully aggregated data includes the last dynamic trajectory data of each preset entity from 0:00 on the day to the current aggregation time point.

4. The method according to claim 2, characterized in that: The dynamic trajectory data of the preset entity is fully aggregated to obtain the second fully aggregated data, including: The dynamic trajectory data generated by the preset entity every year is fully aggregated every day to obtain second fully aggregated data, wherein the second fully aggregated data includes the last dynamic trajectory data of each preset entity from the preset year time point to the current aggregation time point.

5. The method according to claim 2, characterized in that: After searching the dynamic trajectory data of the preset entity in the Doris database based on the event time when the preset entity is in an active state to obtain a second temporary table, the method includes: Based on the event time when the preset entity is in an active state, searching the first full aggregated data of the preset entity in the Doris database to generate a third temporary table; Based on the event time when the preset entity is in an active state, the second full amount of aggregated data of the preset entity in the Doris database is searched to generate a fourth temporary table.

6. The method according to claim 5, characterized in that Performing an Inner join on the first temporary table and the second temporary table to obtain target data that meets the preset conditions and has been active within a specified time period includes: Performing a Full Outer Join on the second temporary table, the third temporary table, and the fourth temporary table to generate a fifth temporary table; An Inner join is performed on the first temporary table and the fifth temporary table to obtain target data that meets the preset conditions and has been active within a specified time period.

7. The method according to claim 2, characterized in that The static attribute data of the preset entity is subjected to field concatenation to obtain entity field data including: Field concatenation is performed on the static attribute data of the preset entity to obtain entity field data, and a corresponding Doris inverted index is created for the entity field data.

8. The method according to claim 7, characterized in that Searching the static attribute data of the preset entity in the Doris database to obtain the entity ID that meets the preset conditions to generate the first temporary table includes: Through the Doris inverted index function, the static attribute data of the preset entities in the Doris database are searched to obtain the entity ID that meets the preset conditions to generate the first temporary table.

9. A data search system based on Doris, characterized in that: The system is used to execute the method according to any one of claims 1 to 8, and the system comprises a static data retrieval module, a dynamic data retrieval module and a matching association module; The static data retrieval module is used to search for static attribute data of preset entities in the Doris database to obtain entity IDs that meet preset conditions to generate a first temporary table, wherein the preset entities include ships, airplanes, and satellites; The dynamic data retrieval module is used to search the dynamic trajectory data of the preset entity in the Doris database according to the event time when the preset entity is in an active state to generate a second temporary table; The matching association module is used to perform an Inner join association on the first temporary table and the second temporary table to obtain target data that meets the preset conditions and has been active within a specified time period.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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