WO2022257390A1

WO2022257390A1 - Data processing method, server, and storage medium

Info

Publication number: WO2022257390A1
Application number: PCT/CN2021/136011
Authority: WO
Inventors: 白乐; 尹强; 黄山; 杨峙岳; 刘有; 杨永坤; 华德义; 王和平; 徐嘉杨; 饶进阳; 邸帅; 卢道和
Original assignee: 深圳前海微众银行股份有限公司
Priority date: 2021-06-11
Filing date: 2021-12-07
Publication date: 2022-12-15
Also published as: CN113326264A

Abstract

Provided in the embodiments of the present application are a data processing method, a server, and a storage medium. The data processing method comprises: a server receiving a data storage request, wherein the data storage request carries at least one type of identifier and configuration information; on the basis of the at least one type of identifier, constructing a first label; allocating a first index value to the first label; and storing, in a first data table and in an associated manner, the first label and the first index value, and storing, in a second data table and in an associated manner, the first index value and the configuration information carried in the data storage request, wherein the configuration information is used for configuring a big data engine.

Description

Data processing method, server and storage medium

Cross References to Related Applications

This application is based on a Chinese patent application with application number 202110653633.2 and a filing date of June 11, 2021, and claims the priority of the above-mentioned Chinese patent application. The entire content of the above-mentioned Chinese patent application is hereby incorporated by reference into this application.

technical field

The present application relates to the field of computer technology, and in particular to a data processing method, server and storage medium.

Background technique

With the development of computer technology, more and more technologies (for example, big data, etc.) are applied in the financial field, and the traditional financial industry is gradually transforming into financial technology. It also puts forward higher requirements for technology. In the field of financial technology, there are different levels of configuration information in the multi-level configuration of big data engines. In related technologies, at least two association tables are used to associate configuration items corresponding to all levels with corresponding configuration parameters. However, there is a large amount of duplicate data between at least two associated tables, for example, configuration items and/or configuration parameters, resulting in waste of memory.

Contents of the invention

In order to solve related technical problems, embodiments of the present application provide a data processing method, a server, and a storage medium.

The embodiment of the present application provides a data processing method, including:

Receive a data storage request; the data storage request carries at least one type of identification and configuration information;

Constructing a first tag based on the at least one type of identifier;

assigning a first index value to the first tag;

storing the first tag and the first index value in a first data table associatively, and storing the first index value and the configuration information carried in the data storage request in a second data table in association; The above configuration information is used to configure the big data engine.

The embodiment of the present application also provides a server, including:

A receiving unit, configured to receive a data storage request; the data storage request carries at least one type of identification and configuration information;

a construction unit configured to construct a first tag based on the at least one type of identifier;

an allocation unit configured to allocate a first index value to the first tag;

The storage unit is configured to associate store the first tag and the first index value in a first data table, and associate store the first index value and the configuration information carried in the data storage request in a second table. Two data tables; the configuration information is used to configure the big data engine.

An embodiment of the present application also provides a server, including: a processor and a memory configured to store a computer program that can run on the processor, wherein the processor is configured to execute the above data processing when running the computer program method steps.

The embodiment of the present application also provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above data processing method are realized.

In the embodiment of the present application, the first index value is assigned to the first tag carried in the received data storage request, the first tag and the first index value are associated and stored in the first data table, and the first index value and the data The configuration information carried in the storage request is associated and stored in the second data table. Therefore, the configuration information of the big data engine is stored by using a first data table (that is, an association table) and a second data table, without setting up multiple association tables, which can reduce the memory resources occupied by the association table. There is no repeated associated data in the table. Compared with the configuration information method stored in the related art, there is only one associated table in this application, and there are no repeatedly associated configuration items and/or configuration parameters in the associated table, which can avoid A large amount of repeated associated data wastes system resources; the first data table and the second data table are associated through index values, which can reduce the complexity of processing the configuration information of the big data engine and improve processing efficiency.

Description of drawings

FIG. 1 is a schematic diagram of the implementation flow of the data processing method provided by the embodiment of the present application;

FIG. 2 is a schematic diagram of the implementation flow of querying configuration information in the data processing method provided by the embodiment of the present application;

FIG. 3 is a schematic diagram of the implementation flow of querying configuration information in the data processing method provided by the application embodiment of the present application;

FIG. 4 is a schematic structural diagram of a server provided by an embodiment of the present application;

FIG. 5 is a schematic diagram of a hardware composition structure of a server provided by an embodiment of the present application.

Detailed ways

In the multi-level configuration of the big data engine, there are different levels of configuration information. In related technologies, a configuration table is used to store the configuration items and configuration parameters corresponding to the configuration items, and at least two association tables are used to store the configuration information corresponding to all levels. Configuration items are associated with corresponding configuration parameters. Associate the configuration items corresponding to all levels with the corresponding configuration parameters. However, the number of association tables increases with the increase in configuration levels. For example, for a three-tier configuration structure, at least two association tables need to be set; for a five-tier configuration structure, at least 4 association tables need to be set; for a 10-layer configuration structure, at least 9 association tables need to be set. When there are many configuration levels, the following problems are caused:

1. Occupies a lot of system resources: too many association relationships in the association table occupy a large storage space, and a large amount of repeated data leads to waste of resources;

2. Complicated management: Too many associations lead to cumbersome operations when storing, updating, and querying the configuration information of the big data engine;

3. Poor expandability: When increasing levels or expanding the number of configuration items at a certain level, new association relationships need to be constructed in all association tables, and dynamic expansion cannot be achieved.

For example, in the case of a three-level configuration of "user level-engine level-application level" for a big data engine, it is necessary to save user-level configuration information, engine-level configuration information, and application-level configuration information. The information includes at least user identification, engine information, configuration items and corresponding configuration parameters, and may also include application identification; engine-level configuration information includes at least engine information, configuration items and corresponding configuration parameters; application-level configuration information includes at least application identification , engine information, configuration items and corresponding configuration parameters.

In related technologies, it is necessary to configure a configuration table to store engine-level configuration information, and to configure at least two association tables, one of which is used to store correspondence between user IDs, engine information, configuration items, and configuration parameters. Another association table is used to store the correspondence between engine information, application identifiers, configuration items, and configuration parameters. Therefore, there may be a large number of repeated configuration items and/or configuration parameters in the same association table or between different association tables.

In order to solve the above technical problems, in the embodiment of the present application, a data storage request is received; the data storage request carries the first label and configuration information; the first label is assigned a first index value; the first The tag and the first index value are associated and stored in the first data table, and the first index value and the configuration information included in the data storage request are associated and stored in the second data table; the configuration information is used for Configure the big data engine. Therefore, the configuration information of the big data engine is stored by using a first data table (that is, an association table) and a second data table, without setting up multiple association tables, which can reduce the memory resources occupied by the association table. There is no repeated associated data in the table, which can avoid a large amount of repeated associated data from wasting system resources; the first data table and the second data table are associated through index values, which can reduce the complexity of processing the configuration information of the big data engine and improve the processing efficiency. efficiency.

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

FIG. 1 is a schematic diagram of the implementation flow of the data processing method provided by the embodiment of the present application, wherein the execution body of the flow is a server, such as a server corresponding to a big data platform. As shown in Figure 1, the data processing method includes:

Step 101: Receive a data storage request; the data storage request carries at least one type of identification and configuration information; wherein the configuration information is used to configure the big data engine.

The server receives the data storage request sent by the terminal; the data storage request is used to request storage of configuration information. The data storage request carries at least one type of identification and configuration information; the configuration information is used to configure the big data engine when calling the big data engine to perform data processing tasks. Wherein, the data processing request may be sent when the terminal initializes the big data engine or the first application, and may also be sent when the user personalizes the big data engine. The first application is an application that needs to call a big data engine to perform data processing tasks.

Exemplarily, in the scenario where the user initializes the big data engine through the set interactive interface, the trigger terminal sends a first data storage request to the server, and the configuration information carried in the first data storage request is the engine corresponding to the big data engine The configuration information of the stage, at least one type of identifier carried in the first data storage request is used to construct the first label of the engine stage. Engine-level configuration information represents the configuration information adopted by the big data engine when no user or application is specified. In actual application, the engine-level configuration information is the default configuration information.

For example, in the scenario where the user initializes the first application through a setting operation, the terminal installed with the first application sends a second data storage request to the server, and the configuration information carried in the second data storage request is the big data engine Corresponding application-level configuration information. At least one type of identifier carried in the second data storage request is used to construct the first tag at the application level. The application-level configuration information represents the configuration information used by the corresponding application when calling the big data engine to perform data processing tasks when no user is specified. In actual application, the application-level configuration information is also the default configuration information.

Exemplarily, in the scenario where the user performs personalized configuration on the big data engine through the set interactive interface, the terminal is triggered to send a third data storage request to the server, and the configuration information carried in the third data storage request is corresponding to the big data engine. The user-level configuration information, at least one type of identification carried in the third data storage request is used to construct the user-level first label. User-level configuration information refers to the user's personalized configuration information for the big data engine, which represents the configuration information used when the user triggers the application to call the big data engine to perform data processing tasks in the process of using an application. It should be noted that the categories of the identifiers included in the first tag at the engine level, the first tag at the application level, and the first tag at the user level are at least partially different. In some embodiments, the at least one type of identifier includes at least one of the following:

User ID;

application identification;

Category identification of the big data engine;

The version identifier of the big data engine.

Here, the user identifier represents the user identity, and the application identifier represents the application type. At least one class of identifiers in the first labels of different levels is different.

In this embodiment, the levels to which the first tags belong are distinguished by different types of identifiers, so that the configuration information corresponding to the first tags of different levels can be conveniently stored.

In actual application, the first tag at the engine level includes the category identifier of the big data engine and the version identifier of the big data engine. The first tag at the application level includes an application identifier, a category identifier of the big data engine, and a version identifier of the big data engine. The first tag at the user level includes a user ID, an application ID, a category ID of the big data engine, and a version ID of the big data engine.

In practical applications, the configuration information includes configuration items and configuration parameters corresponding to the configuration items. The configuration parameters corresponding to at least one configuration item in the configuration information corresponding to the first tags of different levels are different. Configuration items include the maximum usage threshold of memory, the maximum number of concurrency, and so on.

Step 102: Construct a first label based on the at least one type of identifier.

Considering that at the stage of storing configuration information, the first label and configuration information have a one-to-one correspondence, and the first label can only be a label of one of the setting levels, for example, the first label is an engine-level label, an application-level tags or user-level tags, therefore, the server determines the corresponding setting tag construction method based on the type and quantity of the obtained identifiers, and uses the determined setting tag construction method to construct the corresponding first tag. in,

When the server obtains a category identifier, the server determines the category identifier as the first label.

When the server obtains at least two types of identifiers, the server arranges the identifiers of different types according to a set sequence to obtain the corresponding second label.

In the case where at least two types of identifiers are carried in the data storage request, in order to unify the format of the first label so as to facilitate the management of the first label and corresponding configuration information, in some embodiments, based on the at least one type of identification, Constructing the first label, including:

Based on the setting correspondence between the at least two types of setting identifiers and the setting tag construction method, determine the setting tag construction method corresponding to the at least two types of identifiers carried in the data storage request;

According to the determined set label construction method, the first label corresponding to the at least two types of identifiers is constructed.

Here, the setting label construction method represents the arrangement format of different categories of labels, setting connectors and setting separators. The setting connectors are used to connect different types of identifiers, and the setting separators are used to separate The two identities for the connection. The database stores at least two types of setting correspondences between setting identifiers and setting label construction methods; the database can be a local database or a non-local database, for example, a cloud database.

The electronic device carries at least two types of identifiers in the data storage request. In this case, based on the setting correspondence between the at least two types of set identifier categories stored in the database and the set label construction method, determine the obtained at least two types of identifiers. The construction method of the setting label corresponding to the identification; according to the arrangement format represented by the determined setting label construction method, arrange the obtained at least two types of identifications to obtain at least two types of identifications after sorting; use the determined setting label The setting connector represented by the construction method connects every two types of identifiers in at least two types of identifiers after sorting, and uses the setting separator to separate the two identifiers connected by the setting connector, so as to obtain the first label.

It should be noted that, in some embodiments, at least two types of identifiers may also be arranged according to a set sort order, and adjacent identifiers are connected by a set connector to obtain the first label. Of course, the first label may also be set by the user, that is, the data storage request received by the server carries the first label and configuration information.

Step 103: Assign a first index value to the first tag.

When receiving the data storage request, the server assigns a corresponding first index value to the first tag carried in the received data storage request. Wherein, different first labels correspond to different first index values. In actual application, the first index values assigned by the server to different first tags form a set of continuous numbers.

Step 104: Store the first tag and the first index value in a first data table, and store the first index value and the configuration information carried in the data storage request in a second data table Table; the configuration information is used to configure the big data engine.

Here, the server stores the first data table and the second data table configured according to the setting table structure. The first data table is used to store tags and index values, the second data table is used to store index values and configuration information corresponding to tags, and the first data table and the second data table are associated through the index values of tags.

When the server assigns the first index value to the first tag, it associates and stores the first tag and the first index value assigned to the first tag in the first data table, and the first tag assigned to the first tag The index value and the configuration information carried in the data storage request are associated and stored in the second data table.

In actual application, the first data table includes at least a first setting field and a second setting field. The first setting field is used to write the index value of the label; the second setting field is used to write the specific content of the label, and the field name of the second field may be label_key_value. Of course, the first data table may also include a third setting field and a fourth setting field, the third setting field is used for writing the time when the first data table was created; the fourth setting field is used for writing and updating the first The time of the data table. The second data table includes a fifth setting field and a sixth setting field, the fifth setting field is used for writing the index value of the tag, and the sixth setting field is used for writing configuration information.

In practical applications, the format of the field value of the second field is (label_key, label_stringvalue). label_key indicates the labelKey corresponding to the label, that is, the key of the label; label_stringvalue indicates the StringValue corresponding to the label, that is, the key value of the label, which is used to identify the specific content of the label.

Exemplarily, the label_key of the first label may be Combine_UserCreator_EngineType. When user A configures big data engine A with version A under application A, the label_stringvalue of the first label corresponds to "userA-creatorA, engineA-A". userA represents the user ID, creatorA represents the application ID, engineA represents the category ID of the big data engine, and A represents the version ID of the big data engine.

In this embodiment, a data storage request is received; the data storage request carries the first tag and configuration information; the first tag is assigned a first index value; the first tag and the first index value are associated and stored in the first data table, And associating and storing the first index value and the configuration information included in the data storage request to the second data table; the configuration information is used to configure the big data engine. Therefore, the configuration information of the big data engine is stored through a first data table (that is, an association table) and a second data table (configuration table), without setting up multiple association tables, which can reduce the occupied space of the association table. Memory resources, there is no repeated associated data in the associated table, which can avoid a large amount of repeated associated data wasting system resources; the first data table and the second data table are associated through index values, which can reduce the complexity of processing the configuration information of the big data engine degree, improve processing efficiency.

Considering that in the application scenario of multi-level configuration of the big data engine, some levels of configuration information cannot be modified, such as the default configuration information, and some levels of configuration information are allowed to be modified, such as personalized configuration information. To better meet the needs of users to modify configuration information, in some embodiments, after storing the first label and the first index value in the first data table, and associating the first index value corresponding to the first label with the configuration information On the basis of storing to the second data table, the method further includes:

receiving an update request; the update request is used to request to update the first tag and/or the configuration information;

Based on the first index value, the first tag is updated in the first data table and/or the configuration information is updated in the second data table.

Here, when the user wants to update the configuration information of a certain level, he can modify the configuration information of the big data engine through the set interactive interface, and trigger the terminal to send an update request to the server to request to update the data in the first data table. First label and/or configuration information.

Exemplarily, in the scenario where the user modifies the personalized configuration of the big data engine through the set interactive interface, the terminal is triggered to send an update request to the server.

When the server receives the update request, based on the update request and the first index value in the first data table, update the first tag in the first data table, and/or update the configuration information in the second data table . The specific implementation process is as follows:

When the server receives the update request, it searches the first data table for a first tag that matches the first tag carried in the update request, and obtains a search result.

When the search result indicates that no matching first label is found, the first label carried in the update request is not stored in the first data table, and the update request is used to request to update the first label and the second label in the first data table. The configuration information in the data table, at this time, the server assigns the first index value to the first tag carried in the update request, and associates and stores the first tag carried in the update request and the first index value assigned to the first tag in the The first data table, so as to update the first label in the first data table.

In the case where the search result indicates that a matching first tag is found, the update request is used to request to update the configuration information in the second data table, and the server determines from the first data table the first tag corresponding to the first tag carried in the update request. index value, and look up the first index value matching the determined first index value from the second data table, and replace the configuration information corresponding to the matching first index value in the second data table with the one carried in the update request configuration information.

It should be noted that, when the user name of the user is changed, the update request is used to update the first label in the first data table.

Exemplarily, when the user name of the user is changed, the user triggers the update request sent by the terminal to carry the first tag before the change and the first tag after the change. When the server receives the update request, it searches the first data table for the first label that matches the first label before the change carried in the update request, and replaces the found first label with the one carried in the update request. The first label after the change.

For example, when the user's username is changed, and the user has obtained the first index value corresponding to the first label before the change, the user triggers the update request sent by the terminal to carry the first index value and the changed first tab. When the server receives the update request, it searches the first data table for the first index value that matches the first index value carried in the update request, and if a matching first index value is found, based on the found For the matched first index value, replace the first tag corresponding to the matched first index value in the first data table with the changed first tag carried in the update request.

In this embodiment, a first data table (that is, association table) and a second data table (configuration table) are used to store the configuration information of the big data engine, there is no repeated association, and when it is necessary to update the big data When configuring engine configuration information, the user only needs to update the first label in the first data table and/or the configuration information in the second data table, which can improve data update efficiency.

Considering that in the scenario where the user updates the first label in the first data table or the configuration information in the second data table, or in the scenario of invoking the big data engine to perform data processing tasks, it is necessary to query the configuration information of the big data engine , as shown in Figure 2, in some embodiments, the method also includes:

Step 201: Receive a query request for configuration information; the query request carries at least one type of identifier;

Step 202: Construct at least one second tag based on at least one type of identifier in the query request;

Step 203: Find out in the first data table the first index value corresponding to the tag matching each second tag in the at least one second tag;

Step 204: Obtain configuration information corresponding to each determined first index value from the second data table;

Step 205: Based on the obtained configuration information, output a query result about the query request.

Here, when the server receives the configuration information query request sent by the terminal, based on at least one type of identifier in the query request, the server constructs at least one second tag using a correspondingly set tag construction method. Wherein, the implementation process of constructing at least one second label by using the correspondingly set label construction method is as follows:

When the query request carries only one type of identifier, the server determines the type of identifier as the second label.

When the query request carries at least two types of identifiers, the server determines the corresponding identifiers from the database based on the acquired category of each identifier, and based on the first set corresponding relationship and the second set corresponding relationship stored in the database. The set label construction method, and using the set label construction method to construct at least one second label corresponding to the obtained at least two types of identifiers. Among them, the first setting correspondence represents the setting correspondence between labels and label categories at different setting levels; the second setting correspondence represents the setting correspondence between labels at different setting levels and the set label construction method. Determine the corresponding relationship. In practical applications, when the query request carries at least two types of identifiers, the server can construct second labels of different levels. For example, in the case where user-level, engine-level and application-level configurations are performed on the big data engine, the set label construction methods include methods for constructing user-level labels, methods for constructing engine-level labels, and methods for Method for constructing application-level tags; when the query request carries the category identifier of the big data engine and the version identifier of the big data engine, the server can construct a second engine-level tag based on the method used to construct the engine-level tag; when querying When the request carries the application identifier, the category identifier of the big data engine, and the version identifier of the big data engine, the server can construct the engine-level tag Two tags and the second tag at the application level; when the query request carries the user ID, application ID, category ID of the big data engine, and version ID of the big data engine, the server can construct the second tag at the user level, the engine The second tab at the level and the second tab at the application level.

Exemplarily, in the case where user-level, engine-level and application-level configurations are performed on the big data engine, since only user-level configuration information can be modified, in the application scenario where the user wants to update the user-level configuration information Next, the user can use the interactive interface for querying the configuration information of the big data engine in the terminal, input or enter the user name, application ID, category ID and version ID of the big data engine, and trigger the terminal to send a query request to the server. The query request Carry the user ID, application ID, category ID of the big data engine, and version ID of the big data engine. When the server receives the query request sent by the terminal, it can The category identification of the engine and the version identification of the big data engine use the correspondingly set label construction method to construct the second label of the user level, the second label of the engine level and the second label of the application level.

In the case of constructing the second label, the first index value corresponding to the label matching the second label is found in the first data table, and the first index value corresponding to each second label is obtained; from the second data table The configuration information corresponding to each first index value is acquired in , and the configuration information corresponding to each second label is obtained.

When the number of the constructed second tags is one, the configuration information corresponding to the second tag is determined as the query result of the query request, and the configuration information corresponding to the first tag is output.

When the number of constructed second labels is at least two, based on the set priority corresponding to each second label and the configuration information corresponding to each second label, determine the query result about the query request, and Output the query result.

In actual application, the configuration information includes configuration items and configuration parameters corresponding to the configuration items. In the case of constructing two second labels of different levels, the server can use the configuration information corresponding to the second label with higher priority, and configure the configuration information corresponding to the same configuration item in the configuration information corresponding to the second label with lower priority Parameters are replaced, and the configuration information after replacement is output. In the case of constructing at least three second tags of different levels, according to the order of priority from high to low, the configuration information corresponding to the second tag with the highest priority is used to configure the configuration corresponding to the second tag with the second highest priority The information is replaced, and the processing result is obtained. Based on the processing result, the configuration information corresponding to the second label with the next priority is replaced, and so on, until the configuration information corresponding to the second label with the lowest priority is replaced. .

In practical application, outputting the query result about the query request refers to sending the query result to the terminal sending the query request. In the application scenario where the user needs to update the user-level configuration information, the terminal displays the query result after receiving the query result about the query request sent by the server, so as to modify the user-level configuration information based on the query result; In the scenario of manipulating an application and triggering the application to call the big data engine to perform data processing tasks, the terminal uses the configuration information in the query result to update the called big data engine after receiving the query result sent by the server. The engine is configured, and the corresponding data processing tasks are performed through the big data engine.

In this embodiment, the second label is constructed through the identifier carried in the query request of the configuration information, the first index value corresponding to the match with the constructed second label is found from the first data table, and then the The configuration information corresponding to the searched first index value is obtained from the second data table, so that the server can find the corresponding configuration information through the index value corresponding to the second label, and there is no need to query the configuration information through multiple association relationships. Reduce the time consumed for querying configuration information and improve the efficiency of querying configuration information.

Considering that the configuration items contained in the configuration information corresponding to tags at different levels are not exactly the same, in order to obtain configuration information that matches the usage habits or running requirements of the calling object of the big data engine, it is necessary to construct second label, so as to query configuration information corresponding to the second label at different levels from the second data table, wherein the calling object includes a user or an application. In some embodiments, in step 202, at least one second tag is constructed based on at least one type of identifier in the query request, including:

Constructing a third label based on the user identification and application identification in the query request, and constructing a fourth label based on the category identification and version identification of the big data engine in the query request;

combining the third tag and the fourth tag to obtain a second tag with a first priority;

Using the first setting character to replace the user ID and application ID in the second label of the first priority to obtain the second label of the second priority;

Using the second setting character to replace the user identification in the second label of the first priority to obtain the second label of the third priority; wherein,

The first priority is higher than the second priority; the second priority is higher than the third priority.

Here, the query request carries the user identifier, the application identifier, the category identifier of the big data engine, and the version identifier of the big data engine.

The server determines the arrangement sequence of the user identifiers and application identifiers carried in the query request according to the corresponding setting priorities of the user identifiers and application identifiers, arranges the user identifiers and application identifiers according to the determined arrangement order, and obtains the third tag .

The server determines the arrangement order of the category identifiers and version identifiers of the big data engines carried in the query request according to the set priorities corresponding to the category identifiers and version identifiers of the big data engines, and performs the sorting order of the big data engine according to the determined arrangement order. The category identifier and the version identifier are arranged to obtain a fourth label.

When the third label and the fourth label are determined, the third label and the fourth label are combined according to the set rules to obtain the second label with the first priority, that is, the second label at the user level. For example, when the third label is userA-creatorA and the fourth label is engineA-A, the second label with the first priority is "userA-creatorA, engineA-A".

In the case that the second label of the first priority is determined, the user identification and the application identification in the second label of the first priority are replaced by the first set character to obtain the second label of the second priority; and using The second set character replaces the user identification in the second label of the first priority to obtain the second label of the third priority. Both the first set character and the second set character represent a null value, and the first set character and the second set character may be the same or different. In actual application, both the first setting character and the second setting character are "*".

Exemplarily, in the case that the second label of the first priority is "userA-creatorA, engineA-A", the second label of the second priority is engineA-A, and the second label of the third priority is = <creatorA, engineA-A>.

In actual application, the format of the label is (label_key, label_stringvalue). It should be noted that the labels in each embodiment of the present application involve four types of entities: generic label (GenericLabel), user-application label (UserCreatorLabel), engine category label (EngineTypeLabel), combination label (CombineLabel); UserCreatorLabel, EngineTypeLabel Both GenericLabel and CombineLabel inherit the properties of GenericLabel. in,

The fields and methods contained in GenericLabel, UserCreatorLabel, EngineTypeLabel and CombineLabel are explained as follows:

(1) The fields and methods contained in GenericLabel are explained as follows:

The first field labelKey: a fixed string constant used to identify the label type to which the value belongs;

The second field labelValue: the label corresponds to the stored map data, the type is Map<String, String>, the key-value pair information corresponding to the label is stored in the map, and the corresponding value needs to be initialized when the entity class is constructed;

The third field value_separator: the value connection separator, used to connect the value value in the map;

The fourth field stringValue: used to store the result of connecting value in the map through value_separator, which is also the core value stored in the database.

getStringValue(): The core method of constructing StringValue. StringValue is connected and constructed according to value_separator and labelValue. The construction sequence is parsed based on the custom annotation ValueSerialNum in the set method of labelKey in the inherited class. Parsing process: Obtain all methods of the inherited class through class.getDeclaredMethods --> filter the method through method.isAnnotationPresent(ValueSerialNum.class) of each method to get the annotated method ---> obtain the annotated method The corresponding value in the annotation ValueSerialNum --> sort the keys (keys) in the labelValue according to the priority identified by the value of the ValueSerialNum to determine the order in which the keys of the labelValue are arranged. The advantage of this design is that you only need to design the sorting method at the top level, and set the sorting order of the keys by introducing annotations in the inherited class, which greatly reduces the code implementation content of the inherited class, while the traditional method needs to be set through the inherited class Additional variables are used to customize the sort order of the keys, and then reimplement the getStringValue method for sorting.

setStringValue(): The core method of constructing StringValue, the processing logic is similar to that of getStringValue, and will not be described here.

(2) The fields and methods contained in UserCreatorLabel are explained as follows:

labelKey: Rewrite field, fixed string constant "userCreator", mainly used to identify the Label type to which the labelValue belongs;

labelValue: rewrite field, the label corresponds to the stored map data, the type is Map<String, String>, the key-value pair stored in the map contains two types, namely <'user', value>, <'creator ', value>, the corresponding value needs to be initialized and set when the entity class is constructed;

setUser(): The method of setting the label user, annotated by ValueSerialNum(0), representing the highest priority, used for label key priority analysis in GenericLabel;

setCreator(): The method for setting the application to which the label belongs, annotated by ValueSerialNum(1), which represents the sub-priority, and is used for label key priority analysis in GenericLabel.

default_user: represents the value of user when no user is specified.

(3)EngineTypeLabel contains main fields and methods explained as follows:

labelKey: Rewrite field, fixed string constant "engineType", mainly used to identify the Label type to which the labelValue belongs;

labelValue: rewrite field, the label corresponds to the stored map data, the type is Map<String, String>, the key-value pair stored in the map contains two types, namely <'engineType', value>, <'version ', value>, the corresponding value needs to be initialized and set when the entity class is constructed;

setEngine: The method of setting the tag engine, annotated by ValueSerialNum(0), representing the highest priority;

setType: The method to set the version of the tag engine, annotated by ValueSerialNum(1), representing the secondary priority.

(4) CombineLabel is used to combine and convert UserCreatorLabel and EngineTypeLabel. It is a real label for storage. The core classes and methods are as follows:

labelKey: Combined LabelKey, the content must be the result of sorting the key labelKey of the combined label after certain rules.

labelValue: map data, used to store the label of the record being combined;

COMBINED_LABEL_KEY_PREFIX: labelKey prefix, used to identify the label type

LABEL_KEY_JOIN_SYMBOL: labelKey delimiter, used to construct and parse the labelKey of CombineLabel;

LABEL_VALUE_JOIN_SYMBOL: labelValue delimiter, used to construct and parse the labelValue of CombineLabel;

getStringValue(): The core method of constructing StringValue; the steps of this method are as follows: parse labelKey priority and sort --> sort labelValue in the same order --> combine labelValue according to the value of LABEL_VALUE_JOIN_SYMBOL --> return StringValue.

The implementation process of constructing the second label of different levels by the server based on the user identification, application identification, category identification and version identification of the big data engine carried in the query request will be described in detail below with specific examples:

In the scenario of three-level configuration of the big data engine, the priority from high to low is: user level, engine level and application level.

In the case where userA, application A, engine type A and version A are carried in the query request, the implementation process for the server to construct the second label is as follows:

The server obtains the setting parameters, and the setting parameters include the value connection separator (value_separator), the prefix of the combined label, the first separator corresponding to the labelKey of the combined label, the second separator corresponding to the labelValue of the combined label, and the setting character. In actual application, value_separator="-"; the prefix of the combined label COMBINED_LABEL_KEY_PREFIX="Combined"; the first separator corresponding to the labelKey of the combined label LABEL_KEY_JOIN_SYMBOL="_"; the second separator corresponding to the labelValue of the combined label LABEL_VALUE_JOIN_SYMBOL=", "; Set the character as "*", that is, default_user="*".

The server constructs a UserCreatorLabel based on the user ID, application ID, and value in the setting parameters in the query request, and connects the delimiter; based on the category ID, version ID of the big data engine in the query request, and the value in the setting parameters, connect the delimiter , to construct an EngineTypeLabel; based on the first delimiter and the second delimiter in the setting parameters, combine the constructed UserCreatorLabel and the constructed EngineTypeLabel to obtain the second label with the first priority. in,

Based on the user ID and application ID in the query request, the server constructs the UserCreatorLabel as follows:

Create a new UserCreatorLabel object, call the setUser() method to set the value of 'user' to userA, and get the key-value pair <'user', userA>; call the setUser() method to set the value of 'creator' to creatorA, and get the key-value pair <' creator', creatorA>. That is to say, UserCreatorLabel includes two key-value pairs: <'user', userA> and <'creator', creatorA>.

The server calls the getStringValue method of UserCreatorLabel, connects the separator (value_separator) based on the value included in the setting parameter, and constructs the StringValue of UserCreatorLabel. Since the priority of 'user' is higher than that of 'creator', the StringValue of UserCreatorLabel is userA-creatorA when the value concatenation separator is "-".

That is to say, the labelKey of the constructed UserCreatorLabel is userCreator; the labelValue of the constructed UserCreatorLabel includes: <'user', userA> and <'creator', creatorA>; the StringValue of the constructed UserCreatorLabel is userA-creatorA.

The server constructs EngineTypeLabel based on the category identifier and version identifier of the big data engine in the query request:

The server creates a new EngineTypeLabel object, calls the setUser() method to set the value of 'engineType' to engineA, and obtains the key-value pair <'engineType', engineA>; calls the setUser() method to set the value of 'version' to A, and obtains the key-value pair < 'version', A>. That is to say, EngineTypeLabel includes two key-value pairs: <'engineType', engineA> and <'version', A>.

The server calls the getStringValue method of the EngineTypeLabel, and connects the separator (value_separator) based on the value included in the setting parameter to construct the StringValue of the EngineTypeLabel. Since the priority of 'engineType' is higher than that of 'version', the stringValue of EngineTypeLabel is engineA-A when the value concatenation delimiter is "-".

The server combines the constructed UserCreatorLabel with the constructed EngineTypeLabel to obtain the second label with the first priority. The implementation process is as follows:

In the case of the constructed UserCreatorLabel and EngineTypeLabel, the server creates a new CombineLabel object, obtains the labelKey of UserCreatorLabel from the constructed UserCreatorLabel, and obtains userCreator; obtains the labelKey of EngineTypeLabel from the constructed EngineTypeLabel, and obtains engineType; obtains it from the setting parameters The first delimiter corresponding to the labelKey of the combined label; based on the constructed labelKey of the UserCreatorLabel, the constructed LabelKey of the EngineTypeLabel and the first delimiter corresponding to the labelKey of the combined label, the labelKey of the second label with the first priority is constructed; labelKey of the second label of the first priority=Combined_UserCreator_EngineType. Wherein, in the process of constructing the combined label, the constructed UserCreatorLabel and EngineTypeLabel are used as incoming parameters of the combined label. That is to say, the server transfers the constructed UserCreatorLabel's labelKey and the constructed EngineTypeLabel's labelKey to the newly created CombineLabel object, and according to the priorities of UserCreatorLabel and EngineTypeLabel, connect the combinations respectively through the first delimiter corresponding to the labelKey of the combined label The label prefix, the labelKey of UserCreatorLabel and the labelKey of EngineTypeLabel get the labelKey of the second label with the first priority.

The server obtains the stringValue of UserCreatorLabel from the constructed UserCreatorLabel to obtain userA-creatorA; obtains the stringValue of EngineTypeLabel from the constructed EngineTypeLabel to obtain engineA-A, and according to the priority of UserCreatorLabel and EngineTypeLabel, combines the labelValue corresponding to the first The two delimiters separate the stringValue of UserCreatorLabel from the stringValue of EngineTypeLabel to obtain stringValue=<userA-creatorA, engineA-A> of the second label of the first priority.

In practical applications, the constructed labelKey of the first-priority second label is Combined_UserCreator_EngineType; the constructed labelValue of the first-priority second label includes: <user-creator, userA-creatorA> and <engineType-version ,engineA-A>; the constructed stringValue of the first-priority second label is <userA-creatorA,engineA-A>.

When the server determines the second tag with the first priority, it replaces both the user ID and the application ID obtained from the query request with the set character "*". Based on the replaced user ID and the replaced application ID, category ID and version ID of the big data engine to construct the second label with the second priority; replace the user ID obtained from the query request with the set ID "*", based on the replaced user ID, application The identifier, the category identifier and the version identifier of the big data engine construct the second label with the third priority. Wherein, the method of constructing the second tag of the second priority or the third priority is similar to the method of constructing the second tag of the first priority above, please refer to the relevant description above, and will not repeat it here.

In some embodiments, here, considering that the labelKey of the second label of the first priority, the second priority and the third priority is constant, and the StringValue of the combined label is determined by the StringValue in the UserCreatorLabel and the StringValue in the EngineTypeLabel Therefore, the server can keep the labelKey of the second label of the first priority unchanged, replace the user ID and application label in the StringValue of the second label of the first priority with the set character "*", and obtain the first For the second label of the second priority, replace the user identifier in the StringValue of the second label of the first priority with the set character "*" to obtain the third label of the second priority. For example, in the case of the labelKey of the second label of the first priority=Combined_UserCreator_EngineType, the StringValue of the second label of the first priority=<userA-creatorA, engineA-A>, the StringValue of the second label of the second priority =<*-*, engineA-A>, StringValue of the second label of the third priority=<*-creatorA, engineA-A>.

Considering that the configuration items contained in the configuration information corresponding to tags at different levels are not exactly the same, in order to obtain configuration information that matches the usage habits or running requirements of the calling object of the big data engine, in some embodiments, the Based on the acquired configuration information, output query results about the query request, including:

Based on the configuration items included in the configuration information corresponding to each second tag, and based on the priority corresponding to each second tag, determine the configuration item corresponding to each configuration item from the first configuration parameters included in the obtained configuration information. The second configuration parameter;

Output each configuration item and the corresponding second configuration parameter.

Here, in the case that all configuration items included in the configuration information corresponding to the second label are the same, the server determines the first configuration parameter corresponding to each configuration item in the configuration information corresponding to the second label of the first priority as Corresponding to the second configuration parameter corresponding to the configuration item, the configuration information corresponding to the second label of the first priority is output.

If the configuration items included in the configuration information corresponding to the second label of the first priority are not exactly the same as the configuration items included in the configuration information corresponding to the second label of the second priority, based on the first priority The configuration information corresponding to the second label replaces the configuration parameter of the corresponding configuration item in the configuration information corresponding to the second label of the second priority to obtain the first configuration information. Wherein, replacing the configuration information refers to replacing configuration parameters corresponding to the same configuration item.

If the configuration items included in the configuration information corresponding to the second label of the second priority are exactly the same as the configuration items included in the configuration information corresponding to the second label of the third priority, each of the first configuration information The first configuration parameter corresponding to the configuration item is determined as the second configuration parameter corresponding to the corresponding configuration item; and the first configuration information is output.

If the configuration items included in the configuration information corresponding to the second tag of the second priority are not exactly the same as the configuration items included in the configuration information corresponding to the second tag of the third priority, based on the first configuration information, the The configuration parameters corresponding to the corresponding configuration items in the configuration information corresponding to the second label of the three priorities are replaced to obtain the second configuration information, and output the second configuration information.

In actual application, the user-level configuration information includes the least number of configuration items. The configuration items included in the engine-level configuration information and the configuration items included in the application-level configuration information may be identical or partially identical.

Since the configuration information of the big data engine corresponding to different users and different applications is different, in this embodiment, based on the configuration items included in the configuration information corresponding to each second tag, and based on the priority corresponding to each second tag, Determine the second configuration parameter corresponding to each configuration item from the first configuration parameters included in the acquired configuration information; output each configuration item and the corresponding second configuration parameter, thus, output the big data engine Configuration information that matches the usage habits or running requirements of the calling object.

Fig. 3 shows a schematic diagram of the implementation flow of querying configuration information in the data processing method provided by the application embodiment of the present application. As shown in Fig. 3, the method for querying configuration information includes:

Step 301: Receive a query request for configuration information, the query request carries a user ID, an application ID, a category ID of a big data engine, and a version ID of a big data engine.

Step 302: Construct a user-application label based on the user identifier and the application identifier, and construct an engine category label based on the category identifier and the version identifier of the big data engine.

Here, the server constructs the UserCreatorLabel based on the user ID and application ID, and constructs the EngineTypeLabel based on the category ID and version ID of the big data engine. For the specific implementation process, please refer to the relevant description of the construction of the third label and the fourth label above, which will not be repeated here. .

Step 303: Combine the constructed user-application tags and engine category tags to obtain a combined tag.

Here, the server combines UserCreatorLabel and EngineTypeLabel to obtain a combined label. For specific implementation, please refer to the above description of combining the third label and the fourth label to obtain the second label with the first priority, which will not be repeated here.

Step 304: Find the first index value corresponding to the label matching the combined label in the first data table.

Wherein, step 304 is similar to step 203, please refer to the relevant description in step 203 for the specific implementation process, and will not repeat them here.

Step 305: Obtain configuration information corresponding to the determined first index value from the second data table.

Wherein, step 305 is similar to step 204, please refer to the relevant description in step 204 for the specific implementation process, and details are not repeated here.

Step 306: Determine whether the priority of the combined tag is the lowest priority.

The server judges whether the priority of the combined tag is the lowest priority, and obtains a judgment result. If the judging result indicates that the priority of the combined tag is not the lowest priority, execute step 307 , and if the judging result indicates that the priority of the combined tag is the lowest priority, execute step 308 .

Step 307: Use set characters to replace the user ID and application ID, or use set characters to replace the user ID.

It should be noted that when step 307 is executed for the first time, both the user identifier and the application identifier obtained from the query request are replaced with the setting character "*", and steps 302 to 306 are executed again.

If the judgment result obtained by executing step 306 again indicates that the priority of the combined label is not the lowest priority, when step 307 is executed again, the user ID obtained from the query request is replaced with the setting character "*", and the execution is executed again Step 302 to step 306.

It should be noted that, in this application embodiment, the big data engine is configured at three levels: user level, engine level, and application level, and the priorities are user level, engine level, and application level in descending order. The server executes steps 302 to 303 for the first time, and the obtained combined tag is a user-level combined tag; the second time it executes steps 302 to 303, the obtained combined tag is an engine-level combined tag, and the third time it executes steps 302 to 303 , the resulting combined tag is an application-level combined tag.

Step 308: Based on the acquired configuration information, output a query result about the query request.

Among them, the implementation process of step 308 requires referring to the above, in the case of constructing the second tag of the first priority, the second tag of the second priority and the second tag of the third priority, based on these three priorities The configuration information corresponding to the second label of the level, and the implementation process of outputting the query result about the query request will not be described here.

In order to implement the method of the embodiment of the present application, the embodiment of the present application also provides a server, as shown in Figure 4, the server includes:

The receiving unit 41 is configured to receive a data storage request; the data storage request carries at least one type of identification and configuration information;

A construction unit 42 configured to construct the first tag based on the at least one type of identifier;

An assigning unit 43 configured to assign a first index value to the first tag;

The storage unit 44 is configured to associate store the first tag and the first index value in a first data table, and associate store the first index value and the configuration information carried in the data storage request in a The second data table; the configuration information is used to configure the big data engine.

In some embodiments, the at least one type of identifier includes at least one of the following:

User ID;

application identification;

Category identification of the big data engine;

The version identifier of the big data engine.

In some embodiments, the construction unit 42 is specifically configured as:

In some embodiments, the receiving unit 41 is further configured to receive an update request; the update request is used to request to update the first label and/or the configuration information; the server further includes:

An updating unit configured to update the first tag in the first data table and/or update the configuration information in the second data table based on the first index value.

In some embodiments, the receiving unit 41 is also configured to receive a query request for configuration information; the query request carries at least one type of identification; the server also includes:

A construction unit configured to construct at least one second tag based on at least one type of identifier in the query request;

A query unit, configured to find out in the first data table a first index value corresponding to a tag matching each second tag in the at least one second tag;

The determining unit is configured to acquire the determined configuration information corresponding to each first index value from the second data table;

An output unit configured to output a query result about the query request based on the acquired configuration information.

In some embodiments, the construction unit is specifically configured as:

Using the second setting character to replace the user identification in the second label of the first priority to obtain the second label of the third priority; wherein, the first priority is higher than the second priority; The second priority is higher than the third priority.

In some embodiments, the configuration information includes at least one configuration item and corresponding configuration parameters; the output unit is specifically configured as:

In actual application, each unit included in the server can be controlled by a processor in the server, such as a central processing unit (CPU, Central Processing Unit), a digital signal processor (DSP, Digital Signal Processor), a micro control unit (MCU, Microcontroller Unit) Or programmable gate array (FPGA, Field-Programmable Gate Array) and other implementations.

It should be noted that: when the server provided in the above-mentioned embodiment performs data processing, the division of the above-mentioned program modules is used as an example for illustration. The internal structure of the program is divided into different program modules to complete all or part of the processing described above. In addition, the server and the data processing method embodiments provided in the above embodiments belong to the same idea, and the specific implementation process thereof is detailed in the method embodiments, and will not be repeated here.

Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present application, the embodiment of the present application further provides a server. Fig. 5 is a schematic diagram of the hardware composition structure of the server of the embodiment of the present application. As shown in Fig. 5, the server 5 includes:

Communication interface 51, capable of exchanging information with other devices such as network devices;

The processor 52 is connected to the communication interface 51 to implement information interaction with other devices, and is configured to execute the methods provided by one or more of the above technical solutions when running a computer program. Instead, the computer program is stored on the memory 53 .

Certainly, in actual application, various components in the server 5 are coupled together through the bus system 54 . It will be appreciated that the bus system 54 is configured to enable connection communication between these components. In addition to the data bus, the bus system 54 also includes a power bus, a control bus and a status signal bus. However, for clarity of illustration, the various buses are labeled as bus system 54 in FIG. 5 .

The memory 53 in the embodiment of the present application is configured to store various types of data to support the operation of the server 5 . Examples of such data include: any computer program for operating on the server 5 .

It can be understood that the memory 53 may be a volatile memory or a non-volatile memory, and may also include both volatile and non-volatile memories. Among them, the non-volatile memory can be read-only memory (ROM, Read Only Memory), programmable read-only memory (PROM, Programmable Read-Only Memory), erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory) Only Memory), Electrically Erasable Programmable Read-Only Memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), Magnetic Random Access Memory (FRAM, ferromagnetic random access memory), Flash Memory (Flash Memory), Magnetic Surface Memory , CD, or CD-ROM (Compact Disc Read-Only Memory); magnetic surface storage can be disk storage or tape storage. The volatile memory may be random access memory (RAM, Random Access Memory), which is used as an external cache. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM, Static Random Access Memory), Synchronous Static Random Access Memory (SSRAM, Synchronous Static Random Access Memory), Dynamic Random Access Memory Memory (DRAM, Dynamic Random Access Memory), synchronous dynamic random access memory (SDRAM, Synchronous Dynamic Random Access Memory), double data rate synchronous dynamic random access memory (DDRSDRAM, Double Data Rate Synchronous Dynamic Random Access Memory), enhanced Synchronous Dynamic Random Access Memory (ESDRAM, Enhanced Synchronous Dynamic Random Access Memory), Synchronous Link Dynamic Random Access Memory (SLDRAM, Sync Link Dynamic Random Access Memory), Direct Memory Bus Random Access Memory (DRRAM, Direct Rambus Random Access Memory) Memory). The memory 53 described in the embodiment of the present application is intended to include but not limited to these and any other suitable types of memory.

The methods disclosed in the foregoing embodiments of the present application may be applied to the processor 52 or implemented by the processor 52 . The processor 52 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 52 or instructions in the form of software. The aforementioned processor 52 may be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. The processor 52 may implement or execute various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, and the storage medium is located in the memory 53, and the processor 52 reads the program in the memory 53, and completes the steps of the foregoing method in combination with its hardware.

Optionally, when the processor 52 executes the program, it implements a corresponding process implemented by the terminal in each method of the embodiment of the present application, and details are not repeated here for the sake of brevity.

In an exemplary embodiment, the embodiment of the present application also provides a storage medium, that is, a computer storage medium, specifically a computer-readable storage medium, for example, including a first memory 53 storing a computer program, and the above-mentioned computer program can be processed by the terminal The device 52 is executed to complete the steps described in the foregoing method. The computer-readable storage medium can be memories such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disk, or CD-ROM.

In the several embodiments provided in this application, it should be understood that the disclosed devices and methods may be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or May be integrated into another system, or some features may be ignored, or not implemented. In addition, the coupling, or direct coupling, or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical or other forms of.

The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units; Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing module, or each unit can be used as a single unit, or two or more units can be integrated into one unit; the above-mentioned integration The unit can be realized in the form of hardware or in the form of hardware plus software functional unit.

Those of ordinary skill in the art can understand that all or part of the steps for realizing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the Including the steps of the foregoing method embodiments; and the foregoing storage medium includes: a removable storage device, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, etc. A medium on which program code can be stored.

It should be noted that: "first", "second", etc. are used to distinguish similar objects, and not necessarily used to describe a specific order or sequence.

It should be noted that the technical solutions described in the embodiments of the present application may be combined arbitrarily if there is no conflict.

It should be noted that the term "and/or" in the embodiments of the present application is only an association relationship describing associated objects, which means that there may be three kinds of relationships, for example, A and/or B, which may mean that A exists alone , both A and B exist, and B exists alone. In addition, the term "at least one" herein means any combination of any one or more of at least two of a plurality, for example, including at least one of A, B, and C, which may mean including from A, Any one or more elements selected from the set formed by B and C.

The above is only a specific implementation of the application, but the scope of protection of the application is not limited thereto. Anyone familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the application. Should be covered within the protection scope of this application. Therefore, the protection scope of the present application should be determined by the protection scope of the claims.

Claims

A data processing method, comprising:

Receive a data storage request; the data storage request carries at least one type of identification and configuration information;

Constructing a first tag based on the at least one type of identifier;

assigning a first index value to the first tag;

storing the first tag and the first index value in a first data table associatively, and storing the first index value and the configuration information carried in the data storage request in a second data table in association; The above configuration information is used to configure the big data engine.
The method according to claim 1, wherein the at least one type of identification includes at least one of the following:

User ID;

application identification;

Category identification of the big data engine;

The version identifier of the big data engine.
The method according to claim 1 or 2, wherein said constructing a first label based on said at least one type of identification comprises:

Based on the setting correspondence between the at least two types of setting identifiers and the setting tag construction method, determine the setting tag construction method corresponding to the at least two types of identifiers carried in the data storage request;

According to the determined set label construction method, the first label corresponding to the at least two types of identifiers is constructed.
The method according to claim 1, wherein the method further comprises:

receiving an update request; the update request is used to request to update the first tag and/or the configuration information;

Based on the first index value, the first tag is updated in the first data table and/or the configuration information is updated in the second data table.
The method according to claim 2, wherein the method further comprises:

Receive a query request for configuration information; the query request carries at least one type of identifier;

Constructing at least one second tag based on at least one type of identifier in the query request;

Finding, in the first data table, a first index value corresponding to a tag matching each second tag in the at least one second tag;

Acquiring the determined configuration information corresponding to each first index value from the second data table;

Based on the obtained configuration information, a query result about the query request is output.
The method according to claim 5, wherein said at least one second label is constructed based on at least one type of identification in said query request, comprising:

Constructing a third label based on the user identification and application identification in the query request, and constructing a fourth label based on the category identification and version identification of the big data engine in the query request;

combining the third tag and the fourth tag to obtain a second tag with a first priority;

Using the first setting character to replace the user ID and application ID in the second label of the first priority to obtain the second label of the second priority;

Using the second setting character to replace the user identification in the second label of the first priority to obtain the second label of the third priority; wherein,

The first priority is higher than the second priority; the second priority is higher than the third priority.
The method according to claim 6, wherein the configuration information includes at least one configuration item and corresponding configuration parameters; the outputting the query result about the query request based on the acquired configuration information includes:

Based on the configuration items included in the configuration information corresponding to each second tag, and based on the priority corresponding to each second tag, determine the configuration item corresponding to each configuration item from the first configuration parameters included in the obtained configuration information. The second configuration parameter;

Output each configuration item and the corresponding second configuration parameter.
A server comprising:

The receiving unit is configured to receive a data storage request; the data storage request carries at least one type of identification and configuration information;

A construction unit configured to construct a first tag based on the at least one type of identifier;

an allocation unit configured to allocate a first index value to the first tag;

The storage unit is configured to associate store the first tag and the first index value in a first data table, and associate store the first index value and the configuration information carried in the data storage request in a second table. Two data tables; the configuration information is used to configure the big data engine.
The server according to claim 8, wherein the at least one type of identifier includes at least one of the following:

User ID;

application identification;

Category identification of big data engine;

The version identifier of the big data engine.
The server according to claim 8 or 9, wherein the construction unit is specifically configured as:

Based on the setting correspondence between the at least two types of setting identifiers and the setting tag construction method, determine the setting tag construction method corresponding to the at least two types of identifiers carried in the data storage request;

According to the determined set label construction method, the first label corresponding to the at least two types of identifiers is constructed.
The server according to claim 8, wherein the receiving unit is further configured to: receive an update request; the update request is used to request to update the first label and/or the configuration information; the server further includes:

An updating unit configured to update the first tag in the first data table and/or update the configuration information in the second data table based on the first index value.
The server according to claim 9, wherein the receiving unit is further configured to receive a query request for configuration information; the query request carries at least one type of identification; the server further includes:

A construction unit configured to construct at least one second tag based on at least one type of identifier in the query request;

A query unit, configured to find out in the first data table a first index value corresponding to a tag matching each second tag in the at least one second tag;

The determining unit is configured to acquire the determined configuration information corresponding to each first index value from the second data table;

An output unit configured to output a query result about the query request based on the acquired configuration information.
The server according to claim 12, wherein the construction unit is specifically configured as:

Constructing a third label based on the user identification and application identification in the query request, and constructing a fourth label based on the category identification and version identification of the big data engine in the query request;

combining the third tag and the fourth tag to obtain a second tag with a first priority;

Using the first setting character to replace the user ID and application ID in the second label of the first priority to obtain the second label of the second priority;

Using the second setting character to replace the user identification in the second label of the first priority to obtain the second label of the third priority; wherein,

The first priority is higher than the second priority; the second priority is higher than the third priority.
The server according to claim 13, wherein the configuration information includes at least one configuration item and corresponding configuration parameters; the output unit is specifically configured as:

Based on the configuration items included in the configuration information corresponding to each second tag, and based on the priority corresponding to each second tag, determine the configuration item corresponding to each configuration item from the first configuration parameters included in the acquired configuration information. The second configuration parameter;

Output each configuration item and the corresponding second configuration parameter.
A server comprising: a processor and a memory configured to store a computer program capable of running on the processor,

Wherein, the processor is configured to execute the steps of the method according to any one of claims 1 to 7 when running the computer program.
A storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.