Data processing method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a data processing method and device, equipment and a storage medium. The method comprises the steps of obtaining a target index and a target dimension input by a user; in response to the query of a group of candidate logic tables associated with the target index, determining whether a target logic table associated with the target dimension exists in the group of candidate logic tables, the target logic table at least indicates a target physical table associated with the target logic table, a target calculation algorithm corresponding to the target index, a first target field associated with the target index in the target physical table, and a second target field associated with the target dimension in the target physical table; generating a target query statement based on the target logic table; and determining target data associated with the target index and the target dimension from a target physical table by using the target query statement, the target physical table at least comprising data associated with each index and each dimension. According to the embodiment of the invention, the data processing efficiency and accuracy can be improved.

Description

Technical Field

[0001] Example embodiments of the present disclosure generally relate to the field of computers, and more particularly, to methods, apparatuses, devices, and computer-readable storage media for data processing. Background Art

[0002] With the rapid development of the data processing field, obtaining or querying valuable data or data that meets user needs from a large amount of data has become a hot issue. Specifically, data of a predetermined exclusive domain can be queried from the data of the general domain, where the general domain can include multiple exclusive domains. For example, in an e-commerce business scenario, the target platform can record the order and payment behavior data of each user for mobile phones and air conditioners (data in the general domain), and the order and payment behavior data of mobile phones (data in the exclusive domain) can be queried from the data in the general domain. How to improve the efficiency of data processing is a focus of attention. Summary of the invention

[0003] In a first aspect of the present disclosure, a method for data processing is provided. The method includes: obtaining a target indicator and a target dimension input by a user; in response to a query to a set of candidate logical tables associated with the target indicator, determining whether there is a target logical table associated with the target dimension in the set of candidate logical tables, wherein the target logical table at least indicates a target physical table associated with the target logical table, a target calculation algorithm corresponding to the target indicator, a first target field associated with the target indicator in the target physical table, and a second target field associated with the target dimension in the target physical table; based on the target logical table, generating a target query statement; and using the target query statement, determining target data associated with the target indicator and the target dimension from the target physical table, wherein the target physical table at least includes data associated with each indicator and each dimension.

[0004] In a second aspect of the present disclosure, a device for data processing is provided. The device includes: an acquisition module configured to obtain a target indicator and a target dimension input by a user; a first determination module configured to determine whether there is a target logical table associated with the target dimension in a set of candidate logical tables in response to a query to a set of candidate logical tables associated with the target indicator, wherein the target logical table at least indicates a target physical table associated with the target logical table, a target calculation algorithm corresponding to the target indicator, a first target field associated with the target indicator in the target physical table, and a second target field associated with the target dimension in the target physical table; a generation module configured to generate a target query statement based on the target logical table; and a second determination module configured to use the target query statement to determine target data associated with the target indicator and the target dimension from the target physical table, wherein the target physical table at least includes data associated with each indicator and each dimension.

[0005] In a third aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory, the at least one memory is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit. When the instructions are executed by the at least one processing unit, the device executes the method of the first aspect.

[0006] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and the computer program can be executed by a processor to implement the method of the first aspect.

[0007] In a fifth aspect of the present disclosure, a computer program product is provided, which includes computer executable instructions, and when the instructions are executed by a processor, the method according to the first aspect of the present disclosure is implemented.

[0008] It should be understood that the contents described in this content section are not intended to limit the key features or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0010] Figure 1 A schematic diagram showing an example environment in which embodiments of the present disclosure can be implemented;

[0011] Figure 2 A flowchart showing a process of data processing according to some embodiments of the present disclosure;

[0012] Figure 3 A flowchart showing a process of creating a domain-specific logic table according to some embodiments of the present disclosure;

[0013] Figure 4 A flowchart showing a process of generating a target query statement according to some embodiments of the present disclosure is shown;

[0014] Figure 5 A framework diagram showing data processing according to some embodiments of the present disclosure is shown;

[0015] Figure 6 A schematic structural block diagram of a device for data processing according to some embodiments of the present disclosure is shown;

[0016] Figure 7 A block diagram of an electronic device capable of implementing various embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0018] It should be noted that the titles of any sections / subsections provided herein are not restrictive. Various embodiments are described throughout this article, and any type of embodiment may be included under any section / subsection. In addition, the embodiments described in any section / subsection may be combined in any manner with any other embodiments described in the same section / subsection and / or different sections / subsections.

[0019] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may be included below. The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may be included below.

[0020] The embodiments of the present disclosure may involve user data, data acquisition and / or use, etc. These aspects are subject to the corresponding laws, regulations and relevant provisions. In the embodiments of the present disclosure, all data collection, acquisition, processing, processing, forwarding, use, etc. are carried out on the premise that the user knows and confirms. Accordingly, when implementing each embodiment of the present disclosure, the type, scope of use, usage scenario, etc. of the data or information that may be involved should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with the relevant laws and regulations. The specific notification and / or authorization method can vary according to the actual situation and application scenario, and the scope of the present disclosure is not limited in this respect.

[0021] In this specification and the embodiments, if personal information processing is involved, it will be processed on the premise of having a legal basis (such as obtaining the consent of the subject of personal information, or it is necessary to perform a contract, etc.), and will only be processed within the scope of regulations or agreements. If a user refuses to process personal information other than the necessary information for basic functions, it will not affect the user's use of basic functions.

[0022] In the related technology, many types of data may be generated in some predetermined scenarios, and these data can be called general domain data. For example, in the e-commerce business scenario, the e-commerce platform will generate a lot of thematic data every day (ad exposure, clicks, add-to-cart, transactions, etc.). Taking the offline scenario as an example, these data can be processed by Extract-Transform-Load (ETL) on the next day and flow into the data middle platform to form data assets. ETL is mainly used to describe the process of extracting, transforming, and loading data from the source end to the destination end, and the term ETL is more commonly used in data warehouses, but its objects are not limited to data warehouses. As an example, the target platform can record the user's order and payment behavior data for various commodities, and these behavior data can flow into the transaction offline data model (Hive table) of the general domain.

[0023] The data in the general domain can include data from multiple exclusive domains. For example, data assets in e-commerce scenarios are often based on goods (Stock Keeping Unit, SKU) as the basic unit, and a SKU often belongs to a business department, that is, abstracted as a business domain (for example, mobile phones belong to the 3C digital business domain, air conditioners belong to the home appliance business domain, etc.), and the sum of the data in these business domains can be represented by the general domain. SKU is the smallest inventory unit, that is, the basic unit for measuring inventory in and out, which can be in units of pieces, boxes, pallets, etc. SKU is a necessary method for logistics management of large chain supermarket distribution centers (Distribution Center, DC), and each product corresponds to a SKU number.

[0024] With the rapid development of data products, in order to make different commercial layouts according to the characteristics of different business domains in a more fine-grained manner, each business department needs to build data assets of exclusive domains based on general domain assets to form their own exclusive domain indicators. (For example, the total daily commercial transaction volume (Gross Merchandise Volume, GMV) of 3C digital products, etc. This 3C digital GMV is a different indicator from the GMV of the general domain, which is an indicator unique to the 3C digital exclusive domain). In addition, in the process of building exclusive domain asset data, some dimensions unique to one's own exclusive domain (such as 3C digital price bands, home appliance and home price bands, etc.) are often used to perform indicator analysis under specified dimensions. These exclusive domain dimensions are not suitable for precipitation in the general domain data model, but need to be expanded based on the general domain data model to make exclusive domain dimensions.

[0025] In view of the above scenarios, the related technologies generally use technical documents and offline user communication to realize the construction of exclusive domain data assets and the expansion of exclusive domain dimensions. Users can clarify the indicator calculation algorithm based on the technical documents, and add the exclusive domain asset segmentation logic maintained offline to form their own exclusive domain assets. This method has problems such as long overall delivery cycle, inaccurate definition of exclusive domain indicators, poor business expansion, and low data processing efficiency. In addition, there may be problems such as errors in the definition of exclusive domain indicators due to technical documents or user communication problems, resulting in low accuracy of data processing. If you still need to expand your own exclusive domain dimensions, users need to process the dimension tables of this part of the dimensions offline (and maintain the technical documents of the dimension tables), and manually associate them when they need to be used. When a new business domain is generated, the staff of the new business domain need to do the same work as the staff of the previous business domain, and the work will not be reduced, which increases the labor cost.

[0026] The embodiments of the present disclosure propose an improved data processing scheme. Obtain the target indicator and target dimension input by the user; in response to querying a set of candidate logical tables associated with the target indicator, determine whether there is a target logical table associated with the target dimension in the set of candidate logical tables, the target logical table at least indicating the target physical table associated with the target logical table, the target calculation algorithm corresponding to the target indicator, the first target field associated with the target indicator in the target physical table, and the second target field associated with the target dimension in the target physical table; based on the target logical table, generate a target query statement; and use the target query statement to determine the target data associated with the target indicator and the target dimension from the target physical table, wherein the target physical table at least includes data associated with each indicator and each dimension.

[0027] In the embodiments of the present disclosure, the target data associated with the target indicators and target dimensions can be automatically queried from the target physical table based on the target indicators and target dimensions input by the user, which effectively improves the efficiency of data processing, improves the accuracy of data processing, and reduces labor costs.

[0028] Example Environment

[0029] Figure 1 1 is a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. Figure 1 As shown, example environment 100 may include electronic device 110 .

[0030] In the example environment 100, the electronic device 110 can query the target data associated with the target indicator and the target dimension from the target physical table based on the target indicator and the target dimension input by the user 120. The target physical table can include the real feedback information of each user for the object. The object can be any appropriate object, such as a commodity, etc. The real feedback information can be the feedback information generated by any appropriate user when performing feedback behavior, such as advertising exposure information, click information, add-to-purchase information, transaction information, etc.

[0031] In some embodiments, the electronic device 110 can be any type of mobile terminal, fixed terminal or portable terminal, including mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia tablets, PDAs, portable game terminals, VR / AR devices, personal communication systems (PCS) devices, personal navigation devices, personal digital assistants (PDAs), audio / video players, digital cameras / camcorders, positioning devices, television receivers, radio broadcast receivers, e-book devices, game devices, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. In some embodiments, the electronic device 110 can also support any type of interface for the target user (such as "wearable" circuits, etc.). In some embodiments, the electronic device 110 can also be a server with data processing capabilities, etc., which will not be repeated here.

[0032] It should be understood that the structure and function of the various elements in the environment 100 are described for exemplary purposes only and do not imply any limitation on the scope of the present disclosure.

[0033] Some example embodiments of the present disclosure will be described below with continued reference to the accompanying drawings.

[0034] Example Process

[0035] Figure 2 FIG. 2 is a flowchart of a process 200 of data processing according to some embodiments of the present disclosure. The process 200 may be implemented at the electronic device 110. Figure 1 Process 200 is described.

[0036] In box 210 , the electronic device 110 obtains the target indicator and target dimension input by the user 120 .

[0037] In some embodiments, the target indicator may be any appropriate parameter for measuring an object, which may be an index, specification, standard, etc. that is expected to be achieved, and may generally be represented by data. Taking the e-commerce business scenario as an example, the target indicator may be a feedback value corresponding to the feedback behavior of a predetermined object, such as the click-through rate, add-to-cart rate, purchase quantity, etc. of a certain product.

[0038] In some embodiments, the target dimension can be any appropriate dimension, which can be used to query the viewing perspective corresponding to the indicator or the window for users to analyze data. For example, the target dimension can be used to query a certain indicator this year, or to query the indicators corresponding to a part of multiple targets, and so on.

[0039] In some embodiments, the target indicator may include at least one of the following: a first indicator corresponding to an exclusive domain, a second indicator corresponding to a universal domain, wherein the universal domain includes at least two exclusive domains. There are differences between the universal domain and the exclusive domain in terms of authority, scope of use, etc. Specifically, the authority and scope of use corresponding to the exclusive domain are smaller than the authority and scope of use corresponding to the universal domain, wherein the exclusive domain belongs to the universal domain. Taking the e-commerce business scenario as an example, the data generated by this scenario may be data from multiple business fields, wherein the business fields may be home appliance and furniture fields, digital fields, and the like. For example, the data generated by this scenario may include purchase data corresponding to air conditioners, purchase data corresponding to mobile phones, and the like. Data from multiple business fields may be referred to as data corresponding to the universal domain, while purchase data corresponding to mobile phones may be referred to as data corresponding to the 3C digital business domain (exclusive domain), and purchase data corresponding to air conditioners may be referred to as data corresponding to the home appliance and furniture business domain (exclusive domain).

[0040] In block 220 , in response to querying a set of candidate logical tables associated with the target indicator, the electronic device 110 determines whether there is a target logical table associated with the target dimension in the set of candidate logical tables.

[0041] In some embodiments, this group of candidate logical tables is a logical table that can support querying data associated with domain target indicators, and the target logical table is a logical table that can support querying data associated with target indicators and target dimensions. In some embodiments, what is indicated in the logical table is not the real feedback information for the object, but logical information indicating how to obtain the real feedback information that meets the requirements of the indicators and dimensions from the real feedback information for the object (the information included in the physical table) based on the indicators and dimensions. This logical information can be any appropriate form of information and will not be elaborated here. Compared with the physical table, the logical table is a collection of indicators and dimensions. The configuration of the logical table will rely on the physical table, and the indicators and dimensions will be standardized and defined based on the physical table.

[0042] In some embodiments, the target logic table may at least indicate a target physical table associated with the target logic table, a target calculation algorithm corresponding to the target indicator, a first target field associated with the target indicator in the target physical table, and a second target field associated with the target dimension in the target physical table. The target physical table indicates real feedback information for the object, such as real information about each user purchasing each commodity on a certain platform. The target calculation algorithm is used to determine the target indicator based on the first target field associated with the target indicator and the second target field associated with the target dimension. The target calculation algorithm can be any appropriate algorithm, such as summing, averaging, maximum value, etc., which will not be elaborated here.

[0043] In some embodiments, the target logic table may include a first sub-logic table, a second sub-logic table, a third sub-logic table, a fourth sub-logic table, and a fifth sub-logic table.

[0044] The following describes the structure of the target logic table.

[0045] In some embodiments, the first sub-logic table may indicate meta information of the target logic table. The first sub-logic table may be as shown in Table 1 below.

[0046] Table 1

[0047]

[0048]

[0049] In some embodiments, the logical table type shown in Table 1 is used to indicate whether the target logical table is of the first logical table type or the second logical table type, wherein the first logical table type indicates the real feedback information of the logical table user on the object (in this case, the logical table type is FACT-fact), and the second logical table type indicates the predetermined information associated with the object (in this case, the logical table type is DIMENSION-association dimension table). The predetermined information may be any appropriate information, which may include but is not limited to at least one of the following: information about the exclusive domain to which the object belongs, information about the category to which the object belongs, and information about the brand to which the object belongs. As an example, the predetermined information may be that skirt A is a garment under brand B, and skirt A belongs to the exclusive domain of garments, etc. The business domain information to which the logical table belongs represents whether the logical table corresponds to a general domain or a specific exclusive domain. The data source id is the identification information of the data source to which the physical table to which the target logical table depends belongs. This data source id may store multiple physical tables, and of course may also include other tables or data in addition to the physical tables. The technical person in charge of the logical table is the user who configures this target logical table.

[0050] In some embodiments, the second sub-logical table may indicate information about a data source to which the dependent physical table belongs. The second sub-logical table may be as shown in Table 2 below.

[0051] Table 2

[0052]

[0053]

[0054] In some embodiments, Table 2 indicates a data source type, where the data source type can be any appropriate type, such as a Hive data source in an offline scenario, or an online analytical processing (OLAP) data source, etc. The data source depends on the offline market information, which can also be called cluster information, where one data source represents a cluster, and one market can contain multiple clusters. The predetermined type of data source can be an OLAP type data source, and the predetermined type of data source needs to connect to the address of the cluster.

[0055] In some embodiments, the third sub-logic table may indicate information of a physical table that the target logical table depends on. The third sub-logic table may be as shown in Table 3 below.

[0056] Table 3

[0057]

[0058] In some embodiments, the fourth sub-logic table may indicate first relationship information between the target logic table and the indicator. The fourth sub-logic table may be as shown in Table 4 below.

[0059] Table 4

[0060]

[0061]

[0062] In some embodiments, the indicator aggregation type is used to indicate the calculation algorithm. The English name of the physical table field that the indicator depends on is the first target field associated with the target indicator in the physical table. In some embodiments, the target logical table can be a logical table corresponding to the general domain, or a logical table corresponding to the exclusive domain. In response to the target logical table being a logical table corresponding to the general domain, the relevant information corresponding to inheritLogicTableId in Table 4 and the relevant information corresponding to InheritMetricDefId may not be set, and of course, may also be set to a predetermined value (such as 0) to indicate that these two fields are invalid during subsequent data processing.

[0063] In some embodiments, the fifth sub-logic table may indicate the second relationship information between the target logical table and the dimension. The fifth sub-logic table may be as shown in Table 5 below.

[0064] Table 5

[0065] Field Name Field Type Field Description logicTableId bigint(11) Logical table id; dimensionDefId bigint(11) Dimension definition id; field varchar(64) The English name of the physical table field that the dimension depends on; fieldNameCn varchar(64) The Chinese name of the physical table field on which the dimension depends dataType varchar(64) The data type that the dimension finally displays; inheritLogicTableId bigint(11) Inherited from the general domain logical table id; dimLogicTableId bigint(11) Dimension table logical table id;

[0066] In some embodiments, the dimension-dependent physical table field may also be referred to as a second target field associated with the target dimension in the target physical table. In some embodiments, the target logical table may be a logical table corresponding to a general domain or a logical table corresponding to a dedicated domain. In response to the target logical table being a logical table corresponding to a general domain, the relevant information corresponding to inheritLogicTableId and the relevant information corresponding to dimLogicTableId in Table 5 may not be set, and may also be set to a predetermined value (such as 0) to indicate that these two fields are invalid during subsequent data processing.

[0067] In some embodiments, the target logical table may be a logical table corresponding to a dedicated domain, and the target logical table may be a logical table split based on the target general domain.

[0068] Taking the target logical table as a logical table split based on the target general domain as an example, the process of determining the target logical table is described.

[0069] The electronic device 110 may determine a logical table corresponding to the target general domain. The electronic device 110 may determine a target clipping range corresponding to the target exclusive domain. In some embodiments, the target clipping range is a range associated with the target exclusive domain in the logical table corresponding to the target general domain. The electronic device 110 may determine an indicator to be inherited from the logical table corresponding to the target general domain, and this indicator to be inherited may be input by the user. The electronic device 110 may determine a first dimension to be inherited from the logical table corresponding to the target general domain, and this first dimension may be input by the user. The electronic device 110 may generate a logical table corresponding to the target exclusive domain based on the target clipping range, the indicator to be inherited, and the first dimension to be inherited.

[0070] In some embodiments, the logical table inheritance relationship maintenance may be as shown in Table 6 below.

[0071]

[0072] In some embodiments, the clipping range from the general domain to the exclusive domain is also the target clipping range. The target clipping range can be composed of three parts: dimension, operator, and dimension value, which will eventually be translated into a target query statement and assigned to the where condition.

[0073] It should be noted that a dedicated domain logic table can inherit from multiple general domain logic tables, and the different indicators it supports can also be inherited from different logic tables. Therefore, Table 4 can include inheritance information, specifically, mainly including the two fields inheritLogicTableId and inheritMetricDefId, to represent which indicator is inherited from which general domain logic table. Table 5 can include the inheritLogicTableId field to represent which general domain logic table this dimension inherits from.

[0074] In some embodiments, the calculation algorithm corresponding to the indicator to be inherited in the target-specific domain is the same as the calculation algorithm corresponding to the target general domain, and the calculation algorithm corresponding to the first dimension to be inherited in the target-specific domain is the same as the calculation algorithm corresponding to the target general domain. As an example, if the indicator to be inherited is the number of refrigerators purchased, the algorithm for determining this indicator to be inherited in the general domain is to sum the number of refrigerators purchased by each user. After it is inherited to the target-specific domain, the algorithm for this indicator to be inherited is also to sum the number of refrigerators purchased by each user.

[0075] In the embodiment of the present disclosure, in order to solve the problem of exclusive domain asset segmentation, the present disclosure proposes the concept of logical table inheritance, systematically represents the calculation algorithm of the general domain index, gets rid of the way that users determine the calculation algorithm based on technical documents and offline communication, and improves the efficiency of data processing. The specific exclusive domain logic table can inherit from the general domain logic table, and then can inherit the calculation algorithm from the general domain logic table, solving the problem that the calculation algorithm is difficult to determine and easy to confirm errors.

[0076] In some embodiments, the electronic device 110 may create a first dimension logical table in response to receiving confirmation of adding a second dimension. The second dimension may be any appropriate dimension, which will not be described in detail herein. The electronic device 110 may establish an association relationship between the first dimension logical table and the physical logical table corresponding to the target exclusive domain based on the second dimension to complete the dimension configuration corresponding to the target exclusive domain. The disclosed embodiment can quickly and dynamically expand the list of dimensions supported by the physical logical table (fact logical table) by establishing an association relationship between the first dimension logical table and the physical logical table corresponding to the target exclusive domain.

[0077] As an example, taking the physical logic table corresponding to the target exclusive domain as including data corresponding to each commodity, and the newly added second dimension as commodity and price, the electronic device 110 can add commodities and price bands in the first dimension logic table, and can establish an association relationship between the physical logic table corresponding to the target exclusive domain and the first dimension logic table based on the commodities. At this time, the price band corresponding to the commodities can be expanded in the physical logic table.

[0078] In some embodiments, the association relationship between the first dimension logical table and the physical table corresponding to the target exclusive domain indicates obtaining part of the data in the physical table corresponding to the target exclusive domain.

[0079] In some embodiments, the association relationship between the first dimension logic table and the target-specific corresponding physical logic table may be as shown in Table 7 below.

[0080] Table 7

[0081] Field Name Field Type Field Description factLogicTableId bigint(11) Fact logic table id; dimLogicTableId bigint(11) Dimension logical table id; joinDimDefId bigint(11) The associated dimension id; dimDatePeriod Int(4) Dimension logical table partition offset;

[0082] In some embodiments, the fact logic table may also be referred to as a physical logic table. The dimension logic table partition offset is used to indicate which part of the data in the physical table corresponding to the target exclusive domain is obtained. The addition of the dimLogicTableId field is used to ensure which exclusive domain dimension logical table the exclusive domain dimension in the logical table comes from. As an example, the dimension logic table partition offset can be used to indicate obtaining today's data, or to indicate obtaining today's data and yesterday's data. joinDimDefId is a dimension shared by the fact logic table and the dimension logic table. Only the same dimension can be used for the association key. The fact logic table associated through the association key has the unique dimension of the dimension logic table by default.

[0083] The disclosed embodiment can support the expansion of exclusive domain dimensions by associating the fact logic table with the dimension logic table (purely recording dimension information, such as color, size, etc. in product attribute information), that is, binding the exclusive domain dimension to be expanded to the dimension logic table, and associating the dimension logic table with the fact logic table at the same time, so that the dimension in the dimension logic table can be added to the fact logic table, without directly expanding the corresponding data column on the fact physical table, supporting low-cost and scalable expansion of exclusive domain dimensions. In addition, the physical model supports the ability to associate multiple tables, and the exclusive domain dimension can be quickly expanded through the dimension logic table association, reducing the shortcomings of long delivery cycle and poor dimensional expansion capability caused by offline users to determine the calculation algorithm.

[0084] It should be noted that when inheriting indicators and / or dimensions based on the common domain, the data model segmentation logic can be specified. It is only necessary to ensure that different segmentation logics are specified for different exclusive domains. The calculation algorithm of the indicator and the use of the dimension can be automatically inherited. It also supports the materialization of the exclusive domain data model after segmentation.

[0085] Figure 3 A flowchart of a process 300 for creating a dedicated domain logic table according to some embodiments of the present disclosure is shown. Figure 3 Provide explanation.

[0086] In block 301 , the electronic device 110 may determine a logic table corresponding to a target general domain.

[0087] In block 302 , the electronic device 110 may determine a target-specific domain and a target cropping range corresponding to the target-specific domain.

[0088] The target-specific domain and the target cropping range corresponding to the target-specific domain may be determined and input by a user.

[0089] In block 303 , the electronic device 110 may determine an indicator to be inherited.

[0090] Indicators to be inherited are not allowed to be edited. For the same type of indicators, the inherited indicator code in the exclusive domain logic table is different from the indicator code in the general domain because the components of the indicator - business domain information are different, but their calculation algorithms are the same.

[0091] In block 304 , the electronic device 110 may determine a dimension to be inherited (a first dimension).

[0092] Dimensions to be inherited cannot be edited.

[0093] In block 305 , the electronic device 110 determines whether to add a new dimension.

[0094] In response to determining not to add a new dimension (second dimension), the electronic device 110 may execute block 306. In response to determining to add a new dimension, the electronic device 110 may execute block 307.

[0095] In block 306 , the electronic device 110 generates a logic table corresponding to the target-specific domain.

[0096] Specifically, the electronic device 110 may generate a logic table corresponding to the target exclusive domain based on the target clipping range, the indicator to be inherited, and the first dimension to be inherited.

[0097] In block 307 , the electronic device 110 may create a new dimensional logical table (a first dimensional logical table).

[0098] At block 308 , the electronic device 110 may configure the dimension-table association relationship.

[0099] The dimension table association relationship is the association relationship between the dimension logical table and the physical logical table corresponding to the target exclusive domain.

[0100] In block 309 , the electronic device 110 may configure the dimension corresponding to the target-specific domain.

[0101] Back to Figure 2 In block 230 , the electronic device 110 generates a target query statement based on the target logical table.

[0102] The electronic device 110 may parse the query capabilities of the indicators and dimensions indicated by the target logical table into target query statements for use in actual target indicator and target dimension queries.

[0103] In some embodiments, the target query statement may be any appropriate query statement, such as Structured Query Language (SQL). In some embodiments, the target query statement may be generated based on any appropriate method, such as based on tools such as JOOQ, which will not be described in detail here.

[0104] The following is an explanation of the process of generating the target query statement.

[0105] The electronic device 110 may determine a first sub-query statement based on the first target field associated with the target indicator, the second target field associated with the target dimension, and the target calculation algorithm corresponding to the target indicator in the target logic table. The first sub-query statement may include select, where, and groupBy.

[0106] The electronic device 110 may determine a second sub-query statement based on a target physical table indicated in the target logical table and associated with the target logical table. The second sub-query statement may be a from clause.

[0107] The electronic device 110 may determine a third sub-query statement based on the association relationship between the predetermined target physical table and the logical table corresponding to the target dimension. The third sub-query statement may be a join clause.

[0108] The electronic device 110 may generate a target query statement based on the first sub-query statement, the second sub-query statement, and the third sub-query statement.

[0109] Figure 4 A flowchart of a process 400 for generating a target query statement according to some embodiments of the present disclosure is shown. Figure 4 Provide explanation.

[0110] In box 401, the electronic device 110 can perform parameter verification on the target indicator and the target dimension.

[0111] The target indicator and the target dimension may be input by the user. The electronic device 110 may perform parameter verification based on any appropriate verification method, specifically, the security, compliance, etc. of the target indicator and the target dimension may be verified, which will not be elaborated here.

[0112] In block 402 , the electronic device 110 queries a logical table supported by a target indicator.

[0113] In block 403 , the electronic device 110 may determine whether there is logic table support.

[0114] The electronic device 110 can obtain the relationship between the logic table and the indicator based on Table 4, and then determine whether the logic table of the target indicator can be supported.

[0115] In response to determining that there is logic table support, the electronic device 110 may execute block 405. In response to determining that there is no logic table support, the electronic device 110 may end the process.

[0116] In block 404 , the electronic device 110 may traverse a list of supported logical tables.

[0117] In block 405 , the electronic device 110 may determine whether there are dimensions that support the query.

[0118] The electronic device 110 may determine, based on Table 5, whether these logical table lists can support the dimensions of the query again.

[0119] In response to determining that there are dimensions that support the query, the electronic device 110 may execute block 406. In response to determining that there are no dimensions that support the query, the electronic device 110 may execute block 404.

[0120] In block 406 , the electronic device 110 may populate a list of supported logical tables.

[0121] In some embodiments, the logical table list may include one logical table of the dimension supporting the query, or may include multiple logical tables of the dimension supporting the query.

[0122] In block 407 , the electronic device 110 may determine a target logical table.

[0123] In some embodiments, in response to the logical table list including a logical table that supports the query dimension, the electronic device 110 may determine the logical table as the target logical table.

[0124] In other embodiments, the electronic device 110 may randomly select a logical table as the target logical table in response to the logical table list including multiple logical tables supporting the query dimensions.

[0125] In box 408, the electronic device 110 can query the fields and calculation algorithms corresponding to the indicators and dimensions based on the target logic.

[0126] The electronic device 110 can obtain the implementation method of the indicators and dimensions in the logical table based on the physical table field information and aggregation method in Table 4 and Table 5.

[0127] In box 409, the electronic device 110 can generate select, where, groupBy (first sub-query statement) based on the fields and calculation algorithms corresponding to the indicators and dimensions.

[0128] In block 410 , the electronic device 110 may query physical table information corresponding to a target logical table.

[0129] The electronic device 110 may determine the physical information corresponding to the target logical table based on Table 2 and Table 3.

[0130] In block 411 , the electronic device 110 may generate a from clause (a second sub-query statement) based on the physical table information corresponding to the target logical table.

[0131] In block 412 , the electronic device 110 may query the dimension table association relationship.

[0132] The electronic device 110 may determine the dimension table association relationship based on Table 7.

[0133] In box 413, the electronic device 110 may generate a join clause (third sub-query statement) based on the dimension table association relationship.

[0134] In box 414, the electronic device 110 can generate a complete SQL (target query statement) based on the select, where, groupBy, from clause, join clause and JOOQ tool.

[0135] Continue to return Figure 2 In process 200, in box 240, the electronic device 110 uses a target query statement to determine target data associated with a target indicator and a target dimension from a target physical table, wherein the target physical table at least includes data associated with each indicator and each dimension.

[0136] In some embodiments, in response to the target indicator being the first indicator, the target physical table is a physical table corresponding to the exclusive domain. In other embodiments, in response to the target indicator being the second indicator, the target physical table is a physical table corresponding to the universal domain. As an example, if the target indicator is an indicator corresponding to the 3C digital business domain, the target physical table is a physical table including data corresponding to the 3C data business domain, and this physical table includes data corresponding to each 3C digital. If the target indicator is an indicator corresponding to the universal domain, and this universal domain includes the 3C digital business domain and the home appliance and furniture business domain, the target physical table is a physical table including data corresponding to the 3C data business domain and data from the home appliance and furniture business domain.

[0137] Figure 5 A schematic diagram of a data processing framework 500 according to some embodiments of the present disclosure is shown. Figure 5 Provide explanation.

[0138] In some embodiments, the data processing framework of the embodiments of the present disclosure may include a logic table definition module 510 , a logic table inheritance module 520 , a logic table association module 530 , and an SQL generation module 540 .

[0139] The logical table definition module 510 is used to define the required information of the logical table in the system, which at least includes the physical table information that the logical table depends on, the indicator configuration information of the logical table, and the dimension configuration information of the logical table. Taking Table 3 as an example, the physical table information that the logical table depends on may include but is not limited to the cluster, library name, table name and other information that the physical table depends on. Taking Table 4 as an example, the indicator configuration information includes but is not limited to the calculation algorithm corresponding to the indicator, which field the calculation algorithm is based on, and what aggregation method is used to obtain this indicator. Taking Table 5 as an example, the dimension configuration information includes but is not limited to the physical table field information that the dimension depends on, etc.

[0140] The logic table inheritance module 520 is used to define the data asset inheritance relationship between the exclusive domain logic table and the general domain logic table, including at least the segmentation information during inheritance, the inheritance relationship of the indicator and the inheritance relationship of the logic table, etc. The segmentation information represents the logic of how the data assets of the exclusive domain are segmented from the data assets of the general domain. As an example, taking the application scenario as an e-commerce scenario, the electronic device 110 can segment the data assets of the general domain based on the business group ID or department ID, such as determining the data assets corresponding to each business group as a data asset of an exclusive domain. The inheritance relationship of the indicator is the indicator inherited from the general domain logic table in the exclusive domain logic table. This indicator corresponds to different indicators in the exclusive domain logic table and the general domain logic table, that is, it can be the first indicator and the second indicator. The calculation algorithm corresponding to the inherited indicator in the exclusive domain logic table and the general domain logic table is the same. The logic table inheritance relationship refers to the inheritance relationship between the exclusive domain logic table and the general domain logic table.

[0141] The logic table association module 530 is used to define the association relationship between the fact logic table and the dimension logic table, which mainly includes two parts: dimension table association relationship and fact table dimension extension. The dimension table association relationship records at least the dimension table information and the association key. The fact table dimension extension part refers to which dimensions in the dimension logic table need to be extended in the fact logic table, so that the SQL generation module can use this part of information to generate Join SQL.

[0142] The SQL generation module (specifically, a Hive SQL generation module) 540 is used to provide Hive SQL generation logic for exclusive domain asset segmentation and index query of logical tables. Its output is a Hive SQL, which is submitted by the system to the offline computing queue to execute the segmentation or index query logic.

[0143] In some embodiments, the target logical table can be defined as a set of indicators and dimensions, which is based on the target physical table, but is distinguished from the target physical table. The target physical table mainly stores field information, and the field information itself does not have any meaning of indicators or dimensions. In the process of data product construction, if there is no concept of indicators and dimensions, and all data comes from the physical model, if different data dashboards want to reuse the same set of data calculation logic, the user can only determine the target query statement (such as Hive SQL) after determining the calculation algorithm, and the data reusability is poor. In addition, the calculation logic (Hive SQL) is often a research and development language, and it cannot be clearly associated with the business meaning, that is, it cannot be deposited as a data asset in the data middle platform, and the appearance of indicators clearly defines the business meaning of the indicator from a business perspective. For example, in the e-commerce scenario, the definition of indicators often requires information such as business domain (3C digital business domain), theme (transaction), business process (transaction), subject (product SKU) and measurement (amount). When there is an indicator definition, if multiple dashboards want to implement the same set of indicator logic, they only need to reuse the indicators, and there is no need to implement the calculation logic again, which greatly improves the efficiency of data processing.

[0144] In the embodiments of the present disclosure, the target data associated with the target indicators and target dimensions can be automatically queried based on the target indicators and target dimensions input by the user, which effectively improves the efficiency of data processing, improves the accuracy of data processing, and reduces labor costs.

[0145] Example devices and equipment

[0146] The embodiments of the present disclosure also provide corresponding devices for implementing the above methods or processes. Figure 6 1 shows a schematic structural block diagram of an apparatus 600 for data processing according to some embodiments of the present disclosure. The apparatus 600 may be implemented as or included in the electronic device 110 discussed above. Each module / component in the apparatus 600 may be implemented by hardware, software, firmware, or any combination thereof.

[0147] like Figure 6As shown, the device 600 includes an acquisition module 610, which is configured to obtain a target indicator and a target dimension input by a user; a first determination module 620, which is configured to determine whether there is a target logical table associated with the target dimension in a set of candidate logical tables in response to a query to a set of candidate logical tables associated with the target indicator, wherein the target logical table at least indicates a target physical table associated with the target logical table, a target calculation algorithm corresponding to the target indicator, a first target field associated with the target indicator in the target physical table, and a second target field associated with the target dimension in the target physical table; a generation module 630, which is configured to generate a target query statement based on the target logical table; and a second determination module 640, which is configured to use the target query statement to determine target data associated with the target indicator and the target dimension from the target physical table, wherein the target physical table at least includes data associated with each indicator and each dimension.

[0148] In some embodiments, the generation module 630 is further configured to: determine a first sub-query statement based on a first target field associated with the target indicator, a second target field associated with the target dimension, and a target calculation algorithm corresponding to the target indicator indicated in the target logical table; determine a second sub-query statement based on a target physical table associated with the target logical table indicated in the target logical table; determine a third sub-query statement based on an association relationship between a predetermined target physical table and a logical table corresponding to the target dimension; and generate a target query statement based on the first sub-query statement, the second sub-query statement, and the third sub-query statement.

[0149] In some embodiments, the target indicator includes at least one of the following: a first indicator corresponding to an exclusive domain, and a second indicator corresponding to a universal domain, wherein the universal domain includes at least two exclusive domains.

[0150] In some embodiments, in response to the target indicator being a first indicator, the target physical table is a physical table corresponding to the exclusive domain; and in response to the target indicator being a second indicator, the target physical table is a physical table corresponding to the universal domain.

[0151] In some embodiments, the target logical table is a logical table corresponding to a target exclusive domain, wherein the target logical table is determined based on the following manner: determining a logical table corresponding to a target general domain; determining a target clipping range corresponding to the target exclusive domain, the target clipping range being a range associated with the target exclusive domain in the logical table corresponding to the target general domain; determining an indicator to be inherited from the logical table corresponding to the target general domain; determining a first dimension to be inherited from the logical table corresponding to the target general domain; and generating a logical table corresponding to the target exclusive domain based on the target clipping range, the indicator to be inherited, and the first dimension to be inherited.

[0152] In some embodiments, the calculation algorithm corresponding to the indicator to be inherited in the target-specific domain is the same as the calculation algorithm corresponding to the target general domain, and the calculation algorithm corresponding to the first dimension to be inherited in the target-specific domain is the same as the calculation algorithm corresponding to the target general domain.

[0153] In some embodiments, the device 600 also includes a creation module, configured to: create a first dimension logical table in response to receiving confirmation of adding a second dimension; and an establishment module, configured to: establish an association relationship between the first dimension logical table and the physical logical table corresponding to the target exclusive domain based on the second dimension to complete the dimension configuration corresponding to the target exclusive domain.

[0154] In some embodiments, the association relationship between the first dimension logical table and the physical table corresponding to the exclusive domain indicates obtaining part of the data in the physical table corresponding to the target exclusive domain.

[0155] In some embodiments, the target logic table includes a first logic table and a second logic table, wherein the first logic table indicates real feedback information of the user on the object, and the second logic table indicates predetermined information associated with the object.

[0156] In some embodiments, the predetermined information includes at least one of the following: information about an exclusive domain to which the object belongs, information about a category to which the object belongs, and information about a brand to which the object belongs.

[0157] In some embodiments, the target logical table includes a first sub-logical table, a second sub-logical table, a third sub-logical table, a fourth sub-logical table and a fifth sub-logical table, and the first sub-logical table indicates the meta-information of the target logical table; the second sub-logical table indicates the information of the data source to which the dependent physical table belongs; the third sub-logical table indicates the information of the physical table on which the target logical table depends; the fourth sub-logical table indicates the first relationship information between the target logical table and the indicator; and the fifth sub-logical table indicates the second relationship information between the target logical table and the dimension.

[0158] The units included in the device 600 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units can be implemented using software and / or firmware, such as machine executable instructions stored on a storage medium. In addition to or as an alternative to machine executable instructions, some or all of the units in the device 600 can be implemented at least in part by one or more hardware logic components. As an example and not limitation, exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0159] Figure 71 shows a block diagram of an electronic device 700 in which one or more embodiments of the present disclosure may be implemented. It should be understood that Figure 7 The electronic device 700 shown is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein. Figure 7 The electronic device 700 shown can be used to implement Figure 1 The electronic device 110 or Figure 6 Device 600.

[0160] like Figure 7 As shown, the electronic device 700 is in the form of a general electronic device. The components of the electronic device 700 may include, but are not limited to, one or more processors or processing units 710, a memory 720, a storage device 730, one or more communication units 740, one or more input devices 750, and one or more output devices 760. The processing unit 710 may be an actual or virtual processor and is capable of performing various processes according to a program stored in the memory 720. In a multi-processor system, multiple processing units execute computer executable instructions in parallel to improve the parallel processing capability of the electronic device 700.

[0161] The electronic device 700 typically includes a plurality of computer storage media. Such media may be any accessible media that is accessible to the electronic device 700, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 720 may be a volatile memory (e.g., a register, a cache, a random access memory (RAM)), a non-volatile memory (e.g., a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 730 may be a removable or non-removable medium, and may include a machine-readable medium, such as a flash drive, a disk, or any other medium, which may be capable of being used to store information and / or data (e.g., training data for training) and may be accessed within the electronic device 700.

[0162] The electronic device 700 may further include additional removable / non-removable, volatile / non-volatile storage media. Figure 7 As shown in , a disk drive for reading or writing from a removable, non-volatile disk (e.g., a "floppy disk") and an optical drive for reading or writing from a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to the bus (not shown) by one or more data media interfaces. The memory 720 may include a computer program product 725 having one or more program modules that are configured to perform various methods or actions of various embodiments of the present disclosure.

[0163] The communication unit 740 implements communication with other electronic devices through a communication medium. Additionally, the functions of the components of the electronic device 700 can be implemented with a single computing cluster or multiple computing machines that can communicate through a communication connection. Therefore, the electronic device 700 can operate in a networked environment using a logical connection with one or more other servers, a network personal computer (PC), or another network node.

[0164] The input device 750 may be one or more input devices, such as a mouse, a keyboard, a tracking ball, etc. The output device 760 may be one or more output devices, such as a display, a speaker, a printer, etc. The electronic device 700 may also communicate with one or more external devices (not shown) through the communication unit 740 as needed, such as a storage device, a display device, etc., communicate with one or more devices that allow a user to interact with the electronic device 700, or communicate with any device that allows the electronic device 700 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0165] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, wherein the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

[0166] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices, equipment, and computer program products implemented according to the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0167] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0168] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, so that the instructions executed on the computer, other programmable data processing apparatus, or other device implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0169] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple implementations of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of a module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some implementations as replacements, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be realized by a special hardware-based system that performs the function or action of the specification, or can be realized by a combination of special hardware and computer instructions.

[0170] The above descriptions of various implementations of the present disclosure are exemplary, non-exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The selection of terms used herein is intended to best explain the principles of the implementations, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the various implementations disclosed herein.

Claims

1. A method for data processing, comprising: Obtain target indicators and target dimensions input by users; In response to querying a group of candidate logical tables associated with the target indicator, determining whether there is a target logical table associated with the target dimension in the group of candidate logical tables, the target logical table at least indicating a target physical table associated with the target logical table, a target calculation algorithm corresponding to the target indicator, a first target field associated with the target indicator in the target physical table, and a second target field associated with the target dimension in the target physical table; Based on the target logical table, generate a target query statement; as well as The target query statement is used to determine target data associated with the target indicator and the target dimension from the target physical table, wherein the target physical table at least includes data associated with each indicator and each dimension.

2. The method according to claim 1, wherein generating a target query statement based on the target logical table comprises: Determine a first sub-query statement based on the first target field associated with the target indicator, the second target field associated with the target dimension, and the target calculation algorithm corresponding to the target indicator indicated in the target logic table; Determine a second sub-query statement based on a target physical table indicated in the target logical table and associated with the target logical table; Determine a third subquery statement based on a predetermined association relationship between the target physical table and the logical table corresponding to the target dimension; as well as The target query statement is generated based on the first sub-query statement, the second sub-query statement, and the third sub-query statement.

3. The method according to claim 1, wherein the target indicator comprises at least one of the following: The first indicator corresponding to the exclusive domain, A second indicator corresponding to a universal domain, wherein the universal domain includes at least two exclusive domains.

4. The method according to claim 3, wherein in response to the target indicator being the first indicator, the target physical table is the physical table corresponding to the exclusive domain; and in response to the target indicator being the second indicator, the target physical table is the physical table corresponding to the universal domain.

5. The method according to claim 1, wherein the target logic table is a logic table corresponding to the target exclusive domain, wherein the target logic table is determined based on the following manner: Determine the logical table corresponding to the target general domain; Determine a target clipping range corresponding to the target specific domain, where the target clipping range is a range associated with the target specific domain in a logic table corresponding to the target general domain; Determining the index to be inherited from the logic table corresponding to the target universal domain; Determine a first dimension to be inherited from a logic table corresponding to the target universal domain; as well as Based on the target clipping range, the indicator to be inherited, and the first dimension to be inherited, a logic table corresponding to the target exclusive domain is generated.

6. The method according to claim 5, wherein the calculation algorithm corresponding to the indicator to be inherited in the target-specific domain is the same as the calculation algorithm corresponding to the target general domain, and the calculation algorithm corresponding to the first dimension to be inherited in the target-specific domain is the same as the calculation algorithm corresponding to the target general domain.

7. The method according to claim 5, further comprising: In response to receiving confirmation of adding the second dimension, creating a first dimension logical table; Based on the second dimension, an association relationship between the first dimension logic table and the physical logic table corresponding to the target exclusive domain is established to complete the dimension configuration corresponding to the target exclusive domain.

8. The method according to claim 7, wherein the association relationship between the first dimension logical table and the physical table corresponding to the exclusive domain indicates obtaining part of the data in the physical table corresponding to the target exclusive domain.

9. The method according to claim 1, wherein the target logic table comprises a first logic table and a second logic table, wherein the first logic table indicates real feedback information of the user on the object, and the second logic table indicates predetermined information associated with the object.

10. The method according to claim 9, wherein the predetermined information includes at least one of the following: Information about the exclusive domain to which the object belongs, Information about the category to which the object belongs, Information about the brand to which the object belongs.

11. The method according to claim 1, wherein the target logic table includes a first sub-logic table, a second sub-logic table, a third sub-logic table, a fourth sub-logic table, and a fifth sub-logic table, and wherein The first sub-logical table indicates meta information of the target logical table; The second sub-logical table indicates information about the data source to which the dependent physical table belongs; The third sub-logical table indicates information of the physical table that the target logical table depends on; The fourth sub-logical table indicates first relationship information between the target logical table and the indicator; the fifth sub-logical table indicates second relationship information between the target logical table and the dimension.

12. A device for data processing, comprising: An acquisition module is configured to obtain a target indicator and a target dimension input by a user; A first determination module is configured to, in response to querying a group of candidate logical tables associated with the target indicator, determine whether there is a target logical table associated with the target dimension in the group of candidate logical tables, wherein the target logical table at least indicates a target physical table associated with the target logical table, a target calculation algorithm corresponding to the target indicator, a first target field associated with the target indicator in the target physical table, and a second target field associated with the target dimension in the target physical table; A generating module, configured to generate a target query statement based on the target logical table; as well as The second determination module is configured to determine the target data associated with the target indicator and the target dimension from the target physical table using the target query statement, wherein the target physical table at least includes data associated with each indicator and each dimension.

13. An electronic device comprising: at least one processing unit; as well as At least one memory, the at least one memory is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the electronic device to perform the method according to any one of claims 1 to 11.

14. A computer-readable storage medium having a computer program stored thereon, wherein the computer program can be executed by a processor to implement the method according to any one of claims 1 to 11.

15. A computer program product comprising computer executable instructions, wherein the computer executable instructions, when executed by a processor, implement the method according to any one of claims 1 to 11.

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