Data Processing Method, Device, Equipment, and Medium Based on Row Data Type Tags

Abstract

The present invention discloses a data processing method, apparatus, device, and medium based on row data type labels. The present invention divides row data in a target table into different grouping field data sets according to different grouping field values, and divides row data in each grouping field data set into different sorting field values according to different sorting field values, thereby obtaining a plurality of grouping field data sets and a plurality of sorting field data sets associated therewith. The grouping field values of all operation row data in the operation data set are combined to generate a row data type label of the operation data set. The grouping field data set corresponding to the row data type label and the row data type label of the operation data set is filtered as a target grouping field data set. The row sequence number of each operation row data set is determined based on all sorting field data sets associated with the target grouping field data set. The operation data set is then inserted into the target table accordingly. This method can quickly and accurately insert row data into the table, effectively improving the efficiency of table data processing.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data processing method, apparatus, device and medium based on row data type labels. Background Art

[0002] Currently, many business systems can support users to enter multiple rows of data in a table for various business scenarios. There are often strong correlations between the multiple rows of data from the business, such as Figure 1 As shown, for the financial instrument column, users can enter five major types of financial instruments: cash, forward rate agreements, futures, swaps, and bonds. Based on the attributes and business operations of different financial instruments, the relationships between different rows of data are as follows: 1. Futures and forward rate agreements cannot exist in the same table at the same time; 2. For the same type of financial instrument (except futures), only one piece of data can be entered for the same term. For example, there is only one cash data item with a term of 1d (1 day); 3. The contract term for futures and forward rate agreements is 3m (3 months), but different futures contracts have different expiration dates, which is reflected in the futures contract column in the table. For example, if the current futures contract expiration month is Sep2022, it means it expires in September 2022. Calculated based on a 3-month term, the next contract expiration month is Dec2022, which means it expires in December 2022, and so on.

[0003] At this point, if a user needs to enter data for different types of financial instruments in a table or insert new data into a table with multiple rows of data, and then categorize and organize all the data, including merging and displaying data for similar financial instruments, sorting maturities from smallest to largest, and arranging futures or forward rate agreement contracts from earliest to latest expiration months, the user must first find the designated row to insert the data before performing subsequent sorting operations. This involves many user-generated judgments, searches, and audits, and the complexity of user operations increases exponentially when the relationships between the multiple rows of data being entered are complex or the amount of data being processed is enormous. Furthermore, to implement the aforementioned business scenarios (i.e., relationships between different rows of data), each time a user enters a new row of data, the business system code must be executed to traverse all rows of data in the table for data validation. If the data in a cell in a row fails the validation, the user will not be able to enter data for the next cell, which easily restricts the order in which the user enters data. As can be seen, the table data processing efficiency of existing business systems is not high. Summary of the Invention

[0004] In order to overcome the shortcomings of the prior art, the present invention provides a data processing method, device, equipment and medium based on row data type labels, which can quickly and accurately insert data into a table and effectively improve the efficiency of table data processing.

[0005] In order to solve the above technical problems, in a first aspect, an embodiment of the present invention provides a data processing method based on row data type labels, comprising:

[0006] Divide the rows of data with the same grouping field value in the target table into the same grouping field dataset to obtain several grouping field datasets;

[0007] respectively dividing the row data with the same sorting field value in each of the grouping field data sets into the same sorting field data set, to obtain a plurality of sorting field data sets associated with each of the grouping field data sets;

[0008] Combining the grouping field values of all operation row data in the operation data set to generate a row data type label of the operation data set;

[0009] Filtering, from all the grouping field data sets, a grouping field data set whose row data type label corresponds to the row data type label of the operation data set as a target grouping field data set; wherein the row data type label of the grouping field data set is obtained according to the grouping field value of any row of data in the grouping field data set;

[0010] According to all sorting field data sets associated with the target grouping field data set, the row sequence number of each operation row data is determined to insert the operation data set into the target table.

[0011] Furthermore, the data processing method based on row data type labels further includes:

[0012] When the target grouping field data set cannot be obtained, based on predefined business rules, grouping field data sets whose row data type labels are adjacent to the row data type label of the operation data set are filtered from all the grouping field data sets as adjacent grouping field data sets;

[0013] The row sequence number of each of the operation row data is determined according to the adjacent grouping field data sets, so as to add the operation data sets to the target table.

[0014] Furthermore, the row data with the same grouping field value in the target table is divided into the same grouping field data set to obtain several grouping field data sets, specifically:

[0015] The target table is obtained, the grouping field value of each row of data in the target table is extracted respectively, and the row data with the same grouping field value and the corresponding row sequence number are divided into the same grouping field data set to obtain a plurality of the grouping field data sets.

[0016] Furthermore, the row data with the same sorting field value in each of the grouping field data sets are divided into the same sorting field data set to obtain a plurality of sorting field data sets associated with each of the grouping field data sets, specifically:

[0017] For each of the grouping field data sets, the sorting field value of each row of data in the grouping field data set is extracted respectively, and the row data with the same sorting field value and the corresponding row sequence number are divided into the same sorting field data set to obtain several sorting field data sets associated with each of the grouping field data sets.

[0018] Furthermore, the grouping field values of all operation row data in the operation data set are combined to generate the row data type label of the operation data set, specifically:

[0019] The grouping field value of each operation row data in the operation data set is extracted respectively, and the grouping field values of each operation row data are combined according to a preset grouping field combination order to generate a row data type label of the operation data set.

[0020] Furthermore, after combining the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set, the method further includes:

[0021] Caches the row data type labels of the operation dataset.

[0022] Furthermore, the row sequence number of each operation row data is determined based on all sorting field data sets associated with the target grouping field data set, specifically:

[0023] For each of the operation row data, the sorting field value of the operation row data is extracted, and row data whose sorting field values are adjacent to the sorting field value of the operation row data are filtered from all sorting field data sets associated with the target grouping field data sets as adjacent row data, and the row sequence number of the operation row data is determined based on the row sequence number of the adjacent row data.

[0024] In a second aspect, an embodiment of the present invention provides a data processing device based on row data type labels, comprising:

[0025] The grouping field data set acquisition module is used to group the row data with the same grouping field value in the target table into the same grouping field data set to obtain several grouping field data sets;

[0026] A sorting field data set acquisition module is used to group row data with the same sorting field value in each grouping field data set into the same sorting field data set, and obtain a plurality of sorting field data sets associated with each grouping field data set;

[0027] A row data type label generation module is used to combine the grouping field values of all operation row data in the operation data set to generate a row data type label for the operation data set;

[0028] a target grouping field data set screening module, configured to screen, from all the grouping field data sets, a grouping field data set whose row data type label corresponds to the row data type label of the operation data set as a target grouping field data set; wherein the row data type label of the grouping field data set is obtained based on the grouping field value of any row of data in the grouping field data set;

[0029] The operation data set inserting module is used to determine the row sequence number of each operation row data according to all sorting field data sets associated with the target grouping field data set, so as to insert the operation data set into the target table.

[0030] In a third aspect, an embodiment of the present invention provides a data processing device based on row data type labels, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the memory is coupled to the processor, and the processor implements the data processing method based on row data type labels as described above when executing the computer program.

[0031] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the data processing method based on the row data type label as described above.

[0032] In a fifth aspect, an embodiment of the present invention provides a computer program product, which, when running on a computer, enables the computer to execute the data processing method based on row data type labels as described above.

[0033] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0034] The method divides the row data in the target table into different grouping field data sets according to different grouping field values, divides the row data in each grouping field data set into different sorting field values according to different sorting field values, obtains several grouping field data sets and several sorting field data sets associated with each grouping field data set, combines the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set, filters the grouping field data sets corresponding to the row data type label of the operation data set from all grouping field data sets as the target grouping field data set, determines the row sequence number of each operation row data according to all sorting field data sets associated with the target grouping field data set, inserts the corresponding operation row data into the corresponding row of the target table, and completes the insertion of the operation data set into the target table without waiting for the user to complete the judgment, retrieval, and review operations, and without traversing all row data in the table for data verification each time row data is inserted into the table. The method can quickly and accurately insert row data into the table, and effectively improve the efficiency of table data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a schematic diagram of a target table exemplified in the first embodiment of the present invention;

[0036] Figure 2 1 is a flow chart of a data processing method based on row data type labels in the first embodiment of the present invention;

[0037] Figure 3 A schematic diagram illustrating the division of row data in a target table according to the first embodiment of the present invention;

[0038] Figure 4 Schematic diagram of row data type labels of various operation data sets exemplified in the first embodiment of the present invention;

[0039] Figure 5 This is a schematic diagram of caching row data type labels of various operation data sets in a list data object according to an example of the first embodiment of the present invention;

[0040] Figure 6 Schematic diagram of an insert operation data set according to an example of the first embodiment of the present invention;

[0041] Figure 7 2 is a structural diagram of a data processing device based on row data type labels in the second embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0043] It should be noted that the step numbers in this article are only for the convenience of explaining the specific embodiments and do not limit the order in which the steps are executed. The method provided in this embodiment can be executed by a relevant terminal device and / or server, and the following description uses a processor as the execution subject as an example.

[0044] The embodiments of the present invention are applicable to scenarios where data needs to be inserted into a table, wherein the type of the table is not limited. For example, it can be a table in office software or a table in an enterprise resource planning (ERP) system. The ERP system includes but is not limited to a production and manufacturing management system, a supply chain system, a human resources system, a financial system, a tax system, and an audit system.

[0045] like Figure 2 As shown, the first embodiment provides a data processing method based on row data type labels, including steps S1 to S5:

[0046] S1. Divide the rows of data with the same grouping field value in the target table into the same grouping field data set to obtain several grouping field data sets;

[0047] S2. Group the rows of data with the same sorting field value in each grouping field data set into the same sorting field data set, to obtain several sorting field data sets associated with each grouping field data set;

[0048] S3. Combine the grouping field values of all operation row data in the operation dataset to generate a row data type label for the operation dataset;

[0049] S4. Filtering, from all grouping field datasets, a grouping field dataset whose row data type label corresponds to the row data type label of the operation dataset as the target grouping field dataset; wherein the row data type label of the grouping field dataset is obtained based on the grouping field value of any row of data in the grouping field dataset;

[0050] S5. Determine the row sequence number of each operation row data according to all sorting field data sets associated with the target grouping field data set, so as to insert the operation data set into the target table.

[0051] As an example, in step S1, the user can predefine business rules according to actual business needs, including setting the grouping relationship between rows in the target table and the sorting relationship between rows in each group. Figure 1 As shown, based on pre-defined business rules, the financial instrument column involved in the grouping relationship between rows in the target table is used as the grouping field, and the row data with the same grouping field value in the target table are divided into the same grouping field dataset. Specifically, the row data with the grouping field value of "cash" in the target table is divided into one grouping field dataset, the row data with the grouping field value of "futures" in the target table is divided into one grouping field dataset, and the row data with the grouping field value of "bonds" in the target table is divided into one grouping field dataset, thereby obtaining several grouping field datasets.

[0052] In step S2, based on pre-defined business rules, the futures contract, FRA, and term columns involved in the sorting relationship between rows in each group are used as sorting fields, and the row data with the same sorting field value in each grouping field dataset are divided into the same sorting field dataset. For example, the row data with the futures contract value of "Sep2022" in the "Futures" grouping field dataset is divided into one sorting field dataset, the row data with the futures contract value of "Dec2022" in the "Futures" grouping field dataset is divided into one sorting field dataset, and the row data with the futures contract value of "Mar2023" in the "Futures" grouping field dataset is divided into one sorting field dataset, thereby obtaining several sorting field datasets associated with each grouping field dataset.

[0053] Based on predefined business rules, other fields in the target table can also be used as business fields. Figure 3 As shown, Key is the key in the key-value pair, which is used to uniquely identify the object and serves as a cursor for finding the object. Value is the value in the key-value pair, which represents the data stored for the key.

[0054] In step S3, the operation data set input by the user is obtained, and based on pre-defined business rules, the grouping field values of each operation row data in the operation data set are extracted respectively to obtain the grouping field values of all operation row data in the operation data set. The grouping field values of all operation row data in the operation data set are combined to generate the row data type label of the operation data set. Since there may be at least two operation row data with the same grouping field value in the operation data set, in the process of combining the grouping field values of all operation row data in the operation data set, each operation row data can be traversed to determine whether the grouping field value of the currently traversed operation row data is the same as the grouping field value of any previously traversed operation row data. If so, the grouping field value of the currently traversed operation row data is directly discarded, so that after traversing all operation row data, only the grouping field values of all retained operation row data are combined to obtain the row data type label of the operation data set; or all operation row data can be traversed to obtain the grouping field values of all operation row data, first combine the grouping field values of all operation row data, and then deduplicate the combined grouping field value sequence to obtain the row data type label of the operation data set, wherein the combination order can be the traversal order or the arrangement order between each group contained in the pre-defined business rules.

[0055] In step S4, the grouping field values of all rows of data in each grouping field dataset are combined to obtain row data type labels for each grouping field dataset. Since the grouping field values of each row of data in the grouping field dataset are identical, the grouping field value of any row of data in the grouping field dataset can be directly used as the row data type label for the corresponding grouping field dataset. Grouping field datasets whose row data type labels correspond to the row data type labels of the operation dataset are selected from all grouping field datasets as target grouping field datasets. Specifically, a grouping field value in the row data type label of each grouping field dataset is compared with each grouping field value in the row data type label of the operation dataset. If the grouping field value of a grouping field dataset is identical to any grouping field value in the operation dataset, the grouping field dataset is used as the target grouping field dataset.

[0056] In step S5, based on the association relationship between each grouping field data set and each sorting field data set, all sorting field data sets associated with the target grouping field data set are obtained, and according to each row data and the corresponding row sequence number in these sorting field data sets, the row sequence number of each operation row data in the operation data set is determined, so as to insert the corresponding operation row data into the corresponding row of the target table, thereby completing the insertion of the operation data set into the target table.

[0057] Assume that there are two operation row data in an operation dataset, and the grouping field values of these two operation row data are different. Then the row data type label of the operation dataset is a grouping field value sequence obtained by combining the grouping field values of the two operation row data. From all grouping field datasets, a grouping field dataset with a row data type label of the grouping field value of the first operation row data and a grouping field dataset with a row data type of the grouping field value of the second operation row dataset are filtered. The filtered grouping field values are all used as target grouping field datasets. For the grouping field dataset with a row data type label of the grouping field value of the first operation row data, that is, the filtered first target grouping field dataset, the row sequence number of the first operation row data is determined based on all sorting field datasets associated with the target grouping field dataset. Similarly, for the grouping field dataset with a row data type label of the grouping field value of the second operation row data, that is, the filtered second target grouping field dataset, the row sequence number of the second operation row data is determined based on all sorting field datasets associated with the target grouping field dataset, to ensure the orderly insertion of each operation row data.

[0058] It can be understood that when the user inputs an operation data set, a row data type label can be directly generated for the operation data set, and the corresponding operation row data can be automatically inserted into the corresponding row in the target table based on the row data type label of the operation data set. There is no need to wait for the user to complete the judgment, retrieval, and review operations, nor is there a need to traverse all row data in the table for data verification every time row data is inserted into the table.

[0059] This embodiment can quickly and accurately insert row data into a table, effectively improving the efficiency of table data processing.

[0060] In a preferred embodiment, the data processing method based on row data type labels further includes steps S6 to S7:

[0061] S6. When the target grouping field dataset cannot be obtained, based on predefined business rules, grouping field datasets whose row data type labels are adjacent to the row data type label of the operation dataset are filtered from all grouping field datasets as adjacent grouping field datasets;

[0062] S7. Determine the row number of each operation row data according to the adjacent grouping field data set, so as to add the operation data set to the target table.

[0063] As an example, in step S6, when the row data type labels of all grouping field data sets do not correspond to the row data type labels of the operation data set and the target grouping field data set cannot be filtered out from all grouping field data sets, based on pre-defined business rules, including the sorting relationship between each group, that is, the row data type labels, the grouping field data sets whose row data type labels are adjacent to the arrangement position of the row data type labels of the operation data set are filtered out from all grouping field data sets as adjacent grouping field data sets.

[0064] Assume that the order of the predefined groups from front to back is "cash", "futures", "bonds", and "swap". Figure 1 In the target table shown, the row data type labels for all grouped field datasets are "Cash," "Futures," and "Bonds," respectively, while the row data type label for the operation dataset is "Swap." In this case, since the row data type labels for each grouped field dataset differ from the row data type label for the operation dataset, it is assumed that none of the row data type labels for the grouped field datasets correspond to the row data type label for the operation dataset, making it impossible to filter the target grouped field dataset from all the grouped field datasets. Instead, the target grouped field dataset is filtered from all the grouped field datasets to identify grouped field datasets whose row data type labels are adjacent to the row data type labels for the operation dataset. Since "Bonds" and "Swap" are adjacent, the grouped field dataset corresponding to "Bonds" is selected as the adjacent grouped field dataset.

[0065] Assume that the predefined ordering of the groups from front to back is "Cash," "Futures," "Bonds," and "Swaps." The row data type labels for all grouping field datasets are "Cash," "Futures," and "Swaps," respectively, and the row data type label for the operation dataset is "Bonds." In this case, the row data type labels for each grouping field dataset differ from the row data type label for the operation dataset. Therefore, the target grouping field dataset cannot be found from all grouping field datasets. Instead, grouping field datasets whose row data type labels are adjacent to the row data type label of the operation dataset are selected from all grouping field datasets. Since "Futures," "Swaps," and "Bonds" are adjacent, the grouping field datasets corresponding to "Futures" and "Swaps" are selected as adjacent grouping field datasets.

[0066] It can be understood that the grouping field dataset whose row data type label is adjacent to the arrangement position of the row data type label of the operation dataset refers to the grouping field dataset in which, for each grouping field value in the row data type label of the operation dataset, based on the sorting relationship between the various groups, the grouping field value in the row data type label is arranged before and / or after the arrangement position of the grouping field value in the row data type label of the operation dataset.

[0067] In step S7, the row number of each operation row data in the operation data set is determined according to each row data and the corresponding row number in the adjacent grouping field data set, so as to add the corresponding operation row data to the corresponding row of the target table, thereby completing the addition of the operation data set in the target table.

[0068] For example, when inserting a "swap" financial instrument, for the first operation row data, based on the grouping field dataset corresponding to "bond," that is, each row data and corresponding row sequence number in the adjacent grouping field dataset, the row sequence number of the last row data in the adjacent grouping field dataset is determined to be 8. Therefore, the row sequence number of the first operation row data is determined to be 8+1=9. For the second row data, based on the row sequence number of the last row data in the adjacent grouping field dataset and all previous operation row data, that is, the sort field value and row sequence number of the first operation row data, the order of the first and second operation row data is determined. If the first operation row data is determined to be arranged before the second operation row data, the row sequence number of the second operation row data is determined to be 8+1+1=10. Otherwise, the row sequence number of the second operation row data is determined to be 8+1=9, and the row sequence number of the first operation row data is adjusted to 8+1+1=10. This process is repeated until the row sequence numbers of each operation row data in the operation dataset are determined, and the corresponding operation row data is added to the corresponding row in the target table.

[0069] This embodiment can quickly and accurately add new rows of data to a table, effectively improving the efficiency of table data processing.

[0070] In a preferred embodiment, the method of dividing the row data with the same grouping field value in the target table into the same grouping field data set to obtain several grouping field data sets is specifically as follows: obtaining the target table, extracting the grouping field value of each row data in the target table respectively, dividing the row data with the same grouping field value and the corresponding row sequence number into the same grouping field data set to obtain several grouping field data sets.

[0071] As an example, based on pre-defined business rules, the financial instrument column involving the grouping relationship between rows in the target table is used as the grouping field, and the row data and corresponding row numbers with the same grouping field value in the target table are divided into the same grouping field data set. Specifically, the row data and corresponding row numbers with the grouping field value of "cash" in the target table are divided into one grouping field data set, the row data and corresponding row numbers with the grouping field value of "futures" in the target table are divided into one grouping field data set, and the row data and corresponding row numbers with the grouping field value of "bonds" in the target table are divided into one grouping field data set, thereby obtaining several grouping field data sets.

[0072] In a preferred embodiment, the row data with the same sorting field value in each grouping field data set are divided into the same sorting field data set to obtain several sorting field data sets associated with each grouping field data set. Specifically, for each grouping field data set, the sorting field value of each row data in the grouping field data set is extracted respectively, and the row data with the same sorting field value and the corresponding row sequence number are divided into the same sorting field data set to obtain several sorting field data sets associated with each grouping field data set.

[0073] As an example, based on pre-defined business rules, the futures contract, FRA, and term columns involved in the sorting relationship between rows in each group are used as sorting fields, and the row data and corresponding row numbers with the same sorting field value in each grouping field data set are divided into the same sorting field data set. For example, the row data and corresponding row numbers with the futures contract value of "Sep2022" in the "Futures" grouping field data set are divided into one sorting field data set, the row data and corresponding row numbers with the futures contract value of "Dec2022" in the "Futures" grouping field data set are divided into one sorting field data set, and the row data and corresponding row numbers with the futures contract value of "Mar2023" in the "Futures" grouping field data set are divided into one sorting field data set, thereby obtaining several sorting field data sets associated with each grouping field data set.

[0074] In a preferred embodiment, the grouping field values of all operation row data in the operation data set are combined to generate the row data type label of the operation data set. Specifically, the grouping field value of each operation row data in the operation data set is extracted respectively, and the grouping field values of each operation row data are combined according to a preset grouping field combination order to generate the row data type label of the operation data set.

[0075] As an example, obtain the operation data set input by the user, and based on the predefined business rules, extract the grouping field values of each operation row data in the operation data set, and obtain the grouping field values of all operation row data in the operation data set. Based on the predefined business rules, the grouping field combination order is preset according to the sorting relationship between each group. According to the preset grouping field combination order, the grouping field values of all operation row data in the operation data set are combined, for example, the grouping field values corresponding to the group in the front of the arrangement order are placed in the first place, and the grouping field values corresponding to the group in the back of the arrangement order are placed in the last place, to obtain a grouping field value sequence, thereby generating a row data type label for the operation data set. Among them, the schematic diagram of the row data type label of each operation data set is shown as follows Figure 4 As shown, Tag is a label.

[0076] In a preferred embodiment, after combining the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set, the method further includes: caching the row data type label of the operation data set.

[0077] As an example, after generating the row data type labels of the operation data set, the row data type labels of the operation data set are cached in the list data object. The schematic diagram of caching the row data type labels of each operation data set in the list data object is as follows: Figure 5 shown.

[0078] This embodiment caches the row data type labels of the operation dataset in the list data object, so that when a new operation dataset with the same row data type labels as the operation dataset is subsequently inserted into the target table, the row data type labels can be directly obtained from the list data object without having to combine the grouping field values of each new operation row data in the new operation dataset to obtain its row data type label. This allows for faster and more accurate insertion of row data into the table, effectively improving the efficiency of table data processing.

[0079] In a preferred embodiment, the row sequence number of each operation row data is determined based on all sorting field data sets associated with the target grouping field data set. Specifically, for each operation row data, the sorting field value of the operation row data is extracted, and row data whose sorting field values are adjacent to the sorting field value of the operation row data are filtered from all sorting field data sets associated with the target grouping field data set as adjacent row data, and the row sequence number of the operation row data is determined based on the row sequence number of the adjacent row data.

[0080] As an example, based on predefined business rules and the sorting relationship between each grouping, determine the position order of the row data type labels of the operation data set in the row data type labels of all grouping field data sets. Extract the sorting field value of each operation row data separately, and filter the row data whose sorting field values are adjacent to the sorting field value of the operation row data from all sorting field data sets associated with the target grouping field data set as adjacent row data, and determine the row sequence number of the operation row data based on the row sequence number of the adjacent row data, and perform page insertion. For example, if you need to insert a new "bond" financial instrument, the row data type label of "bond" is in the third group of row data type labels of all grouping field data sets. There are currently 4 rows in the first two groups of tags. The newly inserted bond has a term of 2y, which is located after the current 1y, so it is necessary to perform the insertion in the 4th+1+1=6th row. The schematic diagram of inserting the operation data set is as follows: Figure 6 shown.

[0081] It can be understood that the row data whose sorting field values are adjacent to the sorting field values of the operation row data, that is, the adjacent row data, refers to the row data whose sorting field values are arranged before and / or after the arrangement position of the sorting field values of the operation row data based on the sorting relationship between the sorting field values in the group.

[0082] Based on the same inventive concept as the first embodiment, the second embodiment provides Figure 7 The data processing device shown is based on row data type labels and includes: a grouping field data set acquisition module 21 for grouping row data with the same grouping field value in a target table into the same grouping field data set to obtain a plurality of grouping field data sets; a sorting field data set acquisition module 22 for grouping row data with the same sorting field value in each grouping field data set into the same sorting field data set to obtain a plurality of sorting field data sets associated with each grouping field data set; a row data type label generation module 23 for combining the grouping field values of all operation row data in an operation data set to generate a row data type label for the operation data set; a target grouping field data set screening module 24 for screening, from all grouping field data sets, a grouping field data set whose row data type label corresponds to the row data type label of the operation data set as a target grouping field data set; wherein the row data type label of the grouping field data set is obtained based on the grouping field value of any row data in the grouping field data set; and an operation data set insertion module 25 for determining the row sequence number of each operation row data set based on all sorting field data sets associated with the target grouping field data set, so as to insert the operation data set into the target table.

[0083] In a preferred embodiment, the data processing device based on row data type labels further includes: an adjacent grouping field data set screening module, which is used to screen, based on predefined business rules, grouping field data sets whose row data type labels are adjacent to the row data type label of the operation data set from all grouping field data sets as adjacent grouping field data sets when the target grouping field data set cannot be obtained; and an operation data set adding module, which is used to determine the row sequence number of each operation row data based on the adjacent grouping field data set, so as to add the operation data set to the target table.

[0084] In a preferred embodiment, the grouping field data set acquisition module 21 is specifically used to obtain the target table, extract the grouping field value of each row of data in the target table, and divide the row data with the same grouping field value and the corresponding row sequence number into the same grouping field data set to obtain several grouping field data sets.

[0085] In a preferred embodiment, the sorting field data set acquisition module 22 is specifically used to extract the sorting field value of each row of data in the grouping field data set for each grouping field data set, and divide the row data with the same sorting field value and the corresponding row sequence number into the same sorting field data set, so as to obtain several sorting field data sets associated with each grouping field data set.

[0086] In a preferred embodiment, the row data type label generation module 23 is specifically used to extract the grouping field values of each operation row data in the operation data set, and combine the grouping field values of each operation row data according to a preset grouping field combination order to generate a row data type label for the operation data set.

[0087] In a preferred embodiment, the row data type label generation module 23 is further configured to cache the row data type label of the operation data set after combining the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set.

[0088] In a preferred embodiment, the operation data set insertion module 25 is specifically used to extract the sorting field value of the operation row data for each operation row data, filter the row data whose sorting field values are adjacent to the sorting field value of the operation row data from all sorting field data sets associated with the target grouping field data set as adjacent row data, and determine the row sequence number of the operation row data based on the row sequence number of the adjacent row data.

[0089] Based on the same inventive concept as the first embodiment, the third embodiment provides a data processing device based on row data type labels, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. The memory is coupled to the processor, and when the processor executes the computer program, it implements the data processing method based on row data type labels as described in the first embodiment, and can achieve the same beneficial effects as described therein.

[0090] Based on the same inventive concept as the first embodiment, the fourth embodiment provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the data processing method based on row data type labels as described in the first embodiment, and can achieve the same beneficial effects.

[0091] Based on the same inventive concept as the first embodiment, the fifth embodiment provides a computer program product. When the computer program product runs on a computer, it enables the computer to execute the data processing method based on row data type labels as described in the first embodiment, and can achieve the same beneficial effects.

[0092] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0093] The method divides the row data in the target table into different grouping field data sets according to different grouping field values, divides the row data in each grouping field data set into different sorting field values according to different sorting field values, obtains several grouping field data sets and several sorting field data sets associated with each grouping field data set, combines the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set, filters the grouping field data sets corresponding to the row data type label of the operation data set from all grouping field data sets as the target grouping field data set, determines the row sequence number of each operation row data according to all sorting field data sets associated with the target grouping field data set, inserts the corresponding operation row data into the corresponding row of the target table, and completes the insertion of the operation data set into the target table without waiting for the user to complete the judgment, retrieval, and review operations, and without traversing all row data in the table for data verification each time row data is inserted into the table. The method can quickly and accurately insert row data into the table, and effectively improve the efficiency of table data processing.

[0094] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

[0095] Those skilled in the art will appreciate that all or part of the processes in the above embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium, and when executed, the program can include the processes in the above embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

Claims

1. A data processing method based on row data type labels, characterized in that: include: Divide the rows of data with the same grouping field value in the target table into the same grouping field dataset to obtain several grouping field datasets; respectively dividing the row data with the same sorting field value in each of the grouping field data sets into the same sorting field data set, to obtain a plurality of sorting field data sets associated with each of the grouping field data sets; Deduplication and combination are performed on the grouping field values of all operation row data in the operation data set to generate a row data type label of the operation data set; Filtering, from all the grouping field data sets, a grouping field data set whose row data type label corresponds to the row data type label of the operation data set as a target grouping field data set; wherein the row data type label of the grouping field data set is obtained according to the grouping field value of any row of data in each of the grouping field data sets; According to all sorting field data sets associated with the target grouping field data set, the row sequence number of each operation row data is determined to insert the operation data set into the target table.

2. The data processing method based on row data type labels according to claim 1, characterized in that: Also includes: When the target grouping field data set cannot be obtained, based on predefined business rules, grouping field data sets whose row data type labels are adjacent to the row data type label of the operation data set are filtered from all the grouping field data sets as adjacent grouping field data sets; The row sequence number of each of the operation row data is determined according to the adjacent grouping field data sets, so as to add the operation data sets to the target table.

3. The data processing method based on row data type labels according to claim 1, characterized in that: The row data with the same grouping field value in the target table is divided into the same grouping field data set to obtain several grouping field data sets, specifically: The target table is obtained, the grouping field value of each row of data in the target table is extracted respectively, and the row data with the same grouping field value and the corresponding row sequence number are divided into the same grouping field data set to obtain a plurality of the grouping field data sets.

4. The data processing method based on row data type labels according to claim 1, characterized in that: The row data with the same sorting field value in each of the grouping field data sets are divided into the same sorting field data set to obtain a plurality of sorting field data sets associated with each of the grouping field data sets, specifically: For each of the grouping field data sets, the sorting field value of each row of data in the grouping field data set is extracted respectively, and the row data with the same sorting field value and the corresponding row sequence number are divided into the same sorting field data set to obtain several sorting field data sets associated with each of the grouping field data sets.

5. The data processing method based on row data type label according to claim 1, characterized in that: The deduplication operation and combination of the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set is specifically: The grouping field values of each operation row data in the operation data set are extracted respectively, and the grouping field values of each operation row data are deduplicated and combined according to a preset grouping field combination order to generate a row data type label of the operation data set.

6. The data processing method based on row data type labels according to claim 1, characterized in that: After combining the grouping field values of all operation row data in the operation data set to generate the row data type label of the operation data set, the method further includes: Caches the row data type labels of the operation dataset.

7. The data processing method based on row data type labels according to claim 1, characterized in that: The determining of the row sequence number of each operation row data according to all sorting field data sets associated with the target grouping field data set is specifically as follows: For each of the operation row data, the sorting field value of the operation row data is extracted, and row data whose sorting field values are adjacent to the sorting field value of the operation row data are filtered from all the sorting field data sets associated with the target grouping field data sets as adjacent row data, and the row sequence number of the operation row data is determined based on the row sequence number of the adjacent row data.

8. A data processing device based on row data type labels, characterized in that: include: The grouping field data set acquisition module is used to group the row data with the same grouping field value in the target table into the same grouping field data set to obtain several grouping field data sets; A sorting field data set acquisition module is used to group row data with the same sorting field value in each grouping field data set into the same sorting field data set, and obtain a plurality of sorting field data sets associated with each grouping field data set; A row data type label generation module is used to perform deduplication operations and combinations on the grouping field values of all operation row data in the operation data set to generate a row data type label for the operation data set; a target grouping field data set screening module, configured to screen, from all the grouping field data sets, a grouping field data set whose row data type label corresponds to the row data type label of the operation data set as a target grouping field data set; wherein the row data type label of the grouping field data set is obtained based on the grouping field value of any row of data in each of the grouping field data sets; The operation data set inserting module is used to determine the row sequence number of each operation row data according to all sorting field data sets associated with the target grouping field data set, so as to insert the operation data set into the target table.

9. A data processing device based on row data type labels, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the memory is coupled to the processor, and when the processor executes the computer program, it implements the data processing method based on row data type labels as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the data processing method based on row data type labels according to any one of claims 1 to 7.

11. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program product is run on a computer, the computer program product enables the computer program product to execute the data processing method based on row data type labels according to any one of claims 1 to 7.

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