CN115587584A - Big data comparison method and system in financial field - Google Patents
Big data comparison method and system in financial field Download PDFInfo
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Abstract
The invention relates to the technical field of computers, in particular to a big data comparison method and a big data comparison system in the financial field, wherein the method comprises the following steps: acquiring first data source data and second data source data, and preprocessing the first data source data and the second data source data through a preset data unloading rule; obtaining a preset number of peer block areas according to the data type and the content block storage, and distributing the same identification to each pair of peer block areas; cutting the content of file blocks of first data source data and second data source data with the same identification into fields, and extracting keywords; comparing all keywords in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule, and determining a corresponding target library table unit; comparing the data contents of the corresponding target library table units according to a preset comparison rule; and obtaining an alignment result. The method is used for solving various problems caused by comparison of mass data of the new system and the old system in the system reconstruction process.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a big data comparison method and a big data comparison system in the financial field.
Background
The banking business involves financial money, requires accurate data, and has extremely high requirements on the safety and stability of system operation. Therefore, the software system of the banking business has the characteristics of high system complexity and low function upgrading fault-tolerant rate.
In recent years, with the improvement of requirements for user experience, new service development, autonomous research and development core technology and the like, the banking industry develops large-scale service flow reconstruction and software system reconstruction upgrading work, wherein for large-scale reconstruction projects such as system reconstruction, software and hardware replacement and the like, basic data comparison before and after reconstruction is a necessary link for guaranteeing stable operation of a system and product quality. In actual operation, the data of banking business has the characteristics of large data volume, non-uniform new and old data formats, complex mapping rules and the like, and under the condition of limited implementation period, the working efficiency of manually comparing a large amount of data is very low, and the comparison by one item is easy to careless. Particularly, for a scene of comparing mass data of new and old systems reconstructed by the system, a general flow solution is urgently needed in the face of problems of different data sources, format difference, complex comparison mapping rules and the like which may exist in the data.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a big data comparison method and a big data comparison system in the financial field, which are used for a scene of comparing mass data of a new system and an old system in the system reconstruction process, so as to solve the problem of data comparison difficulty caused by different data sources, format difference and complex comparison mapping rules.
In order to achieve the above purpose, the technical scheme adopted by the invention comprises the following steps:
the invention discloses a big data comparison method in the financial field in a first aspect, which comprises the following steps:
acquiring first data source data and second data source data, and respectively preprocessing the first data source data and the second data source data through a preset data unloading rule;
respectively storing the first data source data and the second data source data in a blocking mode according to the data types and the content, generating a preset number of file blocks of the first data source data and file blocks of the second data source data, matching the file blocks of the first data source data and the file blocks of the second data source data in a peer-to-peer mode, and distributing the same identification to each pair of peer-to-peer file blocks of the first data source data and the second data source data;
respectively cutting the contents of file blocks of first data source data and second data source data with the same identification into fields, and extracting keywords;
comparing all keywords in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule, and determining a corresponding target library table unit;
comparing the data contents of the corresponding target library table units according to a preset comparison rule to obtain a comparison result of the first data source data and the second data source data and storing the comparison result;
and displaying the comparison result through a visual window.
Further, the preprocessing is respectively carried out through a preset data unloading rule, and the preprocessing comprises the elimination of format difference and precision difference of data.
Further, the preset mapping rule includes: and constructing a mapping associated word library, and setting mapping associated words to associate corresponding keywords in the first data source and the second data source.
Further, the comparing the data content of the corresponding target library table unit according to the preset comparison rule includes: and comparing the fields of the corresponding target library table units one by one.
Further, the keyword comprises one or more of a customer number, customer identity information, a data amount type and a currency symbol.
Further, the comparison rule configuration file is set to be in an xml format.
Furthermore, the comparison result displayed through the visual window comprises identification of the difference field and marking, and the comparison result is clearly displayed on a browser interface.
In a second aspect of the present invention, a big data comparing system in the financial field is disclosed, comprising:
the preprocessing module is used for acquiring first data source data and second data source data and respectively preprocessing the first data source data and the second data source data according to a preset data unloading rule;
the cutting module is used for respectively storing the first data source data and the second data source data in a blocking mode according to the data types and the content, generating a preset number of file blocks of the first data source data and file blocks of the second data source data, enabling the file blocks of the first data source data and the file blocks of the second data source data to be matched and equal, and distributing the same identification to each pair of equal file blocks of the first data source data and the second data source data;
the processing module is used for cutting the contents of the file blocks of the first data source data and the second data source data with the same identification into fields respectively and acquiring keywords;
the mapping module is used for comparing all key words in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule to determine a corresponding target library table unit;
the comparison module is used for comparing the data content of the corresponding target library table unit according to a preset comparison rule to obtain a comparison result of the first data source data and the second data source data and storing the comparison result;
and displaying the comparison result through a visual window.
In a third aspect of the invention, a computer-readable storage medium is disclosed, on which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out the above-mentioned method.
In a fourth aspect of the invention, an electronic device is disclosed, comprising a processor and a memory;
the memory is used for storing operation instructions;
the processor is used for executing the method by calling the operation instruction.
In a fifth aspect of the invention, a computer program product is disclosed, comprising computer programs and/or instructions which, when executed by a processor, implement the steps of the above-described method.
The invention has the beneficial effects that:
by adopting the method and the system for comparing the big data in the financial field, all keywords in the file blocks of the first data source data and the second data source data with the same identification are compared according to the preset mapping rule, and the corresponding target library table unit is locked; then comparing the data contents of the corresponding target library table units according to a preset comparison rule; the full quantity comparison of new and old system data can be completed, in the comparison process, the difference data can be rapidly and accurately captured, rapid error correction is realized, the comparison requirements of a large amount of data brought by large-scale reconstruction such as system reconstruction and software and hardware replacement are met, and the personnel efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a big data comparison method in the financial field according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a big data comparison system in the financial field according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention relates to a big data comparison method in the financial field, which comprises the following steps:
s1, acquiring first data source data and second data source data, and respectively preprocessing the first data source data and the second data source data according to a preset data unloading rule;
s2, respectively storing the first data source data and the second data source data in a blocking mode according to the data types and the content, generating a preset number of file blocks of the first data source data and file blocks of the second data source data, matching the file blocks of the first data source data and the file blocks of the second data source data in an equivalent mode, and distributing the same identification to each pair of the file blocks of the equivalent first data source data and the file blocks of the equivalent second data source data;
s3, respectively cutting the contents of the file blocks of the first data source data and the second data source data with the same identification into fields, and acquiring keywords;
s4, comparing all keywords in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule, and determining a corresponding target library table unit;
s5, comparing the data contents of the corresponding target library table units according to a preset comparison rule to obtain a comparison result of the first data source data and the second data source data and storing the comparison result;
and S6, displaying the comparison result through a visual window.
In this embodiment, the first data source data and the second data source data are from different data sources respectively, the data sources optionally include mysql, oracle, gaussDB, and the like, the first data source data is old system data, the second data source data is new system data, the first data source data and the second data source data have differences in data format, data storage format, or precision, and the pre-processing includes eliminating the format differences, storage format differences, and precision differences of the data through a preset data unloading rule.
In this embodiment, the data to be compared is written into the HDFS by using the pre-configured script, and the HDFS is a mature highly fault-tolerant distributed system, can provide data access with high throughput, and is suitable for large-scale data access.
Illustratively, taking the amount data as an example, the original system data is mysql DOUBLE type, the new system data is oracle demimal (5,2), and in order to prevent the situation that mysql data is 1.00000000000001 during data unloading, the original system data is processed by TRUNCATE (price, 2) during data unloading operation; for example, the remark field for the data source information in the original system data, the original system data is in xml format,
<site><name>GOOGLE</name><url><！[CDATA[https://www.google.com]]></url></site>，
the new system data is in the json format,
the method comprises the steps of { "site" { "name": GOOGLE "," url ": https:// www.google.com" } }, and comparing whether the site.url in the new and old system data is consistent or not, namely analyzing the two sides of data and extracting corresponding https:// www.google.com.
In this embodiment, the preset mapping rule includes: and constructing a mapping associated word library, and setting mapping associated words to associate corresponding keywords in the first data source and the second data source.
Preferably, the keyword preferably includes a customer number, customer identity information, a data amount type, and a currency symbol.
Wherein, according to the preset comparison rule, comparing the data content of the corresponding target library table unit, including: and comparing the fields of the corresponding target library table units one by one.
In the financial system, the system reconstruction related to foreign exchange business is carried out, the currency field of the old system is currency abbreviation, the new system uses digital codes, and the comparison can be carried out after the field is converted. Illustratively, the value of the renminbi in the old system is CNY, the value in the new system is 156, and the CNY of the old system needs to be mapped into 156 according to a configured mapping table during comparison, and then the CNY is compared with the new system value.
For some more complex scenario applications, such as customer number conversion, etc., mapping rules cannot be described in a configuration file in an enumeration manner, and then a related conversion method needs to be developed by itself to complete comparison in a program. Illustratively, the client code length in the old system is 10 bits, the client code length in the new system is 12 bits, the extra 2 leading digits are used for database routing, and when comparison is performed, only the 10-bit digits after data truncation is performed in the new system. For the data comparison of the above scenes, the design of the comparison rule needs to have good expandability, and can support the new business data comparison requirement with minimum change, so that the comparison rule configuration file adopts an xml format which has good readability, strong expandability and is convenient for java processing.
Specifically, the alignment rule is exemplified as follows:
<RECORD filetype_A＝"split"filetype_B＝"split"split_character_A＝"|@|"split_character_B＝"|@|">
<item name_A＝"TradeID"index_A＝"1"name_B＝"TradeID"index_B＝"2"is_key＝"trye"DateType＝"string"ifCompare＝"true"/>
</RECORD>
the first line shows that each line of text of the file A and the file B is split through | @ | split symbols, tradeID is in the 1 st field after the text A is split, the 2 nd field after the text B is split is of a string type, and data of the same TradeID in the is _ key text A and the same data of the same TradeID in the text B are put together to be used as a comparison set for comparison.
By adopting the method for comparing the big data in the financial field, all keywords in the file blocks of the first data source data and the second data source data with the same identification are compared according to the preset mapping rule, and the corresponding target library table unit is locked; then comparing the data contents of the corresponding target library table units according to a preset comparison rule; the full quantity comparison of new and old system data can be completed, in the comparison process, the difference data can be rapidly and accurately captured, rapid error correction is realized, the comparison requirements of a large amount of data brought by large-scale reconstruction such as system reconstruction and software and hardware replacement are met, and the personnel efficiency is improved.
Another aspect of the present invention also relates to a big data comparison system in the financial field, the structure of which is shown in fig. 2, including:
the preprocessing module is used for acquiring first data source data and second data source data and respectively preprocessing the first data source data and the second data source data according to a preset data unloading rule;
the cutting module is used for respectively storing the first data source data and the second data source data in a blocking mode according to the data types and the content, generating a preset number of file blocks of the first data source data and file blocks of the second data source data, matching the file blocks of the first data source data and the file blocks of the second data source data in an equivalent mode, and distributing the same identification to each pair of the file blocks of the equivalent first data source data and the file blocks of the equivalent second data source data;
the processing module is used for respectively cutting the contents of the file blocks of the first data source data and the second data source data with the same identification into fields and acquiring keywords;
the mapping module is used for comparing all key words in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule to determine a corresponding target library table unit;
the comparison module is used for comparing the data content of the corresponding target library table unit according to a preset comparison rule to obtain a comparison result of the first data source data and the second data source data and storing the comparison result;
and the display module displays the comparison result through a visual window.
By using this system, the above-described arithmetic processing method can be executed and a corresponding technical effect can be achieved.
Embodiments of the present invention also provide a computer-readable storage medium capable of implementing all the steps of the method in the above embodiments, the computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements all the steps of the method in the above embodiments.
Embodiments of the present invention further provide an electronic device for executing the method, as an implementation apparatus of the method, the electronic device at least includes a processor and a memory, and particularly, the memory stores data and related computer programs required for executing the method, and the processor calls the data and the programs in the memory to execute all steps of the implementation method, so as to obtain corresponding technical effects.
Preferably, the electronic device may comprise a bus architecture, which may include any number of interconnected buses and bridges linking together various circuits including one or more processors and memory. The bus may also link various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the receiver and transmitter. The receiver and transmitter may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium. The processor is responsible for managing the bus and general processing, while the memory may be used for storing data used by the processor in performing operations.
Additionally, the electronic device may further include a communication module, an input unit, an audio processor, a display, a power source, and the like. The processor (or controller, operational controls) employed may include a microprocessor or other processor device and/or logic device that receives input and controls the operation of various components of the electronic device; the memory may be one or more of a buffer, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices, and may store the above-mentioned related data information, and may also store a program for executing the related information, and the processor may execute the program stored in the memory to realize information storage or processing, etc.; the input unit is used for providing input to the processor, and can be a key or a touch input device; the power supply is used for supplying power to the electronic equipment; the display is used for displaying display objects such as images and characters, and may be an LCD display, for example. The communication module is a transmitter/receiver that transmits and receives signals via an antenna. The communication module (transmitter/receiver) is coupled to the processor to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal. Based on different communication technologies, a plurality of communication modules, such as a cellular network module, a bluetooth module and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) is also coupled to a speaker and a microphone via an audio processor to provide audio output via the speaker and receive audio input from the microphone to implement the usual telecommunication functions. The audio processor may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor is also coupled to the central processor, so that recording on the local machine can be realized through the microphone, and sound stored on the local machine can be played through the loudspeaker.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A big data comparison method in the financial field is characterized by comprising the following steps:
acquiring first data source data and second data source data, and respectively preprocessing the first data source data and the second data source data through a preset data unloading rule;
respectively storing the first data source data and the second data source data in a blocking mode according to the data types and the content, generating a preset number of file blocks of the first data source data and file blocks of the second data source data, matching the file blocks of the first data source data and the file blocks of the second data source data in a peer-to-peer mode, and distributing the same identification to each pair of peer-to-peer file blocks of the first data source data and the second data source data;
respectively cutting the contents of file blocks of first data source data and second data source data with the same identification into fields, and extracting keywords;
comparing all keywords in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule, and determining a corresponding target library table unit;
comparing the data content of the corresponding target library table unit according to a preset comparison rule to obtain a comparison result of the first data source data and the second data source data and storing the comparison result;
and displaying the comparison result through a visual window.
2. The method of claim 1, wherein the pre-processing by the predetermined data offload rule comprises eliminating format differences and precision differences of the data.
3. The method of claim 1 or 2, wherein the preset mapping rule comprises: and constructing a mapping associated word library, and setting mapping associated words to associate corresponding keywords in the first data source and the second data source.
4. The method according to claim 1 or 2, wherein the comparing the data contents of the corresponding target library table unit according to a preset comparison rule comprises: and comparing the fields of the corresponding target library table units one by one.
5. The method of claim 1, wherein the keywords comprise one or more of customer number, customer identity information, data amount type, and currency symbol.
6. The method of claim 1, wherein the displaying the comparison result through the visual window comprises identifying and marking the difference field for clear display in a browser interface.
7. A big data comparison system in the financial field is characterized by comprising:
the preprocessing module is used for acquiring first data source data and second data source data and respectively preprocessing the first data source data and the second data source data according to a preset data unloading rule;
the cutting module is used for respectively storing the first data source data and the second data source data in a blocking mode according to the data types and the content, generating a preset number of file blocks of the first data source data and file blocks of the second data source data, enabling the file blocks of the first data source data and the file blocks of the second data source data to be matched and equal, and distributing the same identification to each pair of equal file blocks of the first data source data and the second data source data;
the processing module is used for respectively cutting the contents of the file blocks of the first data source data and the second data source data with the same identification into fields and acquiring keywords;
the mapping module is used for comparing all key words in file blocks of the first data source data and the second data source data with the same identification according to a preset mapping rule to determine a corresponding target library table unit;
the comparison module is used for comparing the data content of the corresponding target library table unit according to a preset comparison rule to obtain a comparison result of the first data source data and the second data source data and storing the comparison result;
and the display module displays the comparison result through a visual window.
8. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 6.
9. An electronic device comprising a processor and a memory;
the memory is used for storing operation instructions;
the processor is used for executing the method of any one of claims 1 to 6 by calling the operation instruction.
10. A computer program product comprising a computer program and/or instructions, characterized in that the computer program and/or instructions, when executed by a processor, implement the steps of the method of any one of claims 1 to 6.
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