CN113934744A - Data sharing method and device - Google Patents
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- CN113934744A CN113934744A CN202111545558.4A CN202111545558A CN113934744A CN 113934744 A CN113934744 A CN 113934744A CN 202111545558 A CN202111545558 A CN 202111545558A CN 113934744 A CN113934744 A CN 113934744A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/219—Managing data history or versioning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
Abstract
The method comprises the steps of collecting a log file in a source database, obtaining updating data in the source database based on the log file, and sending the updating data to a first message processing system; transmitting, by the first message processing system, the update data to a database system consumption platform; performing operator chain filtering on the updated data at the consumption platform of the database system to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data; the target shared data is pushed to the data receiver, so that the update data in the source database is collected in real time in a non-invasive mode, the obtained update data is filtered and then sent to the data receiver, and the update data is shared.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a method and an apparatus for data sharing.
Background
In the micro-service architecture, a large amount of business data of an enterprise is stored in each business system database, so that the data share a large limit and a bottleneck, the invasion and low timeliness to the business exist, and the business can not be guaranteed to use the latest data in real time.
At present, the way of implementing data sharing by synchronous incremental data tools Canal, MySQL, and data transmission tool Sqoop is as follows: (1) each data user side requests corresponding data through an interface and caches the data to a local database; (2) extracting data from each system through Sqoop by a uniform data warehouse platform; (3) message transmission based on multicast broadcast service MBS. The timeliness of Sqoop data extraction is poor, generally, the timeliness of T +1 is poor, and the MBS-based message transmission needs to occupy a large amount of MBS resources, and the subscribed unified message is inconsistent with the required conditions. Therefore, the data sharing mode in the prior art has the problems of resource waste, low time efficiency and the like.
Disclosure of Invention
An object of the present application is to provide a data sharing method and device, which implement real-time acquisition of update data in a source database in a non-intrusive manner, and send the acquired update data to a data receiver after filtering, thereby implementing sharing of the update data.
According to an aspect of the present application, there is provided a method of data sharing, wherein the method includes:
collecting a log file in a source database, acquiring update data in the source database based on the log file, and sending the update data to a first message processing system;
transmitting, by the first message processing system, the update data to a database system consumption platform;
performing operator chain filtering on the updated data at the consumption platform of the database system to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data;
and pushing the target shared data to a data receiver.
Further, in the above data sharing method, the operator chain includes a data comparison rule and a conditional operator, and the performing operator chain filtering on the update data at the consumption platform of the database system to obtain target update data includes:
judging whether the updated data meets the data comparison rule or not on the database system consumption platform, and acquiring the updated data matched with the data comparison rule;
and performing conditional operator filtering on the update data matched with the data comparison rule to obtain target update data.
Further, in the above method for data sharing, the performing conditional operator filtering on the update data matched with the data comparison rule to obtain target update data includes:
and judging whether the updating data matched with the data comparison rule meets the condition operator or not, and determining the updating data meeting the condition operator in the updating data matched with the data comparison rule as the target updating data.
Further, in the above method for data sharing, the method further includes:
presetting a data structure for data formatting, wherein the data structure comprises the update data, the target update data and a transmission mode of the data receiver;
wherein the formatting the target update data to obtain the target shared data includes:
and formatting the target updating data according to the data structure to obtain the target shared data.
Further, in the above method for data sharing, pushing the target shared data to a data receiving side includes:
and pushing the target shared data to a target database or a second message processing system.
According to another aspect of the present application, there is also provided a non-volatile storage medium having computer readable instructions stored thereon, which, when executed by a processor, cause the processor to implement a method of data sharing as described above.
According to another aspect of the present application, there is also provided a device for data sharing, wherein the device includes:
one or more processors;
a non-volatile storage medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement a method of data sharing as described above.
Compared with the prior art, the method and the device have the advantages that the log file in the source database is collected, the updating data in the source database is obtained based on the log file, and the updating data is sent to the first message processing system; transmitting, by the first message processing system, the update data to a database system consumption platform; performing operator chain filtering on the updated data at the consumption platform of the database system to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data; the target shared data is pushed to the data receiver, so that the update data in the source database is collected in real time in a non-invasive mode, the obtained update data is filtered and then sent to the data receiver, and the update data is shared.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 illustrates a flow diagram of a method of data sharing in accordance with an aspect of the subject application;
FIG. 2 illustrates a schematic diagram of a particular embodiment of a method of data sharing in accordance with an aspect of the subject application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
Fig. 1 is a schematic flow chart of a data sharing method according to an aspect of the present application. Wherein the method comprises the following steps: step S11, step S12, step S13 and step S14, which specifically include the following steps:
step S11, collecting a log file in a source database, obtaining update data in the source database based on the log file, and sending the update data to a first message processing system. It should be noted that the source database is not fixed and may be configured as needed, so as to obtain the update data in the source database based on the log file; the form of the log file includes but is not limited to binary log file binlog, and the manner of collecting the log file in the source database includes but is not limited to collecting by erecting Canal; the update data refers to data that changes in the source database; the first message processing system needs to be able to satisfy the requirements of high throughput and real-time performance at the same time, including but not limited to the distributed publish-subscribe message system Kafka and the like.
Step S12, transmitting the updated data to a database system consumption platform through the first message processing system.
And step S13, performing operator chain filtering on the updated data in the database system consumption platform to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data. Here, the update data in the source database acquired based on the log file is not necessarily all data that needs to be shared, and therefore, an operator chain filter needs to be performed on the update data so as to obtain the required data, where in the process of performing the operator chain filter on the update data, the update data is subjected to filter cleaning and supplementation, so as to obtain the target update data; in order to enable the data receiving side to receive the target update data, the target update data needs to be formatted so as to obtain the target shared data that the data receiving side can receive.
And step S14, pushing the target shared data to a data receiver.
Here, the push method for pushing the target shared data to the data receiving side includes, but is not limited to, a database method, an MBS method, a Kafka method, and other push methods. The database mode represents that data are directly written into a database by using a Structured Query Language (SQL) statement; the MBS mode means that data is pushed to the MBS, and the MBS informs an interface of a data receiver to consume; the Kafka mode indicates that a data receiver consumes data in a pipeline by using Kafka as the data pipeline; in the present application, the pushing manner of the target shared data is preferably a database manner and a Kafka manner.
Through the steps from S11 to S14, the present application collects a log file in a source database, obtains update data in the source database based on the log file, and sends the update data to a first message processing system; transmitting, by the first message processing system, the update data to a database system consumption platform; performing operator chain filtering on the updated data at the consumption platform of the database system to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data; the target shared data is pushed to the data receiver, so that the update data in the source database is collected in real time in a non-invasive mode, the obtained update data is filtered and then sent to the data receiver, and the update data is shared.
For example, in a preferred embodiment of the present application, a nail database corresponding to a nail business service system is used as a source database, a Canal is erected to collect a log file binlog in the nail database, update data in the nail database is obtained based on the binlog, and the obtained update data is sent to the first message processing system Kafka; and performing operator chain filtering on the acquired updating data at a consumption platform of a database system, wherein if the Zen channel business service system is used as a data receiver and the Zen channel business service system needs a user name and a mobile phone number of a staff of a technical department, whether the updating data belongs to the staff of the technical department is judged through an operator chain piece, if so, the user name and the mobile phone number of the staff of the technical department are further acquired, so that the target updating data is acquired, and the target updating data is formatted and then pushed to the data receiver.
Next to the above embodiments of the present application, the operator chain includes a data comparison rule and a conditional operator, where the step S13 performs operator chain filtering on the update data in the database system consumption platform to obtain target update data, and specifically includes:
judging whether the updated data meets the data comparison rule or not on the database system consumption platform, and acquiring the updated data matched with the data comparison rule;
and performing conditional operator filtering on the update data matched with the data comparison rule to obtain target update data.
Here, the update data includes update operations such as addition, deletion, and modification, that is, the update data includes all update data currently in the source database, and since only data for monitoring the source database needs to be acquired from the update data, the update data needs to be preliminarily filtered according to the data comparison rule in the operator chain, and the update data is matched with the data comparison rule to obtain update data meeting the data comparison rule, that is, obtain monitored data in the source database.
The whole database system comprises at least one independent database, each independent database corresponds to one business service system, when one of the databases is determined as the source database, if the data in the source database is changed and updated, the service system corresponding to the other database in the database system will serve as the data receiver to receive the updated data from the source database meeting the needs of itself, when data in one database in the database system changes and updates, the changed data can be filtered through the operator chain, therefore, the data required by the data receiver is obtained, so that the updated data in the source database can be synchronized to the data receiver according to the requirement of the data receiver, and the data sharing of the updated data is realized. After the update data matched with the data comparison rule is obtained through the data comparison rule in the operator chain, conditional operator filtering needs to be performed on the update data matched with the data comparison rule, wherein the conditional operator is used for indicating conditions met by data needed by a data receiving party, namely the data receiving party performs filtering according to the conditional operator, so that the data needed by the data receiving party is obtained from the update data matched with the comparison rule.
For example, in a preferred embodiment of the present application, the nailing database is used as the source database, and the employee table in the nailing database is monitored, so as to obtain the updated data in the employee table in real time. The nail database may include data information such as a department table and a payroll table in addition to the employee table, and if data in the employee table, the department table and the payroll table are changed currently, the update data in the nail database acquired based on the log file may include all current update data in the employee table, the department table and the payroll table, and the data to be acquired is only the update data in the employee table, and the update information acquired based on the log file includes not only the update data in the employee table but also the update data in the department table and the payroll table, so that the update data in the needed employee table needs to be acquired through a data comparison rule. And if the updated data acquired based on the log file contains the data in the monitored staff table, acquiring the data in the monitored staff table from the updated data acquired based on the log file, namely acquiring the updated data meeting the data comparison rule, so as to perform conditional operator filtering on the updated data meeting the data comparison rule subsequently, thereby acquiring target updated data.
Next, in the above embodiment of the present application, the performing conditional operator filtering on the update data matched with the data comparison rule in step S13 to obtain target update data specifically includes:
and judging whether the updating data matched with the data comparison rule meets the condition operator or not, and determining the updating data meeting the condition operator in the updating data matched with the data comparison rule as the target updating data.
The whole database system comprises at least one independent database, each independent database corresponds to one business service system, and the condition operators corresponding to the business service systems are preset, namely the conditions met by the data required by each business service system are preset, so that when at least one business service system is used as a data receiving party, the relevant data can be acquired according to the requirement of the business service system. After the update data matched with the data comparison rule is obtained, a push target under the rule is obtained, namely, the transmission mode of each business service system serving as a data receiving party is determined, the condition operator corresponding to each business service system is further obtained, and the target update data corresponding to each business service system is respectively obtained according to the condition operator corresponding to each business service system. For example, if the gender classification in the data subjected to the filtering cleaning is "0" and "1", where "0" represents male and "1" represents female, but the gender classification in the data subjected to the filtering cleaning is "male" and "female", at this time, the gender data subjected to the filtering cleaning is supplemented, the data classified as "0" is supplemented to "male" and the data classified as "1" is supplemented to "female", so as to meet the requirement of the data receiving party on the data.
For example, in a preferred embodiment of the present application, if two databases, namely a nail database and a zen channel database, exist in the database system, wherein the nail database corresponds to the nail business service system, and the zen channel database corresponds to the zen channel business service system, in the present application, nail condition operators corresponding to the nail business service system and zen channel condition operators corresponding to the zen channel business service system are preset. When monitoring the employee list in the staple database, at the moment, the Zen channel business service system serves as a data receiver, after the updated data matched with the data comparison rule is obtained through the data comparison rule in the operator chain, the updated data matched with the data comparison rule is filtered according to the Zen channel condition operator, and the target updated data required by the Zen channel business service system is obtained. If the obtained update data matched with the data comparison rule at this time is the name "zhang san", the gender "0", the age "23" and the mobile phone number "1234567890" in the employee table, and the conditions in the zenith condition operator are the name "and the mobile phone number", the target update data obtained after the update data in the employee table is filtered by the zenith condition operator are the name "zhang san" and the mobile phone number "1234567890".
Following the foregoing embodiments of the present application, a method for data sharing according to an aspect of the present application further includes:
presetting a data structure for data formatting, wherein the data structure comprises the update data, the target update data and a transmission mode of a data receiver;
wherein the formatting the target update data to obtain the target shared data includes:
and formatting the target updating data according to the data structure to obtain the target shared data.
In order to determine which update data the target update data comes from and to which specific data receiver the target update data is to be pushed in transmission, before pushing the target update data, formatting the target update data is required to make the target update data be pushed in a preset data structure. Wherein the update data portion in the data structure indicates from which update data the target update data comes; the transmission mode part of the data receiver in the data structure indicates in what way the target update data is to be pushed to which specific target data receiver.
Next, the aforementioned embodiment of the present application, wherein the pushing the target shared data to the data receiving side includes:
and pushing the target shared data to a target database or a second message processing system.
The target database is a database of the data receiver, and the second message processing system is a message processing system of the data receiver; if the data receiver does not need to further process the target shared data, namely the internal system of the data receiver does not have related downstream services which need to use the target shared data, pushing the target shared data to a target database; and if the data receiver needs to further process the target shared data, namely the internal system of the data receiver has related downstream services which need to use the target shared data, pushing the target shared data to a second message processing system so that the data receiver can perform subsequent processing on the target shared data. In the application, preferably, the target shared data is pushed to a target database, namely, a database of a data receiver, in a database manner; and pushing the target shared data to a second message processing system, namely the message processing system Kafka (such as a distributed publish-subscribe message system Kafka) of the data receiver in a Kafka mode.
For example, when the obtained target shared data includes the mobile phone number "1234567890", if the data receiving party needs to further obtain the verification code of the mobile phone number, it indicates that the data receiving party needs to perform subsequent operations on the mobile phone number at this time, and therefore, the data receiving party needs to directly send the mobile phone number "1234567890" to the second message processing system, that is, the message processing system Kafka of the data receiving party, so that the data receiving party obtains the corresponding verification code based on the obtained mobile phone number "1234567890".
The specific implementation of the present application is illustrated in a preferred embodiment, as shown in fig. 2, in which, preferably, the log files in the source database are collected by erecting a Canal, the source database adopts a MySQL database, wherein, the source database comprises merchant data, commodity data and user data, when the commodity data and the user data in the source database are subjected to UPDATE operations such as INSERT, UPDATE and DELETE, through the binary log file binlog in the erected Canal collection source database, and based on binlog, obtaining the updating data in the commodity data and the user data, and sending the obtained updating data to the first message processing system Kafka, transmitting the update data to a database system consumption platform (DBS consumption platform) by the first message processing system Kafka in a message stream, wherein the update data is contained in the messages of the message stream; consuming messages on the consumption platform of the database system, namely consuming messages in a message stream, analyzing message contents, namely obtaining the update data, and performing operator chain filtering on the update data, wherein the update data which accords with the data comparison rule is obtained according to the data comparison rule in the operator chain, namely the update data which is matched with the data comparison rule is obtained, specifically, if the data which monitors the source database system is merchant data, because the obtained update data only comprises commodity data and user data, no update data which is matched with the data comparison rule exists at the moment, subsequent operation is not performed any more, if the data which monitors the source database system is commodity data, because the obtained update data comprises commodity data, the update data which is matched with the data comparison rule is obtained according to the data comparison rule, if the data for monitoring the source database system is user data, acquiring update data matched with the data comparison rule according to the data comparison rule because the update data acquired this time contains the user data; acquiring a pushing target under a rule, namely determining a transmission mode of a data receiver, determining a specific data receiver according to the transmission mode of the data receiver, and further determining a conditional operator of the data receiver; performing conditional operator filtering on the update data matched with the data comparison rule to obtain the target update data; acquiring the push data under the rule to obtain formatted target shared data, determining a transmission mode of a data receiver of a data structure part for formatting according to the previously acquired push target under the rule, further determining a data structure for formatting the target and the updated data, and formatting the target updated data according to the determined data structure to obtain the target shared data; and acquiring a push mode, determining the push mode for pushing the target shared data to the data receiver according to the previously acquired push target under the rule, and further pushing the target shared data to the data receiver according to the determined push mode.
According to another aspect of the present application, there is also provided a non-volatile storage medium having computer readable instructions stored thereon, which, when executed by a processor, cause the processor to implement a method of data sharing as described above.
According to another aspect of the present application, there is also provided a device for data sharing, wherein the device includes:
one or more processors;
a non-volatile storage medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement a method of data sharing as described above.
Here, for details of each embodiment of the data sharing device, reference may be specifically made to corresponding parts of the embodiment of the data sharing method, and details are not described herein again.
In summary, collecting a log file in a source database, acquiring update data in the source database based on the log file, and sending the update data to a first message processing system; transmitting, by the first message processing system, the update data to a database system consumption platform; performing operator chain filtering on the updated data at the consumption platform of the database system to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data; the target shared data is pushed to the data receiver, so that the update data in the source database is collected in real time in a non-invasive mode, the obtained update data is filtered and then sent to the data receiver, and the update data is shared.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (7)
1. A method of data sharing, wherein the method comprises:
collecting a log file in a source database, acquiring update data in the source database based on the log file, and sending the update data to a first message processing system;
transmitting, by the first message processing system, the update data to a database system consumption platform;
performing operator chain filtering on the updated data at the consumption platform of the database system to obtain target updated data, and performing formatting processing on the target updated data to obtain target shared data;
and pushing the target shared data to a data receiver.
2. The method of claim 1, wherein the operator chain comprises data comparison rules and conditional operators, wherein the operator chain filtering the update data at the database system consumption platform to obtain target update data comprises:
judging whether the updated data meets the data comparison rule or not on the database system consumption platform, and acquiring the updated data matched with the data comparison rule;
and performing conditional operator filtering on the update data matched with the data comparison rule to obtain target update data.
3. The method of claim 2, wherein the performing conditional operator filtering on the update data matched with the data comparison rule to obtain target update data comprises:
and judging whether the updating data matched with the data comparison rule meets the condition operator or not, and determining the updating data meeting the condition operator in the updating data matched with the data comparison rule as the target updating data.
4. The method of claim 1, wherein the method further comprises:
presetting a data structure for data formatting, wherein the data structure comprises the update data, the target update data and a transmission mode of the data receiver;
wherein the formatting the target update data to obtain the target shared data includes:
and formatting the target updating data according to the data structure to obtain the target shared data.
5. The method of claim 1, wherein pushing the target shared data to a data recipient comprises:
and pushing the target shared data to a target database or a second message processing system.
6. A non-transitory storage medium having stored thereon computer readable instructions which, when executed by a processor, cause the processor to implement the method of any one of claims 1 to 5.
7. An apparatus for data sharing, wherein the apparatus comprises:
one or more processors;
a non-volatile storage medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-5.
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Application publication date: 20220114 |