CN110471925A - Realize the method and system that index data is synchronous in search system - Google Patents
Realize the method and system that index data is synchronous in search system Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The present invention discloses a kind of method and system for realizing that index data is synchronous in search system, is stored in the relational database of initial data after data change in the method, generation records the change log of the data alteration；The part to determine data change is parsed to the change log；Corresponding part in the index data of search system is synchronized according to the part that determining data change.Due to being only that the part changed for data synchronizes corresponding part in the index data of search system, synchrodata amount is small, greatly reduces index data synchronous time, and the part of real-time synchronization more new data change, ensure that the real-time of data；In addition, due to being only that the part changed for data synchronizes corresponding part in the index data of search system, synchrodata variation is smaller in the short time, and a small amount of simultaneously operating has substantially no effect on query performance, and needing synchronous data volume controllable, scalability is more preferable.
Description
Technical field
The present invention relates to search technique fields, more particularly, it relates to index number in a kind of realization search system
According to synchronous method and system.
Background technique
Search system, which refers to according to certain strategy, with specific computer program, collects information, carries out to information
After tissue and processing, retrieval service is provided for user, the system that the relevant information of user search is showed into user, and Solr is searched
Cable system is a kind of independent enterprise-level search system, and externally offer connects similar to the application programming of Web-service for it
Mouthful api interface, user can be by hypertext transfer protocol http requests, and that submits certain format to search engine server can
Extended markup language file generates index；It can also be operated by Http Get and propose search request, and obtain extensible markup
Language format returns the result.
The index used in above-mentioned solr search system is a kind of individual, physics to one or more columns per page in database table
A kind of storage organization for being ranked up of value, the index data simultaneous techniques used in solr search system, it is therefore an objective to will
Index data in solr search system is updated, to allow users to search out newest data, can be used for electric business quotient
Product search, library book search, search website news search etc., in existing solr search system, index data is synchronous to be used
Be full dose synchronization scheme, i.e., it is a new index, batch synchronization in newest data all write-in solr search systems is complete
Exchange index afterwards, new data comes into force, but the index synchronization scheme has following defects that
Since data volume is larger, and each Service Source is limited, therefore each full dose is synchronized and needed up to time half a day,
Synchronization time is long；In addition, due to occupying a large amount of Service Sources, including network, disk I/O etc., user query when data are synchronous
QPS is reduced, and influences query performance when synchronous；And since the full dose synchronized update time is long, and while synchronizing, influences query performance,
It can only update daily once, therefore the data that cannot be guaranteed that user searches out are always newest, poor in timeliness, and search for system
Most of data may be constant for a long time in system, repeat to synchronize every time, increase a large amount of unnecessary synchronous working amounts.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of methods and be for realizing that index data synchronizes in search system
System improves the synchronous timeliness of index data, reduces the shadow synchronized to query performance to reduce the index data synchronous time
It rings.
In order to solve the above technical problems, the present invention adopts the following technical scheme:
A method of realizing that index data is synchronous in solr search system, includes the following steps:
Enterprise resource planning carries out operation of data modification to the initial data in relational database；
It stores after being changed according to the exception processes to data in the relational database of initial data, generation records the number
According to the change log of alteration；
The change log data, and the change day that Maxwell component will acquire are obtained in real time by Maxwell component
Will batch data is sent to Kafka component, and Kafka component stores after receiving change log data；
The change log number of Kafka component storage is read by the Spark Streaming operation run on Spark engine
According to the change log data for parsing reading find the changed part of initial data to determine the part of data change；
Corresponding part in the index data of search system is synchronized according to the part that determining data change.
Wherein, packet is synchronized to corresponding part in the index data of search system according to the part that determining data change
It includes:
According to the part that determining data change, obtained by the Spark Streaming operation run on Spark engine
Newest data；Corresponding part in the index data of search system is synchronized according to the latest data of the acquisition.
Wherein, the relational database is mysql, and the change log is binlog log.
In addition, a kind of method for realizing that index data is synchronous in search system, includes the following steps:
It stores in the relational database of initial data after data change, generation records the change day of the data alteration
Will；
The part to determine data change is parsed to the change log；
Corresponding part in the index data of search system is synchronized according to the part that determining data change.
Preferably, further includes:
The change log, and the change log number that Maxwell component will acquire are obtained in real time by Maxwell component
It is stored after giving Kafka component, Kafka component to receive change log data according to Batch sending.
Preferably, the change log is parsed and includes: with the part for determining data change
The change log number of Kafka component storage is read by the Spark Streaming operation run on Spark engine
According to the change log data for parsing reading find the changed part of initial data to determine the part of data change.
Preferably, corresponding part in the index data of search system is synchronized according to the part that determining data change
Include:
According to the part that determining data change, obtained by the Spark Streaming operation run on Spark engine
Newest data；Corresponding part in the index data of search system is synchronized according to the latest data of the acquisition.
Wherein, the relational database is mysql, and the change log is binlog log.
In addition, a kind of system for realizing that index data is synchronous in search system comprising:
Change log generates processing module, in the relational database for storing initial data after data change, generates note
Record the change log of the data alteration；
Dissection process module is parsed the part to determine data change to the change log；
Synchronous processing module, for according to the part of determining data change to corresponding to portion in the index data of search system
Divide and synchronizes.
Preferably, the dissection process module obtains the change log by Maxwell component in real time, and
The change log batch data that Maxwell component will acquire is sent to Kafka component, and Kafka component receives change log data
After store；
The dissection process module also passes through the Spark Streaming operation run on Spark engine and reads Kafka group
The change log data of part storage, the change log data for parsing reading find the changed part of initial data to determine number
According to the part of change.
Compared with prior art, the invention has the following advantages:
Number in the relational database of initial data is stored in present invention realization search system in the synchronous method of index data
After change, the change log for recording the data alteration is generated；The change log is parsed to determine data
The part of change；Corresponding part in the index data of search system is synchronized according to the part that determining data change.By
In being only that corresponding part synchronizes in index data of the part to search system for data change, therefore, synchrodata
It measures small, greatly reduces index data synchronous time, and the part of real-time synchronization more new data change, ensure that the real-time of data
Property；In addition, due to being only that the part changed for data synchronizes corresponding part in the index data of search system, in short-term
Interior synchrodata variation is smaller, and a small amount of simultaneously operating has substantially no effect on query performance, and needs synchronous data volume controllable,
Scalability is more preferable.
Detailed description of the invention
Fig. 1 is a specific embodiment flow chart of the method that the present invention realizes that index data is synchronous in search system；
Fig. 2 is a specific embodiment composition block diagram of the system that the present invention realizes that index data is synchronous in search system；
Fig. 3 is a specific embodiment process of the method that the present invention realizes that index data is synchronous in solr search system
Figure.
Specific embodiment
With reference to Fig. 1, which is a specific embodiment of the method that the present invention realizes that index data is synchronous in search system
The method of flow chart, the present embodiment mainly includes the following steps:
Step S101 is stored in the relational database of initial data after data change, and generation records the data change feelings
The change log of condition, when specific implementation, for different relational databases, change log may be different, for example, having as one
Body embodiment, relational database can be mysql relational database, and change log can be binlog, due to different relation datas
Library, change log is also different, here without limitation to relational database and change log concrete type；
Step S102 is parsed the part to determine data change to the change log, when specific implementation, is needed pair
Change log is monitored, for example, maxwell component real time monitoring change log can be used for mysql relational database
Binlog, when specific implementation can also using other components, for example, canal component or mysql_streamer component etc.,
As long as being able to achieve monitoring and obtaining change log, it is not specifically limited here；
Step S103, the part changed according to determining data carry out corresponding part in the index data of search system same
Step, when specific implementation, the part that can be changed first according to determining data obtain newest data；Then according to the acquisition
Latest data corresponding part in the index data of search system is synchronized.
With reference to Fig. 2, which is a specific embodiment of the system that the present invention realizes that index data is synchronous in search system
Composition block diagram, specific mainly includes following module: change log generates processing module 11, dissection process module 12 and synchronization process
Module 13
Wherein change log generation processing module 11 is mainly used for data change in the relational database for storing initial data
Afterwards, the change log for recording the data alteration is generated, it has been observed that becoming in the present invention for different relational databases
More log may be different, for example, relational database can be mysql relational database, change log as a specific embodiment
It can be binlog, it has been observed that due to different relational databases, change log is also different, here to relational database and change
More log concrete type is without limitation；
The part that dissection process module 12 is mainly used for parsing the change log to determine data change, specifically
When realization, the dissection process module 12 can obtain in real time the change log by Maxwell component or other serviced components,
And the change log batch data that Maxwell component will acquire is sent to Kafka component, and Kafka component is by change log number
According to being stored after reception；In addition, heretofore described dissection process module 12 can also be by running on Spark engine
The change log data of Kafka component storage are read in Spark Streaming operation, and the change log data for parsing reading are found
The changed part of initial data with determine data change part；
The part that synchronous processing module 13 is mainly used for being changed according to determining data is in the index data of search system
Corresponding part synchronizes, and when specific implementation, the part that synchronous processing module 13 can be changed according to determining data first is obtained
Newest data；Then corresponding part in the index data of search system is synchronized according to the latest data of the acquisition,
Which is not described herein again.
Below with search system for solr search system, relational database uses mysql, the storage of mysql relational database
Electric business commodity data information, change log use binlog, pass through ERP enterprise resource planning, maxwell component, Kafka
Component and the cooperation of Spark platform realize that the index data of solr search system is synchronous, and with reference to Fig. 3, which is realization of the present invention
A specific embodiment flow chart of the synchronous method of index data, specifically mainly includes the following steps: in solr search system
Step S301, ERP enterprise resource planning carries out data change to the initial data in MySQL relational database
Processing, when specific implementation, for example, the initial data stored in MySQL relational database is mainly commodity ID and its title, up and down
The attribute informations such as frame, classification, description, ERP enterprise resource planning changes processing to merchandise news, for example, passing through ERP
Enterprise resource planning can increase commodity data, deleted, modified, be inquired, and illustrate, in ERP corporate resources meter
Increase commodity and its attribute information in the system of drawing, data are stored in the commodity data table of MySQL relational database by row after increase
In, it is as shown in table 1 below commodity data table, each commodity is stored as a line (identifying commodity with unique id) in the table, each
The data value and field name (including commodity id, title, upper undercarriage, classification id, description etc.) of column are corresponding；
Table 1
| id | name | is_on_line | category_id | detail |
| 1 | iphone 8 | 0 | 1 | Memory 64G... |
| 2 | iphone x | 1 | 1 | Memory 256G... |
In addition, table 2 show scheme of classes, category information, including classification id, title, description etc. are stored in the table；
Table 2
| id | name | description |
| 1 | Mobile phone | Mobile phone |
As an example, commodity can be deleted in ERP enterprise resource planning, the commodity are stored in after deletion
Correspondence row data in the commodity data table of MySQL relational database will be deleted and (use Unique ID commodity), in addition, In
Undercarriage information on commodity can be modified in ERP enterprise resource planning, data value is changed to 1 by 0 and (wherein 0 represents undercarriage, 1 represents
Restocking), the corresponding upper undercarriage field value of the commodity has been changed to 1 after modification；
In addition, commodity can be inquired in ERP enterprise resource planning, it can be in MySQL relation data according to commodity ID
Commodity data of the row are navigated in library, are checked out, are then shown in systems, which is not described herein again.
Step S302 is stored after being changed according to the exception processes to data in the relational database of initial data, is generated
The change log of the data alteration is recorded, when specific implementation, for example, MySQL relational database provides the ERP enterprise
All data after the change of source planning system are stored, and MySQL relational database passes through binlog log for change
Data recorded, for example, listings are changed to by 0 by taking the commodity listings of id=1 in above-mentioned modification table 1 as an example
1, MySQL relational database generates a binlog log after modification, and journal format is as follows:
The value of each field after the value and modification of each field before modifying is contained in the binlog log, wherein@1 is represented
The value of first character section, and so on ,@n represents the value of n-th of field, it has been observed that binlog log recording listings
1 is changed to by 0.
Step S303 obtains the change log by Maxwell component in real time, and Maxwell component will acquire
Change log batch data is sent to Kafka component, and Kafka component will store after change log data receiver, specific real
Now, for example, Maxwell component obtains binlog log, it is organized into json character string, to modify the quotient of id=1 in table 1
For product listings, listings are changed to 1 by 0, and format is as follows:
It mainly include three fields in json character string, operation is mode of operation, and data is modified data
(the inside include all field names and corresponding value), old be that (the inside includes all field names and corresponding for data before modification
Value), after the binlog log that Maxwell component will acquire in the present embodiment all changes into json character string, Batch sending is given
Kafka component, Kafka component store data after receiving, and use kafka component by binlog log number in the present embodiment
It after being received according to library and stores, is equivalent to and a large amount of binlog daily record datas to be treated are done into a caching, on the one hand may be used
To handle mass data in real time, binlog daily record data is on the other hand avoided to lose；
Step S304 reads the storage of Kafka component by the Spark Streaming operation run on Spark engine
Change log data, the change log data for parsing reading find the changed part of initial data to determine data change
Part, when specific implementation, for example, it is (artificial that the Spark Streaming operation write is submitted to operation on Spark engine
Nonintervention can be continued for operation and go down), the json character string stored in Kafka component is read in Spark Streaming operation,
The changed commodity id of initial data is found by parsing, it should be noted that passing through Spark Streaming in the present embodiment
Operation and the cooperation of Kafka component can handle mass data in real time, and it is same in real time that the part progress changed for data can be realized
Step updates, and ensure that the real-time of data；For example, the Spark Streaming operation run on Spark engine was at interval of 10 seconds
After (ensure that near real-time) requests a Kafka component, batch to obtain the json character string increased newly on Kafka component, pass through solution
The changed part of initial data (the commodity id=1 in example) is found in analysis, so that it is determined that the part of data change, here not
It repeats again；
Step S305, the part changed according to determining data carry out corresponding part in the index data of search system same
Step, when specific implementation, for example, the commodity of parsing discovery commodity id=1 are changed, then from the quotient of MySQL relational database
A line commodity data that id=1 is obtained in product tables of data, then according to classification category_id=1, from MySQL relation data
A line classification data that id=1 is obtained in the category information table in library, to the index data of solr search system after combining data
Middle corresponding part can synchronize, when specifically synchronizing, for example, as an example, to indexing in Solr search system
The synchronization process of data corresponding part can be divided into two steps, that is, delete the data of commodity id=1, as shown in table 4, delete front and back index
Data comparison can refer to shown in table 3 and table 4, and wherein table 3 is that index data, table 4 are to synchronize middle Solr in Solr system before synchronizing
Index data (after the data for deleting commodity id=1, not increasing) in search system；
Table 3
Table 4
In addition, after the index data of increase commodity id=1 as shown in table 5, increasing front and back data comparison, can refer to 4 He of table
Table 5；
Table 5
It should be noted that passing through parsing binlog log in the present embodiment, it may be determined that the part of data change, and due to only
It is that the part changed for data synchronizes corresponding part in the index data of solr search system, therefore, synchrodata
It measures small, greatly reduces the index data synchronous time, in addition, by kafka component by binlog daily record data in the present embodiment
It after library receives and stores, is equivalent to and a large amount of binlog daily record data is done into a caching, a large amount of numbers can be handled simultaneously
According to, avoid binlog daily record data from losing, and cooperated by Spark Streaming operation and Kafka component, at streaming
Reason can handle mass data in real time, it can be achieved that carrying out real-time synchronization update for the part of data change, ensure that the reality of data
Shi Xing.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of method for realizing that index data is synchronous in solr search system, which comprises the steps of:
Enterprise resource planning carries out operation of data modification to the initial data in relational database；
It stores after being changed according to the exception processes to data in the relational database of initial data, generation records the data and becomes
The change log of more situation；
The change log data, and the change log number that Maxwell component will acquire are obtained in real time by Maxwell component
It is stored after giving Kafka component, Kafka component to receive change log data according to Batch sending；
The change log data of Kafka component storage are read by the Spark Streaming operation run on Spark engine,
The change log data that parsing is read find the changed part of initial data to determine the part of data change；
Corresponding part in the index data of search system is synchronized according to the part that determining data change.
2. the method according to claim 1, wherein the part changed according to determining data is to search system
Corresponding part, which synchronizes, in index data includes:
According to the part that determining data change, obtained by the Spark Streaming operation run on Spark engine newest
Data；Corresponding part in the index data of search system is synchronized according to the latest data of the acquisition.
3. method according to claim 1 or 2, which is characterized in that the relational database is mysql, the change day
Will is binlog log.
4. a kind of method for realizing that index data is synchronous in search system, which comprises the steps of:
It stores in the relational database of initial data after data change, generation records the change log of the data alteration；
The part to determine data change is parsed to the change log；
Corresponding part in the index data of search system is synchronized according to the part that determining data change.
5. according to the method described in claim 4, it is characterized by further comprising:
The change log, and the change log data batch that Maxwell component will acquire are obtained in real time by Maxwell component
Amount is sent to Kafka component, and Kafka component stores after receiving change log data.
6. according to the method described in claim 5, it is characterized in that, being parsed to the change log to determine that data change
Part include:
The change log data of Kafka component storage are read by the Spark Streaming operation run on Spark engine,
The change log data that parsing is read find the changed part of initial data to determine the part of data change.
7. according to the method described in claim 6, it is characterized in that, the part changed according to determining data is to search system
Corresponding part, which synchronizes, in index data includes:
According to the part that determining data change, obtained by the Spark Streaming operation run on Spark engine newest
Data；Corresponding part in the index data of search system is synchronized according to the latest data of the acquisition.
8. according to the described in any item methods of claim 4-7, which is characterized in that the relational database is mysql, the change
More log is binlog log.
9. a kind of system for realizing that index data is synchronous in search system characterized by comprising
Change log generates processing module, in the relational database for storing initial data after data change, generates record institute
State the change log of data alteration；
Dissection process module is parsed the part to determine data change to the change log；
Synchronous processing module, for according to the part of determining data change to corresponding part in the index data of search system into
Row synchronizes.
10. system according to claim 9, which is characterized in that the dissection process module is real-time by Maxwell component
The change log is obtained, and the change log batch data that Maxwell component will acquire is sent to Kafka component, Kafka
Component stores after receiving change log data；
The dissection process module also passes through the Spark Streaming operation reading Kafka component run on Spark engine and deposits
The change log data of storage, the change log data for parsing reading find the changed part of initial data to determine that data become
Part more.
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| CN111506646A (en) * | 2020-03-16 | 2020-08-07 | 阿里巴巴集团控股有限公司 | Data synchronization method, device, system, storage medium and processor |
| CN112100276A (en) * | 2020-09-03 | 2020-12-18 | 上海微亿智造科技有限公司 | Data synchronization system, method and medium for processing database change in real time |
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