CN108664573A - A kind of quick processing system of big data and method with double-channel data library - Google Patents
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- 230000009897 systematic effect Effects 0.000 claims abstract description 8
- 230000009466 transformation Effects 0.000 claims description 25
- 238000006243 chemical reaction Methods 0.000 claims description 18
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- 238000006116 polymerization reaction Methods 0.000 description 5
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Abstract
The present invention relates to big data processing technology fields, disclose a kind of quick processing system of big data with double-channel data library, including condition judgment module, the first data processing module, the second data processing module and data interworking module, for wherein condition judgment module for presetting reference value in systems, the data volume that the condition of reference value and user input systems is formed carries out size comparison；First data processing module is used to, when condition data amount is less than reference value, the module be selected to carry out data processing；Second data processing module is used to, when condition data amount is more than reference value, the module be selected to carry out data processing；Data interchange module is converted to the return value of systematic unity identical with the data processed result format of the second data processing module, realizes data interchange for converting the data processed result of the first data processing module.It is switched fast use between present invention realization disparate databases.
Description
Technical field
The present invention relates to big data processing technology field, especially a kind of big data with double-channel data library is quickly located
Manage system and method.
Background technology
Database (Database) is to come tissue, storage and the warehouse for managing data according to data structure, with information skill
The development of art and market, data management are no longer only to store and manage data, and be transformed into the required various data of user
The mode of management.Database is there are many kinds of type, from the simplest table for being stored with various data to can carry out magnanimity number
It is all widely used in all fields according to the large-scale database system of storage.
MySQL is a kind of Relational DBMS, and relevant database saves the data in different tables,
Rather than all data are placed in one big warehouse, which adds speed and improve flexibility.MySQL is used
SQL language be the most frequently used standardized language for accessing database.MySQL softwares due to its is small, speed is fast,
The total cost of ownership is low, especially this feature of open source code, and the exploitation of general middle-size and small-size website all selects MySQL as net
It stands database.
MySQL has its shortcoming by oneself, such as small scale, function are limited, faces growing data, traditional pass
It is the demand that type database can not meet increasingly increased data, it is on complex query and unhappy, it is less efficient.
And Elasticsearch is the distributed full-text search engine of a high extension increased income, it can almost in real time
Storage, retrieval data；Autgmentability itself is fine, can expand to up to a hundred servers, handles the structuring or non-of PB ranks
Structural data.In recent years ElasticSearch development is swift and violent, has surmounted the role of its initial pure search engine, now
Data aggregate analysis and visual characteristic are increased.
And how to balance or be compatible with big data and relevant database MySQL and advanced database Elasticsearch
Contact be urgent problem instantly.
Invention content
In order to solve above-mentioned the deficiencies in the prior art, the invention discloses a kind of big data with double-channel data library is fast
Fast processing system and method, it is therefore an objective to realize between equilibrium relation type database MYSQL and advanced database Elasticsearch
Mutual switching use, and can quickly return to implementing result, increase the competitiveness of product.
To realize above-mentioned technical purpose and the technique effect, the invention discloses one kind having double-channel data library
The quick processing system of big data, including condition judgment module, the first data processing module, the second data processing module and data
Interworking module, wherein
The condition judgment module is formed the condition of reference value and user input systems for presetting reference value in systems
Data volume carry out size comparison；
First data processing module is used to, when condition data amount is less than reference value, the module be selected to carry out at data
Reason；
Second data processing module is used to, when condition data amount is more than reference value, the module be selected to carry out at data
Reason；
The data interchange module is converted to and for converting the data processed result of the first data processing module
The return value of the identical systematic unity of data processed result format of two data processing modules realizes data interchange.
Further, further include emergency processing module,
The emergency processing module is used for when condition data amount is more than reference value, and event occurs in second data module
When hindering and data can not be handled, the first data module is selected to carry out data processing.
Further, the data interchange module include transformation rule module and conversion output module,
The transformation rule module is used for through a data definition transformation rule, at the data to store the first data module
The rule that reason result format and the data processed result format of the second data module are converted,
The conversion output module is for the transformation rule according to transformation rule module, by the number of the first data module
According to handling result format conversion at the data processed result format of the second data module, the data of different data processing module are realized
Intercommunication.
The invention also discloses a kind of big data immediate processing methods with double-channel data library, have condition judgment mould
Block, the first data processing module, the second data processing module and data interworking module, described method includes following steps：
S1：Reference value is preset in systems, and the data volume that the condition of reference value and user input systems is formed carries out size ratio
Compared with；
S2：According to the judging result of S1, if condition data amount is less than reference value, the first data module is selected to carry out at data
Reason；
S3：According to the judging result of S1, if condition data amount is more than reference value, the second data module is selected to carry out at data
Reason；
S4：The data processed result of S2 is converted by data interchange module, is converted to the data processed result lattice with S3
The return value of the identical systematic unity of formula realizes data interchange.
5. a kind of big data immediate processing method with double-channel data library as claimed in claim 4, feature exist
In further including following steps：
S5：According to the judging result of S1, if condition data amount is more than reference value, when second data module breaks down
And when can not handle data, select the first data module to carry out data processing.
Further, the conversion described in step S4 the specific steps are：
S4-1：By a data definition transformation rule, data processed result format for storing the first data module and the
The rule that the data processed result format of two data modules is converted；
S4-2：According to the transformation rule described in step S4-1, by the data processed result format conversion of the first data module at
The data processed result format of second data module realizes the data interchange of different data processing module.
Further, the SQL statement that the sentence that first data module uses can perform for MySQL, described the
The json sentences that the sentence that two data modules use can perform for Elasticsearch.
Further, the condition includes one or more rule of user setting, can between a plurality of rule
A complex rule is formed in a manner of using and ask union, difference set or intersection.
Further, in the S1, the condition of user input systems forms XML data；
In the S2, the data processing specific method of the first data module refers to：XML data is read, XML data is parsed, is obtained
Each node data splits field, carries out condition splicing, then all conditions are merged, XML data is converted to SQL
Sentence executes data processing；
In the S3, the data processing specific method of the second data module refers to：It presets and XML data is converted into json sentences
Input and output rule, read XML data, converted according to input and output rule, XML data be converted into json sentences,
Data processing is executed by Elasticsearch；
In the S4, realize that the specific method of data interchange refers to：By a data definition MySQL tables, for storing SQL numbers
The rule converted according to handling result format and json data processed result formats；And according to the transformation rule, by SQL data
Handling result format conversion realizes the data interchange of different data processing module at json data processed result formats.
The invention has the advantages that：
（1）The quick processing system of big data and method of the present invention can be switched fast relevant database MySQL and new types of data
Language between the Elasticsearch of library makes to carry out accessible switching and use between MySQL and Elasticsearch.
（2）The present invention can quickly return to implementing result, increase the competitiveness of product, solve MySQL and looked into complex conditions
The persistent ailment that can not be returned the result in time in the case of asking big data.
Description of the drawings
Fig. 1 is the schematic block diagram of the quick processing system of big data with double-channel data library of the present invention.
Fig. 2 is the signal of the data interchange module of the quick processing system of big data with double-channel data library of the present invention
Property block diagram.
Fig. 3 is the schematic flow chart of the big data immediate processing method with double-channel data library of the present invention.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.
The present invention provides the quick processing system 10 of big data with double-channel data library, as shown in Figure 1, including：Condition
Judgment module 101, the first data processing module 102, the second data processing module 103 and data interworking module 104.Wherein,
Condition judgment module 101 is formed the condition of reference value and user input systems for presetting reference value in systems
Data volume carries out size comparison；
First data processing module 102 is used to, when condition data amount is less than reference value, the module be selected to carry out data processing；
Second data processing module 103 is used to, when condition data amount is more than reference value, the module be selected to carry out data processing；
Data interchange module 104 is converted to and for converting the data processed result of the first data processing module 102
The return value of the identical systematic unity of data processed result format of two data processing modules 103 realizes data interchange.
Further include emergency processing module 105,
Emergency processing module 105 is used for when condition data amount is more than reference value, and the second data module 104 breaks down and nothing
When method handles data, the first data module 103 is selected to carry out data processing.
As shown in Fig. 2, data interchange module 104 further comprises transformation rule module 1041 and conversion output module
1042。
Transformation rule module 1041 is used for by a data definition transformation rule, to store the first data module 102
The rule that data processed result format and the data processed result format of the second data module 103 are converted；
Output module 1042 is converted to be used for according to transformation rule mould transformation rule in the block, by the data of the first data module 102
Handling result format conversion realizes the number of different data processing module at the data processed result format of the second data module 103
According to intercommunication.
According to above system provided by the invention, the present invention also provides a kind of big data with double-channel data library is fast
Fast processing method has condition judgment module 101, the first data processing module 102, the second data processing module 103 and data
Interworking module 104.
As shown in figure 3, this method comprises the following steps：
S1：Reference value is preset in systems, and the data volume that the condition of reference value and user input systems is formed carries out size ratio
Compared with；
S2：According to the judging result of S1, if condition data amount is less than reference value, the first data module is selected to carry out at data
Reason；
S3：According to the judging result of S1, if condition data amount is more than reference value, the second data module is selected to carry out at data
Reason；
S4：The data processed result of S2 is converted by data interchange module, is converted to the data processed result lattice with S3
The return value of the identical systematic unity of formula realizes data interchange.Specifically, conversion the specific steps are：
S4-1：By a data definition transformation rule, data processed result format for storing the first data module and the
The rule that the data processed result format of two data modules is converted；
S4-2：According to the transformation rule described in step S4-1, by the data processed result format conversion of the first data module at
The data processed result format of second data module realizes the data interchange of different data processing module.
This method further includes following steps：
S5：According to the judging result of S1, if condition data amount is more than reference value, when the failure of the second data module can not
When handling data, the first data module is selected to carry out data processing.
Specifically, the SQL statement that the sentence that the first data module in the present embodiment uses can perform for MySQL, second
The json sentences that the sentence that data module uses can perform for Elasticsearch.
The condition of input system carries out personalized input according to the business demand of user itself, condition may include one or
A plurality of rule be may be used union, difference set or the mode of intersection is asked to form a complex rule condition between a plurality of rule.This
When, rule is more, and the relationship between rule is more interlocked, and finally formed rule is more complicated, using traditional equilibrium relation type number
Speed according to library MySQL is slower.
The condition of user input systems forms XML data.Reference value is preset in systems, and reference value and user are inputted into system
The data volume that the condition of system is formed carries out size comparison.
When the data volume of condition is less than reference value, equilibrium relation type database MySQL is used to carry out data processing at this time,
Processing speed is not slow.The specific method is as follows for data processing：XML data is read, XML data is parsed, obtains each node data,
Field is split, condition splicing is carried out, then all conditions is merged, XML data is converted into SQL statement, is passed through
MySQL executes data processing.
Specifically, the transformation rule that XML is converted to SQL is：
1, in XML<group>Node finds attribute es_table attributes, obtains the table name under attribute, and close to table
Connection.
1.1, multilist association uses EXISTS not EXISTS connections
2, in XML<group>Node finds attribute es_query=" aggs " attribute, obtains aggregation information under attribute
2.1, congruent point is defined：Define group by and having entrances
2.2, polymeric type is defined：Corresponding table tables information
2.3, definition polymerization radix：Define group by and having rules
2.4, Aggregation field is defined：Group by and having fields
2.5, polymerizing condition is defined：Group by and having numerical value
3, in XML<group>Node finds attribute all_customer attributes, returns to the result information of inquiry；
4, in XML<group>Node finds attribute es_field attributes, obtains field information under attribute；
5, in XML<group>Node finds attribute operator attributes, obtains conditional information under attribute
（5.1）Definition【String character types】In relationship：Many condition terms, be equal to term, not equal to must_not+term,
Including like, do not include notLike, be sky is null or=" ", be not sky is not null or!=" ", prefix matching
Like, suffix match like, prefix mismatch not like, suffix mismatches not like；
（5.2）Definition【Data time types】In relationship：Equal to AND, not equal to OR, earlier than equal to<=, be later than and be equal to>=, away from
From current>= and ；
（5.3）Definition【Int value types】In relationship：Equal to=, be not equal to!=, be more than>, be more than or equal to>=, be less than<, be less than etc.
In<=；
6, in XML<group>Node finds attribute<![CDATA[1]]>Attribute obtains numerical information under attribute；
7, table association, field and value combination, conditional combination are integrated into corresponding SQL statement.
When the data volume of condition is more than reference value, advanced database Elasticsearch is selected to carry out data processing, at this time by
The big data quantity that complex rule is formed, then if being handled with equilibrium relation type database MySQL, it may appear that processing speed is slow
Slow problem, and advanced database Elasticsearch then can rapidly return to implementing result.Data processing specific method is such as
Under：Preset by XML data be converted to json sentences input and output rule, read XML data, according to input and output rule into
Row conversion, is converted to json sentences by XML data, data processing is executed by Elasticsearch.Wherein, XML data is converted
It can be realized by using preset ES plug-in units for the input and output rule of json sentences, in ES plug-in units, define input
And output format rule, so that it may XML format is converted to json formats.
Specifically, the input and output rule that XML is converted to the ES plug-in units of json is：
1, in XML<group>Node finds attribute es_table attributes, obtains the table name under attribute, and be type to table
Association；
2, in XML<group>Node finds attribute es_query=" aggs " attribute, obtains aggregation information under attribute, conversion
It polymerize statement syntax at ES
2.1 are converted into polymerization mark aggregations,
2.2 association polymerization type
2.3 define radix cardinality definition polymerization numerical value
2.4 define Aggregation field field
2.5 define script conditions
3, in XML<group>Node finds attribute all_customer attributes, returns to ES result informations；
4, in XML<group>Node finds attribute es_field attributes, obtains ES field informations under attribute；
5, in XML<group>Node finds attribute operator attributes, obtains ES conditional informations under attribute
（5.1）Definition【String character types】In relationship：Many condition trems [" 0 ", " 1 "], it is equal to trem, is not equal to must_
Not trem, comprising wildcard, not comprising must_not wildcard, be sky must_not, be not sky exists, prefix
It matches wildcard, suffix match wildcard, prefix and mismatches must_not wildcard, suffix mismatch must_not
wildcard
（5.2）Definition【Data time types】In relationship：Equal to range to, it is not equal to must_not range
From to, earlier than equal to range to, be later than equal to range to, apart from current range to
（5.3）Definition【Int value types】In relationship：Equal to trem, it is not equal to must_not trem, more than range from
To, it is more than or equal to range to, is less than range to, is less than or equal to range to
6, type, document, field, association DSL conditions are combined, ES sentences is completed and integrates.
The data processed result of equilibrium relation type database MySQL is converted by data interchange module, is converted to
The return value of systematic unity identical with the data processed result format of advanced database Elasticsearch realizes that data are mutual
It is logical.Realize that the specific method of data interchange refers to：By a data definition MySQL tables, for storing SQL data processed result lattice
The rule that formula is converted with json data processed result formats；And according to the transformation rule, by SQL data processed result formats
Json data processed result formats are converted into, realize the data interchange of different data processing module.
Specifically, the content that MySQL tables define is：
Core xml rules
（1）Define XML base nodes<root></root>；
（2）Define bis- node layers of XML<group></group>, the addible scenes of group or attribute such as es_table are set
=（Tables of data）、es_query=（Conditional information）、all_customer=（The numerical value of return）:
2.1 define congruent point： es_query="aggs"
2.2 define polymeric type es_table=" XXX "
2.3 definition polymerization radix es_aggs=" cardinality "
2.4 define Aggregation field es_field=" XXX "
2.5 define polymerizing condition operator=" "
（3）Define each packet attributes of XML<term></term>；
（4）The database information of locating query corresponds to the index in the database and elasticsearch in MYSQL；
（5）Relationship between the definition more a same alike results of XML<relation></relation>；
（6）Splice Database field and field comparison
（6.1）XML field is defined with es_field=" "；
（6.2）XML comparisons are defined with operator=" "；
（6.2.1）Definition【String character types】In relationship：Many condition in, equal to equal, not equal to notEqual, include
Like, not comprising notLike, be sky isNull, be not sky isNotNull, prefix matching preLike, suffix match
PostLike, prefix mismatch notPreLike, suffix mismatches notPostLike；
（6.2.2）Definition【Data time types】In relationship：Equal between, not equal to notBetween, earlier than equal to
SmallerEqual, it is later than equal to largerEqual, apart from current earlierNow；
（6.2.3）Definition【Int value types】In relationship：Equal to equal, not equal to notEqual, be more than larger, be more than etc.
In largerEqual, it is less than smaller, less than or equal to smallerEqual；
（7）Define XML storage organizations.
The main concept of MySQL and Elasticserach data frameworks compare as listed in table 1.
1 MySQL of table and the main concept of Elasticserach data frameworks compare
| MySQL | Elasticserach |
| database | index |
| table | type |
| row | Document |
| column | field |
| schema | mapping |
| index | Everything is index |
| select * from | GET |
| INSERT | PUT |
| UPDATE | _UPDATE |
| DELETE | DEL |
This method further includes following steps：
When the data volume of condition is more than reference value, advanced database Elasticsearch should be selected into line number at this time
According to processing；But when advanced database Elasticsearch breaks down and can not handle data, system can select to balance
Relevant database MySQL carries out data processing.Although data processing speed can be slack-off at this time, in Elasticsearch
In the case of database failure, it is unlikely to the problem of system can not be run occur, ensure that the stable operation of system.
More than, it is merely preferred embodiments of the present invention, but scope of protection of the present invention is not limited thereto, it is any
Those familiar with the art in the technical scope disclosed by the present invention, all answer by the change or replacement that can be readily occurred in
It is included within the scope of the present invention.
Claims (9)
1. a kind of quick processing system of big data with double-channel data library, which is characterized in that including condition judgment module,
One data processing module, the second data processing module and data interworking module, wherein
The condition judgment module is formed the condition of reference value and user input systems for presetting reference value in systems
Data volume carry out size comparison；
First data processing module is used to, when condition data amount is less than reference value, the module be selected to carry out at data
Reason；
Second data processing module is used to, when condition data amount is more than reference value, the module be selected to carry out at data
Reason；
The data interchange module is converted to and for converting the data processed result of the first data processing module
The return value of the identical systematic unity of data processed result format of two data processing modules realizes data interchange.
2. a kind of quick processing system of big data with double-channel data library as claimed in claim 2, which is characterized in that also
Including emergency processing module,
The emergency processing module is used for when condition data amount is more than reference value, and event occurs in second data module
When hindering and data can not be handled, the first data module is selected to carry out data processing.
3. a kind of quick processing system of big data with double-channel data library as claimed in claim 2, which is characterized in that institute
The data interchange module stated include transformation rule module and conversion output module,
The transformation rule module is used for through a data definition transformation rule, at the data to store the first data module
The rule that reason result format and the data processed result format of the second data module are converted,
The conversion output module is for the transformation rule according to transformation rule module, by the number of the first data module
According to handling result format conversion at the data processed result format of the second data module, the data of different data processing module are realized
Intercommunication.
4. a kind of big data immediate processing method with double-channel data library has condition judgment module, the first data processing
Module, the second data processing module and data interworking module, which is characterized in that described method includes following steps：
S1：Reference value is preset in systems, and the data volume that the condition of reference value and user input systems is formed carries out size ratio
Compared with；
S2：According to the judging result of S1, if condition data amount is less than reference value, the first data module is selected to carry out at data
Reason；
S3：According to the judging result of S1, if condition data amount is more than reference value, the second data module is selected to carry out at data
Reason；
S4：The data processed result of S2 is converted by data interchange module, is converted to the data processed result lattice with S3
The return value of the identical systematic unity of formula realizes data interchange.
5. a kind of big data immediate processing method with double-channel data library as claimed in claim 4, which is characterized in that also
Include the following steps：
S5：According to the judging result of S1, if condition data amount is more than reference value, when second data module breaks down
And when can not handle data, select the first data module to carry out data processing.
6. a kind of big data immediate processing method with double-channel data library as claimed in claim 5, which is characterized in that step
Conversion described in rapid S4 the specific steps are：
S4-1：By a data definition transformation rule, data processed result format for storing the first data module and the
The rule that the data processed result format of two data modules is converted；
S4-2：According to the transformation rule described in step S4-1, by the data processed result format conversion of the first data module at
The data processed result format of second data module realizes the data interchange of different data processing module.
7. a kind of big data immediate processing method with double-channel data library as claimed in claim 6, which is characterized in that institute
The SQL statement that the sentence that the first data module stated uses can perform for MySQL, the sentence that second data module uses
The json sentences that can perform for Elasticsearch.
8. a kind of big data immediate processing method with double-channel data library as claimed in claim 7, which is characterized in that institute
The condition stated includes one or more rule of user setting, may be used between the described a plurality of rule ask union, difference set or
The mode of intersection forms a complex rule.
9. a kind of big data immediate processing method with double-channel data library as claimed in claim 8, which is characterized in that
In the S1, the condition of user input systems forms XML data；
In the S2, the data processing specific method of the first data module refers to：XML data is read, XML data is parsed, is obtained
Each node data splits field, carries out condition splicing, then all conditions are merged, XML data is converted to SQL
Sentence executes data processing；
In the S3, the data processing specific method of the second data module refers to：It presets and XML data is converted into json sentences
Input and output rule, read XML data, converted according to input and output rule, XML data be converted into json sentences,
Data processing is executed by Elasticsearch；
In the S4, realize that the specific method of data interchange refers to：By a data definition MySQL tables, for storing SQL numbers
The rule converted according to handling result format and json data processed result formats；And according to the transformation rule, by SQL data
Handling result format conversion realizes the data interchange of different data processing module at json data processed result formats.
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Cited By (2)
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|---|---|---|---|---|
| CN109542963A (en) * | 2018-10-31 | 2019-03-29 | 平安科技（深圳）有限公司 | Hospital data processing method and relevant apparatus based on big data |
| CN110008173A (en) * | 2019-03-07 | 2019-07-12 | 深圳市买买提信息科技有限公司 | A kind of method and device of data storage |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002259257A (en) * | 2001-03-05 | 2002-09-13 | Casio Comput Co Ltd | Document preparing device and method for automatically switching data transfer |
| CN103678609A (en) * | 2013-12-16 | 2014-03-26 | 中国科学院计算机网络信息中心 | Large data inquiring method based on distribution relation-object mapping processing |
| CN106294805A (en) * | 2016-08-15 | 2017-01-04 | 成都九鼎瑞信科技股份有限公司 | Data processing method and device |
| CN106709012A (en) * | 2016-12-26 | 2017-05-24 | 北京锐安科技有限公司 | Method and device for analyzing big data |
| CN107958080A (en) * | 2017-12-14 | 2018-04-24 | 上海特易信息科技有限公司 | A kind of big data report processing method based on ElasticSearch |
-
2018
- 2018-04-27 CN CN201810389728.6A patent/CN108664573A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002259257A (en) * | 2001-03-05 | 2002-09-13 | Casio Comput Co Ltd | Document preparing device and method for automatically switching data transfer |
| CN103678609A (en) * | 2013-12-16 | 2014-03-26 | 中国科学院计算机网络信息中心 | Large data inquiring method based on distribution relation-object mapping processing |
| CN106294805A (en) * | 2016-08-15 | 2017-01-04 | 成都九鼎瑞信科技股份有限公司 | Data processing method and device |
| CN106709012A (en) * | 2016-12-26 | 2017-05-24 | 北京锐安科技有限公司 | Method and device for analyzing big data |
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