CN110309162A - A kind of optimization method and server-side of ES more new data - Google Patents
A kind of optimization method and server-side of ES more new data Download PDFInfo
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- CN110309162A CN110309162A CN201910513718.3A CN201910513718A CN110309162A CN 110309162 A CN110309162 A CN 110309162A CN 201910513718 A CN201910513718 A CN 201910513718A CN 110309162 A CN110309162 A CN 110309162A
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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
- G06F16/22—Indexing; Data structures therefor; Storage structures
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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
- G06F16/2358—Change logging, detection, and notification
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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
- G06F16/2365—Ensuring data consistency and integrity
Abstract
The invention discloses the optimization methods and server-side of a kind of ES more new data, obtain index data more new information, and index data is updated information update to real time data library unit；Judge whether to reach default renewal time, if so, the index data in real time data library unit is updated information update to full dose Database Unit；The present invention is indexed data by real time data library unit and updates, then timing is updated into full dose Database Unit again, it ensure that the data integrity of full dose Database Unit, simultaneously, when system is based on full dose Database Unit and real time data library unit progress data query, since the data volume being indexed in the real time data library unit of update and data query simultaneously is smaller, so when carrying out data update, influence for the search efficiency of user will be much smaller than the prior art, to realize in the case where big data quantity, the quick update of data and efficiently inquiry are supported simultaneously.
Description
Technical field
The present invention relates to ES technical field, in particular to the optimization method and server-side of a kind of ES more new data.
Background technique
ElasticSearch, abbreviation ES, it is the search server based on Lucene.It is based on RESTful web
Interface simultaneously provides the full-text search engine of a distributed multi-user ability, ElasticSearch be developed with Java, and
It is Enterprise search engine currently popular as the open source code publication under Apache license terms.Designed for cloud computing
In, real-time search can be reached, stablized, it is reliably, quickly, easy to install and use.
In existing many projects, index storage is all to accelerate the efficiency of inquiry with this using ES.Although big
In most cases, the search efficiency of ES is very high and uses the project of ES and can also be basically completed relevant query function.Than in full
According to amount within 1,000,000,000 rank magnitudes, then the requirement of most projects, the inquiry and correlation of index can be substantially completed
Updating operation can also be normally carried out.But high concurrent request application scenarios under, if data volume continues to increase, into
When line index data update, then server regular hour and resource can be occupied, so that the search efficiency of user is affected, so that
Quick data query is unable to reach using the project of ES.
Summary of the invention
The technical problems to be solved by the present invention are: the optimization method and server-side of a kind of ES more new data are provided, so that
It obtains in big data quantity, supports the quick update of data and efficiently inquiry.
In order to solve the above-mentioned technical problem, the technical solution adopted by the present invention are as follows:
A kind of optimization method of ES more new data, comprising steps of
S1, index data more new information is obtained, the index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, by the index number in the real time data library unit
According to update information update to full dose Database Unit.
In order to solve the above-mentioned technical problem, the another technical solution that the present invention uses are as follows:
A kind of optimization server-side of ES more new data, including memory, processor and storage on a memory and can located
The computer program run on reason device, the processor perform the steps of when executing the computer program
S1, index data more new information is obtained, the index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, by the index number in the real time data library unit
According to update information update to full dose Database Unit.
The beneficial effects of the present invention are: a kind of optimization method and server-side of ES more new data pass through real-time data base
Unit is indexed data update, and then timing is updated into full dose Database Unit again, ensure that full dose Database Unit
Data integrity, meanwhile, when system is based on full dose Database Unit and real time data library unit progress data query, due to simultaneously
The data volume being indexed in the real time data library unit of update and data query is smaller, so when carrying out data update, it is right
It to be much smaller than the prior art in the influence of the search efficiency of user, to realize in the case where big data quantity, while supporting number
According to it is quick update with efficiently inquiry.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of the optimization method of ES more new data of the embodiment of the present invention；
Fig. 2 is a kind of structural schematic diagram of the optimization server-side of ES more new data of the embodiment of the present invention；
Fig. 3 is a kind of optimization server-side of ES more new data of the embodiment of the present invention and the connection schematic diagram of other modules.
Label declaration:
1, the optimization server-side of a kind of ES more new data；2, processor；3, memory.
Specific embodiment
To explain the technical content, the achieved purpose and the effect of the present invention in detail, below in conjunction with embodiment and cooperate attached
Figure is explained.
Please refer to Fig. 1, a kind of optimization method of ES more new data, comprising steps of
S1, index data more new information is obtained, the index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, by the index number in the real time data library unit
According to update information update to full dose Database Unit.
As can be seen from the above description, the beneficial effects of the present invention are: data are indexed more by real time data library unit
Newly, then timing is updated into full dose Database Unit again, ensure that the data integrity of full dose Database Unit, meanwhile, it is
When system carries out data query based on full dose Database Unit and real time data library unit, due to being indexed update and data simultaneously
Data volume in the real time data library unit of inquiry is smaller, so when carrying out data update, for the search efficiency of user
Influence to be much smaller than the prior art, to realize in the case where big data quantity, while support the quick update of data with it is efficient
Inquiry.
Further, the step S1 specifically:
S1, index data more new information is obtained, the index data is updated into information update to hour data library unit；
It is further comprised the steps of: between the step S1 and the step S2
S20, judge whether current time and the time difference of previous renewal time hour are super after an hour, if so, by institute
The index data stated in hour data library unit updates information update Summer Solstice or the Winter Solstice Database Unit；
The step S2 specifically:
S2, current time and the time difference of proxima luce (prox. luc) renewal time are judged whether more than one day, if so, by the number of days
Information update is updated to full dose Database Unit according to the index data in library unit.
As can be seen from the above description, i.e. by subdivision day Database Unit and hour data library unit, when index data carries out
When update, data in real-time update hour data library unit, then timing is updated to day Database Unit, day database list
Timing is updated to full dose Database Unit member again.When day Database Unit is updated to full dose Database Unit, due to being logical
The operation of batch updating index is crossed to carry out, overall request number of times is fewer than the number that existing frequent updating indexes very much.Separately
Outside for repeatedly updating same index in the short time, the application only needs only to be updated within one day time once, phase
For existing frequent updating index, so the influence that the application requests high concurrent will be much smaller than the prior art, thus
The search efficiency of user can be improved.
Further, the step S2 further include:
After index data update information update is finished to full dose Database Unit, the real-time data base is deleted
The index data more new information in unit.
As can be seen from the above description, the data in real time data library unit are deleted after having updated, to reduce real time data
The storage pressure of library unit, while will receive the last influence updated but also update not next time, it ensure that renewal speed
With update accuracy.
Further, it further comprises the steps of:
S3, obtain data inquiry request, from the full dose Database Unit obtain full dose query result, from it is described in real time
Real-time query result is obtained in Database Unit；
S4, judge the full dose query result and the real-time query result with the presence or absence of identical first ID, and if it exists,
Then data cover corresponding to the first ID described in the real-time query result is fallen first described in the full dose query result
Data corresponding to ID, have been updated query result；
Query result has been updated described in S5, return.
As can be seen from the above description, i.e. when carrying out data query, in order to guarantee the data of customer inquiries be it is newest, understand from
Inquire simultaneously duplicate removal in full dose Database Unit and real time data library unit, although real time data library unit is to carry out at the same time
Index data updates and data query, but the data volume of real time data library unit is very small, so being indexed data
Also very small for the influence of data query while update, data query twice adds duplicate removal also can be than frequent updating rope again
Delay caused by drawing will more efficiently.
Further, the step S4 specifically:
The full dose query result and the real-time query result are put into set and gathered, to have been updated inquiry knot
Fruit.
Wherein, set set includes HashSet, LinkedHashSet and TreeSet, and the characteristics of HashSet is unordered
And the element in set does not repeat, the HashSet that LinkedHashSet is ordered into, TreeSet can go to reorder automatically no matter
Be it is wherein any, all have the function of duplicate removal, all query results can be covered, with guarantee obtain newest inquiry
As a result.
As can be seen from the above description, carrying out covering operation automatically by set set, guarantee the efficiency of data query.
Referring to figure 2. and Fig. 3, a kind of optimization server-side of ES more new data, including memory, processor and it is stored in
On memory and the computer program that can run on a processor, the processor are realized following when executing the computer program
Step:
S1, index data more new information is obtained, the index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, by the index number in the real time data library unit
According to update information update to full dose Database Unit.
As can be seen from the above description, the beneficial effects of the present invention are: data are indexed more by real time data library unit
Newly, then timing is updated into full dose Database Unit again, ensure that the data integrity of full dose Database Unit, meanwhile, it is
When system carries out data query based on full dose Database Unit and real time data library unit, due to being indexed update and data simultaneously
Data volume in the real time data library unit of inquiry is smaller, so when carrying out data update, for the search efficiency of user
Influence to be much smaller than the prior art, to realize in the case where big data quantity, while support the quick update of data with it is efficient
Inquiry.
Further, the step S1 specifically:
S1, index data more new information is obtained, the index data is updated into information update to hour data library unit；
It is further comprised the steps of: between the step S1 and the step S2
S20, judge whether current time and the time difference of previous renewal time hour are super after an hour, if so, by institute
The index data stated in hour data library unit updates information update Summer Solstice or the Winter Solstice Database Unit；
The step S2 specifically:
S2, current time and the time difference of proxima luce (prox. luc) renewal time are judged whether more than one day, if so, by the number of days
Information update is updated to full dose Database Unit according to the index data in library unit.
As can be seen from the above description, i.e. by subdivision day Database Unit and hour data library unit, when index data carries out
When update, data in real-time update hour data library unit, then timing is updated to day Database Unit, day database list
Timing is updated to full dose Database Unit member again.When day Database Unit is updated to full dose Database Unit, due to being logical
The operation of batch updating index is crossed to carry out, overall request number of times is fewer than the number that existing frequent updating indexes very much.Separately
Outside for repeatedly updating same index in the short time, the application only needs only to be updated within one day time once, phase
For existing frequent updating index, so the influence that the application requests high concurrent will be much smaller than the prior art, thus
The search efficiency of user can be improved.
Further, the step S2 further include:
After index data update information update is finished to full dose Database Unit, the real-time data base is deleted
The index data more new information in unit.
As can be seen from the above description, the data in real time data library unit are deleted after having updated, to reduce real time data
The storage pressure of library unit, while will receive the last influence updated but also update not next time, it ensure that renewal speed
With update accuracy.
Further, it further comprises the steps of:
S3, obtain data inquiry request, from the full dose Database Unit obtain full dose query result, from it is described in real time
Real-time query result is obtained in Database Unit；
S4, judge the full dose query result and the real-time query result with the presence or absence of identical first ID, and if it exists,
Then data cover corresponding to the first ID described in the real-time query result is fallen first described in the full dose query result
Data corresponding to ID, have been updated query result；
Query result has been updated described in S5, return.
As can be seen from the above description, i.e. when carrying out data query, in order to guarantee the data of customer inquiries be it is newest, understand from
Inquire simultaneously duplicate removal in full dose Database Unit and real time data library unit, although real time data library unit is to carry out at the same time
Index data updates and data query, but the data volume of real time data library unit is very small, so being indexed data
Also very small for the influence of data query while update, data query twice adds duplicate removal also can be than frequent updating rope again
Delay caused by drawing will more efficiently.
Further, the step S4 specifically:
The full dose query result and the real-time query result are put into set and gathered, to have been updated inquiry knot
Fruit.
As can be seen from the above description, carrying out covering operation automatically by set set, guarantee the efficiency of data query.
Please refer to Fig. 1, the embodiment of the present invention one are as follows:
The application scenarios of the present embodiment are that scene more than 1,000,000,000 data amounts uses, and following full dose database lists
Member is the storage recording unit of total data, and real time data library unit is the storage recording unit of real-time update.
A kind of optimization method of ES more new data, comprising steps of
S1, index data more new information is obtained, index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, the index data in real time data library unit is updated letter
Breath is updated to full dose Database Unit, after index data update information update is finished to full dose Database Unit, deletes real
When Database Unit in index data more new information.
When needing to carry out data query, following steps are executed:
S3, data inquiry request is obtained, full dose query result is obtained from full dose Database Unit, from real-time data base list
Real-time query result is obtained in member；
S4, judge full dose query result and real-time query result with the presence or absence of identical first ID, and if it exists, then will be real-time
Data cover corresponding to the first ID falls data corresponding to the first ID in full dose query result in query result, has been updated
Query result, in the present embodiment, the step specifically: full dose query result and real-time query result are put into set and gathered,
To have been updated query result；
S5, return have updated query result.
Referring to figure 2., the embodiment of the present invention two are as follows:
The application scenarios of the present embodiment are that scene more than 1,000,000,000 data amounts uses, and following full dose database lists
Member is the storage recording unit of total data, and day Database Unit is the storage recording unit of daily more new data, hour data
Library unit is the storage recording unit of more new data per hour.
A kind of optimization method of ES more new data, on the basis of the above embodiment 1, real-time data base in the present embodiment
Unit includes day Database Unit and hour data library unit, the specific implementation process is as follows:
Step S1 specifically: obtain index data more new information, index data is updated into information update to hour data library
When unit, i.e. each data change, the information in full dose Database Unit and day Database Unit will not be modified, it will according to small
When mode only record update data information into hour data library unit；
It is further comprised the steps of: between step S1 and step S2
S20, judge whether current time and the time difference of previous renewal time hour are super after an hour, if so, by small
When Database Unit in index data update information update Summer Solstice or the Winter Solstice Database Unit, and delete hour data after the completion of update
All index datas more new information stored in library unit；
Step S2 specifically: judge current time and the time difference of proxima luce (prox. luc) renewal time whether more than one day, if so,
By the index data update information update in day Database Unit to full dose Database Unit, and number of days is deleted after the completion of update
According to all index datas more new information stored in library unit.
It in the present embodiment, is the acquisition full dose query result from full dose Database Unit when carrying out data query, from
Day query result is obtained in day Database Unit, and hour query result is inquired from hour data library unit；
S4, judge full dose query result and day query result with the presence or absence of identical first ID, and if it exists, then to inquire day
As a result data cover corresponding to the first ID falls data corresponding to the first ID in full dose query result in, obtains day updating inquiry
As a result；Judge to update day query result and hour query result again with the presence or absence of identical first ID, and if it exists, then look into hour
It askes data cover corresponding to the first ID in result and falls to update data corresponding to the first ID in query result day, to obtain
Update query result.
In order to make it easy to understand, the present embodiment concrete example is as follows: in certain inquiry, being inquired from full dose Database Unit A
The data of 10 ID come out out, to obtain a set；Later, 4 ID can be inquired in day Database Unit B, to obtain b set,
Wherein there are 3 ID to gather in a in b set；Later, 2 ID can be inquired from hour data library unit C, to obtain c set,
Wherein there is 1 ID to gather in b in c set；Then, using b gather in latest data covering a gather, at this time a set in number
According to being full dose Database Unit plus the latest data in day Database Unit；Data in c set are reused to gather to cover a,
Data will be that full dose Database Unit adds day Database Unit plus the newest number in hour data library unit in a set at this time
According to finally obtained 10 ID after merging, and data therein have all been that day Database Unit or hour data library are single
Latest data in member.
Referring to figure 2. and Fig. 3, the embodiment of the present invention three are as follows:
A kind of optimization server-side 1 of ES more new data, including memory 3, processor 2 and be stored on memory 3 and can
The step of computer program run on processor 2, processor 2 realizes above-described embodiment one when executing computer program.
As shown in figure 3, a kind of optimization server-side 1 of ES more new data includes ES and data transferring module, wherein ES includes
Full dose Database Unit, day Database Unit and hour data library unit are by Data Migration module periodically by hour data library
Data in unit are updated to day Database Unit, and then timing updates the data in day Database Unit to full dose database
Unit.
As shown in figure 3, the process of entire data query is as follows: client request api interface, api interface request are relevant
ES cluster is assembled, and finally return that user with carrying out the acquisitions of data after getting related data.
Referring to figure 2. and Fig. 3, the embodiment of the present invention four are as follows:
A kind of optimization server-side 1 of ES more new data, on the basis of above-described embodiment three, processor 2 executes computer
The step of above-described embodiment two are realized when program.
In conclusion the optimization method and server-side of a kind of ES more new data provided by the invention, when index data carries out
When update, data in real-time update hour data library unit, then timing is updated to day Database Unit, day database list
Timing is updated to full dose Database Unit member again, ensure that the data integrity of full dose Database Unit, meanwhile, it is based on full dose number
Data query is carried out according to library unit, day Database Unit and hour data library unit, although hour data library unit is same
When be indexed data and update and data query, but the data volume of hour data library unit is very small, so carrying out rope
Argument is also very small according to influence while update for data query, and data query three times adds duplicate removal also can be than frequent again
Updating delay caused by index will more efficiently；In addition, when day Database Unit is updated to full dose Database Unit, by
The operation of batch updating index is then passed through to carry out, overall request number of times is fewer than the number that existing frequent updating indexes very
It is more.In addition for repeatedly updating same index in the short time, the application only needs only to be updated one within one day time
It is secondary, for relatively existing frequent updating index, so the influence that the application requests high concurrent will be much smaller than the prior art,
To realize in the case where big data quantity, while supporting the quick update of data and efficiently inquiry；In addition, having updated it
Afterwards, the data in real time data library unit are deleted, to reduce the storage pressure of real time data library unit, while but also next time
The influence that not will receive last update or not, ensure that renewal speed and updates accuracy.
The above description is only an embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalents made by bright specification and accompanying drawing content are applied directly or indirectly in relevant technical field, similarly include
In scope of patent protection of the invention.
Claims (10)
1. a kind of optimization method of ES more new data, which is characterized in that comprising steps of
S1, index data more new information is obtained, the index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, more by the index data in the real time data library unit
New information is updated to full dose Database Unit.
2. a kind of optimization method of ES more new data according to claim 1, which is characterized in that the step S1 is specific
Are as follows:
S1, index data more new information is obtained, the index data is updated into information update to hour data library unit；
It is further comprised the steps of: between the step S1 and the step S2
S20, judge whether current time and the time difference of previous renewal time hour are super after an hour, if so, by described small
When Database Unit in the index data update information update Summer Solstice or the Winter Solstice Database Unit；
The step S2 specifically:
S2, current time and the time difference of proxima luce (prox. luc) renewal time are judged whether more than one day, if so, by the day database
The index data in unit updates information update to full dose Database Unit.
3. a kind of optimization method of ES more new data according to claim 1, which is characterized in that the step S2 is also wrapped
It includes:
After index data update information update is finished to full dose Database Unit, the real time data library unit is deleted
In the index data more new information.
4. a kind of optimization method of ES more new data according to claim 1, which is characterized in that further comprise the steps of:
S3, data inquiry request is obtained, full dose query result is obtained from the full dose Database Unit, from the real time data
Real-time query result is obtained in library unit；
S4, judge the full dose query result and the real-time query result with the presence or absence of identical first ID, and if it exists, then will
Data cover corresponding to first ID described in the real-time query result falls the first ID institute described in the full dose query result
Corresponding data, have been updated query result；
Query result has been updated described in S5, return.
5. a kind of optimization method of ES more new data according to claim 4, which is characterized in that the step S4 is specific
Are as follows:
The full dose query result and the real-time query result are put into set and gathered, to have been updated query result.
6. a kind of optimization server-side of ES more new data, including memory, processor and storage on a memory and can handled
The computer program run on device, which is characterized in that the processor performs the steps of when executing the computer program
S1, index data more new information is obtained, the index data is updated into information update to real time data library unit；
S2, judge whether to reach default renewal time, if so, more by the index data in the real time data library unit
New information is updated to full dose Database Unit.
7. a kind of optimization server-side of ES more new data according to claim 6, which is characterized in that the step S1 is specific
Are as follows:
S1, index data more new information is obtained, the index data is updated into information update to hour data library unit；
It is further comprised the steps of: between the step S1 and the step S2
S20, judge whether current time and the time difference of previous renewal time hour are super after an hour, if so, by described small
When Database Unit in the index data update information update Summer Solstice or the Winter Solstice Database Unit；
The step S2 specifically:
S2, current time and the time difference of proxima luce (prox. luc) renewal time are judged whether more than one day, if so, by the day database
The index data in unit updates information update to full dose Database Unit.
8. a kind of optimization server-side of ES more new data according to claim 6, which is characterized in that the step S2 is also wrapped
It includes:
After index data update information update is finished to full dose Database Unit, the real time data library unit is deleted
In the index data more new information.
9. a kind of optimization server-side of ES more new data according to claim 6, which is characterized in that further comprise the steps of:
S3, data inquiry request is obtained, full dose query result is obtained from the full dose Database Unit, from the real time data
Real-time query result is obtained in library unit；
S4, judge the full dose query result and the real-time query result with the presence or absence of identical first ID, and if it exists, then will
Data cover corresponding to first ID described in the real-time query result falls the first ID institute described in the full dose query result
Corresponding data, have been updated query result；
Query result has been updated described in S5, return.
10. a kind of optimization server-side of ES more new data according to claim 9, which is characterized in that the step S4 tool
Body are as follows:
The full dose query result and the real-time query result are put into set and gathered, to have been updated query result.
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| CN116959656A (en) * | 2023-08-18 | 2023-10-27 | 成都医星科技有限公司 | Medical main index extraction merging method and system based on ES |
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