CN104951552A - Big data statistical method and system used for big data statistics - Google Patents
Big data statistical method and system used for big data statistics Download PDFInfo
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- CN104951552A CN104951552A CN201510367373.7A CN201510367373A CN104951552A CN 104951552 A CN104951552 A CN 104951552A CN 201510367373 A CN201510367373 A CN 201510367373A CN 104951552 A CN104951552 A CN 104951552A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24564—Applying rules; Deductive queries
- G06F16/24565—Triggers; Constraints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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Abstract
The invention relates to the technical field of big data processing, in particular to a big data statistical method and a system used for big data statistics. The method comprises the steps of timing statistics and dynamic idle time statistics. The timing statistics and the dynamic idle time statistics are executed at the same time. According to the method, the timing statistics and the dynamic idle time statistics are combined, statistics is carried out on archived data during dynamic idle time, the needed statistic data can be obtained fast and accurately when statistic analysis is carried out on the mass data, when statistic faults occur during the dynamic idle time, statistics is carried out on the archived data in a timing mode so that the statistic foundation can be provided for carrying out statistic analysis on the mass data, and it is ensured that the needed statistic data can be obtained fast.
Description
Technical field
The present invention relates to large technical field of data processing, particularly relate to a kind of large data statistical approach and the system for large data statistics.
Background technology
Enter 2012, large data (big data) word is mentioned more and more, and people describe with it the mass data produced with definition information explosion time generation.By the end of 2012, data volume rose to PB (1024TB=1PB), EB (1024PB=1EB) and even ZB (1024EB=1ZB) rank from TB (1024GB=1TB) rank.The result of study of International Data Corporation (IDC) (IDC) shows, the data volume of whole world generation in 2008 is 0.49ZB, and the data volume of 2009 is 0.8ZB, within 2010, increases as 1.2ZB, the data volume of 2011 is especially up to 1.82ZB, and everyone produces the data volume of more than 200GB to be equivalent to the whole world.
Carrying out statistical study to mass data, is a thing very consuming time, particularly when the data of ZB rank, carries out real time data statistics and not only can not return statistics in time, and more likely system application worn down.So instantly, real-time statistical study may be provided to mass data hardly.Even if well-known friendly alliance, when providing data statistics to serve to client, be also adding up in advance on the data basis of filing, from the data of having filed, carrying out secondary inquiry, statistical study is carried out to data.The advantage of this way is that the response time of statistical study is fast, but shortcoming is also clearly, and filing data is that processed offline is good, on this basis query and statistical analysis result out, and the true data accurately of non-present.
Summary of the invention
Fundamental purpose of the present invention is to propose a kind of large data statistical approach and the system for large data statistics.Timing statistics and dynamic idle are added up and are combined by the present invention, and making can be not only quick but also obtain required data of adding up accurately when carrying out mass data statistics.
The technical scheme that the present invention solves the problems of the technologies described above is as follows:
A kind of large data statistical approach, comprising: timing is added up and dynamic idle statistics, described timing statistics and the synchronous execution of described dynamic idle statistics.
Further, described dynamic idle statistics comprises:
Middleware system judges whether current database is in idle condition, and if so, then transmission calls the information of idle statistics interface to large data statistics system;
Call the information of idle statistics interface described in large data statistics system receives, judge whether current idle statistics interface can be called by legal, if so, then starts idle statistics.
Further, described middleware system judges that current database is in idle condition and is specially: described middleware system judges whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value, if so, then current database is in idle condition; Otherwise current database is in busy state.
Further, described middleware system also comprises before judging whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value: dynamically preset triggering intervals and activation threshold value.
Further, described middleware system dynamically presets triggering intervals and activation threshold value.
Further, described large data statistics system dynamically presets triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to described middleware system by described large data statistics system, and described middleware system receives described dynamically default triggering intervals and activation threshold value.
Further, describedly on described large data statistics system, dynamically preset triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to described middleware system by described large data statistics system, described middleware system receives described dynamically default triggering intervals and activation threshold value, be specially: on the control page of described large data statistics system, dynamically preset triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to described middleware system with http agreement by described large data statistics system, described middleware system receives described dynamically default triggering intervals and activation threshold value.
Further, described timing statistics comprises:
The administration page of described large data statistics system arranges the execution frequency of timing statistics;
Described large data statistics system starts timing statistics according to described execution frequency.
A kind of system for large data statistics, comprise middleware system and large data statistics system, described large data statistics system performs the timing statistics described in above-mentioned a kind of large data statistical approach, described middleware system and described large data statistics system perform the dynamic idle statistics described in above-mentioned a kind of large data statistical approach jointly, described timing statistics and the synchronous execution of described dynamic idle statistics.
The invention provides a kind of large data statistical approach and the system for large data statistics, described method comprises timing statistics and dynamic idle statistics, and described timing statistics and described dynamic idle are added up synchronous and performed.Dynamic idle statistics and timing statistics combine by the present invention, the data of dynamic idle statistics filing can enable the statistics when carrying out mass data statistical study required for not only quick but also accurate acquisition, when dynamic idle statistics breaks down, the statistical study that the data that timing statistics is filed can be mass data provides statistical basis, guarantees the statistics required for obtaining fast.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of a kind of large data statistical approach of the present invention;
Fig. 2 is the process flow diagram of a preferred embodiment of dynamic idle statistics in a kind of large data statistical approach of the present invention;
Fig. 3 is the process flow diagram that a kind of system for large data statistics of the present invention performs a preferred embodiment of dynamic idle statistics;
The realization of the object of the invention, functional characteristics and advantage will in conjunction with the embodiments, are described further with reference to accompanying drawing.
Embodiment
The technical matters solved for making the present invention, the technical scheme of employing and the technique effect that reaches are clearly, be described in further detail below in conjunction with the technical scheme of accompanying drawing to the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those skilled in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Embodiment one
See the schematic flow sheet that Fig. 1, Fig. 1 are a kind of large data statistical approach of the present invention.
A kind of large data statistical approach, comprising: timing is added up and dynamic idle statistics, described timing statistics and the synchronous execution of described dynamic idle statistics.
Dynamic idle statistics and timing statistics combine by the present invention, and the mechanism of double insurance provides reliable and stable data basis for statistical study mass data quickly and accurately.
Further, described dynamic idle statistics comprises:
Middleware system judges whether current database is in idle condition, and if so, then transmission calls the information of idle statistics interface to large data statistics system;
Call the information of idle statistics interface described in large data statistics system receives, judge whether current idle statistics interface can be called by legal, if so, then starts idle statistics.
As long as the present invention's dynamic idle statistics database is in idle condition, just timely sorting and file is carried out to database data, statistical study for mass data provides up-to-date filing data the most accurately, when carrying out mass data statistical study on this up-to-date basis of filing data the most accurately, the statistics required for can obtaining not only quick but also accurately.
Further, described timing statistics comprises:
The administration page of described large data statistics system arranges the execution frequency of timing statistics;
Described large data statistics system starts timing statistics according to described execution frequency.
The statistical study that the data of the present invention's timing statistics timing statistics filing when dynamic idle statistics breaks down can be mass data provides data basic, guarantee the statistics required for obtaining fast, and be unlikely to when dynamic idle statistics breaks down, cause system crash, can not statistics be returned.
Embodiment two
Participate in the process flow diagram that Fig. 2, Fig. 2 are preferred embodiments of dynamic idle statistics in a kind of large data statistical approach of the present invention.
A kind of dynamically idle statistical method comprises:
S101, dynamically default triggering intervals and activation threshold value.
In step S101, directly on middleware system, dynamically can preset triggering intervals and activation threshold value; Or, large data statistics system dynamically presets triggering intervals and activation threshold value, and described dynamically default triggering intervals and activation threshold value is sent to described middleware system.
The mode that large data statistics system is dynamically preset triggering intervals and activation threshold value has multiple, as an embodiment, the control page of large data statistics system dynamically presets triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to middleware system with http agreement by large data statistics system, and the described dynamically default triggering intervals of middleware system reception and activation threshold value are with the contrast using this triggering intervals and activation threshold value to carry out later step.
S102, middleware system judge whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value.
Step S102 is that middleware system judges whether current database is in the concrete mode of one of idle condition, middleware system judges whether current database is in idle condition and can also has other implementation, to middleware system, the present invention judges that the mode whether current database is in idle condition is not restricted.In the present embodiment, middleware system judges whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value, and if so, then current database is in idle condition; Otherwise current database is in busy state.
If S103 current database is in idle condition, then middleware system transmission calls the information of idle statistics interface to large data statistics system.
The information of idle statistics interface is called described in S104, large data statistics system receive.
In step S104, call the information of idle statistics interface described in large data statistics system receives, large data statistics system enters the idle statistics preparatory stage.
S105, large data statistics system judge whether current idle statistics interface can be called by legal.
In step S105, before large data statistics system formally starts idle statistics, large data statistics system must judge whether current idle statistics interface can be called by legal, if current idle statistics interface can be called by legal, then large data statistics system starts idle statistics; Otherwise large data statistics system does not do any operation.
In step S105, whether current idle statistics interface can be set a state value and decide by legal calling on the administration page of large data statistics system.
S106, large data statistics system start idle statistics.
As long as the present invention's dynamic idle statistics database is in idle condition, just timely sorting and file is carried out to database data, statistical study for mass data provides up-to-date filing data the most accurately, when carrying out mass data statistical study on this up-to-date basis of filing data the most accurately, the statistics required for can obtaining not only quick but also accurately.
Embodiment three
A kind of system for large data statistics, comprise middleware system and large data statistics system, described large data statistics system performs timing statistics, described middleware system and described large data statistics system perform dynamic idle statistics jointly, described timing statistics and the synchronous execution of described dynamic idle statistics.
Large data statistics system not only performs regularly statistics but also perform dynamic idle statistics, and described timing statistics and described dynamic idle statistics synchronously perform; So large data statistics system has two threads carried out simultaneously, be respectively used to perform timing and add up and perform dynamic idle statistics.
Elaborate with Fig. 3 the process that middleware system and large data statistics system perform dynamic idle statistics jointly below, it should be noted that, at the same time, large data statistics system performs timing statistics.
Participating in Fig. 3, Fig. 3 is the process flow diagram that a kind of system for large data statistics of the present invention performs a preferred embodiment of dynamic idle statistics.
System for large data statistics performs a step for dynamic idle statistics, comprising:
S201, on the control page of described large data statistics system, dynamically preset triggering intervals and activation threshold value.
In step S201, the mode dynamically presetting triggering intervals and activation threshold value has multiple, such as, directly on middleware system, dynamically can preset triggering intervals and activation threshold value; Or, large data statistics system dynamically presets triggering intervals and activation threshold value, and described dynamically default triggering intervals and activation threshold value is sent to described middleware system.
The mode that large data statistics system is dynamically preset triggering intervals and activation threshold value has multiple, as an embodiment, the control page of large data statistics system dynamically presets triggering intervals and activation threshold value, plant set-up mode therewith corresponding, described dynamically default triggering intervals and activation threshold value are sent to middleware system with http agreement by large data statistics system.
Described dynamically default triggering intervals and activation threshold value are sent to described middleware system with http agreement by S202, described large data statistics system.
S203, described middleware system receive described dynamically default triggering intervals and activation threshold value.
In step S203, the described dynamically default triggering intervals of middleware system reception and activation threshold value are with the contrast using this triggering intervals and activation threshold value to carry out step S204.
S204, described middleware system judge whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value.
Step S204 is that middleware system judges whether current database is in the concrete mode of one of idle condition, middleware system judges whether current database is in idle condition and can also has other implementation, to middleware system, the present invention judges that the mode whether current database is in idle condition is not restricted.In the present embodiment, middleware system judges whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value, and if so, then current database is in idle condition; Otherwise current database is in busy state.
If S205 current database is in idle condition, described middleware system transmission calls the information of idle statistics interface to large data statistics system.
The information of idle statistics interface is called described in S206, large data statistics system receive.
In step S206, call the information of idle statistics interface described in large data statistics system receives, large data statistics system enters the idle statistics preparatory stage.
S207, large data statistics system judge whether current idle statistics interface can be called by legal.
Step S207 is the idle statistics preparatory stage of large data statistics system, namely before large data statistics system formally starts idle statistics, large data statistics system must judge whether current idle statistics interface can be called by legal, if current idle statistics interface can be called by legal, then large data statistics system starts idle statistics; Otherwise large data statistics system does not do any operation.
S208, startup idle statistics.
As long as the present invention's dynamic idle statistics database is in idle condition, just timely sorting and file is carried out to database data, statistical study for mass data provides up-to-date filing data the most accurately, when carrying out mass data statistical study on this up-to-date basis of filing data the most accurately, the statistics required for can obtaining not only quick but also accurately.
Add up with above-mentioned dynamic idle the timing simultaneously performed to add up and comprise:
The administration page of described large data statistics system arranges the execution frequency of timing statistics;
Described large data statistics system starts timing statistics according to described execution frequency.
Such as, the execution frequency that the administration page of described large data statistics system arranges timing statistics is 1 time/hour (when the execution frequency arranging timing statistics is 1 time/hour, large data statistics system acquiescence starts timing statistics when each integral point), then large data statistics system starts timing statistics at each integral point, and using the data of the last time timing statistics as filing data, in order to using when dynamic idle statistics breaks down.
The statistical study that the data of the present invention's timing statistics timing statistics filing when dynamic idle statistics breaks down can be mass data provides data basic, guarantee the statistics required for obtaining fast, and be unlikely to when dynamic idle statistics breaks down, cause system crash, can not statistics be returned.
These are only the preferred embodiments of the present invention; not thereby the scope of the claims of the present invention is limited; every utilize instructions of the present invention and accompanying drawing content to do equivalent structure or equivalent flow process conversion; or be directly or indirectly used in other relevant technical fields, be all in like manner included in scope of patent protection of the present invention.
Claims (9)
1. a large data statistical approach, is characterized in that, comprising: timing statistics and dynamic idle statistics, and described timing statistics and described dynamic idle are added up synchronous and performed.
2. the large data statistical approach of one according to claim 1, is characterized in that, described dynamic idle statistics comprises:
Middleware system judges whether current database is in idle condition, and if so, then transmission calls the information of idle statistics interface to large data statistics system;
Call the information of idle statistics interface described in large data statistics system receives, judge whether current idle statistics interface can be called by legal, if so, then starts idle statistics.
3. the large data statistical approach of one according to claim 2, it is characterized in that, described middleware system judges that current database is in idle condition and is specially: described middleware system judges whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value, if so, then current database is in idle condition; Otherwise current database is in busy state.
4. the large data statistical approach of one according to claim 3, it is characterized in that, described middleware system also comprises before judging whether the Concurrency Access amount of described middleware system in the triggering intervals preset is less than default activation threshold value: dynamically preset triggering intervals and activation threshold value.
5. the large data statistical approach of one according to claim 4, is characterized in that, described middleware system dynamically presets triggering intervals and activation threshold value.
6. the large data statistical approach of one according to claim 4, it is characterized in that, described large data statistics system dynamically presets triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to described middleware system by described large data statistics system, and described middleware system receives described dynamically default triggering intervals and activation threshold value.
7. the large data statistical approach of one according to claim 6, it is characterized in that, describedly on described large data statistics system, dynamically preset triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to described middleware system by described large data statistics system, described middleware system receives described dynamically default triggering intervals and activation threshold value, be specially: on the control page of described large data statistics system, dynamically preset triggering intervals and activation threshold value, described dynamically default triggering intervals and activation threshold value are sent to described middleware system with http agreement by described large data statistics system, described middleware system receives described dynamically default triggering intervals and activation threshold value.
8. the large data statistical approach of one according to claim 1, is characterized in that, described timing statistics comprises:
The administration page of described large data statistics system arranges the execution frequency of timing statistics;
Described large data statistics system starts timing statistics according to described execution frequency.
9. the system for large data statistics, it is characterized in that, comprise middleware system and large data statistics system, described large data statistics system performs the timing statistics as described in any one of claim 1-8, described middleware system and described large data statistics system perform the dynamic idle statistics as described in any one of claim 1-8 jointly, described timing statistics and the synchronous execution of described dynamic idle statistics.
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