CN105573889A - Virtual machine monitoring data access method and apparatus - Google Patents
Virtual machine monitoring data access method and apparatus Download PDFInfo
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- CN105573889A CN105573889A CN201510936964.1A CN201510936964A CN105573889A CN 105573889 A CN105573889 A CN 105573889A CN 201510936964 A CN201510936964 A CN 201510936964A CN 105573889 A CN105573889 A CN 105573889A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
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Abstract
The invention provides a virtual machine monitoring data access method and apparatus. The virtual machine monitoring data access method comprises the steps that at least a cache block is configured, wherein at least a second-level time window, a minute-level time window, a hour-level time window and a day-level time window are arranged in each cache block; the obtained monitoring data is stored into one unit of the second-level time window at regular intervals, wherein the second-level time window obtains a mean value of the cached data every one minute and stores the mean value into one unit of the minute-level time window; the minute-level time window obtains a mean value of the cached data every one hour and stores the mean value into one unit of the hour-level time window; the hour-level time window obtains a mean value of the cached data every one day and stores the mean value into one unit of the day-level time window; therefor, the cached data has the time features; and the data corresponding to time can be called from the respective windows according to the time features. According to the virtual machine monitoring data access method and apparatus, even if the monitored data volume is quite large, the resource use conditions also can be obtained rapidly by users.
Description
Technical field
The present invention relates to Intel Virtualization Technology, in particular the access technique of virtual machine monitoring data.
Background technology
Growing along with cloud computing, Intel Virtualization Technology is widely used.A large amount of entity computational resource and storage resources put together by cloud service, and have a large amount of virtual machines, configure different stock numbers, realize resource sharing, substantially increase the utilization factor of actual resource to every platform virtual machine.As the main body of virtual cloud service, the running status of virtual machine embodies the running status of server indirectly, thus need to monitor the running status of virtual machine, a such as OpenStack (cloud computing management platform project of increasing income, to be combined specific works by several main assembly) virtual machine monitoring technology in framework, ceilometer (assembly in OpenStack) may produce a large amount of back-end datas, operator needs to carry out adding up according to lengthy and jumbled data the object realizing monitoring, when data volume is less, data comparatively fast can obtain statistical treatment, inquiry also can be comparatively timely, and when back-end data amount is excessive, often need to spend the plenty of time just can count the service condition of resource, in addition, when operator wishes the monitor data obtaining the corresponding time, perhaps long time is wanted to inquire about, thus need to be optimized it.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of access method and device of virtual machine monitoring data, even if when monitor data amount is very large, user still can obtain resource service condition fast.
For solving the problem, the present invention proposes a kind of access method of virtual machine monitoring data, comprising:
Configure at least one cache blocks, be provided with in each cache blocks at least second level time window, minute level time window, hour level time window and sky level time window;
At regular intervals by a unit stored in level time window described second of the monitor data that obtains; Described second, the data of buffer memory were made average every 1 minute by level time window, and by average stored in a unit of described minute level time window; Within described minute, the data of buffer memory were made average every 1 hour by level time window, and by average stored in a unit of described hour level time window; Within described hour, the data of buffer memory were made average every 1 day by level time window, and by the unit of average stored in described sky level time window; Thus the data of buffer memory all have time response;
From each window, the data of corresponding time are transferred according to time response.
According to one embodiment of present invention, in each cache blocks, moon level time window and grade's time window is also provided with;
The data of buffer memory are made average every January by described sky level time window, and by the unit of average stored in described moon level time window; The described moon, the data of buffer memory were made average every 1 year by level time window, and by average stored in a unit of described grade time window.
According to one embodiment of present invention, each rank time window corresponding make average after or empty data itself after arriving setting-up time time limit point; Or the legacy data of each unit of each rank time window is replaced by new data.
According to one embodiment of present invention, when described grade time window arrives setting-up time time limit point, the prompting needing Backup Data is provided.
According to one embodiment of present invention, the data cached size of each unit of each rank time window is determined according to the monitor data feature obtained, and immobilizes.
According to one embodiment of present invention, the rear end of each described cache blocks adopts database to store, and storage mode stores according to the level association of time window, and user transfers the data of corresponding time according to time response from database.
According to one embodiment of present invention, if described second, level time window did not get monitor data in described certain hour, or when the monitor data that described second, level time window got is abnormal, then generates a flag data and be cached in corresponding units; When described second, level time window arrived setting-up time time limit point, the data got rid of after this flag data are made average, and by average stored in a unit of described minute level time window.
According to one embodiment of present invention, described monitor data is produced by ceilometer, the monitor data of separate sources is by the different case-based system of virtual machine, and the monitor data in same source is cached in a cache blocks, using the key word of the instance identification of virtual machine as monitor data.
For solving the problem, the present invention also proposes a kind of access device of virtual machine monitoring data, comprising:
Cache module, has at least one cache blocks, be provided with in each cache blocks at least second level time window, minute level time window, hour level time window and sky level time window;
Data processing module, in order to: at regular intervals by a unit stored in level time window described second of the monitor data that obtains; The data of buffer memory were made average every 1 minute by level time window described second, and by average stored in a unit of described minute level time window; The data of buffer memory were made average every 1 hour by described minute level time window, and by average stored in a unit of described hour level time window; The data of buffer memory were made average every 1 day by described hour level time window, and by the unit of average stored in described sky level time window; Thus the data of buffer memory all have time response;
Data transfer interface module, in order to transfer the data of corresponding time from each window according to time response.
According to one embodiment of present invention, moon level time window and grade's time window is also included in each cache blocks of described cache module;
Described data processing module also in order to, the data of buffer memory are made average every January by described sky level time window, and by the unit of average stored in described moon level time window; The data of buffer memory were made average every 1 year by described moon level time window, and by average stored in a unit of described grade time window.
After adopting technique scheme, the present invention has following beneficial effect compared to existing technology: by arranging cache blocks, and in each cache blocks, other time window of classification is set, stored in other time window of next stage after the data volume computation of mean values that other time window of upper level is obtained, owing to being passing according to the time and the buffer memory that flows in each time window, therefore the storage of each data all has time response, user can find the data of corresponding time period fast according to these time responses, when user needs Gains resources service condition, can queried access rapidly and accurately to data, no matter and whether back-end data amount constantly increases, all can ensure that the time of user accesses data is constant.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the access method of the virtual machine monitoring data of one embodiment of the invention;
Fig. 2 is the schematic flow sheet of the access method of the virtual machine monitoring data of another embodiment of the present invention;
Fig. 3 is the data flow schematic diagram of one embodiment of the invention;
Fig. 4 is the structured flowchart of the access device of the virtual machine monitoring data of one embodiment of the invention.
Embodiment
For enabling above-mentioned purpose of the present invention, feature and advantage become apparent more, are described in detail the specific embodiment of the present invention below in conjunction with accompanying drawing.
Set forth a lot of detail in the following description so that fully understand the present invention.But the present invention can be much different from alternate manner described here to implement, those skilled in the art can when without prejudice to doing similar popularization when intension of the present invention, therefore the present invention is by the restriction of following public concrete enforcement.
In the present embodiment, the access method of virtual machine monitoring data, comprising:
Configure at least one cache blocks, be provided with in each cache blocks at least second level time window, minute level time window, hour level time window and sky level time window;
At regular intervals by a unit stored in level time window described second of the monitor data that obtains; Described second, the data of buffer memory were made average every 1 minute by level time window, and by average stored in a unit of described minute level time window; Within described minute, the data of buffer memory were made average every 1 hour by level time window, and by average stored in a unit of described hour level time window; Within described hour, the data of buffer memory were made average every 1 day by level time window, and by the unit of average stored in described sky level time window; Thus the data of buffer memory all have time response;
From each window, the data of corresponding time are transferred according to time response.
Concrete, referring to Fig. 1, first, need allocating cache block, the number of cache blocks can have multiple, be used for respectively storing identical or different monitor data, at this said identical or different monitor data, can refer to that source is identical or different, can certainly refer to that data characteristics is identical or different, in each cache blocks, configure level time window second, minute level time window, hour level time window and sky level time window, each time window all has multiple storage unit, just can run after this configuration always, and without the need to repeating this configuration step.
Then, obtain monitor data, in an optional embodiment, second, level time window can configure 6 storage unit, then obtained a secondary data every 10 seconds, second level time window less than time, data are deposited in a unit of level time window second, if window is full, there is data batchmove, so arrive 1 minute time second level time window be just filled with data, be appreciated that, the number of storage unit and the occurrence of interval time be not all as restriction, can according to circumstances be configured, when meeting arrival 1 minute, the data of buffer memory are made average, the data of this buffer memory refer to all data of depositing in 1 minute in arrival, and not there is between these data the possibility be capped because successively storing, namely the data of buffer memory are deposited in different unit, average is deposited in a unit of minute level time window, and each gained average that calculates at the corresponding levels is kept in a unit of the corresponding levels (level time window second), this average can be covered by the average newly produced, that is, window at the corresponding levels can only provide a unit to be used for storing average at the corresponding levels, prevent all unit of final time window from being sky.
In one embodiment, before acquisition monitor data is deposited into level time window second, also carry out judging the whether problematic step of monitor data, if there is problem, mark value be generated, monitor data produce problem be such as second level time window in described certain hour, do not get monitor data, and be that of obtaining clear data, or the monitor data exception that second, level time window got, this exception can be got the inconsistent data of feature or inconsistent data of originating, then generating a flag data is cached in corresponding units, this flag data is in order to be identified rear eliminating within the data making average, thus ensure that in cache blocks and can not produce junk data, impact stores the correctness of the monitor data of statistics, afterwards do in average step, namely when second, level time window arrived setting-up time time limit point (1 minute), the data got rid of after this flag data are made average, and by average stored in a unit of minute level time window.
The average of what each unit of minute level time window stored is all monitor data that second, level time window different time sections passed over, after the average of each reception level time window second, need to judge that whether minute level time window is full, if less than, continue to receive average, if full, then show that minute level time window arrives setting-up time time limit point (1 hour), the data that minute level time window stored in this 1 hour are made average, average is stored in a unit of hour level time window, same, each gained average that calculates at the corresponding levels is kept in a unit of the corresponding levels (minute level time window), this average can be covered by the average newly produced.
The average of what each unit of hour level time window stored is all monitor data that minute level time window different time sections passes over, after the average of each reception minute level time window, need to judge that whether hour level time window is full, if less than, continue to receive average, if full, then show that hour level time window arrives setting-up time time limit point (1 day), the data that hour level time window stored in this 1 day are made average, average is stored in a unit of sky level time window, same, each gained average that calculates at the corresponding levels is kept in a unit of the corresponding levels (hour level time window), this average can be covered by the average newly produced.And sky level time window as the superlative degree time, the corresponding levels can not make average, also with regard to time only can preserve the average of upper level.
Storage due to monitor data is passing according to the time and flows and to store, thus monitor data carries time response, when user need to carry out queried access put sometime or the monitor data of time period time, can inquire according to time response fast, and the average be through after numerical statistic that stores of the time window of higher level, thus a large amount of visit datas can not be produced, access speed can be very fast, the data volume no matter backstage produces is much, and queried access speed generally can not be affected.
Referring to Fig. 2, in the present embodiment, in each cache blocks, moon level time window and grade's time window is also provided with; The data of buffer memory are made average every January by described sky level time window, and by the unit of average stored in described moon level time window, the average that sky level time window calculates simultaneously is also kept in a unit of sky level time window; The described moon, the data of buffer memory were made average every 1 year by level time window, and by average stored in a unit of described grade time window, and the moon, the average that calculates of level time window was also kept in a unit of moon level time window simultaneously.And in the present embodiment, age time window is as the superlative degree, the corresponding levels can not make average, and only preserve the average of moon level generation.The difference part of the embodiment that the present embodiment and Fig. 1 describe is, also comprises the time window of more high-grade, thus will be accurate to date Hour Minute Second the time, can store according to actual time value and obtain data.
Concrete, the data of buffer memory are made average every January by it level time window, and by the unit of average stored in described moon level time window, the average of what each unit of month level time window stored is all monitor data that sky level time window different time sections passes over, after the average of each reception sky level time window, need to judge that whether moon level time window is full, if less than, continue to receive average, if full, then show that moon level time window arrives setting-up time time limit point (1 year), the data that moon level time window stored in this 1 year are made average, average is stored in a unit of grade time window.
In one embodiment, each rank time window corresponding make average after or empty data itself after arriving setting-up time time limit point; Or the legacy data of each unit of each rank time window is replaced by new data.The data emptied or the data of replacement, not only comprise monitor data, also comprises other data, such as be flag data, and the data of grade's time window such as can be set to empty once for 100 years.Empty the generation that data can avoid redundant data, but if arranging data volume that each time window can hold is just in time the data volume that it just in time obtains when reaching setting-up time time limit point, so only data are replaced and are also fine.
Further, when grade's time window arrives setting-up time time limit point, provide the prompting needing Backup Data, such as, can point out keeper, first carry out data backup, also to need to use these data in the future.
Preferably, the data cached size of each unit of each rank time window is determined according to the monitor data feature obtained, and immobilize, according to the time window of data characteristics determination fixed size unit, the storage of redundant data can be avoided, if the unit that data characteristics does not meet time window can store size of data, then remove this data.
Preferably, the rear end of each described cache blocks adopts database to store, this database is such as mongodb database, the time response of data is not destroyed when storing in a database, storage mode stores according to the level association of time window, and user transfers the data of corresponding time according to time response from database.
Referring to Fig. 3, in one more specific embodiment, based on OpenStack framework, the monitor data of virtual machine is produced by assembly ceilometer, the monitor data of separate sources is obtained by the example (i.e. instance) that virtual machine is different, the monitor data in same source is cached in a cache blocks, using the key word of the instance identification of virtual machine as monitor data, represents same derived data or same class data.In figure 3, can see, data transmit, and ceilometer can get monitor data from the various resources such as network, processor, storer, and these are the resources in artificial scene certainly, and monitor data can represent the operation conditions of these resources.Ceilometer is delivered to level time window second after producing these data, thus is solved when it produces a large amount of back-end data by the present invention, and resource service condition need a large amount of computing time could query statistic problem out.
Referring to Fig. 4, in the present embodiment, the access device of virtual machine monitoring data comprises cache module 11, data processing module 12 and data and transfers interface module 13.
Cache module has at least one cache blocks, be provided with in each cache blocks at least second level time window, minute level time window, hour level time window and sky level time window; Data processing module in order to monitor data process is deposited in each time window and goes, at regular intervals by a unit stored in level time window described second of the monitor data to obtain; The data of buffer memory were made average every 1 minute by level time window described second, and by average stored in a unit of described minute level time window; The data of buffer memory were made average every 1 hour by described minute level time window, and by average stored in a unit of described hour level time window; The data of buffer memory were made average every 1 day by described hour level time window, and by the unit of average stored in described sky level time window; Thus the data of buffer memory all have time response; Data transfer interface module in order to transfer the data of corresponding time from each window according to time response.
Further, moon level time window and grade's time window is also included in each cache blocks of cache module; Described data processing module also in order to the data of buffer memory are made average every January by described sky level time window, and by the unit of average stored in described moon level time window; The data of buffer memory were made average every 1 year by described moon level time window, and by average stored in a unit of described grade time window.
The embodiment of device of the present invention referring to the related content of aforesaid method, all can be applicable to device about the content described by method, does not thus repeat them here.
Although the present invention with preferred embodiment openly as above; but it is not for limiting claim; any those skilled in the art without departing from the spirit and scope of the present invention; can make possible variation and amendment, the scope that therefore protection scope of the present invention should define with the claims in the present invention is as the criterion.
Claims (10)
1. an access method for virtual machine monitoring data, is characterized in that, comprising:
Configure at least one cache blocks, be provided with in each cache blocks at least second level time window, minute level time window, hour level time window and sky level time window;
At regular intervals by a unit stored in level time window described second of the monitor data that obtains; Described second, the data of buffer memory were made average every 1 minute by level time window, and by average stored in a unit of described minute level time window; Within described minute, the data of buffer memory were made average every 1 hour by level time window, and by average stored in a unit of described hour level time window; Within described hour, the data of buffer memory were made average every 1 day by level time window, and by the unit of average stored in described sky level time window; Thus the data of buffer memory all have time response;
From each window, the data of corresponding time are transferred according to time response.
2. the access method of virtual machine monitoring data as claimed in claim 1, is characterized in that, be also provided with moon level time window and grade's time window in each cache blocks;
The data of buffer memory are made average every January by described sky level time window, and by the unit of average stored in described moon level time window; The described moon, the data of buffer memory were made average every 1 year by level time window, and by average stored in a unit of described grade time window.
3. the access method of virtual machine monitoring data as claimed in claim 1 or 2, is characterized in that, each rank time window corresponding make average after or empty data itself after arriving setting-up time time limit point; Or the legacy data of each unit of each rank time window is replaced by new data.
4. the access method of virtual machine monitoring data as claimed in claim 2, is characterized in that, when described grade time window arrives setting-up time time limit point, provides the prompting needing Backup Data.
5. the access method of virtual machine monitoring data as claimed in claim 1, is characterized in that, the data cached size of each unit of each rank time window is determined according to the monitor data feature obtained, and immobilizes.
6. the access method of virtual machine monitoring data as claimed in claim 1, it is characterized in that, the rear end of each described cache blocks adopts database to store, and storage mode stores according to the level association of time window, and user transfers the data of corresponding time according to time response from database.
7. the access method of virtual machine monitoring data as claimed in claim 1, it is characterized in that, if described second, level time window did not get monitor data in described certain hour, or when described second, monitor data that level time window gets was abnormal, then generates a flag data and be cached in corresponding units; When described second, level time window arrived setting-up time time limit point, the data got rid of after this flag data are made average, and by average stored in a unit of described minute level time window.
8. the access method of virtual machine monitoring data as claimed in claim 1, it is characterized in that, described monitor data is produced by ceilometer, the monitor data of separate sources is by the different case-based system of virtual machine, the monitor data in same source is cached in a cache blocks, using the key word of the instance identification of virtual machine as monitor data.
9. an access device for virtual machine monitoring data, is characterized in that, comprising:
Cache module, has at least one cache blocks, be provided with in each cache blocks at least second level time window, minute level time window, hour level time window and sky level time window;
Data processing module, in order to: at regular intervals by a unit stored in level time window described second of the monitor data that obtains; The data of buffer memory were made average every 1 minute by level time window described second, and by average stored in a unit of described minute level time window; The data of buffer memory were made average every 1 hour by described minute level time window, and by average stored in a unit of described hour level time window; The data of buffer memory were made average every 1 day by described hour level time window, and by the unit of average stored in described sky level time window; Thus the data of buffer memory all have time response;
Data transfer interface module, in order to transfer the data of corresponding time from each window according to time response.
10. the access device of virtual machine monitoring data as claimed in claim 9, is characterized in that, also include moon level time window and grade's time window in each cache blocks of described cache module;
Described data processing module also in order to, the data of buffer memory are made average every January by described sky level time window, and by the unit of average stored in described moon level time window; The data of buffer memory were made average every 1 year by described moon level time window, and by average stored in a unit of described grade time window.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106412108A (en) * | 2016-11-09 | 2017-02-15 | 深圳云联讯数据科技有限公司 | Cloud platform architecture-based user data deployment method and system |
| CN107193710A (en) * | 2017-05-26 | 2017-09-22 | 山东浪潮云服务信息科技有限公司 | One kind realizes self-defining data assemblage method and device based on storing process |
| CN108241647A (en) * | 2016-12-23 | 2018-07-03 | 北京奇虎科技有限公司 | Data processing and the method and apparatus of inquiry |
| WO2020135737A1 (en) * | 2018-12-28 | 2020-07-02 | 杭州海康威视数字技术股份有限公司 | Methods, apparatuses, devices and mediums for partition management and data storage and querying |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101047776A (en) * | 2006-04-17 | 2007-10-03 | 华为技术有限公司 | Mobile broadcast network system and method for implementing synchronous of the network |
| US20090199047A1 (en) * | 2008-01-31 | 2009-08-06 | Yahoo! Inc. | Executing software performance test jobs in a clustered system |
| CN103500071A (en) * | 2013-09-18 | 2014-01-08 | 湖南蚁坊软件有限公司 | Method and device for storing performance index data quantitatively |
| CN104765765A (en) * | 2015-02-15 | 2015-07-08 | 杭州邦盛金融信息技术有限公司 | Moveable dynamic data rapid processing method based on time window |
-
2015
- 2015-12-15 CN CN201510936964.1A patent/CN105573889A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101047776A (en) * | 2006-04-17 | 2007-10-03 | 华为技术有限公司 | Mobile broadcast network system and method for implementing synchronous of the network |
| US20090199047A1 (en) * | 2008-01-31 | 2009-08-06 | Yahoo! Inc. | Executing software performance test jobs in a clustered system |
| CN103500071A (en) * | 2013-09-18 | 2014-01-08 | 湖南蚁坊软件有限公司 | Method and device for storing performance index data quantitatively |
| CN104765765A (en) * | 2015-02-15 | 2015-07-08 | 杭州邦盛金融信息技术有限公司 | Moveable dynamic data rapid processing method based on time window |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106412108A (en) * | 2016-11-09 | 2017-02-15 | 深圳云联讯数据科技有限公司 | Cloud platform architecture-based user data deployment method and system |
| CN106412108B (en) * | 2016-11-09 | 2019-07-26 | 深圳华远云联数据科技有限公司 | User data dispositions method and system based on cloud platform framework |
| CN108241647A (en) * | 2016-12-23 | 2018-07-03 | 北京奇虎科技有限公司 | Data processing and the method and apparatus of inquiry |
| CN108241647B (en) * | 2016-12-23 | 2022-03-11 | 北京奇虎科技有限公司 | Data processing and querying method and device |
| CN107193710A (en) * | 2017-05-26 | 2017-09-22 | 山东浪潮云服务信息科技有限公司 | One kind realizes self-defining data assemblage method and device based on storing process |
| WO2020135737A1 (en) * | 2018-12-28 | 2020-07-02 | 杭州海康威视数字技术股份有限公司 | Methods, apparatuses, devices and mediums for partition management and data storage and querying |
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