CN106776251A - A kind of monitoring data processing unit and method - Google Patents
A kind of monitoring data processing unit and method Download PDFInfo
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- CN106776251A CN106776251A CN201611072949.8A CN201611072949A CN106776251A CN 106776251 A CN106776251 A CN 106776251A CN 201611072949 A CN201611072949 A CN 201611072949A CN 106776251 A CN106776251 A CN 106776251A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3466—Performance evaluation by tracing or monitoring
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
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- G06F11/3495—Performance evaluation by tracing or monitoring for systems
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Abstract
The invention discloses a kind of monitoring data processing unit and method, described device includes：Data acquisition module, for the monitoring data of acquisition monitoring object, the monitoring data that will be collected in monitoring data table is preserved by the timing node order of collection；Catch of exception module, for when the monitored object occurs abnormal, the corresponding timing node in abnormality data table to insert abnormality mark data；Supplementing Data module, in front-end interface query monitor data, for the corresponding timing node of the abnormality mark data, the corresponding monitoring data of completion.The present invention is only in user's query monitor data trend graph just according to abnormal data mark, the timing node broken down to monitored object carries out Supplementing Data, it is presented to user front end interface, without inserting rubbish redundant data in monitoring data table, can avoid in monitoring data trend graph that data are linearly connected but the time staggers problem and unnecessary rubbish redundant data.
Description
Technical field
The present invention relates to Internet technology, more particularly to a kind of monitoring data processing unit and method.
Background technology
At this stage, in order to provide good service to Internet user, Internet enterprises mostly have developed and meet own service
Monitoring and early warning platform ensure the high availability of oneself product.The fact that monitoring and early warning platform is typically used for performance indications is looked into
See analysis.When carrying out fact to performance indications and checking, mostly based on linear trend graph, more intuitively, it is easy to carry out anticipation
With the presence or absence of problem.But, in the case where the machine of delaying occurs in the service of monitoring, the basic data of linear trend graph can gather mistake
Lose, cause trend graph situation about being linearly connected but the time staggers occur so that research staff is in the positioning specific time of origin of failure
Point and duration become more difficult.
In current techniques, in order to repair this problem, industry common method is automatically to refer to each performance when failure is gathered
Mark data are filled with 0.Although do so can eliminate it is now linear be connected but the time staggers this problem, it is invalid to produce simultaneously
Data bulk redundancy.By taking the monitoring collection of Tomcat services as an example, in storing process is gathered, depositing for 6 table data can be related to
Storage, i.e. Tomcat dynamics and static data, JVM dynamics and static data, C3P0 connection pools dynamic and static data, according to every 5
Second collection is once calculated, and the machine one day if single Tomcat delays occurs 103680 (12*60*24*6) bar rubbish redundant datas,
Data are not easy to check.
The content of the invention
It is a primary object of the present invention to propose a kind of monitoring data processing unit and method, it is intended to solve monitoring data and adopt
Collection can cause linear trend graph curve mistake correlation problem when interrupting, while avoiding the occurrence of substantial amounts of rubbish redundant data.
To achieve the above object, the invention provides a kind of monitoring data processing unit, including：
Data acquisition module, for the monitoring data of acquisition monitoring object, the monitoring that will be collected in monitoring data table
Data are preserved by the timing node order of collection；
Catch of exception module, for when the monitored object occurs abnormal, segmentum intercalaris during corresponding in abnormality data table
Point insertion abnormality mark data；
Supplementing Data module, it is corresponding for the abnormality mark data in front-end interface query monitor data
Timing node, the corresponding monitoring data of completion.
Alternatively, wherein, described for the corresponding timing node of abnormality mark data, the corresponding monitoring data of completion, bag
Include：
When the monitoring data table and abnormality data table are respectively present normal acquisition data and exception in same timing node
During flag data, using the normal acquisition data as the monitoring data of the timing node.
Alternatively, wherein, described for the corresponding timing node of abnormality mark data, the corresponding monitoring data of completion, also
Including：
Only there are abnormality mark data in the abnormality data table and in the monitoring data table when same timing node
During in the absence of normal acquisition data, using data 0 as the monitoring data of the timing node.
Further, described device also includes：
Display module, for the monitoring data after completion to be shown into linear trend graph in the front-end interface, wherein,
Respectively using timing node and monitoring data as abscissa and ordinate.
Alternatively, wherein, when the monitored object occurs abnormal, the corresponding timing node in abnormality data table is inserted
Abnormality mark data, including：
Catch the abnormal information that data acquisition module sends, and the corresponding timing node insertion exception in abnormality data table
Flag data.
Present invention also offers a kind of monitoring data processing method, including：
The monitoring data of acquisition monitoring object, the monitoring data that will be collected in monitoring data table is by the when segmentum intercalaris for gathering
Dot sequency is preserved；
When the monitored object occurs abnormal, the corresponding timing node insertion abnormality mark number in abnormality data table
According to；
In front-end interface query monitor data, for the corresponding timing node of the abnormality mark data, completion is corresponding
Monitoring data.
Alternatively, wherein, described for the corresponding timing node of abnormality mark data, the corresponding monitoring data of completion, bag
Include：
When the monitoring data table and abnormality data table are respectively present normal acquisition data and exception in same timing node
During flag data, using the normal acquisition data as the monitoring data of the timing node.
Alternatively, wherein, described for the corresponding timing node of the abnormality mark data, completion monitors number accordingly
According to also including：
Only there are abnormality mark data in the abnormality data table and in the monitoring data table when same timing node
During in the absence of normal acquisition data, using data 0 as the monitoring data of the timing node.
Further, methods described, also includes：
The monitoring data after completion is shown into linear trend graph in the front-end interface, wherein, respectively with when segmentum intercalaris
Point and monitoring data are used as abscissa and ordinate.
Alternatively, wherein, when the monitored object occurs abnormal, the corresponding timing node in abnormality data table is inserted
Abnormality mark data, including：
The abnormal information sent during the monitoring data for catching acquisition monitoring object, and the corresponding time in abnormality data table
Node inserts abnormality mark data.
Scheme provided in an embodiment of the present invention, by the information capture of monitored object abnormality mark only in user's query monitor number
During according to trend graph, just according to abnormal data mark, the timing node broken down to monitored object carries out Supplementing Data, Ran Houcheng
User front end interface is now given, without inserting rubbish redundant data (i.e. zero data) in monitoring data table, prison can be not only avoided
Control data trend graph time data mistake is connected, while unnecessary a large amount of rubbish redundant digits are occurred in can avoiding monitoring data
According to problem.
Brief description of the drawings
When Fig. 1 is interrupted to there is monitoring data collection in the prior art, the linear tendency schematic diagram of monitoring data；
Fig. 2 is the monitoring data processing unit structured flowchart of first embodiment of the invention；
Fig. 3 is the monitoring data processing unit structured flowchart of second embodiment of the invention；
Fig. 4 is the monitoring data process flow schematic diagram of third embodiment of the invention；
Fig. 5 is the monitoring data process flow schematic diagram of fourth embodiment of the invention；
Fig. 6 is that a kind of of one exemplary embodiment of the present invention occurs after monitoring data collection interrupts, the prison of completion monitoring data
The control linear tendency schematic diagram of data；
Fig. 7 is that the another of one exemplary embodiment of the present invention occurs after monitoring data collection interrupts, completion monitoring data
The linear tendency schematic diagram of monitoring data；
Fig. 8 is the monitoring data process flow schematic diagram of one exemplary embodiment of the present invention.
The realization of the object of the invention, functional characteristics and advantage will be described further referring to the drawings in conjunction with the embodiments.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
Technical scheme is described in detail below in conjunction with drawings and Examples.
If it should be noted that not conflicting, each feature in the embodiment of the present invention and embodiment can be tied mutually
Close, within protection scope of the present invention.In addition, though logical order is shown in flow charts, but in some situations
Under, shown or described step can be performed with different from order herein.
When Fig. 1 is interrupted to there is monitoring data collection in the prior art, the linear tendency schematic diagram of monitoring data, abscissa
It it is the collection moment, ordinate is busy Thread Count；As shown in figure 1, by taking the busy Thread Count of Tomcat as an example, being checked from Fig. 1
It is continuous without disconnection during linear tendency curves, but from the point of view of abscissa, data acquisition be every 5 seconds once, in two black surrounds
Data break 15 seconds (three collection period), this represents and is belonging to collection failure in middle 2 acquisition time nodes；So
And, because the two acquisition time nodes do not have data loading, any completion treatment is not done yet, so checking tendency
During curve map, monitoring collection process can be mistaken for normal.(as inquired about 12 prisons of hour when interval long between when queried
Control tendency), close and numerous can be covered with time point on the abscissa in linear trend graph, it is difficult to be positioned at which timing node goes out
Problem, and problem how long did it last.
In order to solve the above technical problems, first embodiment of the invention provides a kind of monitoring data processing unit, such as Fig. 2 institutes
Show, including：
Data acquisition module, for the monitoring data of acquisition monitoring object, the monitoring that will be collected in monitoring data table
Data are preserved by the timing node order of collection；
Catch of exception module, for when the monitored object occurs abnormal, segmentum intercalaris during corresponding in abnormality data table
Point insertion abnormality mark data；
Supplementing Data module, it is corresponding for the abnormality mark data in front-end interface query monitor data
Timing node, the corresponding monitoring data of completion.
In the embodiment of the present invention, data acquisition module is monitored data acquisition to monitored object in a conventional manner, adopts
Collection result is preserved in monitoring data table according to the timing node order of collection.Monitored when certain timing node or in certain time
Object break down (machine of such as delaying) when, monitoring data will not collected, such as in timing node 10:00:After 10 gathered datas, prison
Control object breaks down, to 10:00:25 points are just recovered normal, period 10:00:15、10:00:20 two timing nodes gather mould
Block does not collect monitoring data, and in the monitoring data table, the data of actual storage are 10:00:10 and data before and 10:
00:Data after 25, although that is, data are deposited in chronological order in monitoring data table, not actually exist 10:00；15、
10:00:20 two data of timing node.To avoid the occurrence of junk data redundancy, the embodiment of the present invention is not to monitoring data table
In the two timing nodes carry out zero padding operation, and simply in user's query monitor data, if monitoring data covering prison
There is abnormal time interval in control object, and such as query monitor data are related to timing node 10:00:15 and 10:00:When 20,
For the corresponding timing node of the abnormality mark data, it is necessary to the corresponding monitoring data of completion.
When monitored object breaks down, data acquisition module meeting throw exception mark, catch of exception module is in the prison
Control object can catch the abnormality mark when occurring abnormal, and the corresponding timing node insertion one in abnormality data table is different in time
Normal flag data.For example, 10:00:15 and 10:00:20 the two timing nodes insert two days corresponding abnormality marks respectively
Data.
When user is in front-end interface query monitor data, if there is the abnormal time in monitoring data covering monitored object
Interval, such as query monitor data are related to time interval to be 10:00:00 to 10:00:30, then for the abnormality mark data
Corresponding timing node is, it is necessary to the corresponding monitoring data of completion.So, during user's inquiry associated monitoring data, it is related to monitoring right
It is connected (i.e. time coordinate misplaces) as the timing node for breaking down would not occur monitoring data trend graph error in data
Problem.
Monitoring data processing unit provided in an embodiment of the present invention, by the information capture of monitored object abnormality mark only with
During the query monitor data trend graph of family, just according to abnormal data mark, line number is entered to the timing node that monitored object breaks down
According to completion, user front end interface is then presented to, without inserting rubbish redundant data (i.e. zero data) in monitoring data table, no
Monitoring data trend graph time data mistake can be only avoided to be connected, while occurring during monitoring data can be avoided unnecessary big
Amount rubbish redundant data problem.
Alternatively, in described device, described for the corresponding timing node of abnormality mark data, completion monitors number accordingly
According to, including：
When the monitoring data table and abnormality data table are respectively present normal acquisition data and exception in same timing node
During flag data, using the normal acquisition data as the monitoring data of the timing node.
In the embodiment of the present invention, when Supplementing Data is monitored, if certain or some abnormality mark data are corresponding
Timing node, when both there are abnormality mark data and there is also normal acquisition data, then using normal acquisition data as segmentum intercalaris when this
The monitoring data of point.When being broken down due to monitored object, data acquisition module may acquire part monitoring data simultaneously
It is stored in corresponding monitoring data list, the influence of the not monitored object outages of this partial data.Therefore, this part is acquired simultaneously
The data of storage are valid data, can be directly presented in the monitoring data trend graph of inquiry terminal.
Alternatively, in apparatus of the present invention, described for the corresponding timing node of abnormality mark data, completion is monitored accordingly
Data, also include：
Only there are abnormality mark data in the abnormality data table and in the monitoring data table when same timing node
During in the absence of normal acquisition data, using data 0 as the monitoring data of the timing node.
In the embodiment of the present invention, when Supplementing Data is monitored, if certain or some abnormality mark data are corresponding
Timing node, only exists abnormality mark data and does not exist normal acquisition data, then show monitored object failure, and data acquisition is lost
Lose.It is compared by the timestamp of monitoring data and the timing node of abnormality mark data, which timing node is easily found
Upper data acquisition failure.When user inquires about the trend graph of associated monitoring data, to the timing node of these data acquisitions failure,
Completion is carried out with data 0, is then presented in the monitoring data trend graph of inquiry terminal.So, can not only avoid monitoring number
There is error in data according to trend graph to be connected, it also avoid inserting unnecessary a large amount of rubbish redundant datas in monitoring data.
Alternatively, the invention provides the monitoring data processing unit of second embodiment, as shown in figure 3, the device is also wrapped
Include：
Display module, for the monitoring data after completion to be shown into linear trend graph in the front-end interface, wherein,
Respectively using timing node and monitoring data as abscissa and ordinate.
In the embodiment of the present invention, in order to avoid substantial amounts of rubbish redundant data insertion monitoring data table in, actually to existing
The monitoring data table for having technology is not transformed (causes data acquisition to fail, in monitoring in the event of monitored object failure
It is discontinuous on the monitoring data time in tables of data, occurs in that the covering of timing node order, only preserves collect true
Real data), only when user inquires about associated monitoring data, just under the cooperation of abnormality mark data, to data acquisition failure
Corresponding timing node carries out Supplementing Data, and the monitoring data after completion is presented on into user in the form of monitoring data trend graph
In the front-end interface of inquiry.The linear trend graph of monitoring data after completion, is vertical with monitoring data with timing node as abscissa
Coordinate, 0 is expressed as to the monitoring data at the timing node of collection failure, and gathers normal timing node normally to monitor number
According to (including there is the timing node of normal acquisition data and abnormality mark data simultaneously) is represented, user front end circle is so presented on
The linear trend graph of monitoring data in face, it is to avoid the connected problem of error in data occur, by the timing node of data acquisition failure
Also significantly show, be easy to user to carry out being accurately positioned analysis to the fault time of monitored object and defect content.
Alternatively, in apparatus of the present invention, when the monitored object occurs abnormal, the corresponding time in abnormality data table
Node inserts abnormality mark data, including：
Catch the abnormality mark information that data acquisition module sends, and the corresponding timing node insertion in abnormality data table
Abnormality mark data.
As the preferred embodiment of the embodiment of the present invention, abnormal information is set for data acquisition module or mark catches
Mechanism, usual data acquisition module can be dished out or sent out when discovery monitored object breaks down and cannot collect monitoring data
Go out abnormal information or mark, by abnormal information or mark seizure mechanism, can in time find the fault time of monitored object
Point, so as to the corresponding timing node insertion abnormality mark data in abnormality data table, to be mended as follow-up monitoring data
Full reference frame.
Monitoring data processing unit provided in an embodiment of the present invention, catch of exception machine is set by for data acquisition module
System, catches abnormal information or mark and its timing node of generation that data acquisition module sends, in abnormality data table in time
Corresponding timing node insertion abnormality mark data, as the reference frame of follow-up monitoring data completion, only inquired about in user and supervised
During control data trend graph, just according to abnormal data mark, the timing node broken down to monitored object carries out Supplementing Data, so
After be presented to user front end interface, without in monitoring data table insert rubbish redundant data (i.e. zero data), can not only keep away
Exempt from monitoring data trend graph error in data correlation problem, while a large amount of rubbish redundant digits unnecessary during monitoring data can be avoided
According to.
Correspondingly, third embodiment of the invention provides a kind of monitoring data processing method, as shown in figure 4, including：
Step S10：The monitoring data of acquisition monitoring object, the monitoring data that will be collected in monitoring data table is by collection
Timing node order preserve；
Step S12：When the monitored object occurs abnormal, the corresponding timing node insertion in abnormality data table is abnormal
Flag data；
Step S14：In front-end interface query monitor data, for the corresponding timing node of the abnormality mark data,
The corresponding monitoring data of completion.
In the embodiment of the present invention, data acquisition module is monitored data acquisition to monitored object in a conventional manner, adopts
Collection result is preserved in monitoring data table according to the timing node order of collection.Monitored when certain timing node or in certain time
Object break down (machine of such as delaying) when, monitoring data will not collected, such as in timing node 10:00:After 10 gathered datas, prison
Control object breaks down, to 10:00:25 points are just recovered normal, period 10:00:15、10:00:20 two timing nodes gather mould
Block does not collect monitoring data, and in the monitoring data table, the data of actual storage are 10:00:10 and data before and 10:
00:Data after 25, although that is, data are deposited in chronological order in monitoring data table, not actually exist 10:00：15、
10:00:20 two data of timing node.To avoid the occurrence of junk data redundancy, the embodiment of the present invention is not to monitoring data table
In the two timing nodes carry out zero padding operation, and simply in user's query monitor data, if monitoring data covering prison
There is abnormal time interval in control object, and such as query monitor data are related to timing node 10:00:15 and 10:00:When 20,
For the corresponding timing node of the abnormality mark data, it is necessary to the corresponding monitoring data of completion.
When monitored object breaks down, data acquisition module meeting throw exception mark, catch of exception module is in the prison
Control object can catch the abnormality mark when occurring abnormal, and the corresponding timing node insertion one in abnormality data table is different in time
Normal flag data.For example, 10:00:15 and 10:00:20 the two timing nodes insert two days corresponding abnormality marks respectively
Data.
When user is in front-end interface query monitor data, if there is the abnormal time in monitoring data covering monitored object
Interval, such as query monitor data are related to time interval to be 10:00:00 to 10:00:30, then for the abnormality mark data
Corresponding timing node is, it is necessary to the corresponding monitoring data of completion.So, during user's inquiry associated monitoring data, it is related to monitoring right
It is connected (i.e. time coordinate misplaces) as the timing node for breaking down would not occur monitoring data trend graph error in data
Problem.
Monitoring data processing method provided in an embodiment of the present invention, is caught by the abnormality mark information of monitored object, is only existed
During user's query monitor data trend graph, just according to abnormal data mark, the timing node broken down to monitored object is carried out
Supplementing Data, is then presented to user front end interface, without inserting rubbish redundant data (i.e. zero data) in monitoring data table,
Monitoring data trend graph error in data can be not only avoided to be connected, while occurring during monitoring data can be avoided unnecessary a large amount of
Rubbish redundant data problem.
Alternatively, in the inventive method, described for the corresponding timing node of abnormality mark data, completion is monitored accordingly
Data, including：
When the monitoring data table and abnormality data table are respectively present normal acquisition data and exception in same timing node
During flag data, using the normal acquisition data as the monitoring data of the timing node.
In the embodiment of the present invention, when Supplementing Data is monitored, if certain or some abnormality mark data are corresponding
Timing node, when both there are abnormality mark data and there is also normal acquisition data, then using normal acquisition data as segmentum intercalaris when this
The monitoring data of point.When being broken down due to monitored object, data acquisition module may acquire part monitoring data simultaneously
It is stored in corresponding monitoring data list, the influence of the not monitored object outages of this partial data.Therefore, this part is acquired simultaneously
The data of storage are valid data, can be directly presented in the monitoring data trend graph of inquiry terminal.
Alternatively, in the inventive method, described for the corresponding timing node of the abnormality mark data, completion is corresponding
Monitoring data, also includes：
Only there are abnormality mark data in the abnormality data table and in the monitoring data table when same timing node
During in the absence of normal acquisition data, using data 0 as the monitoring data of the timing node.
In the embodiment of the present invention, when Supplementing Data is monitored, if certain or some abnormality mark data are corresponding
Timing node, only exists abnormality mark data and does not exist normal acquisition data, then show monitored object failure, and data acquisition is lost
Lose.It is compared by the timestamp of monitoring data and the timing node of abnormality mark data, which timing node is easily found
Upper data acquisition failure.When user inquires about the trend graph of associated monitoring data, to the timing node of these data acquisitions failure,
Completion is carried out with data 0, is then presented in the monitoring data trend graph of inquiry terminal.So, can not only avoid monitoring number
There is error in data according to trend graph to be connected, it also avoid inserting unnecessary a large amount of rubbish redundant datas in monitoring data.
Alternatively, present invention also offers a kind of monitoring data processing method of fourth embodiment, as shown in figure 5, this hair
In bright method, also include：
Step S16：The monitoring data after completion is shown into linear trend graph in the front-end interface, wherein, respectively
Using timing node and monitoring data as abscissa and ordinate.
In the embodiment of the present invention, in order to avoid substantial amounts of rubbish redundant data insertion monitoring data table in, actually to existing
The monitoring data table for having technology is not transformed (causes data acquisition to fail, in monitoring in the event of monitored object failure
It is discontinuous on the monitoring data time in tables of data, occurs in that the covering of timing node order, only preserves collect true
Real data), only when user inquires about associated monitoring data, just under the cooperation of abnormality mark data, to data acquisition failure
Corresponding timing node carries out Supplementing Data, and the monitoring data after completion is presented on into user in the form of monitoring data trend graph
In the front-end interface of inquiry.The linear trend graph of monitoring data after completion, is vertical with monitoring data with timing node as abscissa
Coordinate, 0 is expressed as to the monitoring data at the timing node of collection failure, and gathers normal timing node normally to monitor number
According to (including there is the timing node of normal acquisition data and abnormality mark data simultaneously) is represented, user front end circle is so presented on
The linear trend graph of monitoring data in face, it is to avoid the connected problem of error in data occur, by the timing node of data acquisition failure
Also significantly show, be easy to user to carry out being accurately positioned analysis to the fault time of monitored object and defect content.
Alternatively, in the inventive method, when the monitored object occurs abnormal, the corresponding time in abnormality data table
Node inserts abnormality mark data, including：
The abnormal information sent during the monitoring data for catching acquisition monitoring object, and the corresponding time in abnormality data table
Node inserts abnormality mark data.
As the preferred embodiment of the embodiment of the present invention, abnormal information is set for data acquisition module or mark catches
Mechanism, usual data acquisition module can be dished out or sent out when discovery monitored object breaks down and cannot collect monitoring data
Go out abnormal information or mark, by abnormal information or mark seizure mechanism, can in time find the fault time of monitored object
Point, so as to the corresponding timing node insertion abnormality mark data in abnormality data table, to be mended as follow-up monitoring data
Full reference frame.
Monitoring data processing method provided in an embodiment of the present invention, catch of exception machine is set by for data acquisition module
System, catches abnormal information or mark and its timing node of generation that data acquisition module sends, in abnormality data table in time
Corresponding timing node insertion abnormality mark data, as the reference frame of follow-up monitoring data completion, only inquired about in user and supervised
During control data trend graph, just according to abnormal data mark, the timing node broken down to monitored object carries out Supplementing Data, so
After be presented to user front end interface, without in monitoring data table insert rubbish redundant data (i.e. zero data), can not only keep away
Exempt from monitoring data trend graph error in data, while unnecessary a large amount of rubbish redundant datas are occurred in can avoiding monitoring data.
Below by an one exemplary embodiment, the present invention is described in further detail.
By taking the monitoring of Tomcat performance indications as an example：When each acquisition tasks are performed, Tomcat dynamic numbers can be in succession captured
According to, Tomcat static datas, JVM dynamic datas, JVM static datas, C3P0 dynamic datas, C3P0 static datas, six are performed altogether
Secondary data acquisition operations and six MongoDB data insertion operations of non-transactional；In the process, single operation fails not
Operating result before influencing whether it, for example, the collection of JVM static datas fails, the Tomcat that takes before not interfering with it is moved
State data, Tomcat static datas, the collection of JVM dynamic datas with storage, but can cause its follow-up C3P0 dynamic data,
C3P0 static datas cannot be gathered and are put in storage.Once any in this gatherer process once fail, all can throw exception.
Therefore, it can add catch of exception mechanism (i.e. in collecting method outermost layer：try{…}catch{…}).
Data acquisition because collection failure and during throw exception flag information, can be caught by outermost catch of exception mechanism and
Treatment, performs in Catch method bodies and is inserted in the MongoDB tables of entitled TOMCAT_EXCEPTION_ specific services numbering
Enter an abnormality mark data.
For example, it is assumed that in data acquisition time node 10:00:15,10:00:There is service and delay machine in 20 two timing nodes,
Data cannot be collected, data acquisition module can timely throw exception flag information.
For the monitoring of Tomcat performance indications, when each acquisition tasks are performed, Tomcat dynamics can be in succession captured
Data, Tomcat static datas, JVM dynamic datas, JVM static datas, C3P0 dynamic datas, C3P0 static datas.Assuming that
10:00:There is the collection failure of JVM static datas in 15 this timing node, then static for Tomcat dynamic datas, Tomcat
Data, three kinds of monitoring datas of JVM dynamic datas, 10:00:15 this timing node, it is normal during data acquisition, and JVM is quiet
State data, C3P0 dynamic datas, three kinds of monitoring data collection failures (being put in storage without gathered data) of C3P0 static datas.Now,
In fault data table, correspondence 10:00:15 timing nodes are, it is necessary to insert an abnormality mark data.
Timing node 10 afterwards:00:20, Tomcat dynamic datas, Tomcat static datas, JVM dynamic datas, JVM
Static data, C3P0 dynamic datas, C3P0 static datas are put in storage without gathered data.In fault data table, correspondence 10:00:
20 timing nodes, it is also desirable to insert an abnormality mark data.
Front-end interface is carried out when the linear trend graph of the specified time interval of certain class index is inquired about, with Tomcat's in user
As a example by busy Thread Count this performance indications, if inquiry Tomcat dynamic datas, program can first from MongoDB's
TOMCAT_DYNAMIC_ specific services take out the gathered data for specifying time interval in numbering this table, then from TOMCAT_
EXCEPTION_ specific services take out the abnormality mark data for specifying time interval in numbering this table；According to normal acquisition data
Preference strategy (if same timing node has normal acquisition data and abnormality mark data simultaneously, only takes normal acquisition number
According to), the table data taken out from two tables is integrated, the Tomcat dynamic data lists t of the completion that will be finally given is returned to
Front-end interface, linear trend graph exhibition is assembled according to the algorithm of time ascending order by each the busy thread-data in the data list
Show and checked to user.
For example, when user checks Tomcat dynamic datas, 10:00:15 moment, Tomcat dynamic datas exist normal
Gathered data, although now there are abnormality mark data in abnormality data table, without being processed；And 10:00:When 20
Carve, Tomcat dynamic datas do not exist normal acquisition data, and there are abnormality mark data in abnormality data table, then 10:00:
The Tomcat dynamic datas at 20 moment need to carry out mending 0 operation.So, the Tomcat dynamic datas for being presented on front-end interface are linear
Trend graph would not the dislocation of time of occurrence coordinate cause error in data correlation problem, and the actual node of data acquisition failure is obtained
To significantly prompting.As shown in fig. 6, abscissa is the collection moment, ordinate is busy Thread Count.
When user checks JVM static datas, 10:00:15 and 10:00:20 the two moment, due to JVM static numbers
According to not existing normal acquisition data in table, and then there are abnormality mark data in abnormality data table, then the segmentum intercalaris at the two
The JVM static datas of point need to carry out mending 0 operation.So, the linear trend graph of JVM static datas of front-end interface it is not presented on just not
Occur that time coordinate dislocation causes error in data correlation problem, the timing node of the two data acquisitions failure is also obtained significantly
Prompting.As shown in fig. 7, abscissa is the collection moment, ordinate is busy Thread Count.
Fig. 8 be user in front end query monitor data, the reference flowchart processed monitoring data, as shown in figure 8,
Including：
Step S20：The monitoring data for specifying time interval is inquired about from target monitoring tables of data List-i；
Here, target monitoring tables of data can have multiple, such as the monitoring of Tomcat performance indications, adopting every time
Set task perform when, have Tomcat dynamic data tables, Tomcat static list of data, JVM dynamic data tables, JVM static list of data,
C3P0 dynamic data tables, C3P0 static list of data, totally 6 target monitoring tables of data for being available for customer inquiries, i=1 here, 2,3,
4,5,6.User can inquire about it is therein any or it is various.
Step S22：The abnormal marking data for specifying time interval are inquired about from abnormality data table List-e, temporally ascending order
Order recursive query；One monitor task, such as Tomcat performance indications are monitored, it is only necessary to an abnormality data table.
Step S24：Judge that the abnormality mark data in every List-e whether there is in target monitoring data List-i
The monitoring data of corresponding timing nodeIf it does, not making the direct step S28 of other treatment；If it does not, meeting step S26.
Step S26：The record that a data is 0 is inserted in the corresponding timing node of target monitoring tables of data List-i；
Step S28:The final goal monitoring data table List-i after (completion) will be integrated to be shown according to time increase order
Be not in the connected linear trend graph of monitoring data of error in data such that it is able to present in front-end interface.
The present invention proposes the scheme of the linear trend graph of completion monitoring data, in can solving the acquisition time of linear trend graph
Connected (the i.e. time coordinate dislocation) problem of disconnected but curve data mistake, and the geometry times of rubbish redundant data can be avoided sudden and violent
Rise.
This programme is more easy to extension for collection is unsuccessfully inserted into the scheme of 0 data, without paying close attention to original business thing
Business relation, only need to add catch of exception in the outermost of collecting method；0 data are unsuccessfully inserted into relative to collection
For scheme, then the increase of invalid redundant data is significantly reduced；The number of time interruption but linear trend graph is solved well
According to the problem of connected (i.e. time coordinate dislocation).
It should be noted that herein, term " including ", "comprising" or its any other variant be intended to non-row
His property is included, so that process, method, article or device including a series of key elements not only include those key elements, and
And also include other key elements being not expressly set out, or also include for this process, method, article or device institute are intrinsic
Key element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including this
Also there is other identical element in the process of key element, method, article or device.
The embodiments of the present invention are for illustration only, and the quality of embodiment is not represented.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably implementation method.Based on such understanding, technical scheme is substantially done to prior art in other words
The part for going out contribution can be embodied in the form of software product, and the computer software product is stored in a storage medium
In (such as ROM/RAM, magnetic disc, CD), including some instructions are used to so that station terminal equipment (computer, server, or a net
Network equipment etc.) perform method described in each embodiment of the invention.
The preferred embodiments of the present invention are these are only, the scope of the claims of the invention is not thereby limited, it is every to utilize this hair
Equivalent structure or equivalent flow conversion that bright specification and accompanying drawing content are made, or directly or indirectly it is used in other related skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of monitoring data processing unit, it is characterised in that including：
Data acquisition module, for the monitoring data of acquisition monitoring object, the monitoring data that will be collected in monitoring data table
Preserved by the timing node order of collection；
Catch of exception module, for when the monitored object occurs abnormal, the corresponding timing node in abnormality data table to be inserted
Enter abnormality mark data；
Supplementing Data module, in front-end interface query monitor data, for the abnormality mark data corresponding time
Node, the corresponding monitoring data of completion.
2. device as claimed in claim 1, it is characterised in that described for the corresponding timing node of abnormality mark data, mends
Complete corresponding monitoring data, including：
When the monitoring data table and abnormality data table are respectively present normal acquisition data and abnormality mark in same timing node
During data, using the normal acquisition data as the monitoring data of the timing node.
3. device as claimed in claim 1 or 2, it is characterised in that described for the corresponding timing node of abnormality mark data,
The corresponding monitoring data of completion, also includes：
Do not deposited in the monitoring data table when same timing node only has abnormality mark data in the abnormality data table
In normal acquisition data, using data 0 as the monitoring data of the timing node.
4. device as claimed in claim 3, it is characterised in that also include：
Display module, for the monitoring data after completion to be shown into linear trend graph in the front-end interface, wherein, respectively
Using timing node and monitoring data as abscissa and ordinate.
5. device as claimed in claim 1, it is characterised in that when the monitored object occurs abnormal, in abnormality data table
In corresponding timing node insertion abnormality mark data, including：
Catch the abnormal information that data acquisition module sends, and the corresponding timing node insertion abnormality mark in abnormality data table
Data.
6. a kind of monitoring data processing method, it is characterised in that including：
The monitoring data of acquisition monitoring object, the monitoring data that will be collected in monitoring data table is suitable by the timing node of collection
Sequence is preserved；
When the monitored object occurs abnormal, the corresponding timing node insertion abnormality mark data in abnormality data table；
In front-end interface query monitor data, for the corresponding timing node of the abnormality mark data, completion is supervised accordingly
Control data.
7. method as claimed in claim 6, it is characterised in that described for the corresponding timing node of abnormality mark data, mends
Complete corresponding monitoring data, including：
When the monitoring data table and abnormality data table are respectively present normal acquisition data and abnormality mark in same timing node
During data, using the normal acquisition data as the monitoring data of the timing node.
8. method as claimed in claims 6 or 7, it is characterised in that described for the abnormality mark data corresponding time
Node, the corresponding monitoring data of completion, also includes：
Do not deposited in the monitoring data table when same timing node only has abnormality mark data in the abnormality data table
In normal acquisition data, using data 0 as the monitoring data of the timing node.
9. method as claimed in claim 8, it is characterised in that also include：
The monitoring data after completion is shown into linear trend graph in the front-end interface, wherein, respectively with timing node and
Monitoring data is used as abscissa and ordinate.
10. method as claimed in claim 6, it is characterised in that when the monitored object occurs abnormal, in abnormality data table
In corresponding timing node insertion abnormality mark data, including：
The abnormal information sent during the monitoring data for catching acquisition monitoring object, and the corresponding timing node in abnormality data table
Insertion abnormality mark data.
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