CN101883004A - Method, device and system for synthesizing service data - Google Patents
Method, device and system for synthesizing service data Download PDFInfo
- Publication number
- CN101883004A CN101883004A CN2009101376590A CN200910137659A CN101883004A CN 101883004 A CN101883004 A CN 101883004A CN 2009101376590 A CN2009101376590 A CN 2009101376590A CN 200910137659 A CN200910137659 A CN 200910137659A CN 101883004 A CN101883004 A CN 101883004A
- Authority
- CN
- China
- Prior art keywords
- data
- tdr data
- tdr
- match
- affairs
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the invention discloses a method, a device and a system for synthesizing service data. The method disclosed by the embodiment of the invention comprises the following steps of: loading transaction detail record (TDR) data; matching the loaded TDR data according to the matching rule of the TDR data; and integrating the matched TDR data into service detail record (SDR). The embodiment of the invention realizes end-to-end service synthesis of the TDR data.
Description
Technical field
The present invention relates to communication technical field, relate in particular to a kind of business datum synthetic method, Apparatus and system.
Background technology
In the face of intense market competition, how telecom operators improves user experience quality (Quality of Experience QOE) meets consumers' demand, to reduce churn rate if more and more paying close attention to.
The common way that improves QOE is: the user level that user experience is related to and the factor indexization of network level, and in service level agreement (Service Level Agreement monitors and manages in SLA).Reach the purpose that improves QOE by SLA middle finger target optimization, and it is maintained on the higher level.
SLA middle finger target architecture is divided into 3 levels with business network, is respectively from low to high: Service Source (Service Resources), Service Elements (service element) and ProductComponents (product component).The index that corresponds respectively to above-mentioned 3 levels is: KPIs (Key Performance Indicator), service Key Quality Indicator (Service KQIs) and professional Key Quality Indicator (ProductKQIs).
Based on SLA middle finger target architecture, the existing scheme that improves QOE is: gather in real time and analyze at each network interface based on standard agreement, the TDR data that take place on each interface of business network are provided in real time.Corresponding SLA middle finger target architecture, this scheme provides the ServiceElements of whole service network and the data analysis of Service Resources aspect.The data of Service Resources aspect by on the probe slave unit interface directly monitoring obtain, the data of Service Elements aspect (i.e. all TDR data) by the message of probe collection resolve with adaptive after obtain.These data are calculated, added up, and then can obtain comprehensive KPIs and Service KQIs.
The inventor is in research process, find that there is following shortcoming at least in the above-mentioned existing scheme that improves QOE based on SLA middle finger target architecture: when professional end-to-end index is provided, need manually the TDR data to be carried out post analysis and statistics, efficient is low, and real-time is poor.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of business datum synthetic method, Apparatus and system, the TDR data is carried out professional end to end synthetic.
The method that a kind of business datum is synthetic, described method comprises:
Loading transaction detail record TDR data;
According to the matched rule of TDR data, the TDR data of having carried out loading are mated;
The TDR data that match are integrated into professional detail record SDR.
The device that a kind of business datum is synthetic, described device comprises:
Load-on module is used for loading transaction detail record TDR data;
Matching module is used for the matched rule according to the TDR data, and the TDR data that described load-on module has carried out loading are mated;
Integrate module, the TDR data that are used for that matching module is matched are integrated into professional detail record SDR.
The system that a kind of business datum is synthetic, described system comprises:
Analysis server is used for loading transaction detail record TDR data; According to the matched rule of TDR data, the TDR data of having carried out loading are mated; The TDR data that match are integrated into professional detail record SDR, and export described SDR to client.
As can be seen, by loading the TDR data, the TDR data that loaded are mated, the TDR data that match are integrated into SDR, can realize professional end to end synthetic.Thereby do not need manually Transaction Information to be carried out post analysis and statistics, improved operating efficiency, satisfied the real-time requirement.
Description of drawings
Fig. 1 is an embodiment of the invention system architecture schematic diagram;
Fig. 2 is an embodiment of the invention method flow diagram;
Fig. 3 loads the method flow diagram of TDR data for the embodiment of the invention;
The method flow diagram that Fig. 4 mates initial affairs TDR data for the embodiment of the invention;
The method flow diagram that Fig. 5 mates non-initial affairs TDR data for the embodiment of the invention;
Fig. 6 is the embodiment of the invention method flow diagram that the mapping relations in the internal memory are recovered during to system break;
Fig. 7 carries out life cycle management for the embodiment of the invention to the historical data analysis pattern method flow diagram;
Fig. 8 carries out life cycle management for the embodiment of the invention to the real time data analytical model method flow diagram;
Fig. 9 provides the method flow diagram of accident analysis for the embodiment of the invention;
Figure 10 is an embodiment of the invention structured flowchart;
Figure 11 is the another kind of structured flowchart of the embodiment of the invention.
Embodiment
For above-mentioned feature, the advantage that makes the embodiment of the invention becomes apparent more, be elaborated below in conjunction with embodiment.
In order no longer manually Transaction Information to be carried out post analysis and statistics, improve user experience quality, to increase work efficiency, requirement of real time, the embodiment of the invention provide following technical scheme.
Please refer to Fig. 1, be embodiment of the invention system architecture schematic diagram.Analysis server 101 obtains affairs detail record TDR data from storage server 102, through handling, and outgoing traffic detail record SDR, and export described SDR to Web client 103.
In embodiments of the present invention, each performed step of Analysis server sees also following description.
Please refer to Fig. 2, be embodiment of the invention method flow diagram, can may further comprise the steps:
Step 201: loading transaction detail record TDR data;
Step 202:, the TDR data of having carried out loading are mated according to the matched rule of TDR data;
Step 203: the TDR data that match are integrated into professional detail record SDR.
Alternatively, step shown in Figure 1 can further include: deposit SDR in database.
As can be seen, by loading the TDR data, the TDR data that loaded are mated, the TDR data that match are integrated into SDR, can realize professional end to end synthetic.Thereby do not need manually Transaction Information to be carried out post analysis and statistics, improved operating efficiency, satisfied the real-time requirement.
The embodiment of the invention be in order dynamically to support multiple business, need carry out abstractly to professional, affairs and rule etc., is described with the form of relation database table.These relation database tables are called business model, are used to carry out initialization.The relation database table that the embodiment of the invention is used can be with reference to following example:
(1) traffic table is used to describe service attribute.
Describe: traffic table (traffic ID, professional name ...)
(2) transaction table is used to describe transaction attributes, mainly comprises the TDR table name of Data Source etc.
Describe: transaction table (affairs ID, the affairs name, affairs TDR table name ...)
(3) business transaction relation table is used to describe the relation of professional and affairs, which affairs is arranged under professional, and whether the ordinal relation of these affairs in business participates in synthesizing or accident analysis etc.
Describe: the business transaction relation table (the affairs serial number synthesizes and enables sign for traffic ID, affairs ID, and sign is enabled in accident analysis ...)
(4) matched rule table is used for the matched rule between two affairs of the business of describing, and the relation of an a pair of field of record description can have one or more field relation between two affairs.
Describe: the matched rule table (traffic ID, the ID of affairs A, the Field ID of affairs A, the ID of affairs B, the Field ID of affairs B, match-type ...)
(5) transaction status description list is used to describe the implication that the transaction status sign indicating number is represented, and state is used for accident analysis.
Describe: the transaction status description list (affairs ID, transaction field ID, conditional code, state description successfully identifies ...)
Below step shown in Figure 1 is elaborated.At first introduce and load the TDR data.
Please refer to Fig. 3, the method flow diagram for embodiment of the invention loading TDR data can may further comprise the steps:
Step 301: according to traffic ID loading transaction descriptor;
Described affairs descriptor is the affairs descriptor of all affairs of comprising of a business, and this business is determined by described traffic ID.
Step 302: read an affairs descriptor;
Step 303: according to the affairs descriptor that reads, judge whether it is to start affairs, if, enter step 304, otherwise, step 305 entered;
Start an attribute of affairs descriptor, identify the professional affairs of initiating, normally Ye Wu first affairs.
Step 304: according to affairs ID match query rule list, obtain the child node affairs quantity, child node affairs ID and by matching field information, enter step 306;
Step 305: according to affairs ID match query rule list, obtain the ID of father node affairs, the quantity of matching field information, child node affairs and ID and by matching field information enter step 306;
Step 306: judge whether other affairs descriptor in addition,, return step 302, and read next bar affairs descriptor if having, otherwise, enter step 307.
Step 307: according to affairs descriptor and matched rule, the TDR data of beginning loading transaction correspondence, flow process finishes.
Because be not that all fields to the TDR data load, the field that only relates to coupling just loads, and therefore, in step 307, also needs to learn matched rule.
The so-called loading, all needs when interrupting recovering by loading the TDR data to be read in system coupling, and the time of loading is different and different according to the mode that the TDR data are provided.With the database mode is example, obtains the table name, the field name that need to load exactly and be combined into the SQL script in initialization procedure, by the interface (as the OCI of Oracle) that database provides script is passed to database and is obtained result set.It is in the data structure of TDR data allocations that system inserts the data in the result set in the internal memory, promptly finishes loading.
Step shown in Figure 3 is used for the TDR data load of database is come in, and changes into the data structure of embodiment of the invention functional entity self.Load different TDR data conditions for adapting to different business, need be before loading initialization affairs descriptor and match information, can support different business thereby just need not recompilate.
At step shown in Figure 3, also it is to be noted:
(1) each different business is by embodiment of the invention functional entity independent process, so that because of reason distributed deployments such as performances.
(2) matched rule is that to form one by the matching relationship between affairs be the tree of root node with initial affairs for all affairs of a business, coupling is carried out step by step from root node, the field information of using when matching field information refers to these affairs and its father node affairs coupling is referred to that by matching field information child node affairs and these affairs relate to the field of these affairs when mating.Initial affairs (being root node) do not have matching field information.Is the leaf node affairs by matching field information for empty affairs.
(3) step 301 is initialization procedures to step 306, only needs to carry out once.The loading procedure of step 307 can continue to carry out.
Below the TDR data of having carried out loading are mated and be elaborated.
For the initial affairs TDR data that loaded, with new SDR of described initial affairs TDR data initialization, and according to the mapping relations in the matched rule updating memory, mapping relations are the match information of preserving in the internal memory and the mapping relations of SDR unique identification (CallID).
For the non-initial affairs TDR data that loaded, mate according to the match information in matched rule and the internal memory, if the match is successful, the mapping relations in the updating memory; If it fails to match, when described non-initial affairs TDR data are historical data analysis patterns, then flow process finishes, and when described non-initial affairs TDR data are real time data analytical models, then mates once more behind the buffer memory in internal memory.
By the historical data analysis pattern is independent from the real time data analytical model, when analyzing non-real-time data, needs can obtain higher efficient.
Please refer to Fig. 4, the method flow diagram for the embodiment of the invention is mated initial affairs TDR data can may further comprise the steps:
Step 401: the initial affairs TDR data that read a loading;
Step 402: be the unique identification (CallID) of this TDR data allocations SDR, and upgrade by the mapping relations between matching field information and the CallID;
Match information just is kept at internal memory and has suffered like this.The corresponding mapping relations of each child node affairs.
Step 403: with the effective information warehouse-in of these TDR data, the effective information of TDR data discharges from internal memory, and flow process finishes.
Need to prove, each field of TDR data can be divided into effective information (effective information is the information that need be incorporated among the SDR) and match information (match information is the field information that is used for mating between affairs, comprise matching field information and by matching field information).Allow a field be effective information also be match information.The field that effective information and match information comprise all needs to load, after coupling, the effective information of TDR data separated with match information, and every TDR data effective information warehouse-in renewal SDR, match information is stayed and is upgraded mapping relations in the internal memory.Because effective information needn't equally with match information be retained in internal memory up to finishing once the synthetic of business or surpassing life cycle, saved memory headroom.If further simplify the effective information that loads, only keep the intrinsic fields of all TDR such as TDR serial number, warehouse-in can also stipulate that unified format submits in batches, raises the efficiency.
Please refer to Fig. 5, the method flow diagram for the embodiment of the invention is mated non-initial affairs TDR data can may further comprise the steps:
Step 501: the non-initial affairs TDR data that read a loading;
Step 502: mate;
Promptly inquire about the match information that the father node affairs are preserved with the matching field value of the TDR data that load in the step 501, then the match is successful to find identical record, otherwise it fails to match;
Step 503: judge whether coupling is successful, if success enters step 504, otherwise, enter step 505;
Step 504: for the child node affairs of these affairs are upgraded by the mapping relations between matching field information and the CallID, with the effective information warehouse-in of these TDR data, the effective information of TDR data discharges from internal memory, and flow process finishes;
Step 505: judge that these non-initial affairs TDR data are historical data analysis pattern or real time data analytical model, if the historical data analysis pattern, flow process finishes, if the real time data analytical model enters step 506:
For the historical data analysis pattern, because all data all are static, the TDR data that it fails to match can be carried out buffer memory when handling real time data.The historical data analysis pattern is independent, and the mode that adopt buffer memory not, loads successively can improve the efficient under the analysis of history data application scenarios.
Step 506: these non-initial TDR data buffer memory in internal memory mates after one end section time again;
Need the reason of buffer memory to be under the real time data analytical model: it fails to match for the TDR data loading of avoiding once professional different affairs out of order (the TDR data acquisition of different affairs is handled different generation of time delay with transmission) causes, and the TDR data that it fails to match carried out the buffer memory of certain hour.After mating once more through the TDR data of buffer memory, no matter success or not all can be released.
Step 507: judge whether coupling is final successful, if success enters step 504, otherwise flow process finishes.
It is pointed out that coupling can carry out according to following rule:
1, if the value of two TDR data fields equates that then the match is successful;
For example: if TDR1.field11=TDR2.field21, then the match is successful for TDR1 and TDR2.Particularly, after every TDR1 finishes loading, upgrade mapping relations with CallID with field1, every TDR2 searches this mapping relations with field1, find field1 after, obtain the CallID of TDR1, the match is successful.
After when 2, loading the field of TDR data having been carried out computing (for example arithmetic operator, character string computing etc.), equate that with the value of another TDR data field then the match is successful.
For example: TDR1.field11=substr (TDR2.field21 ,-12,12).
3, if two TDR data have the value of two group fields to equate that then the match is successful respectively.
For example: TDR1.field11=TDR2.field21AND TDR1.field12=TDR2.field22.
4, if satisfying two TDR data of any two matched rules in above-mentioned 1,2,3 (can belong to same matched rule, also can belong to two different matched rules) satisfies condition, then the match is successful.
For example: (TDR1.field11=TDR2.field21AND TDR1.field12=TDR2.field22) OR (TDR1.field11=TDR2.field21AND TDR1.field13=TDR2.field23).
5, the time field of two TDR data is subtracted each other, if satisfy predetermined scope, then the match is successful.
For example: TDR1 field value=TDR2 field value ANDTDR2.timestamp-TDR1.timestamp＜time range.
More than to loading the TDR data and coupling TDR data have been described in detail.
Alternatively, before carrying out loading TDR data, can also comprise interrupt recovery procedure.
Please refer to Fig. 6, the method flow diagram that the mapping relations in the internal memory are recovered during to system break for the embodiment of the invention can may further comprise the steps:
Step 601: obtain business, affairs descriptor and match information by initialization;
Step 602: judge whether that needs recover the mapping relations in the internal memory,, enter step 603 if do not need, otherwise, enter step 604;
Step 603: begin to load, flow process finishes;
Step 604: with reference to the SDR data of having put in storage, reload corresponding TDR data, the mapping relations before reconstruct is interrupted in the internal memory (also being the mapping relations of SDR correspondence in the life cycle) enter 603;
Judge whether that the condition that needs to recover is: the state that can write down each time granularity SDR data structure in the internal memory when moving in system is to external memory.If not having the state of record or all records all is to finish, then do not need to recover.Otherwise, be the state of handling as long as any record is arranged, just need to recover.
Alternatively, because business has life cycle, before TDR Data Matching, can also carry out life cycle management to the match information that the TDR data are preserved to each time period.
For the TDR data of historical data analysis pattern, regularly removing exceeds the mapping relations of life cycle, and withdraws from after the integration of finishing set period.For the TDR data of real time data analytical model, regularly remove the mapping relations that exceed life cycle.Be elaborated below.
Please refer to Fig. 7, the method flow diagram for the embodiment of the invention is carried out life cycle management to the historical data analysis pattern can may further comprise the steps:
Step 701: all TDR Data Matching of finishing a time granularity correspondence;
Because be mass data, generally can divide the TDR data according to the time, corresponding in the database may be submeter or subregion.The size of the period of dividing is exactly time granularity (according to service life cycle and the decision of traffic carrying capacity summation), selects to carry out life cycle control according to time granularity during coupling TDR data, and it is higher to select time of every TDR data to carry out control efficiency relatively.
Step 702: judge whether to finish the integration of set period, if flow process finishes, otherwise, enter step 703;
Step 703: judge the mapping relations whether N time granularity has been arranged in the internal memory, if, enter step 704, otherwise, step 701 entered;
N is by the time granularity and the service life cycle decision of TDR data, and the N=service life cycle is 1 day divided by time granularity+1 as granularity, and life cycle is 2 days, then N=2/1+1=3.(adding 1 reason is that TDR strides the period, as life cycle be the TDR of 2 days business may appear at 3 time granularities for day period in)
Step 704: remove in the internal memory mapping relations (life cycle that is this batch data finishes) of 1 time granularity the earliest, enter step 701.
Please refer to Fig. 8, the method flow diagram for the embodiment of the invention is carried out life cycle management to the real time data analytical model can may further comprise the steps:
Step 801: load all TDR data of analyzing a time granularity correspondence;
Step 802: judge the mapping relations whether N time granularity has been arranged in the internal memory, if, enter step 803, otherwise, step 801 entered;
The definition of N please refer to the description in the step 703.
Step 803: remove in the internal memory mapping relations (life cycle that is this batch data finishes) of 1 time granularity the earliest, enter step 801.
The difference of step shown in Figure 8 and step shown in Figure 7 is: when the historical data analysis pattern is carried out life cycle management, usually only need to handle the data of a time period, do not need to continue to handle, so after the processing of the data of finishing the fixed time section, will no longer continue to carry out.
For integration, be will belong to all once professional TDR data identical ID of mark all, the process of integration be exactly with these marks the TDR data of identical ID be merged into SDR data.Implementation mainly contains two types, a kind of is to be combined into complete SDR data to output to database or file then in internal memory, another kind be with mark the TDR data of ID (not necessarily original TDR, can be to have only serial number) output to database or file, finish integration by database or background program.Preferred second type.
Alternatively, in integration process, the embodiment of the invention can also provide accident analysis, promptly according to the transaction state information of TDR data, upgrades the business state information of SDR data, makes the data after the integration comprise business state information.
Please refer to Fig. 9,, can may further comprise the steps for the embodiment of the invention provides the method flow diagram of accident analysis:
Step 901: read out a TDR who finishes coupling;
Step 902: judge whether to be the TDR on first coupling in the same once business, if, enter step 903, otherwise, step 904 entered;
Step 903: take out the value of the mode field in the TDR record, judge whether the state of affairs is successful, and with the affairs serial number, successfully sign, conditional code are updated to SDR, flow process finishes;
Step 904: judge whether the affairs serial number is equal to, or greater than the current affairs serial number of SDR, if enter step 903, otherwise flow process finishes.
In matching process, each finishes the TDR information of coupling, information such as the transaction status definition that defines in the comparable data storehouse, and whether the conditional code that obtains affairs is described, malfunctioning node, and successful.According to whether successful, and the current maximum transaction serial number of SDR data, the more state of new business.As certain bar SDR record, its affairs of finishing maximum serial number are affairs A, and these affairs fail, and then service condition is exactly affairs A failure, and the node of the description of fault and correspondence has that the affairs conditional code is related to be obtained.
The sequential of affairs in the affairs serial number reflection business (numerical value more little more early), sequential might not be identical with the coupling along order, therefore there is the situation of mating after the little TDR data of affairs serial number, at this moment be need not upgrade service condition, the state that service condition only need be preserved the TDR reflection of serial number maximum gets final product.
When realizing professional complex functionality, can select to carry out simultaneously accident analysis, provide the basic fault information, state of body etc. of attending to the basic or the fundamental of getting over, when business datum is analyzed, can be more prone to like this based on Transaction Information.
As can be seen, by loading the TDR data, the TDR data that loaded are mated, the TDR data that match are integrated into SDR, can realize professional end to end synthetic.Thereby do not need manually Transaction Information to be carried out post analysis and statistics, improved operating efficiency, satisfied the real-time requirement.
In addition, by the embodiment of the invention, make and just can support multiple business by simple configuration.
Please refer to Figure 10, be embodiment of the invention structured flowchart, comprising:
Load-on module 1001 is used for loading transaction detail record TDR data;
Integrate module 1003, the TDR data that are used for that matching module 1002 is matched are integrated into professional detail record SDR.
As can be seen, by loading the TDR data, the TDR data that loaded are mated, the TDR data that match are integrated into SDR, can realize professional end to end synthetic.Thereby do not need manually Transaction Information to be carried out post analysis and statistics, improved operating efficiency, satisfied the real-time requirement.
Please refer to Figure 11, be the another kind of structured flowchart of the embodiment of the invention, can comprise:
Load-on module 1101 is used for loading transaction detail record TDR data;
Integrate module 1103, the TDR data that are used for that matching module 1102 is matched are integrated into professional detail record SDR;
Interrupt recovering module 1104, be used for before described load-on module 1101 loads, the mapping relations in the internal memory being recovered;
Life cycle management module 1105 is used for before the TDR data that 1102 pairs of described matching modules have carried out loading are mated the TDR data being carried out the life cycle management operation;
Go into library module 1107, be used for that integrate module 1103 is integrated good SDR and deposit database in.
In addition, in the invention process, described data comprise profile data, are used to provide the parameter of system's operation; The business model data are used for business, affairs, matched rule are described; TDR data and SDR data: being the main input and output of system, can be the form of database table, also can be file.
The embodiment of the invention also provides a kind of business datum synthetic system, is used to improve user experience quality, and described system can comprise Analysis server, is used for loading transaction detail record TDR data; According to the matched rule of TDR data, the TDR data of having carried out loading are mated; The TDR data that match are integrated into professional detail record SDR, and export described SDR to client.
Described Analysis server and particular server carry out integrated, and perhaps, described Analysis server is independent of particular server.
At last, also need to prove, in this article, relational terms such as first and second grades only is used for an entity or operation are made a distinction with another entity or operation, and not necessarily requires or hint and have the relation of any this reality or in proper order between these entities or the operation.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thereby make and comprise that process, method, article or the equipment of a series of key elements not only comprise those key elements, but also comprise other key elements of clearly not listing, or also be included as this process, method, article or equipment intrinsic key element.Do not having under the situation of more restrictions, the key element that limits by statement " comprising ... ", and be not precluded within process, method, article or the equipment that comprises described key element and also have other identical element.
Through the above description of the embodiments, those skilled in the art can be well understood to the present invention and can realize by the mode that software adds essential hardware platform, can certainly all implement, but the former is better execution mode under a lot of situation by hardware.Based on such understanding, all or part of can the embodying that technical scheme of the present invention contributes to background technology with the form of software product, this computer software product can be stored in the storage medium, as ROM/RAM, magnetic disc, CD etc., comprise that some instructions are with so that a computer equipment (can be a personal computer, server, the perhaps network equipment etc.) carry out the described method of some part of each embodiment of the present invention or embodiment.
More than the present invention is described in detail, used specific case herein principle of the present invention and execution mode set forth, the explanation of above embodiment just is used for help understanding method of the present invention and core concept thereof; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, the part that all can change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (11)
1. the synthetic method of a business datum is characterized in that described method comprises:
Loading transaction detail record TDR data;
According to the matched rule of TDR data, the TDR data of having carried out loading are mated;
The TDR data that match are integrated into professional detail record SDR.
2. method according to claim 1 is characterized in that, the described TDR data of having carried out loading are mated comprises:
For the initial affairs TDR data that loaded, with new SDR of described initial affairs TDR data initialization, and according to the mapping relations in the matched rule updating memory, described mapping relations are match information and SDR uniquely identified mapping relations.
3. method according to claim 1 is characterized in that, the described TDR data of having carried out loading are mated comprises:
For the non-initial affairs TDR data that loaded, mate according to matched rule and match information, if the match is successful, the mapping relations in the updating memory; If it fails to match, when described non-initial affairs TDR data are historical data analysis patterns, finish this flow process, when described non-initial affairs TDR data are real time data analytical models, then in internal memory, mate once more behind the buffer memory.
4. according to claim 2 or 3 described methods, it is characterized in that described matched rule comprises:
If the value of two TDR data fields equates that then the match is successful;
Perhaps,
During loading the field of TDR data has been carried out after the computing, equated that with the value of another TDR data field then the match is successful;
Perhaps,
If two TDR data have the value of two group fields to equate that then the match is successful respectively;
Perhaps,
If two TDR data that belong to above-mentioned same matched rule or belong to above-mentioned two different matched rules satisfy the condition that the match is successful, then the match is successful;
Perhaps,
The time field of two TDR data is subtracted each other, if satisfy predetermined scope, then the match is successful.
5. according to claim 2 or 3 described methods, it is characterized in that, described the TDR data of having carried out loading are mated before, described method also comprises:
The match information that the TDR data are preserved is carried out life cycle management.
6. method according to claim 5 is characterized in that, the match information of TDR data preservation is carried out life cycle management comprise:
For the TDR data of historical data analysis pattern, regularly removing exceeds the mapping relations of life cycle, and withdraws from after the integration of finishing set period;
Perhaps,
For the TDR data of real time data analytical model, regularly remove the mapping relations that exceed life cycle.
7. method according to claim 1 is characterized in that, before described loading transaction detail record TDR data, described method also comprises:
If interrupted when system moved last time, the mapping relations when described system interrupts generation earlier after startup in the internal memory are recovered.
8. the synthetic device of a business datum is characterized in that described device comprises:
Load-on module is used for loading transaction detail record TDR data;
Matching module is used for the matched rule according to the TDR data, and the TDR data that described load-on module has carried out loading are mated;
Integrate module, the TDR data that are used for that matching module is matched are integrated into professional detail record SDR.
9. device according to claim 8 is characterized in that, described device also comprises:
The life cycle management module is used for before described matching module mates the TDR data of having carried out loading the TDR data being carried out the life cycle management operation.
10. device according to claim 8 is characterized in that, described device also comprises:
Interrupt recovering module, be used for before described load-on module loads, the mapping relations in the internal memory being recovered.
11. the system that business datum is synthetic is characterized in that described system comprises:
Analysis server is used for loading transaction detail record TDR data; According to the matched rule of TDR data, the TDR data of having carried out loading are mated; The TDR data that match are integrated into professional detail record SDR, and export described SDR to client.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2009101376590A CN101883004A (en) | 2009-05-04 | 2009-05-04 | Method, device and system for synthesizing service data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2009101376590A CN101883004A (en) | 2009-05-04 | 2009-05-04 | Method, device and system for synthesizing service data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101883004A true CN101883004A (en) | 2010-11-10 |
Family
ID=43054905
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2009101376590A Pending CN101883004A (en) | 2009-05-04 | 2009-05-04 | Method, device and system for synthesizing service data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101883004A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112306664A (en) * | 2020-11-13 | 2021-02-02 | 苏州浪潮智能科技有限公司 | Service restarting method, system, equipment and medium |
| CN112491595A (en) * | 2020-11-12 | 2021-03-12 | 杭州迪普信息技术有限公司 | Fault area positioning method, device, equipment and computer readable storage medium |
-
2009
- 2009-05-04 CN CN2009101376590A patent/CN101883004A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112491595A (en) * | 2020-11-12 | 2021-03-12 | 杭州迪普信息技术有限公司 | Fault area positioning method, device, equipment and computer readable storage medium |
| CN112306664A (en) * | 2020-11-13 | 2021-02-02 | 苏州浪潮智能科技有限公司 | Service restarting method, system, equipment and medium |
| CN112306664B (en) * | 2020-11-13 | 2022-07-08 | 苏州浪潮智能科技有限公司 | Service restarting method, system, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9679021B2 (en) | Parallel transactional-statistics collection for improving operation of a DBMS optimizer module | |
| CN107908672B (en) | Application report realization method, device and storage medium based on Hadoop platform | |
| CN102117306B (en) | Method and system for monitoring ETL (extract-transform-load) data processing process | |
| CN108536761A (en) | Report data querying method and server | |
| CN105051729A (en) | Data records selection | |
| CN103336790A (en) | Hadoop-based fast neighborhood rough set attribute reduction method | |
| CN102073640A (en) | Method, system and server for testing structured query language (SQL) statements | |
| CN111339073A (en) | Real-time data processing method and device, electronic equipment and readable storage medium | |
| CN114218218A (en) | Data processing method, device and equipment based on data warehouse and storage medium | |
| CN103077192B (en) | A kind of data processing method and system thereof | |
| CN112148578A (en) | IT fault defect prediction method based on machine learning | |
| CN116244367A (en) | Visual big data analysis platform based on multi-model custom algorithm | |
| CN115564071A (en) | Method and system for generating data labels of power Internet of things equipment | |
| CN112001539B (en) | High-precision passenger transport prediction method and passenger transport prediction system | |
| CN106919566A (en) | A kind of query statistic method and system based on mass data | |
| CN110309206B (en) | Order information acquisition method and system | |
| Martinez-Mosquera et al. | Development and evaluation of a big data framework for performance management in mobile networks | |
| CN116048817B (en) | Data processing control method, device, computer equipment and storage medium | |
| CN101883004A (en) | Method, device and system for synthesizing service data | |
| CN114757448B (en) | Manufacturing inter-link optimal value chain construction method based on data space model | |
| CN115599871A (en) | Lake and bin integrated data processing system and method | |
| Wang et al. | Research and design of RFID data processing model based on complex event processing | |
| CN114860851A (en) | Data processing method, device, equipment and storage medium | |
| CN110750582A (en) | Data processing method, device and system | |
| CN115391286A (en) | Link tracking data management method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20101110 |