CN106951557A - Daily record correlating method, device and apply its computer system - Google Patents
Daily record correlating method, device and apply its computer system Download PDFInfo
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- CN106951557A CN106951557A CN201710205435.3A CN201710205435A CN106951557A CN 106951557 A CN106951557 A CN 106951557A CN 201710205435 A CN201710205435 A CN 201710205435A CN 106951557 A CN106951557 A CN 106951557A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/18—File system types
- G06F16/1805—Append-only file systems, e.g. using logs or journals to store data
- G06F16/1815—Journaling file systems
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Abstract
Disclose a kind of daily record correlating method, device and apply its computer system, by the content for detecting journal file/log stream in real time, extract increment content, associated log content is pushed to key assignments data set, the content of log stream by query key Value Data collection in real time for newly increasing is associated, thus, it is possible to which the time complexity that massive logs are associated is reduced into O (N), daily record associated speed is improved.
Description
Technical field
The present invention relates to big data process field, and in particular to a kind of daily record correlating method, device and apply its calculating
Machine system.
Background technology
During big data analysis is carried out, the operation of different operation system or hardware devices can constantly produce difference
Journal file, each journal file is labeled with a class business or a kind of working condition of hardware device, for example, surf the Net URL days
Will is used to record all URL situations that user's online is accessed；All authentication informations of Verification System log recording etc..Due to daily record
The independence of generation, causes individually to have been analyzed limitation to each journal file, and 2 or multiple journal files are carried out
Analysis is carried out after association becomes have very much value.Simultaneously as journal file possesses the characteristics of data volume is huge, therefore make
It is very important with a kind of method of effective association daily record
Daily record correlating method conventional at present be based on the associated key (KEY) between two or more journal files using by
The mode of bar circular treatment is realized.By taking two journal files as an example, its nested multiple circulation carries out daily record association：
This interrelational form time, multiple complexity was very high, and system can be significantly increased as the journal file of merging is more and more
Computation burden, simultaneously as needing nested circulation, associated speed is slower.
The content of the invention
In view of this, the present invention provides a kind of daily record correlating method, device and applies its computer system, to improve sea
Measure the speed of daily record association.
First aspect is there is provided a kind of daily record correlating method, for by the letter of the information of the second log stream and the first log stream
Breath association, methods described includes：
The content of the first log stream is obtained in real time, extracts the incremental record of the first log stream；
The content of N number of second log stream is obtained in real time, and the Content Transformation of acquisition is loaded into key-value data set, wherein N
More than or equal to 1；And,
The key-value data set is inquired about according to the key of the incremental record of first log stream and by Query Result
Associated with corresponding record.
Preferably, the key-value data set is stored in calculator memory.
Preferably, the key-value data set is the data set based on Redis systems or the number based on memcached systems
According to collection.
Preferably, the content of first log stream and second log stream is obtained in real time by Flume systems.
Preferably, methods described also includes：
Exported after the record of the record for first log stream that is mutually related and the second log stream is merged.
Second reverse side is there is provided a kind of daily record associated apparatus, for by the letter of the information of the second log stream and the first log stream
Breath association, the daily record associated apparatus includes：
First acquisition module, the content for obtaining the first log stream in real time, extracts the incremental record of the first log stream；
Second acquisition module, for obtaining the content of N number of second log stream in real time, and is converted the first key-value of addition
Data set, N is more than or equal to 1；And,
Relating module, is looked into the first key-value data set according to the key of the incremental record of first log stream
Ask and associate Query Result with corresponding record.
Preferably, the key-value data set is stored in calculator memory.
Preferably, the key-value data set is the data set based on Redis systems or the number based on memcached systems
According to collection.
Preferably, described device also includes：
Output module, is exported after the record of the record for first log stream that is mutually related and the second log stream is merged.
The third aspect there is provided a kind of computer system, including：
One or more computer processors；
One or more computer readable storage devices；And
The programmed instruction in one or more of computer readable storage devices is stored in, for by one or many
In individual computer processor at least one execution, for perform method as described above the step of.
The embodiment of the present invention extracts increment content by detecting the content of journal file/log stream in real time, will be associated
Log content is pushed to key-value data set, is carried out by the content of the log stream of query key-Value Data collection in real time for newly increasing
Association, thus, it is possible to which the time complexity that massive logs are associated is reduced into O (N), improves daily record associated speed.
Brief description of the drawings
By description referring to the drawings to the embodiment of the present invention, above-mentioned and other purpose of the invention, feature and
Advantage will be apparent from, in the accompanying drawings：
Fig. 1 is the flow chart of the daily record correlating method of the embodiment of the present invention；
Fig. 2 is the DFD of the daily record correlating method of the embodiment of the present invention；
Fig. 3 is that the embodiment of the present invention carries out the DFD that URL daily records are associated with authenticating user identification daily record；
Fig. 4 is that the embodiment of the present invention carries out the DFD that URL daily records are associated with user attribute data daily record；
Fig. 5 is the block diagram of the daily record associated apparatus of the embodiment of the present invention；
Embodiment
Below based on embodiment, present invention is described, but the present invention is not restricted to these embodiments.Under
Text is detailed to describe some specific detail sections in the detailed description of the present invention.Do not have for a person skilled in the art
The description of these detail sections can also understand the present invention completely.In order to avoid obscuring the essence of the present invention, known method, mistake
Journey, flow, element and circuit do not have detailed narration.
Unless the context clearly requires otherwise, otherwise entire disclosure is similar with the " comprising " in claims, "comprising" etc.
Word should be construed to the implication included rather than exclusive or exhaustive implication；That is, being containing for " including but is not limited to "
Justice.
In the description of the invention, it is to be understood that term " first ", " second " etc. be only used for describe purpose, without
It is understood that to indicate or imply relative importance.In addition, in the description of the invention, unless otherwise indicated, the implication of " multiple "
It is two or more.
Fig. 1 is the flow chart of the daily record correlating method of the embodiment of the present invention.As shown in figure 1, the daily record association of the present embodiment
Method includes：
Step S100, the content for obtaining the first log stream in real time, extract the incremental record of the first log stream.
Specifically, log stream can be managed and monitored by Flume systems, so as to obtain log stream in real time
Content.In the present embodiment, log stream is the journal file of continuous real-time update.Certainly, log stream can also be in computer
The data flow being identified in Installed System Memory.
Flume is a High Availabitity, highly reliable, the system of distributed massive logs collection, polymerization and transmission,
Flume supports to customize Various types of data sender in log system, for collecting data.Meanwhile, Flume is provided to be carried out to data
Simple process, and write the ability of various data receivings (customizable).Daily record flow content is monitored in real time using it, can be improved
Monitoring efficiency.Certainly, it should be readily apparent to one skilled in the art that daily record can also be carried out using other existing systems or method
Monitoring in real time
Meanwhile, day can be carried out in real time using Kafka (Mark reaction) systems or SparkStreaming (spark stream) system
Will content extraction, in order to which the key (key) and corresponding content required for being associated are operated with for subsequent association.Kafka
Distributed a, high-throughput, it is easy to the message system based on theme publish/subscribe of extension, be earliest by
Linkedin is developed, and is increased income in 2011 and contributed to Apache Software Foundation.Kafaka systems regard daily record as message,
The extraction of increment content can easily be carried out.Meanwhile, Spark Streaming are the Open Frameworks of distributed stream processing, its
Streaming can be calculated and resolve into a series of short and small batch processing jobs, suitable for locating to flow data as log stream
Reason.Certainly, it should be readily apparent to one skilled in the art that can also be carried out using other existing systems or method in the increment of daily record
The extraction of appearance.
Step S200, the content for obtaining N number of second log stream in real time, and the Content Transformation of acquisition is added into key-value data
Collection, wherein N is more than or equal to 1.
The other log streams (namely N number of second log stream in step S200) or data being associated for needs, together
Sample monitors its content in real time, will be constantly added to after increment Content Transformation in key-value data set.Key-value (KEY-VALUE) number
It is for relational database according to collection.Traditional relational database is by the set of tables of data, based on the constraint between table
Data storage is carried out with relation, it is possible to inquired about based on SQL query language.Key-value data set (database) belongs to non-pass
It is type database, it carries out data storage by way of key-value pair, can greatly improve the speed of data query.Meanwhile,
Key-value data set is suitable to completely or partially be deployed in internal memory, so as to further improve read or write speed.
The embodiment of the present invention will need the content push of the second log stream being associated to key-value data set, and preferably
The data set is stored in the internal memory of computer system, so as to exchange the raising of inquiry velocity for by memory headroom,
So as to further improve daily record associated speed.
Preferably, the key-value data set is the data set based on Redis systems or the number based on Memcached systems
According to collection.Redis systems are a key-value type storage systems.Similar with Memcached, it supports that the Value types of storage are relative
It is more, including String (character string), List (chained list), Set (set), Zset (ordered set) and Hash (Hash type).
These data types all support push/pop, add/remove and take common factor union and difference set and more rich operation, and this
A little operations are all atomicities.On this basis, Redis supports the sequence of various different modes.As Memcached, it is
Guaranteed efficiency, data are buffered in internal memory.Difference be redis can periodically the data of renewal write disk or
Person is the additional log file of modification operation write-in, and it is synchronous to realize master-slave (principal and subordinate) on this basis.
Memcached systems are also key-value type
Step S300, according to the key of the incremental record of first log stream key-value data set is inquired about and will be looked into
Result is ask to associate with corresponding record.
Due to all current not associated daily record datas that are stored with key-value data set, therefore, in step S300,
Inquired about by the key of the incremental record of the first log stream in key-value data set, obtain the note of corresponding need association
Record, so as to be associated.
In step S300, association can be just realized due to only needing to the progress one query in key-value data set, by
Computation complexity, can be reduced to O (N) by this.
Preferably, after the completion of association, output step can also be included, that is, step S400, first will be mutually related
The record of log stream and the record of the second log stream are exported after merging.
Fig. 2 is the DFD of the daily record correlating method of the embodiment of the present invention.As shown in Fig. 2 for first day of input
Will stream, is monitored in real time to it, find have incremental data when, data be pushed to Spark Streaming systems or
Kafka systems are extracted, and extract its key.Simultaneously for the log stream of at least one associated second, adopt in a like fashion
Monitored in real time, the incremental data monitored conversion is pushed into key-value data set is stored.
And then, it is obtained with by the key of the first log stream incremental data in key-value data Integrated query interrelated
Log information, by the record of incremental data the second log stream corresponding with what is inquired be associated just associated after day
Will is recorded.The record can be exported further.
Fig. 3 is that the embodiment of the present invention carries out the DFD that URL daily records are associated with authenticating user identification daily record.URL daily records
In core field include IP address, URL, the field such as time.And authenticating user identification daily record includes IP address, user name,
The fields such as time.As shown in figure 3, for the association of the two daily records, to be associated by IP address, reach each
The purpose that URL records are associated with an actual user.In figure 3, URL daily records are pushed to Spark by monitoring in real time
In Streaming streaming computing engines, certification log information is equally by real time propelling movement to streaming computing engines.Log information is with IP
Address is key, and the entitled value storage of user is into key-value data set.When detecting new URL log recordings, pass through log recording
Middle IP address is inquired about key-value data set, and the username information inquired is associated in itself with log recording, output
Into storage.
Fig. 4 is that the embodiment of the present invention carries out the DFD that URL daily records are associated with user attribute data daily record.URL daily records
In core field include data attribute in the field such as IP address, URL, time, user name, operation system database and include：With
The fields such as name in an account book, unit one belongs to, sex, age, educational background.For the daily record under this scene and the pass of operation system database
Connection, will be associated by user name, each URL record is obtained the attributes such as access people unit, age, sex, educational background.
And then can be analysed in depth by these attributes, for example obtain 35-40 Sui user's favorite access website and 25-30 Sui
The website that user's favorite is accessed, the difference of two age bracket user network behaviors is found by contrasting.As shown in figure 4, URL daily records
Spark Streaming streaming computing engines are pushed to by monitoring in real time.Operation system data, which are changed, is loaded into key-value
Data are centrally stored, using user name address as key, with customer attribute information, for example, the composition value such as age, sex, educational background.In inspection
When measuring new URL log recordings, key-value data set is inquired about by the user name in log recording, by what is inquired
User attribute data daily record is associated with URL log recordings, and is output in storage.
As can be seen here, the method for the present embodiment is applied to daily record or the data correlation of various scenes.
Fig. 5 is the block diagram of the daily record associated apparatus of the embodiment of the present invention.As shown in figure 5, the daily record association dress of the present embodiment
Put including the first acquisition module 51, the second acquisition module 52 and relating module 53.Wherein, the first acquisition module 51 is used to obtain in real time
The content of the first log stream is taken, the incremental record of the first log stream is extracted.Second acquisition module 52 is used to obtain N number of second in real time
The content of log stream, and the first key-value data set of addition is converted, N is more than or equal to 1.Relating module 53 is according to described first
The key of the incremental record of log stream is inquired about the first key-value data set and is closed Query Result with corresponding record
Connection.
Preferably, the key-value data set is stored in calculator memory.
Preferably, the key-value data set is the data set based on Redis systems or the number based on Memcached systems
According to collection.
Preferably, described device also includes output module 54.Output module 54 is by the note for first log stream that is mutually related
The record of record and the second log stream is exported after merging.
The embodiment of the present invention extracts increment content by detecting the content of journal file/log stream in real time, will be associated
Log content is pushed to key-value data set, is carried out by the content of the log stream of query key-Value Data collection in real time for newly increasing
Association, thus, it is possible to which the time complexity that massive logs are associated is reduced into O (N), improves daily record associated speed.
Obviously, it will be understood by those skilled in the art that above-mentioned each module of the invention or each step can be with general
Computer system realizes that they can be concentrated on a single computer, or be distributed in the net that multiple computing devices are constituted
On network, alternatively, they can be realized with the executable program code of computer installation, be deposited so as to be stored in
Performed in storage device by computing device, they are either fabricated to each integrated circuit modules respectively or by them
Multiple modules or step are fabricated to single integrated circuit module to realize.So, the present invention is not restricted to any specific hardware
With the combination of software.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for those skilled in the art
For, the present invention can have various changes and change.It is all any modifications made within spirit and principles of the present invention, equivalent
Replace, improve etc., it should be included within the scope of the present invention.
Claims (10)
1. a kind of daily record correlating method, for by the information association of the information of the second log stream and the first log stream, methods described
Including：
The content of the first log stream is obtained in real time, extracts the incremental record of the first log stream；
The content of N number of second log stream is obtained in real time, and the Content Transformation of acquisition is loaded into key-value data set, and wherein N is more than
Equal to 1；And,
The key-value data set is inquired about according to the key of the incremental record of first log stream and by Query Result with it is right
The record association answered.
2. daily record correlating method according to claim 1, it is characterised in that the key-value data set is stored in computer
In internal memory.
3. daily record correlating method according to claim 2, it is characterised in that the key-value data set is based on Redis systems
The data set of system or the data set based on Memcached systems.
4. daily record correlating method according to claim 1, it is characterised in that obtain described in real time by Flume systems
The content of one log stream and second log stream.
5. daily record correlating method according to claim 1, it is characterised in that methods described also includes：
Exported after the record of the record for first log stream that is mutually related and the second log stream is merged.
6. a kind of daily record associated apparatus, for by the information association of the information of the second log stream and the first log stream, the daily record
Associated apparatus includes：
First acquisition module, the content for obtaining the first log stream in real time, extracts the incremental record of the first log stream；
Second acquisition module, for obtaining the content of N number of second log stream in real time, and is converted the first key-value data of addition
Collection, N is more than or equal to 1；And,
Relating module, is inquired about simultaneously the first key-value data set according to the key of the incremental record of first log stream
Query Result is associated with corresponding record.
7. daily record associated apparatus according to claim 6, it is characterised in that the key-value data set is stored in computer
In internal memory.
8. daily record associated apparatus according to claim 7, it is characterised in that the key-value data set is based on Redis systems
The data set of system or the data set based on Memcached systems.
9. daily record associated apparatus according to claim 1, it is characterised in that described device also includes：
Output module, is exported after the record of the record for first log stream that is mutually related and the second log stream is merged.
10. a kind of computer system, including：
One or more computer processors；
One or more computer readable storage devices；And
The programmed instruction in one or more of computer readable storage devices is stored in, by by based on one or more of
At least one execution in calculation machine processor, the step of requiring any one of 1 to 5 for perform claim.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107391770A (en) * | 2017-09-13 | 2017-11-24 | 北京锐安科技有限公司 | A kind of method, apparatus of processing data, equipment and storage medium |
| CN107835080A (en) * | 2017-11-09 | 2018-03-23 | 成都国盛天丰网络科技有限公司 | A kind of distributed system method of data capture and data signature generation method |
| CN110019068A (en) * | 2017-10-19 | 2019-07-16 | 阿里巴巴集团控股有限公司 | A kind of log text handling method and device |
| CN110389989A (en) * | 2019-07-15 | 2019-10-29 | 阿里巴巴集团控股有限公司 | A kind of data processing method, device and equipment |
| CN112286895A (en) * | 2020-10-30 | 2021-01-29 | 北京深演智能科技股份有限公司 | Log real-time attribution processing method, device and platform |
| CN112395157A (en) * | 2020-11-13 | 2021-02-23 | 广州至真信息科技有限公司 | Audit log obtaining method and device, computer equipment and storage medium |
| CN113010480A (en) * | 2020-03-26 | 2021-06-22 | 腾讯科技（深圳）有限公司 | Log processing method and device, electronic equipment and computer readable storage medium |
| CN114201461A (en) * | 2021-12-14 | 2022-03-18 | 合肥全息网御科技有限公司 | Log tracing service data security event method and system based on acanthopanax root-tuple |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107391770A (en) * | 2017-09-13 | 2017-11-24 | 北京锐安科技有限公司 | A kind of method, apparatus of processing data, equipment and storage medium |
| CN107391770B (en) * | 2017-09-13 | 2020-02-07 | 北京锐安科技有限公司 | Method, device and equipment for processing data and storage medium |
| CN110019068A (en) * | 2017-10-19 | 2019-07-16 | 阿里巴巴集团控股有限公司 | A kind of log text handling method and device |
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| CN107835080A (en) * | 2017-11-09 | 2018-03-23 | 成都国盛天丰网络科技有限公司 | A kind of distributed system method of data capture and data signature generation method |
| CN110389989A (en) * | 2019-07-15 | 2019-10-29 | 阿里巴巴集团控股有限公司 | A kind of data processing method, device and equipment |
| CN113010480A (en) * | 2020-03-26 | 2021-06-22 | 腾讯科技（深圳）有限公司 | Log processing method and device, electronic equipment and computer readable storage medium |
| CN113010480B (en) * | 2020-03-26 | 2024-03-19 | 腾讯科技（深圳）有限公司 | Log processing method, device, electronic equipment and computer readable storage medium |
| CN112286895A (en) * | 2020-10-30 | 2021-01-29 | 北京深演智能科技股份有限公司 | Log real-time attribution processing method, device and platform |
| CN112395157A (en) * | 2020-11-13 | 2021-02-23 | 广州至真信息科技有限公司 | Audit log obtaining method and device, computer equipment and storage medium |
| CN112395157B (en) * | 2020-11-13 | 2023-08-08 | 广州至真信息科技有限公司 | Audit log acquisition method and device, computer equipment and storage medium |
| CN114201461A (en) * | 2021-12-14 | 2022-03-18 | 合肥全息网御科技有限公司 | Log tracing service data security event method and system based on acanthopanax root-tuple |
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