CN111984860B - Event context correlation processing method and system for time series data - Google Patents
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Abstract
The invention discloses an event context association processing method and system of time sequence data, firstly defining event context association logic, including two parts of adjacent event association logic and context merging processing logic, after obtaining event data and time stamp, reading intermediate result in computer memory and merging processing, finally carrying out event context association processing to obtain unique context association processing result. The method overcomes the defects of long time consumption and low efficiency in the prior art, and can quickly perform event context correlation processing on massive time sequence data; in addition, the invention calculates the intermediate result in advance, thereby avoiding a large amount of useless repeated operation of the computer during query and having extremely high response speed; in addition, the intermediate result is changed continuously along with the system time movement, and the purpose of smooth movement of the time window can be achieved. The invention can obviously improve the efficiency of event context correlation processing of the time sequence data.
Description
Technical Field
The invention relates to the technical field of data processing systems or methods, in particular to an event context association processing method and system for time sequence data.
Background
Nowadays, internet technology is rapidly developed, and massive users perform operations such as page browsing, resource downloading, information searching and the like on the internet. These human operations involve many specific complex events such as staying on a page for 30 seconds, clicking on a link 5 times in a row, uploading data to a website in the size of 2MB, etc. When a plurality of events occur in succession, the context correlation information is included between adjacent events, which can reflect the behavior characteristics of the user activity, or can be used for monitoring some abnormal conditions, such as suddenly increased network traffic, suddenly changed location information, and the like. Therefore, the event context correlation information has high application value, and event context correlation processing is required in the fields of automatic recommendation, data mining, network security, risk monitoring and the like.
However, in a stream processing system, each piece of data input to the system is often processed immediately, and the state of each piece of data is not preserved, so how to maintain the context association information of the data and support fast query is a difficult point. In addition, the current network events have wide sources, large quantity and long spanning time, and the data dimension needing to be analyzed in the event context correlation processing is high and consumes much resources. In such a scenario, the existing event context association processing method and system for time series data have the defects of long time consumption and low efficiency. This is because the processing and query analysis logic of the prior methods and systems is complex and inefficient, involving a large number of unnecessary iterations of computer operations.
Taking the scenario shown in fig. 2 as an example, the prior art will perform the following steps to perform the event context association processing: if the event context processing of 16; thereafter, if event context processing of 15. However, it is obvious that there are duplicate logic already executed in the previous process, which can still be executed in the prior art, resulting in unnecessary waste of computer resources and inefficient processing.
Currently, there is a need for a method and a system for processing event context association of time series data, which can overcome the defects of long time consumption and low efficiency in the prior art, quickly perform event context association processing of massive time series data, and support query of a specified time window.
Disclosure of Invention
The invention aims to provide a method and a system for processing event context of time series data aiming at the defects of the prior art.
The purpose of the invention is realized by the following technical scheme: a method for processing event context association of time sequence data is realized by a computer memory, and specifically comprises the following steps:
step 2, when a user operates and triggers an event, acquiring data and a time stamp of the event; this event is referred to as "this event"; the event with the largest timestamp among events occurring before the current event is referred to as the last event. The acquiring action realizes real-time streaming acquisition by providing a program interface;
step 4, reading an intermediate result R3 in the computer memory in the time period according to the query time period, and performing event context correlation processing; when the query time span a plurality of intermediate results R3, merging all the intermediate results R3 one by one according to time from far to near; and obtaining a context correlation processing result according to the unique intermediate result R3 after the intermediate result is merged.
Further, in step 3, the method for constructing the intermediate result by using the data and the timestamp of the current event includes:
for this event E, there is data d and a timestamp s. Initializing an intermediate result R, wherein the intermediate result has four parts of initial data b, termination data e, correlation processing result R and time mark t. Setting the values of b and e as d, t as s and r as null. Then R is the intermediate result R2 of the completion of the construction.
Further, the method for merging the intermediate results in the step 3 comprises the following steps:
the two intermediate results R1 and R2 are ordered by a time stamp t, the time stamp of R1 being less than the time stamp of R2, R1 preceding R2. And executing the adjacent event association logic defined in the step 1 by using the termination data e of the R1 and the start data b of the R2 to obtain an association processing result R0. And executing the context merging processing logic defined in the step 1 by using the correlation processing results R1 and R2 contained in the R0 and R1 to obtain R3 in a new intermediate result R3. The value of e of R3 is the value of e of R2; the value of b of R3 is the value of b of R1; the value of t for R3 is the value of t for R1. And R3 is the intermediate result merging processing result.
Further, the method for merging the intermediate results in the step 4 comprises the following steps:
assigning the intermediate result R3 with the farthest time to the R1, assigning the intermediate result R3 with the second farthest time to the R2, deleting the intermediate result R3 with the farthest time and the intermediate result R3 with the second farthest time, and merging the R1 and the R2 according to the method for merging the intermediate results in the step 3; and continuing the merging processing of the intermediate results in the step 4 in this way until a unique intermediate result R3 is obtained, and obtaining a context association processing result according to the R value of the R3.
Further, the query operation in step 4 and the data and time stamp obtaining action in step 2 can be performed simultaneously.
An event context association processing system of time sequence data, which is realized by a computer memory and comprises an event context association logic definition module, a local event information acquisition module, an event context merging module and an event context association query module:
the event context association logic definition module is used for defining event context association logic aiming at events caused by user operation; the event context correlation logic comprises two parts, namely adjacent event correlation logic and context merging processing logic;
the local event information acquisition module is used for executing acquisition behaviors on the data and the time stamp of an event when the event is caused by user operation; this event is referred to as "this event"; the event with the largest time stamp among events occurring before the current event is referred to as the last event. The acquiring action realizes real-time streaming acquisition by providing a program interface;
the event context merging module is used for reading an intermediate result R1 in a computer memory according to the timestamp of the event, and if the event is a first event, the value of R1 is null; otherwise, the value of R1 is R3 written into the computer memory when the event context merging module is operated by the last event; using the data and the timestamp of the event to construct an intermediate result to obtain R2; processing the R1 and the R2 according to adjacent event association logic to obtain an association processing result, then merging the obtained association processing result and intermediate results of the R1 and the R2 according to context merging processing logic to obtain R3, and writing the R3 into a computer memory;
the event context correlation query module is used for reading an intermediate result R3 in the computer memory in the query time period according to the query time period and performing event context correlation processing; when the query time span a plurality of intermediate results R3, merging all the intermediate results R3 one by one according to time from far to near; and obtaining a context correlation processing result according to the unique intermediate result R3 after the intermediate result is merged.
Further, the method for constructing the intermediate result by using the data and the timestamp of the current event in the event context merging module comprises the following steps:
for this event E, there is data d and a timestamp s. Initializing an intermediate result R, wherein the intermediate result has four parts of starting data b, ending data e, an associated processing result R and a time mark t. Setting the values of b and e as d, t as s and r as null. Then R is the intermediate result R2 of the completion of the construction.
Further, the method for merging and processing the intermediate result in the event context merging module comprises the following steps:
the two intermediate results R1 and R2 are ordered by a time stamp t, the time stamp of R1 being less than the time stamp of R2, R1 preceding R2. And executing adjacent event correlation logic defined in the event context correlation logic definition module by using the termination data e of the R1 and the start data b of the R2 to obtain a correlation processing result R0. And executing the context merging processing logic defined in the event context association logic definition module by using the association processing results R1 and R2 contained in the R0 and R1 to obtain R3 in the new intermediate result R3. The value of e for R3 is the value of e for R2; the value of b for R3 is the value of b for R1; the value of t for R3 is the value of t for R1. And R3 is the intermediate result merging processing result.
Further, the method for merging and processing the intermediate results in the event context association query module comprises the following steps:
assigning the intermediate result R3 with the farthest time to R1, assigning the intermediate result R3 with the second farthest time to R2, deleting the intermediate result R3 with the farthest time and the intermediate result R3 with the second farthest time, and merging R1 and R2 according to an intermediate result merging processing method in the event context merging module; and continuing merging the intermediate results in the event context correlation query module in this way until a unique intermediate result R3 is obtained, and obtaining a context correlation processing result according to the R value of the R3.
Further, the query module can operate simultaneously with the local event information acquisition module.
The beneficial technical effects of the invention are as follows: firstly, the method overcomes the defects of long time consumption and low efficiency in the prior art, and can quickly perform event context association processing on massive time sequence data; in addition, the invention calculates the intermediate result in advance, thereby avoiding a large amount of useless repeated operation of the computer during query and having extremely high response speed; in addition, the intermediate result is changed continuously along with the system time movement, and the purpose of smooth movement of the time window can be achieved. The invention is suitable for the technical field of event context association processing methods and systems related to time sequence data, and can remarkably improve the efficiency of event context association processing of the time sequence data.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a diagram of a page view event, according to one embodiment;
FIG. 3 is a graph comparing the effect of the present invention and the conventional method.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, embodiments accompanied with figures are described in detail below.
Example 1
Suppose that a website needs to perform event context correlation processing on user behaviors, so as to distinguish traffic caused by normal human users and traffic caused by abnormal machine crawlers. Meanwhile, the website needs to judge whether the machine crawler flow is in a specified time period or not so as to analyze the activity rule of a crawler attacker. The website comprises a plurality of pages, the content of each page is different, the content is different in length, when a normal human user browses the webpage, the HTTP connection maintenance time established between the browser and the website is different due to different content lengths, and the difference between different pages can reach the second level or the minute level. But for web crawlers, the executed program logic is fixed, the text processing speed is very fast, and the different page content lengths do not cause significant HTTP connection maintaining time difference. And when the minimum value of the adjacent page maintaining time difference is less than 5 seconds in a specified time period, the crawler behavior can be judged. Existing page view records from the same operation source are shown in fig. 2, where the number represents the HTTP connection maintenance time in seconds between the operation source and the page.
The method and the system for processing context association of the time sequence data events are used for judging and inquiring the crawler in a specified time period, and the specific processing steps are as follows:
(1) In the event context association logic definition module, event context association logic is defined. The event context association logic comprises two parts, namely adjacent event association logic and context merging processing logic. Here, the adjacent event correlation logic is defined as "absolute value of current event elapsed time minus last event elapsed time"; context merge processing logic is defined as "minimum".
(2) In the local event information acquisition module, a program interface is provided for acquiring the data and the time stamp of the event in real time. In the embodiment, a POST writing method is adopted, and the POST is reported by a page js script. In the present embodiment, nine information acquisitions are performed in total.
(3) Reading an intermediate result R1 in a computer memory in an event context merging module according to the timestamp of the current event; using the data and the timestamp of the event to construct an intermediate result to obtain R2; and merging the intermediate results of the R1 and the R2 to obtain R3, and writing the R3 into a computer memory.
In this embodiment, there are nine events, and the intermediate result R1, R2 obtained by constructing the intermediate result, and R3 obtained by merging the intermediate result, which are read from the computer memory each time according to the event timestamp, are shown in the following table:
| Time | data of | R1 | R2 | R3 |
| 14:30 | 12 | null | b＝12,e＝12,r＝null,t＝14 | b＝12,e＝12,r＝null,t＝14 |
| 15:10 | 10 | null | b＝10,e＝10,r＝null,t＝15 | b＝10,e＝10,r＝null,t＝15 |
| 15:20 | 40 | b＝10,e＝10,r＝null,t＝15 | b＝40,e＝40,r＝null,t＝15 | b＝10,e＝40,r＝30,t＝15 |
| 15:45 | 80 | b＝10,e＝40,r＝30,t＝15 | b＝80,e＝80,r＝null,t＝15 | b＝10,e＝80,r＝30,t＝15 |
| 15:50 | 8 | b＝10,e＝80,r＝30,t＝15 | b＝8,e＝8,r＝null,t＝15 | b＝10,e＝8,r＝30,t＝15 |
| 16:15 | 12 | null | b＝12,e＝12,r＝null,t＝16 | b＝12,e＝12,r＝null,t＝16 |
| 16:45 | 110 | b＝12,e＝12,r＝null,t＝16 | b＝110,e＝110,r＝null,t＝16 | b＝12,e＝110,r＝98,t＝16 |
| 17:15 | 15 | null | b＝15,e＝15,r＝null,t＝17 | b＝15,e＝15,r＝null,t＝17 |
| 17:45 | 16 | b＝15,e＝15,r＝null,t＝17 | b＝16,e＝16,r＝null,t＝17 | b＝15,e＝16,r＝1,t＝17 |
(4) In the event context correlation query module, reading an intermediate result in a computer memory according to a query time period, and performing event context correlation processing; when the query time period spans a plurality of intermediate results, merging all the intermediate results one by one from far to near according to time; the query module may operate concurrently with the local event information acquisition module.
In this embodiment, the crawler crawling behavior of query 15 from 00 to 18 00 first reads the intermediate results on each timestamp, and then merges one by one from far to near, that is, reads the intermediate results of 15. The specific process is shown in the following table:
according to the results, r =1 and less than 5 seconds are consistent with the behavior characteristics of the crawler, so that the invention performs event context processing and successfully detects the behavior of the crawler according to the specified query time period 15.
Example 2
To demonstrate the practical benefit of the method of the present invention, we performed a set of experiments. Compared with the traditional method, the method disclosed by the invention has the advantage that the effect of the method disclosed by the invention is shown in a shorter time than that of the traditional method when the same data amount is processed.
The experimental scene is as follows: random 5 ten thousand sets of test data are generated, each set of test data including a time stamp and an event data. The time stamps represent the timing of the data and the event data represents the data required in the defined event context correlation logic. The test data were distributed over 50 consecutive hours with 1000 groups per hour. The time stamps of each group of data are uniformly distributed in the hour, and the event data are randomly generated.
The test method comprises the following steps: the method and the traditional method are respectively used for processing and inquiring the context association processing results of every 1 or 2.. 50 hours of events, then the time of each test is recorded, and finally a chart is drawn.
The test results are shown in fig. 3. From the results it can be seen that:
(1) The processing time of the traditional method is far longer than that of the method of the invention.
(2) As the amount of data grows, the processing time of the conventional method grows linearly, while the method of the present invention remains substantially unchanged.
The above-described embodiments are intended to illustrate rather than to limit the invention, and any modifications and variations of the present invention are within the spirit of the invention and the scope of the appended claims.
Claims (4)
1. A method for processing event context association of time sequence data is realized by a computer memory, and specifically comprises the following steps:
step 1, aiming at an event caused by user operation, defining event context association logic; the event context correlation logic comprises two parts, namely adjacent event correlation logic and context merging processing logic;
step 2, when a user operates and triggers an event, acquiring data and a time stamp of the event; this event is referred to as the "present event"; the event with the largest timestamp in the events occurring before the current event is called as the last event; the acquiring action realizes real-time streaming acquisition by providing a program interface;
step 3, reading an intermediate result R1 in a computer memory according to the timestamp of the current event, wherein if the current event is a first event, the value of R1 is null; otherwise, the value of R1 is R3 written into the computer memory when the last event is processed in the step 3; using the data and the time stamp of the current event to construct an intermediate result, and regarding the current event E, having data d and a time stamp s; initializing an intermediate result R, wherein the intermediate result has four parts of initial data b, termination data e, an association processing result R and a time mark t; setting the values of b and e as d, t as s and r as null; r is an intermediate result R2 after construction is completed; processing the R1 and the R2 according to the adjacent event correlation logic to obtain a correlation processing result, then merging the obtained correlation processing result and intermediate results of the R1 and the R2 according to the context merging processing logic to obtain R3, and writing the R3 into a computer memory; the method for merging the intermediate results comprises the following steps: sorting the two intermediate results R1 and R2 by a time stamp t, the time stamp of R1 being less than the time stamp of R2, R1 preceding R2; executing the adjacent event correlation logic defined in the step 1 by using the termination data e of the R1 and the start data b of the R2 to obtain a correlation processing result R0; executing context merging processing logic defined in the step 1 by using the correlation processing results R1 and R2 contained in the R0 and R1 to obtain R3 in a new intermediate result R3; the value of e of R3 is the value of e of R2; the value of b of R3 is the value of b of R1; the value of t for R3 is the value of t for R1; r3 is the intermediate result merging processing result;
step 4, reading the intermediate result R3 in the computer memory in the period of time according to the query period of time, and performing event context correlation processing; when the query time period spans a plurality of intermediate results R3, merging all the intermediate results R3 one by one from far to near according to time, specifically: assigning the intermediate result R3 with the farthest time to R1, assigning the intermediate result R3 with the second farthest time to R2, deleting the intermediate result R3 with the farthest time and the intermediate result R3 with the second farthest time, and merging R1 and R2 according to the method for merging the intermediate results in the step 3; and continuing the merging processing of the intermediate results in the step 4 in this way until a unique intermediate result R3 is obtained, and obtaining a context association processing result according to the R value of the R3.
2. The method of claim 1, wherein the query operation in step 4 and the data and timestamp obtaining in step 2 can be performed simultaneously.
3. An event context association processing system of time series data is characterized in that the system is realized by a computer memory and comprises an event context association logic definition module, a local event information acquisition module, an event context merging module and an event context association query module:
the event context correlation logic definition module is used for defining event context correlation logic aiming at events caused by user operation; the event context association logic comprises two parts, namely adjacent event association logic and context merging processing logic;
the local event information acquisition module is used for executing acquisition behaviors on the data and the time stamp of an event when the event is caused by user operation; this event is referred to as "this event"; the event with the largest timestamp in the events occurring before the current event is called as the last event; the acquiring action realizes real-time streaming acquisition by providing a program interface;
the event context merging module is used for reading an intermediate result R1 in a computer memory according to the timestamp of the event, and if the event is the first event, the value of R1 is null; otherwise, the value of R1 is R3 written into the computer memory when the event context merging module is operated by the last event; using the data and the time stamp of the current event to construct an intermediate result, and regarding the current event E, having data d and a time stamp s; initializing an intermediate result R, wherein the intermediate result has four parts of initial data b, termination data e, an association processing result R and a time mark t; setting the values of b and e as d, setting t as s and setting r as null; r is an intermediate result R2 after the construction is finished; processing the R1 and the R2 according to the adjacent event correlation logic to obtain a correlation processing result, then merging the obtained correlation processing result and intermediate results of the R1 and the R2 according to the context merging processing logic to obtain R3, and writing the R3 into a computer memory; the method for merging the intermediate results comprises the following steps: sorting the two intermediate results R1 and R2 by a time stamp t, the time stamp of R1 being less than the time stamp of R2, R1 preceding R2; executing adjacent event correlation logic defined in the event context correlation logic definition module by using the termination data e of the R1 and the start data b of the R2 to obtain a correlation processing result R0; executing context merging processing logic defined in an event context association logic definition module by using association processing results R1 and R2 contained in the R0 and R1 to obtain R3 in a new intermediate result R3; the value of e of R3 is the value of e of R2; the value of b of R3 is the value of b of R1; the value of t of R3 is the value of t of R1; r3 is the merging processing result of the intermediate result;
the event context correlation query module is used for reading an intermediate result R3 in a computer memory in a query time period according to the query time period and performing event context correlation processing; when the query time period spans a plurality of intermediate results R3, merging all the intermediate results R3 one by one according to time from far to near; the method specifically comprises the following steps: assigning the intermediate result R3 with the farthest time to R1, assigning the intermediate result R3 with the second farthest time to R2, deleting the intermediate result R3 with the farthest time and the intermediate result R3 with the second farthest time, and merging R1 and R2 according to an intermediate result merging processing method in the event context merging module; and continuing merging the intermediate results in the event context correlation query module in this way until a unique intermediate result R3 is obtained, and obtaining a context correlation processing result according to the R value of the R3.
4. The system of claim 3, wherein the query module is capable of running concurrently with the local event information acquisition module.
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