CN111061588A - Method and device for locating database abnormal source - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for locating a database exception source. The method for locating the abnormal source of the database is applied to the server and comprises the following steps: receiving access data which are periodically sent by all client sides and correspond to a database; accessing the data includes: the method comprises the steps that a task identifier of a task executed by a client, a library identifier of a database corresponding to the client and access flow are obtained; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service. The embodiment of the invention can receive the access data sent by the client, determine the abnormal task identifier according to the access data, further determine the abnormal service, and quickly and accurately position the abnormal service without manual analysis and judgment.
Description
Technical Field
The invention relates to the field of database exception location, in particular to a method and a device for locating a database exception source.
Background
Background servers are usually adopted in the internet to build a database for users to access. When a user accesses a database, a corresponding client is determined according to a service accessed by the user, and then the database is accessed by using the determined client. In addition, the existing database usually carries multiple services, that is, when a user performs multiple different services, the same database is accessed. However, the amount of user access traffic that the database can withstand is limited. When a user performs a certain service, if an abnormality occurs (for example, the user access flow is too large), the normal use of other services in the database will be affected. In order to avoid the recurrence of the abnormality, the source of the abnormality needs to be located after the occurrence of the abnormality.
At present, when an abnormality occurs in a database, methods for locating the abnormality generally include collecting TCP (Transmission Control Protocol) connection information and the like on a database machine, and then manually determining an IP (Internet Protocol) address of the abnormality by a maintenance person. And because a plurality of services may be operated on the machine, even if the IP address causing the abnormity is determined, the service causing the abnormity still cannot be accurately found.
Disclosure of Invention
In view of the foregoing problems, embodiments of the present invention provide a method and an apparatus for locating a database exception source, so as to solve the problems in the prior art that the database exception source is determined manually and an exception service cannot be determined.
In a first aspect of the implementation of the present invention, there is provided first a method for locating a database exception source, where the method is applied to a server, and the method includes:
receiving access data which are periodically sent by all client sides and correspond to a database; wherein the accessing data comprises: the method comprises the steps that task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the client accessing the database within a first preset time length are obtained;
aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods;
determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods;
and determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
Optionally, the database corresponding to the client is a database accessed when the client executes the task indicated by the task identifier.
Optionally, the number of the databases is multiple, and each database corresponds to a different client.
Optionally, the aggregating the access data according to a second preset time duration to obtain the access traffic of each task identifier in multiple consecutive time periods includes:
marking a statistical time for each access data, wherein the statistical time is the time of receiving the access data;
obtaining a plurality of continuous time periods by taking the preset time as a starting time and the second preset time as a step length;
and counting the sum of the access flow of each task identifier in each database in each time period according to the counting time.
Optionally, the step of determining an abnormal task identifier according to the change speed of the access traffic in a plurality of continuous time periods includes:
receiving a target time period and a target library identification input by a user;
according to the target library identification, determining the access flow of each target task identification corresponding to the target library identification in a plurality of continuous time periods;
determining a target access flow, a first access flow and a second access flow according to the target time period and the access flows of the target task identifier in a plurality of continuous time periods, wherein the target access flow is the access flow of the target task identifier in the target time period, and the first access flow is the access flow of the target task identifier in a first time period which is immediately before the target time period and is next to the target time period; the second access flow is the access flow of the target task identifier in a second time period which is next to the target time period after the target time period;
determining the flow change speed of each target task identifier according to the target access flow, the first access flow and the second access flow;
and determining the target task identifier corresponding to the flow change speed with the maximum value as the abnormal task identifier.
In a second aspect of the embodiment of the present invention, there is also provided a method for locating a database exception source, which is applied to a client, and the method includes:
acquiring a task identifier of a task executed by the client, a library identifier of a database corresponding to the client and access flow of the client accessing the database within a first preset time;
taking the task identifier, the library identifier and the access flow as access data, and periodically sending the access data to a server by taking a first preset time length as a sending period so that the server receives the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
In a third aspect of the present invention, there is also provided an apparatus for locating a source of an abnormality in a database, where the apparatus is applied to a server, and the apparatus includes:
the receiving module is used for receiving access data which are sent by all clients corresponding to the database at regular intervals; wherein the accessing data comprises: the method comprises the steps that task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the client accessing the database within a first preset time length are obtained;
the aggregation module is used for aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods;
the task abnormity confirmation module is used for determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods;
and the service abnormity confirmation module is used for determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service.
In a fourth aspect of the implementation of the present invention, there is also provided an apparatus for locating a source of an exception in a database, where the apparatus is applied to a client, and the apparatus includes:
the acquisition module is used for acquiring a task identifier of a task executed by the client, a library identifier of a database corresponding to the client and access flow of the client accessing the database within a first preset time length;
the sending module is used for taking the task identifier, the library identifier and the access flow as access data, and regularly sending the access data to a server by taking a first preset time as a sending period so that the server receives the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
In a fifth aspect of the present invention, there is also provided an electronic device, including a processor, a communication interface, a memory and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
the processor is used for realizing the steps of the method for locating the abnormal source of the database when executing the program stored in the memory.
In a sixth aspect implemented by the present invention, there is also provided a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the method of locating a source of a database exception as set forth in any one of the first or second aspects.
In a seventh aspect of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the above method of locating a source of a database exception.
Aiming at the prior art, the invention has the following advantages:
the method for locating the abnormal source of the database can receive access data which are sent by all clients corresponding to the database at regular intervals; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a flowchart illustrating steps of a method for locating a source of an anomaly in a database applied to a server according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a second step of a method for locating a source of an anomaly in a database applied to a server according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a third step of a method for locating a source of an anomaly in a database applied to a server according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps of a method for locating a source of a database anomaly applied to a client according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating an architecture of an application system of the method for locating a source of database anomaly according to an embodiment of the present invention;
FIG. 6 is a block diagram of an apparatus for locating a source of an anomaly in a database applied to a server according to an embodiment of the present invention;
FIG. 7 is a second block diagram of an apparatus for locating a source of a database exception applied to a server according to an embodiment of the present invention;
FIG. 8 is a third block diagram of an apparatus for locating a source of an anomaly in a database applied to a server according to an embodiment of the present invention;
FIG. 9 is a block diagram of an apparatus for locating a source of a database exception applied to a client according to an embodiment of the present invention;
fig. 10 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a method for locating a database anomaly source, which is applied to a server, and the method includes:
It should be noted that the database may be a database built by a single server, or may be a clustered database, that is, a database cluster. The database bears a plurality of services, each service corresponds to at least one task, and each task is executed through a unique client, so all the clients corresponding to each database are the clients corresponding to all the services borne by the database. Preferably, the number of databases is one or more.
And when the client executes the task, the corresponding database is accessed, so that access data is generated. Thus, for each client access data comprising: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. The access flow of the client accessing the database within the first preset time is the data exchange amount or the accumulation amount of the returned data amount when the client accesses the database for multiple times within the first preset time. For example, the client sends the access data every five minutes, the task identifier and the library identifier in the access data sent every time are the same, and the access flow is the data exchange amount or the accumulated amount of the returned data amount when the database is accessed for multiple times within five minutes before the current time. The task identification can be a task name or related information of a task principal.
And step 102, aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods.
It should be noted that the second preset time period is longer than the first preset time period, and the first preset time period is usually smaller and can be set to several minutes, for example, five minutes, but is not limited thereto. The second preset time period may be set to several hours, for example, one hour, but is not limited thereto. Thereby facilitating querying the anomaly source for a fixed period of time.
And 103, determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods.
It should be noted that when the access traffic suddenly increases or decreases, it is indicated that there is a problem. After the time period of the occurrence of the abnormity is determined, the abnormity task identification can be easily determined by accessing the change speed of the flow.
And step 104, determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
It should be noted that the correspondence between the service and the task is predetermined. For example, for a bullet screen service, the bullet screen service corresponds to a plurality of tasks, and the bullet screen service and the corresponding tasks are predetermined. As long as the task is determined, the corresponding service can be found.
In the embodiment of the invention, access data periodically sent by all clients corresponding to the database can be received; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
Preferably, the database corresponding to the client is a database accessed when the client executes the task indicated by the task identifier.
It should be noted that each client performs a different task, and the clients will access the database when performing the tasks. For example, the client a will execute a task B, which is one of the tasks under the service C, and the service C is carried in the database D. Each time client a performs a task, task B will be performed and database D will be accessed.
Preferably, the number of the databases is multiple, and each database corresponds to a different client.
Fig. 2 is a flowchart of steps of another method for locating a source of an anomaly in a database according to an embodiment of the present invention, as shown in fig. 2, where the method is applied to a server, and may include:
It should be noted that the database may be a database built by a single server, or may be a clustered database, that is, a database cluster. The database bears a plurality of services, each service corresponds to at least one task, and each task is executed through a unique client, so all the clients corresponding to each database are the clients corresponding to all the services borne by the database. Preferably, the number of databases is one or more.
And when the client executes the task, the corresponding database is accessed, so that access data is generated. Thus, for each client access data comprising: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. The access flow of the client accessing the database within the first preset time is the data exchange amount or the accumulation amount of the returned data amount when the client accesses the database for multiple times within the first preset time. For example, the client sends the access data every five minutes, the task identifier and the library identifier in the access data sent every time are the same, and the access flow is the data exchange amount or the accumulated amount of the returned data amount when the database is accessed for multiple times within five minutes before the current time. The task identification can be a task name or related information of a task principal.
It should be noted that, after the statistical time is marked, the access data is the access data of the statistical time.
And step 203, taking the preset time as the starting time and the second preset duration as the step length to obtain a plurality of continuous time periods.
It should be noted that the preset time may be an hour, and the second preset time may be one hour, but is not limited thereto. For example, the obtained plurality of continuous time periods are 01: 00-02: 00, 02: 00-03: 00 … … 00: 00-01: 00, and the total number is 24 continuous time periods.
And 204, counting the sum of the access flow of each task identifier in each database in each time period according to the counting time.
It should be noted that, when statistics is performed on the integration of the access traffic of each task identifier in each database in each time period, it is preferred to determine which access data belong to the same time period according to the statistical time, and then overlap the access traffic in the access data with the same database and task identifier. For example, the first access data with the statistical time of 01:15 is (database a, task a, 500), wherein the database a is a library identifier, the task a is a task identifier, and 500 is access traffic; the second access data with the statistical time of 01:20 is (database a, task a, 800), wherein the database a is a library identifier, the task a is a task identifier, and 800 is an access flow. And the statistical time of the rest access data does not fall in the time period of 01: 00-02: 00, the first access data and the second access data are aggregated and then become (database A, task A, 1300).
It should be noted that when the access traffic suddenly increases or decreases, it is indicated that there is a problem. After the time period of the occurrence of the abnormity is determined, the abnormity task identification can be easily determined by accessing the change speed of the flow.
And step 206, determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relationship between the task identifiers and the services.
It should be noted that the correspondence between the service and the task is predetermined. For example, for a bullet screen service, the bullet screen service corresponds to a plurality of tasks, and the bullet screen service and the corresponding tasks are predetermined. As long as the task is determined, the corresponding service can be found.
In the embodiment of the invention, access data periodically sent by all clients corresponding to the database can be received; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
Fig. 3 is a flowchart illustrating steps of another method for locating a source of an anomaly in a database according to an embodiment of the present invention, where as shown in fig. 3, the method is applied to a server and may include:
It should be noted that the database may be a database built by a single server, or may be a clustered database, that is, a database cluster. The database bears a plurality of services, each service corresponds to at least one task, and each task is executed through a unique client, so all the clients corresponding to each database are the clients corresponding to all the services borne by the database. Preferably, the number of databases is one or more.
And when the client executes the task, the corresponding database is accessed, so that access data is generated. Thus, for each client access data comprising: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. The access flow of the client accessing the database within the first preset time is the data exchange amount or the accumulation amount of the returned data amount when the client accesses the database for multiple times within the first preset time. For example, the client sends the access data every five minutes, the task identifier and the library identifier in the access data sent every time are the same, and the access flow is the data exchange amount or the accumulated amount of the returned data amount when the database is accessed for multiple times within five minutes before the current time. The task identification can be a task name or related information of a task principal.
It should be noted that the second preset time period is longer than the first preset time period, and the first preset time period is usually smaller and can be set to several minutes, for example, five minutes, but is not limited thereto. The second preset time period may be set to several hours, for example, one hour, but is not limited thereto. Thereby facilitating querying the anomaly source for a fixed period of time.
It should be noted that, after an exception occurs to a database, the repository identification of the database in which the exception occurred, i.e., the target repository identification, and the time period in which the exception occurred, i.e., the target time period, may be determined.
And step 304, determining the access flow of each target task identifier corresponding to the target library identifier in a plurality of continuous time periods according to the target library identifier.
It should be noted that after aggregating the access data, the access traffic of each task identifier corresponding to each library identifier over a plurality of consecutive time periods may be determined. The access flow of the plurality of task identifications corresponding to the target library identification in a plurality of continuous time periods can be obtained through screening.
It should be noted that the target access traffic is an access traffic of the target task identifier in the target time period, and the first access traffic is an access traffic of the target task identifier in a first time period immediately before the target time period; the second access flow is the access flow of the target task identifier in a second time period which is next to the target time period after the target time period;
and step 306, determining the flow change speed of each target task identifier according to the target access flow, the first access flow and the second access flow.
It should be noted that the traffic change speed is an access traffic change situation in a time period before and after an abnormality, and the traffic change speed is determined based on a difference between the target access traffic and the first access traffic and a difference between the target access traffic and the second access traffic.
And 307, determining the target task identifier corresponding to the flow change speed with the maximum value as an abnormal task identifier.
And 308, determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relationship between the task identifiers and the services.
It should be noted that the correspondence between the service and the task is predetermined. For example, for a bullet screen service, the bullet screen service corresponds to a plurality of tasks, and the bullet screen service and the corresponding tasks are predetermined. As long as the task is determined, the corresponding service can be found.
In the embodiment of the invention, access data periodically sent by all clients corresponding to the database can be received; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
The method for locating the source of the database exception provided by the embodiment of the present invention is described above by the server side, and the method for locating the source of the database exception at the client side will be described below with reference to the accompanying drawings.
Referring to fig. 4, an embodiment of the present invention provides a method for locating a database anomaly source, which is applied to a client, where the method includes:
it should be noted that the client accesses the corresponding database when performing the task to generate access data, which includes: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. The access flow of the client accessing the database within the first preset time is the data exchange amount or the accumulation amount of the returned data amount when the client accesses the database for multiple times within the first preset time. For example, the client sends the access data every five minutes, the task identifier and the library identifier in the access data sent every time are the same, and the access flow is the data exchange amount or the accumulated amount of the returned data amount when the database is accessed for multiple times within five minutes before the current time.
Step 402, taking the task identifier, the library identifier and the access flow as access data, and periodically sending the access data to a server by taking a first preset time length as a sending period so that the server receives the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service.
It should be noted that the access data may be sent via heartbeat packets.
In the embodiment of the invention, the access data is periodically sent to the server, so that the server can receive the access data periodically sent by all clients corresponding to the database; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
Fig. 5 is a diagram illustrating an architecture of an application system of the method for locating a source of a database exception according to an embodiment of the present invention; the method comprises the following steps: the system comprises a unified client, a controller, a real-time online analysis processing system, a rule engine and a front-end display.
Unifying the client: one layer of encapsulation is done on the native official client, with the specific differences as follows. The method comprises the steps of automatically registering a unique task identifier when starting, and sending heartbeat with a controller periodically (configurable and default to 5 minutes), wherein the heartbeat content comprises a database cluster, the task identifier and access flow. The task identifier is specified by a task developer, and is usually a directional identifier such as a task name or a person in charge.
A controller: and developing an independent webpage server, receiving heartbeats of all clients, recording survival conditions of the clients, and forwarding the database cluster, the task identifier and the access flow to the real-time online analysis processing system.
Real-time online analysis processing system: apache drive may be used, arranged to aggregate database clusters and task identities, and count the sum of access traffic for each group of cluster and task identity dyads.
A rule engine: and developing an independent webpage server, and acquiring aggregated data from the real-time online analysis processing system by taking the time period and the cluster as screening conditions, namely (the time period, the cluster, the task identifier and the total access flow). Two rules are set to find out problematic task identifiers: a) b) visiting the highest ranking of total traffic, b) visiting the highest speedup of total traffic.
Front-end presentation: and developing a network page, and allowing a database operation and maintenance person or a user to input a time period and displaying a result calculated by the rule engine on the page.
The method for locating the source of the database exception provided by the embodiment of the present invention is described above, and an apparatus for locating the source of the database exception provided by the embodiment of the present invention is described below with reference to the accompanying drawings.
Referring to fig. 6, an embodiment of the present invention further provides an apparatus for locating a source of an exception in a database, where the apparatus is applied to a server, and the apparatus includes:
a receiving module 601, configured to receive access data periodically sent by all clients corresponding to the database; wherein accessing the data comprises: the method comprises the steps that a task identifier of a task executed by a client, a library identifier of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length are obtained;
the aggregation module 602 is configured to aggregate the access data according to a second preset time duration to obtain an access flow of each task identifier in multiple consecutive time periods;
the task exception confirmation module 603 is configured to determine an exception task identifier according to a change speed of the access flow in multiple continuous time periods;
the service exception determining module 604 is configured to determine, according to a preset correspondence between the task identifier and the service, an exception service corresponding to the exception task identifier.
It should be noted that the database corresponding to the client is a database that is accessed when the client executes the task indicated by the task identifier.
The number of the databases is multiple, and each database corresponds to different clients.
Referring to fig. 7, the aggregation module 602 includes:
a labeling unit 6021, configured to label a statistical time for each access data, where the statistical time is a time when the access data is received;
the time period unit 6022 is configured to obtain a plurality of continuous time periods by taking a preset time as a start time and a second preset time as a step length;
the counting unit 6023 is configured to count a total access flow of each task identifier in each database in each time period according to the counting time.
Referring to fig. 8, the task exception confirmation module 603 includes:
a receiving unit 6031 configured to receive a target time period and a target library identifier input by a user;
a first determining unit 6032, configured to determine, according to the target library identifier, access traffic of each target task identifier corresponding to the target library identifier in multiple consecutive time periods;
a second determining unit 6033, configured to determine, according to a target time period and access traffic of a target task identifier in multiple consecutive time periods, a target access traffic, a first access traffic, and a second access traffic, where the target access traffic is the access traffic of the target task identifier in the target time period, and the first access traffic is the access traffic of the target task identifier in the first time period immediately before the target time period and in the first time period immediately before the target time period; the second access flow is the access flow of the target task identifier in a second time period which is next to the target time period after the target time period;
a third determining unit 6034, configured to determine a traffic change speed of each target task identifier according to the target access traffic, the first access traffic, and the second access traffic;
a fourth determining unit 6035, configured to determine the target task identifier corresponding to the flow rate change speed with the largest value as the abnormal task identifier.
The taxi taking application processing device provided by the embodiment of the invention can realize each process realized by the taxi taking application processing device in the method embodiments of fig. 1 to fig. 3, and is not repeated here for avoiding repetition.
In the embodiment of the invention, access data periodically sent by all clients corresponding to the database can be received; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
Referring to fig. 9, an embodiment of the present invention further provides an apparatus for locating a database exception source, which is applied to a client, and the apparatus includes:
an obtaining module 901, configured to obtain a task identifier of a task executed by a client, a library identifier of a database corresponding to the client, and an access flow for the client to access the database within a first preset duration;
a sending module 902, configured to send the task identifier, the library identifier, and the access flow as access data to the server periodically with a first preset time as a sending period, so that the server receives the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service.
The device for locating the database abnormal source provided by the embodiment of the present invention can implement each process implemented by the method for locating the database abnormal source in the method embodiment of fig. 4, and is not described herein again to avoid repetition.
In the embodiment of the invention, the access data is periodically sent to the server, so that the server can receive the access data periodically sent by all clients corresponding to the database; wherein accessing data comprises: the method comprises the steps of task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length. Since each client corresponds to a unique task, the access condition of each task can be determined by accessing the data. Then aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; and then determining the abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods. The task identifier of which the change speed of the access traffic exceeds the threshold value in a plurality of continuous time periods can be determined as the abnormal task identifier. Because each service corresponds to one or more fixed tasks, the abnormal service corresponding to the abnormal task identifier can be determined according to the preset corresponding relation between the task identifier and the service. The abnormal service is directly and automatically positioned without manual analysis and judgment in the whole process, so that the method is quick and accurate, and the stability of the database is indirectly improved.
The embodiment of the present invention further provides an electronic device, as shown in fig. 10, including a processor 1001, a communication interface 1002, a memory 1003 and a communication bus 1004, where the processor 1001, the communication interface 1002, and the memory 1003 complete mutual communication through the communication bus 1004;
a memory 1003 for storing a computer program;
the processor 1001 is configured to implement the following steps when executing the program stored in the memory 1003:
receiving access data which are periodically sent by all client sides and correspond to a database; wherein accessing the data comprises: the method comprises the steps that a task identifier of a task executed by a client, a library identifier of a database corresponding to the client and access flow of the database accessed by the client within a first preset time length are obtained;
aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods;
determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods;
and determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service.
Or
Acquiring a task identifier of a task executed by a client, a library identifier of a database corresponding to the client and access flow of the client accessing the database within a first preset time length;
taking the task identifier, the library identifier and the access flow as access data, and periodically sending the access data to a server by taking a first preset time as a sending period so as to enable the server to receive the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service.
The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the terminal and other equipment.
The Memory may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In yet another embodiment of the present invention, there is also provided a computer-readable storage medium having stored therein instructions, which when run on a computer, cause the computer to execute the method for locating a source of a database exception as described in any of the above embodiments.
In yet another embodiment of the present invention, there is provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method for locating a source of a database exception as described in the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A method for locating a database exception source, applied to a server, the method comprising:
receiving access data which are periodically sent by all client sides and correspond to a database; wherein the accessing data comprises: the method comprises the steps that task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the client accessing the database within a first preset time length are obtained;
aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods;
determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods;
and determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
2. The method according to claim 1, wherein the database corresponding to the client is a database accessed by the client when executing the task indicated by the task identification.
3. The method of claim 1, wherein the number of the databases is multiple, and each database corresponds to a different client.
4. The method according to claim 3, wherein the step of aggregating the access data according to a second preset time duration to obtain the access traffic of each task identifier in a plurality of consecutive time periods comprises:
marking a statistical time for each access data, wherein the statistical time is the time of receiving the access data;
obtaining a plurality of continuous time periods by taking the preset time as a starting time and the second preset time as a step length;
and counting the sum of the access flow of each task identifier in each database in each time period according to the counting time.
5. The method of claim 3, wherein the step of determining an abnormal task identifier based on the rate of change of the access traffic over a plurality of consecutive time periods comprises:
receiving a target time period and a target library identification input by a user;
according to the target library identification, determining the access flow of each target task identification corresponding to the target library identification in a plurality of continuous time periods;
determining a target access flow, a first access flow and a second access flow according to the target time period and the access flows of the target task identifier in a plurality of continuous time periods, wherein the target access flow is the access flow of the target task identifier in the target time period, and the first access flow is the access flow of the target task identifier in a first time period which is immediately before the target time period and is next to the target time period; the second access flow is the access flow of the target task identifier in a second time period which is next to the target time period after the target time period;
determining the flow change speed of each target task identifier according to the target access flow, the first access flow and the second access flow;
and determining the target task identifier corresponding to the flow change speed with the maximum value as the abnormal task identifier.
6. A method for locating a database exception source, applied to a client, comprises the following steps:
acquiring a task identifier of a task executed by the client, a library identifier of a database corresponding to the client and access flow of the client accessing the database within a first preset time;
taking the task identifier, the library identifier and the access flow as access data, and periodically sending the access data to a server by taking a first preset time length as a sending period so that the server receives the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
7. An apparatus for locating a source of an anomaly in a database, the apparatus being applied to a server, the apparatus comprising:
the receiving module is used for receiving access data which are sent by all clients corresponding to the database at regular intervals; wherein the accessing data comprises: the method comprises the steps that task identification of a task executed by a client, library identification of a database corresponding to the client and access flow of the client accessing the database within a first preset time length are obtained;
the aggregation module is used for aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods;
the task abnormity confirmation module is used for determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods;
and the service abnormity confirmation module is used for determining the abnormal service corresponding to the abnormal task identifier according to the preset corresponding relation between the task identifier and the service.
8. An apparatus for locating a source of an anomaly in a database, the apparatus being applied to a client, the apparatus comprising:
the acquisition module is used for acquiring a task identifier of a task executed by the client, a library identifier of a database corresponding to the client and access flow of the client accessing the database within a first preset time length;
the sending module is used for taking the task identifier, the library identifier and the access flow as access data, and regularly sending the access data to a server by taking a first preset time as a sending period so that the server receives the access data; aggregating the access data according to a second preset time length to obtain the access flow of each task identifier in a plurality of continuous time periods; determining an abnormal task identifier according to the change speed of the access flow in a plurality of continuous time periods; and determining abnormal services corresponding to the abnormal task identifiers according to the preset corresponding relation between the task identifiers and the services.
9. An electronic device comprising a processor, a memory and a computer program stored on the memory and executable on the processor, characterized in that the computer program, when executed by the processor, implements the method of locating a source of a database exception as claimed in any one of claims 1 to 5 or the steps of the method of locating a source of a database exception as claimed in claim 6.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method for locating a source of a database exception as set forth in any one of claims 1 to 5 or the method for locating a source of a database exception as set forth in claim 6.
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Application publication date: 20200424 |