CN113051120A - Data monitoring method and device, readable medium and electronic equipment - Google Patents
Data monitoring method and device, readable medium and electronic equipment Download PDFInfo
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- CN113051120A CN113051120A CN201911362641.0A CN201911362641A CN113051120A CN 113051120 A CN113051120 A CN 113051120A CN 201911362641 A CN201911362641 A CN 201911362641A CN 113051120 A CN113051120 A CN 113051120A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
- G06F11/324—Display of status information
- G06F11/327—Alarm or error message display
Abstract
The invention discloses a data monitoring method, a device, a readable medium and electronic equipment, wherein the method is applied to a data monitoring platform and comprises the following steps: determining a monitoring object, wherein the monitoring object comprises at least two different types of databases; acquiring the current variable quantity of the monitoring attributes in different types of databases; and if the current variable quantity of the monitoring attribute in the different types of databases does not accord with the preset variable range corresponding to the monitoring attribute in the different types of databases, performing alarm processing. The technical scheme provided by the invention can monitor at least two different types of databases, and effectively improves the efficiency of a data monitoring platform using the data monitoring method.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a data monitoring method and apparatus, a readable medium, and an electronic device.
Background
In the process of big data production, data transmission among different databases is involved, and data monitoring is needed in the process of data transmission so as to ensure the stability and integrity of data transmission.
At present, when a data monitoring method of an existing data monitoring platform is used for monitoring data transmission, the data transmission is limited by the types of databases, the existing data monitoring method of the data monitoring platform generally only supports a certain type, and different monitoring platforms are required to be selected for data monitoring of multiple database types. Nowadays, large data information is increasingly developed, types of databases are more and more, and the existing data monitoring method cannot realize uniform monitoring management on data of various databases of different types, so that the existing data monitoring method is low in efficiency.
Disclosure of Invention
The invention provides a data monitoring method, a data monitoring device, a readable medium and electronic equipment, which can monitor at least two different types of databases and effectively improve the efficiency of a data monitoring platform using the data monitoring method.
In a first aspect, the present invention provides a data monitoring method applied to a data monitoring platform, including:
determining a monitoring object, wherein the monitoring object comprises at least two different types of databases;
acquiring the current variable quantity of the monitoring attributes in different types of databases;
and if the current variable quantity of the monitoring attribute in the different types of databases does not accord with the preset variable range corresponding to the monitoring attribute in the different types of databases, performing alarm processing.
In a second aspect, the present invention provides a data monitoring apparatus applied to a data monitoring platform, including:
the determining and processing module is used for determining a monitoring object, and the monitoring object comprises at least two different types of databases;
the acquisition processing module is used for acquiring the current variable quantity of the monitoring attributes in different types of databases;
and the alarm processing module is used for carrying out alarm processing if the current variable quantity of the monitoring attributes in the different types of databases does not conform to the preset variable range corresponding to the monitoring attributes in the different types of databases.
In a third aspect, the invention provides a readable medium comprising executable instructions, which when executed by a processor of an electronic device, perform the method according to the first aspect.
In a fourth aspect, the present invention provides an electronic device, comprising a processor and a memory storing execution instructions, wherein when the processor executes the execution instructions stored in the memory, the processor performs the method according to the first aspect.
The invention provides a data monitoring method, a data monitoring device, a computer readable medium and electronic equipment; the method is applied to a data monitoring platform, and comprises the steps of determining a monitored object which comprises at least two databases of different types, then obtaining the current variable quantity of the monitoring attribute in the databases of different types, further judging whether the current variable quantity of the monitoring attribute in the databases of different types is in accordance with the preset variable range corresponding to the monitoring attribute in the databases of the type, and if not, carrying out alarm processing, thereby realizing data monitoring on the databases of different types and effectively improving the efficiency of the data monitoring platform using the data monitoring method.
Further effects of the above-mentioned unconventional preferred modes will be described below in conjunction with specific embodiments.
Drawings
In order to more clearly illustrate the embodiments or the prior art solutions of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a schematic flow chart of a data monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a data monitoring method according to another embodiment of the present invention;
fig. 3 is a schematic interface diagram illustrating a configuration of a monitoring object in the data monitoring method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a data monitoring apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a data monitoring apparatus according to another embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the 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.
In the foregoing, a data monitoring method of a data monitoring platform commonly used at the present stage only supports monitoring of data transmission of a certain type of database, and the types of the database are increasing with development of big data information at present, and more non-mainstream databases are applied to various fields, so that the data monitoring method of the existing data monitoring platform cannot implement unified monitoring management on data of various types, and the efficiency of the existing data monitoring method is low. Therefore, the technical scheme provided by the invention can monitor at least two different types of databases, and effectively improves the efficiency of a data monitoring platform using the data monitoring method.
Referring to fig. 1, a specific embodiment of a data monitoring method according to the present invention is shown. The method in this embodiment includes the following steps:
In this embodiment, at least two different types of databases are determined as monitoring objects, where the types of databases may be current mainstream databases, such as MySQL, SQL Server, and Oracle, and may also include non-mainstream databases, such as MongoDB, hypertext, and Apache CouchDB. Specifically, a configuration interface can be built on the data monitoring platform, and the monitoring object can be configured through the configuration interface.
In this embodiment, the current variation of the monitoring attribute in the different types of databases is determined, where the current variation is real-time variation data of the monitoring attribute in the different types of databases before and after data transmission.
And 103, if the current variable quantity of the monitoring attribute in the different types of databases does not accord with the preset variable range corresponding to the monitoring attribute in the different types of databases, performing alarm processing.
In this embodiment, the preset variable ranges of the monitoring attributes in the different types of databases are predetermined, and if the current variation of the monitoring attributes in the different types of databases does not conform to the preset variable range corresponding to the monitoring attribute in the different types of databases, it is proved that the monitoring attributes in the different types of databases have problems before and after data transmission, and therefore, alarm processing needs to be performed, and related personnel needs to be reminded to perform processing in time. The alarm processing mode can be short message, telephone or mail. For example, the preset variable range of a certain monitoring object a is 1-5000 every day, and if the current variation of the monitoring object a is found to be 0, it may be that data synchronization has a problem, and at this time, alarm processing is performed.
In the above embodiment, by determining a monitoring object, which includes at least two different types of databases, and then obtaining the current variation of the monitoring attribute in the different types of databases, it is further determined whether the current variation of the monitoring attribute in the different types of databases conforms to the preset variable range corresponding to the monitoring attribute in the different types of databases, and if not, an alarm is performed, so that data monitoring on the databases of multiple different types is achieved, and the efficiency of a data monitoring platform using the data monitoring method is effectively improved.
Fig. 1 shows only a basic embodiment of the method of the present invention, and based on this, certain optimization and expansion can be performed, and other preferred embodiments of the method can also be obtained.
Fig. 2 shows another embodiment of the data monitoring method according to the present invention. In this embodiment, the data monitoring method includes the following steps:
In this embodiment, the monitoring object may be determined by configuring the monitoring object, and when the monitoring object is configured, the monitoring attribute in the different types of databases and the preset variable range of the monitoring attribute in the different types of databases may be configured together.
Specifically, the interface shown in fig. 3 may be used to configure the preset variable range of the monitoring attributes in the monitoring object and the databases of different types, where the configurable monitoring attributes include a table structure, a total number of table rows, a percentage of table rows, or a table value, and a user may select the monitoring attributes according to an actual service scenario. In fig. 3, the source database and the target database jointly form the monitoring object in this embodiment, where the source database is a database for performing data extraction and transmission, and the target database is a database for receiving data transmission. It should be noted that, when a user needs to determine a monitored object in this embodiment, the monitored object may be further determined as a data table in a certain database.
For example, now for 3 databases: and the MySQL, the SQL Server and the MongoDB are used for data monitoring. Wherein, the monitored object 1: a target database corresponding to the source database MySQL is hive1, the monitoring attribute is the total number of rows of change, and the variable range of the monitoring attribute is 1-5000; the monitored object 2: a target database corresponding to a source data table in a source database SQL Server is a target data table in hive2, the monitoring attribute is row number percentage change, and the variable range of the monitoring attribute is 0.1% -1%; the monitored object 3: the target database corresponding to the source database mongoDB is hive3, the monitoring attribute is the total number of rows change, and the variable range of the monitoring attribute is 0-300. 3 new monitoring tables are established and corresponding contents are filled in.
When data in a database is transmitted, in consideration of security factors, data is usually transmitted to a front-end processor in a data synchronization or file backup manner, so that a backup database is formed in the front-end processor, and then data is extracted from the backup database into a target database, such as a hive database.
In this embodiment, a first data value corresponding to source data before data transmission is performed on monitoring attributes in different types of databases is obtained, where the source data is a source database or a source database table. For example, for the monitored object 1 and the monitored object 3, the determined monitoring attribute is the total number of rows; for the monitored object 2, the determined monitoring attribute is the percentage of the number of rows. The following data can thus be acquired: determining a first data value corresponding to the total number of rows of MySQL of the source database of the monitored object 1 as 3267937; determining that the total number of rows in a source data table in the SQL Server of the source database of the monitored object 2 corresponds to a first data value of 2.1%, and determining that the total number of rows in the MongoDB of the source database of the monitored object 3 corresponds to a first data value of 1999525.
In this embodiment, similarly, it is necessary to determine a second data value in the target data after the transmission of the monitoring attribute data in the different types of databases, where the target data is a target database or a target database table. For example, the following data may be obtained: determining a second data value corresponding to the total number of rows of MySQL of the source database of the monitored object 1 as 3269679; determining that the row percentage of a first source data table in a SQL Server of a source database of the monitored object 2 is 2.3% of a corresponding second data value; and determining that the second data value corresponding to the total number of the line numbers of the source database MongoDB of the monitored object 3 is 1999000.
And 204, acquiring the current variable quantity of the monitoring attributes in the different types of databases according to the first data value and the second data value.
In this embodiment, the first data value and the second data value are respectively corresponding data values before and after transmission of the monitoring attribute data in the different types of databases, so that the current variation of the monitoring attribute in the different types of databases can be determined according to the first data value and the second data value. For example, through the first data value and the second data value respectively corresponding to the monitoring object 1, the monitoring object 2, and the monitoring object 3, it may be obtained that the current variation of the total number of rows of the monitoring object 1 is +1742, the current variation of the percentage of the rows of the monitoring object 2 is + 0.2%, and the current variation of the total number of rows of the monitoring object 3 is-525.
In this embodiment, after the current variation of the monitoring attribute in the different types of databases is determined, the current variation of the monitoring attribute in the different types of databases is recorded to generate a data monitoring log, so that the data monitoring log can be checked if necessary. In a possible implementation manner, monitoring information such as a source database, a first data value in the source database, a target database, a second data value in the target database, and a current variation corresponding to a monitoring attribute in different types of databases is recorded to generate a data monitoring log.
For example, 3 log records are added to the monitoring object 1, the monitoring object 2 and the monitoring object 3:
source database MySQL, target database hive1, source database row number total 3267937, target database row number total 3269679, and monitor attribute current variation + 1742.
A source database table in the source database SQL Server, a target database table in the target database hive2, a percentage of rows of the source database is 2.1%, a percentage of rows of the target database is 2.3%, and a current variation of the monitoring attribute is + 0.2%.
The source database MongoDB, the target database hive3, the source database row number total 1999525, the target database row number total 1999000, and the monitoring attribute current variation-525.
Specifically, a MySQL database is deployed while a monitoring tool is deployed on the front-end processor, and is used for recording monitoring information of a monitored object, and the monitoring information can be viewed through openapi.
And step 206, if the current variation of the monitoring attributes in the different types of databases does not conform to the preset variable range corresponding to the monitoring attributes in the different types of databases, performing alarm processing.
In this embodiment, when the current variation of the monitoring attribute in the different types of databases does not conform to the preset variable range corresponding to the monitoring attribute in the different types of databases, it is proved that a problem occurs in the monitoring object during the data transmission process, and then an alarm process is performed, for example, alarm information is sent to related personnel.
For example, if the current variation of the monitored object 1 and the current variation of the monitored object 2 both conform to the preset variable range, the monitoring is continued; the current variation of the monitored object 3 is-525 and the preset variable range of the monitored object 3 is 0-300, the current variation of the monitored object 3 does not conform to the preset variable range, and thus the alarm information related to the monitored object 3 is transmitted.
And step 207, determining the reason why the current variation of the monitoring attributes in the different types of databases does not conform to the preset variable range corresponding to the monitoring attributes in the different types of databases based on the source data and the target data.
In this embodiment, when the current variation of the monitoring attribute in the different types of databases does not conform to the preset variable range corresponding to the monitoring attribute in the database of the type, it is described that the monitored object has a problem in the data transmission process, and therefore, in order to determine that there may be a problem in the data transmission process, the first backup data corresponding to the source data is determined. In order to ensure the safety of the data, the target data also has a backup database, so that the second backup data corresponding to the target data also needs to be determined. After the first backup data and the second backup data are determined, the reason that the current variation does not meet the preset variable range in data transmission, such as data loss in the data transmission process, can be determined, the data loss is determined by comparing the first backup data with the second backup data, and the possible reason is further determined, so that relevant personnel can solve the problem as soon as possible.
According to the technical scheme, monitoring information such as the current variation of the monitoring attributes in the databases of different types can be recorded in the embodiment, so that related personnel can conveniently inquire the monitoring information, the reason that the current variation is not in accordance with the preset variable range is further determined by determining the first backup data corresponding to the source data and the second backup data corresponding to the target data, so that the related personnel can conveniently solve the existing problems as soon as possible, and the efficiency and the practicability of the data monitoring platform using the data monitoring method can be effectively improved.
Fig. 4 shows a data monitoring apparatus according to an embodiment of the present invention. The apparatus of this embodiment is a physical apparatus for performing the method described in fig. 1-2. The technical solution is essentially the same as that in the above embodiment, and the corresponding description in the above embodiment is also applicable to this embodiment. The device in this embodiment includes:
a determination processing module 41, configured to determine a monitoring object, where the monitoring object includes at least two different types of databases;
an obtaining processing module 42, configured to obtain current variation of the monitoring attributes in the different types of databases;
and an alarm processing module 43, configured to perform alarm processing if the current variation of the monitoring attribute in the different types of databases does not conform to the preset variable range corresponding to the monitoring attribute in the different types of databases.
As shown in fig. 5, in an embodiment of the present invention, the obtaining processing module 42 includes:
a first obtaining unit 421, configured to obtain a first data value corresponding to a monitoring attribute in different types of databases before data transmission;
a second obtaining unit 422, configured to obtain a second data value corresponding to the monitoring attribute in the different types of databases after data transmission is performed on the monitoring attribute;
a third obtaining unit 423, configured to obtain, according to the first data value and the second data value, a current variation of the monitoring attribute in the different types of databases.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. On the hardware level, the electronic device comprises a processor and optionally an internal bus, a network interface and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 6, but that does not indicate only one bus or one type of bus.
And the memory is used for storing the execution instruction. In particular, a computer program that can be executed by executing instructions. The memory may include both memory and non-volatile storage and provides execution instructions and data to the processor.
In a possible implementation manner, the processor reads the corresponding execution instruction from the nonvolatile memory to the memory and then runs the execution instruction, and the corresponding execution instruction can also be obtained from other equipment, so as to form the data monitoring device on a logic level. The processor executes the execution instruction stored in the memory, so that the data monitoring method provided by any embodiment of the invention is realized through the executed execution instruction.
The method executed by the data monitoring apparatus according to the embodiment of the present invention shown in fig. 4 or fig. 5 may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
An embodiment of the present invention further provides a readable storage medium, where the readable storage medium stores an execution instruction, and when the stored execution instruction is executed by a processor of an electronic device, the electronic device can be caused to execute the data monitoring method provided in any embodiment of the present invention, and is specifically configured to execute the method shown in fig. 1 or fig. 2.
The electronic device described in the foregoing embodiments may be a computer.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It should also be noted that 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 like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A data monitoring method is applied to a data monitoring platform and is characterized by comprising the following steps:
determining a monitoring object, wherein the monitoring object comprises at least two different types of databases;
acquiring the current variable quantity of the monitoring attributes in different types of databases;
and if the current variable quantity of the monitoring attribute in the different types of databases does not accord with the preset variable range corresponding to the monitoring attribute in the different types of databases, performing alarm processing.
2. The method of claim 1, wherein obtaining the current amount of change in the monitored attribute in the different types of data comprises:
acquiring corresponding first data values in source data before data transmission of monitoring attributes in different types of databases;
acquiring a corresponding second data value in the target data after the monitoring attributes in the different types of databases are subjected to data transmission;
and acquiring the current variable quantity of the monitoring attributes in the different types of databases according to the first data value and the second data value.
3. The method according to claim 2, wherein after the step of determining that the current variation of the monitoring attribute in the different types of databases does not conform to the preset variable range corresponding to the monitoring attribute in the different types of databases, the method further comprises:
and determining the reason that the current variable quantity of the monitoring attributes in the different types of databases does not accord with the preset variable range corresponding to the monitoring attributes in the different types of databases based on the source data and the target data.
4. The method according to claim 3, wherein the determining the reason why the current variation of the monitoring attribute in the different types of databases does not conform to the preset variable range corresponding to the monitoring attribute in the different types of databases comprises:
determining first backup data corresponding to the source data;
determining second backup data corresponding to the target data;
and determining the reason that the current variable quantity of the monitoring attributes in the different types of databases does not accord with the preset variable range corresponding to the monitoring attributes in the different types of databases based on the first backup data and the second backup data.
5. The method of claim 1, wherein after the step of obtaining the current variance of the monitored attribute in the different types of databases, further comprising:
and generating a data monitoring log according to the current variable quantity of the monitoring attributes in the different types of databases.
6. The method of any one of claims 1 to 5, wherein the monitoring attributes comprise table structure, total number of table rows, percentage of table rows, or table value.
7. The utility model provides a data monitoring device, is applied to data monitoring platform, its characterized in that includes:
the determining and processing module is used for determining a monitoring object, and the monitoring object comprises at least two different types of databases;
the acquisition processing module is used for acquiring the current variable quantity of the monitoring attributes in different types of databases;
and the alarm processing module is used for carrying out alarm processing if the current variable quantity of the monitoring attributes in the different types of databases does not conform to the preset variable range corresponding to the monitoring attributes in the different types of databases.
8. The apparatus of claim 7, wherein the acquisition processing module comprises:
the first acquisition unit is used for acquiring corresponding first data values in the source data before data transmission is carried out on the monitoring attributes in the databases of different types;
the second acquisition unit is used for acquiring a corresponding second data value in the target data after the monitoring attributes in the different types of databases are subjected to data transmission;
and the third acquiring unit is used for acquiring the current variable quantity of the monitoring attribute in the different types of databases according to the first data value and the second data value.
9. A readable medium comprising executable instructions which, when executed by a processor of an electronic device, the electronic device performs the data monitoring method of any one of claims 1 to 6.
10. An electronic device comprising a processor and a memory storing execution instructions, the processor performing the data monitoring method of any one of claims 1 to 6 when the processor executes the execution instructions stored by the memory.
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