CN113641567A - Database inspection method and device, electronic equipment and storage medium - Google Patents
Database inspection method and device, electronic equipment and storage medium Download PDFInfo
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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
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3466—Performance evaluation by tracing or monitoring
- G06F11/3476—Data logging
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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
- G06F11/3055—Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available
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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
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
- G06F2201/80—Database-specific techniques
Abstract
The disclosure relates to a database inspection method, a database inspection device, electronic equipment and a storage medium, wherein the method comprises the following steps: pulling original index data from a data source; the original index data includes: base index data related to the instances and business index data related to the database; acquiring a pre-configured automatic inspection parameter; the automatic inspection parameters include: polling period, performance polling item and data analysis parameter; acquiring polling data from the original index data according to a polling period; the polling data comprises first index data corresponding to each performance polling item; and analyzing the routing inspection data according to the data analysis parameters. This openly can promote data and patrol and examine efficiency.
Description
Technical Field
The present disclosure relates to the field of database technologies, and in particular, to a database inspection method, an apparatus, an electronic device, and a storage medium.
Background
The importance of databases in internet applications is self-evident in that it organizes, stores and manages data according to a data structure. Regular inspection and risk prevention of the database are important links of daily maintenance of the database, and whether the database runs well can be generally evaluated through inspection so as to ensure normal operation of the whole data communication system.
At present, the database is mainly patrolled and examined in a manual mode, the time of about two days is needed for patrolling and examining once, a large amount of labor cost is needed for the patrolling and examining mode, and the patrolling and examining efficiency is low. However, as the information age has been continuously developed, the patrol period required by an actual user should be shorter. If still rely on the manual mode to carry out the database and patrol and examine, patrol and examine the cycle and can receive operating time's restraint, patrol and examine inefficiency and patrol and examine the quality poor, easily miss the inspection.
Disclosure of Invention
In order to solve the technical problems or at least partially solve the technical problems, the present disclosure provides a database inspection method, an apparatus, an electronic device, and a storage medium.
According to one aspect of the disclosure, a database inspection method is provided, which includes:
pulling raw index data from a data source, wherein the raw index data comprises: base index data related to the instances and business index data related to the database; acquiring a preconfigured automatic inspection parameter, wherein the automatic inspection parameter comprises: polling period, performance polling item and data analysis parameter; acquiring polling data from the original index data according to the polling period, wherein the polling data comprises first index data corresponding to each performance polling item; and analyzing the routing inspection data according to the data analysis parameters.
According to another aspect of the present disclosure, there is provided a database inspection device including:
the data pulling module is used for pulling original index data from a data source, wherein the original index data comprises: base index data related to the instances and business index data related to the database;
the parameter acquisition module is used for acquiring preconfigured automatic inspection parameters, wherein the automatic inspection parameters comprise: polling period, performance polling item and data analysis parameter;
the inspection data acquisition module is used for acquiring inspection data from the original index data according to the inspection period, wherein the inspection data comprises first index data corresponding to each performance inspection item;
and the data analysis module is used for analyzing the routing inspection data according to the data analysis parameters.
According to another aspect of the present disclosure, there is provided an electronic apparatus including: a processor; and a memory storing a program comprising instructions which, when executed by the processor, cause the processor to perform a method according to the above.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the above method.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
the embodiment of the disclosure provides a database inspection method, a database inspection device, an electronic device and a storage medium, wherein the method comprises the following steps: pulling original index data from a data source; the original index data includes: base index data related to the instances and business index data related to the database; acquiring a pre-configured automatic inspection parameter; the automatic inspection parameters include: polling period, performance polling item and data analysis parameter; acquiring polling data from the original index data according to a polling period; the polling data comprises first index data corresponding to each performance polling item; and analyzing the routing inspection data according to the data analysis parameters. This openly can promote data and patrol and examine efficiency.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present disclosure, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a flowchart of a database inspection method provided in an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a database inspection scene provided by the embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a database inspection device provided in the embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure can be more clearly understood, embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description. It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Referring to a flow chart of a database inspection method shown in fig. 1, the database inspection method provided by the embodiment includes the following steps:
and S102, pulling original index data from a data source.
As shown in the scenario diagram of fig. 2, the data source in this embodiment may be a cloud vendor and/or a self-built database cluster (simply referred to as a self-built cluster). When the data source is a cloud manufacturer, data pulling can be performed through distributed tasks, the data pulling frequency is generally in the minute level, and the pulled original index data is stored in a cache, so that subsequent analysis is facilitated. When the data source is a self-established cluster, data reporting can be performed according to an Agent (proxy service), the data pulling frequency generally takes a day as a unit, for example, one day, and the pulled original index data is also stored in the cache, so that subsequent analysis is facilitated. An expiration time may be set for the raw index data pulled from the self-created cluster, for example, the expiration time is seven days, and then each piece of raw index data is saved for seven days by default.
Referring to fig. 2, the original index data includes the following two parts: base index data associated with the instance and business index data associated with the database. The basic index data includes: one or more of a Central Processing Unit (CPU) utilization rate, a memory utilization rate, a master-slave latency threshold, and a network utilization rate; the service index data comprises: one or more of QPS (Query Per Second, Query rate Per Second), transaction number Per Second, IO (Input Output) number, and SQL (Structured Query Language) records.
The present embodiment may automatically patrol the pulled original index data by using an automatic patrol method, which may refer to the following steps S104 to S108.
Step S104, acquiring a pre-configured automatic inspection parameter; the automatic inspection parameters include: polling period, performance polling item and data analysis parameter.
In this embodiment, the automatic inspection parameter is a parameter pre-configured based on the actual inspection requirement, and may include but is not limited to: the method comprises the steps of (1) polling period, performance polling item, data analysis parameter and key time point; the data analysis parameters are used for expressing parameters such as comparison analysis parameters, comparison periods, alarm thresholds and the like; key time points such as rush hour time points and user-defined arbitrary time points; the performance inspection items correspond to original index data, and comprise a CPU, a memory, master-slave delay, a network, QRS, IO, transaction number per second, SQL and the like. It should be noted that fig. 2 only shows, by way of example, a part of the patrol inspection parameters in the present embodiment and a part of the patrol inspection parameters in the subsequent embodiments.
And S106, acquiring polling data from the original index data according to a polling period, wherein the polling data comprises first index data corresponding to each performance polling item.
In this embodiment, assuming that the polling cycle is one week, the performance polling item includes a CPU, a memory and a network in the hardware item, so that when the polling data is obtained, the CPU usage rate, the memory usage rate and the network utilization rate in one week can be obtained from the original index data, and the obtained CPU usage rate, the memory usage rate and the network utilization rate are all used as the first index data.
And S108, analyzing the routing inspection data according to the data analysis parameters.
The data analysis parameters in the present embodiment include, for example: and comparing the analysis parameters, the comparison period of the comparison analysis parameters and the first data alarm threshold. The contrast analysis parameters can be the same ratio and/or the ring ratio, and the contrast period can be in units of time periods such as days, months, quarters or years. When the inspection data are analyzed according to the data analysis parameters, the first index data corresponding to each performance inspection item can be analyzed according to the comparison analysis parameters and the comparison period, and the risk level and the health degree of the analysis result of the first index data are further judged according to the first data alarm threshold value.
According to the database inspection method provided by the embodiment of the disclosure, inspection data are obtained from the pulled original index data according to the automatic inspection parameters, and the inspection data are automatically analyzed. By the technical scheme, automatic routing inspection can be realized on the two major index data, namely the basic index data and the service index data; the system comprises a data analysis parameter, a performance inspection item and a data analysis item, wherein the performance inspection item in the automatic inspection parameter is configured, inspection can be conducted on important index data, and the inspection data is analyzed in combination with the data analysis parameter. Therefore, the embodiment of the disclosure can realize automatic data inspection according to automatic inspection parameters, and does not need operation and maintenance personnel to manually inspect, thereby reducing labor cost, avoiding the problem of missed inspection and false inspection of manual inspection, and improving inspection efficiency and quality.
In order to adapt to actual production application, a user needs to acquire inspection data under specific conditions, and in this case, the embodiment may acquire other inspection data by configuring different automatic inspection parameters. For example, when the automatic routing inspection parameter further includes a key time point, the routing inspection data may include second index data; the manner of acquiring the second index data is as follows: and at the key time point, acquiring second index data corresponding to at least one preset performance inspection item from the original index data. Wherein, at least one performance polling item can be a performance polling item configured corresponding to the key time point. In one possible example, SQL records corresponding to the performance patrol term SQL may be collected from the raw index data as the second index data at peak time points.
The first index data is data corresponding to each performance inspection item in an inspection cycle, has universality, can avoid data omission by taking the first index data as inspection data, and improves the integrity of the data; the second index data are data corresponding to certain specific performance inspection items at key time points, can meet the data requirements of users in actual production application, and can enhance the data directivity by taking the data as inspection data. Therefore, the first index data and the second index data can be used as patrol data respectively, or the first index data and the second index data can be used as patrol data together. Based on this, the first index data and the second index data improve the richness of the routing inspection data in different data dimensions, and the accuracy of an analysis result is improved subsequently.
In order to facilitate understanding of the automated inspection mode, the present embodiment describes the step S108, and refers to the following four steps.
Step 1, analyzing the first index data corresponding to each performance inspection item according to the comparative analysis parameters and the comparative period thereof to obtain a first change trend of each first index data. For example, the ring has a first trend of CPU usage over 2 comparison cycles (such as two consecutive months), or a first trend of memory usage over the same year as the nth month and the nth month of the last year.
And 2, determining the trend type and the change amplitude of the first change trend according to the first data alarm threshold value.
The performance inspection items are multiple items, the corresponding first index data are also multiple items, and each item of first index data corresponds to a first data alarm threshold value. The present embodiment is described by taking any one of the first index data as an example. In this embodiment, the first data alarm threshold may be understood as a threshold of the first index data variation trend, where the threshold is used to determine the trend type and the variation amplitude of the first variation trend; in specific implementation, by comparing the first variation trend with the first data alarm threshold, it is determined whether the trend type of the first variation trend is rising, shaking or falling, and the corresponding variation amplitudes, such as rising amplitude and falling amplitude.
And step 3, determining the risk level of each first index data according to a preset amplitude range and the trend type and the change amplitude of the first change trend, wherein the amplitude range and the risk level have a corresponding relation.
In a specific embodiment, the variation amplitudes corresponding to different trend types may be preset with the same or different amplitude ranges, for example, for an upward trend type, the corresponding upward amplitude range may be preset to be 30%, for a downward trend type, the corresponding downward amplitude range may also be preset to be 30%, or may also be preset to be other amplitude ranges, which is not limited herein.
The amplitude range and the risk level have a corresponding relationship, for example, when the rising amplitude is within a preset amplitude range of 30% -50%, the risk level of the first index data is determined to be first level, and when the rising amplitude exceeds the preset amplitude range of 50%, the risk level of the first index data is determined to be second level; further, when the rising amplitude is less than a preset amplitude range of 30%, it is determined that the first index data is not at risk.
And 4, determining the health degree of the inspection data in the current inspection period according to the risk level of each first index data.
In this embodiment, the health degree of the patrol data in the current patrol cycle may be determined according to the proportion of the number of the first index data determining the risk level in all the first index data and/or the risk level of each first index data. A simple example of determining fitness on a scale is provided herein: the first index data of the risk level is determined to be three, and if all the first index data are eight, the percentage is 37.5%, and the health degree is determined to be 37.5%.
After the risk level of each first index data and the health degree of the complete inspection data in the current inspection period are determined through the steps, the inspection report can be generated according to the embodiment, and the inspection report is used for reflecting the risk level and the health degree.
The automatic inspection mode provided by the embodiment of the disclosure can replace manual inspection, and an inspection report is issued after automatic inspection is completed, so that the labor cost is reduced, and the inspection efficiency is improved.
In this embodiment, another inspection method is provided, which includes: and mapping the original index data according to the data generation time aiming at the original index data corresponding to each performance inspection item to form a visual data chart, wherein the visual data chart is used for displaying a second change trend of the original index data.
Aiming at the basic index data and the service index data, a visual data chart can be drawn; the data chart may be in units of minutes, hours, or days. Specifically, when the original index data is mapped, ring ratio or same ratio data analysis can be performed on the original index data corresponding to each performance inspection item according to the generation time, a visual data chart corresponding to each original index data is obtained through the ring ratio or the same ratio, the change trend of the original index data is checked through each visual data chart, and in order to distinguish the change trend from the first change trend in the automatic inspection mode, the change trend displayed through the visual data chart can be called as a second change trend.
For example, the following steps are carried out: analyzing the CPU utilization rate of the CPU utilization rate ring at the peak time of each week compared with the CPU utilization rate at the peak time of the last three weeks, thereby generating a visual data chart corresponding to the CPU utilization rate, and displaying a second change trend of the CPU utilization rate, namely the original index data through the visual data chart, so that the CPU utilization condition of the current database can be reflected; the same is true for other original index data, which are not listed here.
The inspection mode provided by the embodiment can realize data visualization, and has more visual experience when a user checks the data change trend, thereby improving the friendliness of user use.
The reason why the SQL records in the service index data are special is that if the execution time of each type of SQL is long and the concurrency is large, the CPU of the database is likely to be filled, and the risk that the database cannot provide services occurs. Based on this, the present embodiment can monitor for SQL records alone.
In this embodiment, first, the SQL record is parsed to obtain the SQL template and the execution time of the SQL template. For example the following two SQL records,
SQL record 1: select from book where a =1 and b =2
SQL record 2: select from book where a =4 and b =4
The SQL template formed after the two SQL records are analyzed is as follows: selectfrom book where a=
and b=
。
In practical application, the SQL records can be classified into four types of query, insertion, update and deletion so as to facilitate routing inspection visualization.
Then, in response to determining that the execution time exceeds a preset time threshold, the SQL recorded alarm information is marked.
And judging whether the execution time exceeds a threshold value. And if the execution time exceeds the preset time threshold, marking alarm information in response to a judgment result that the execution time exceeds the preset time threshold. The risk is exposed by marking alarm information and alarming in advance; meanwhile, an audit function can be set, wherein the audit function shows that after the SQL records are marked with the alarm information, the alarm information is prohibited to be marked again within a preset time limit according to a preset alarm convergence function so as to prevent the alarm from overflowing. If the threshold is not exceeded, no processing is required.
Except for the above several inspection modes, the embodiment can also provide other inspection modes according to the actual inspection requirement.
In this embodiment, the specified index data corresponding to the specified performance inspection item can be obtained from the original index data, and the specified index data is formatted and templated to form target index data meeting the personalized requirements of the user; and then analyzing the target index data according to a preset data alarm threshold value and a comparison mode of the same ratio and/or a ring ratio. Specific examples thereof include: when the designated index data is the service index data, the deadlock condition of the service index data can be analyzed, and whether deadlock occurs or the frequency of deadlock is monitored. Or, for example, when the index data is designated as the base index data, the instance operation state of the base index data may be analyzed.
In the above embodiment, whether any one of the original index data, the first index data, the second index data, or the specified index data is used, the alarm management may be performed as follows:
and acquiring a second data alarm threshold corresponding to each performance patrol item. And aiming at the original index data corresponding to each performance inspection item, responding to the fact that the original index data exceeds the corresponding second data alarm threshold value, and performing alarm management on the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold value.
In the specific implementation process, whether the original index data exceeds the corresponding second data alarm threshold or not is judged according to the original index data corresponding to each performance inspection item. And if the first data exceeds the second data alarm threshold, responding to the judgment result of the exceeding, and carrying out alarm management on the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold. In practical application, for original index data which is suitable for condition alarm such as network utilization rate or no condition alarm, alarm management may be to mark alarm information corresponding to the original index data as long as the original index data exceeds a corresponding second data alarm threshold, and alarm is performed according to a preset alarm reminding mode. For the original index data such as the memory utilization rate and the like suitable for the graded alarm, the alarm level of the original index data can be determined, and the alarm information is marked.
For original index data applicable to a hierarchical alarm, a specific embodiment of alarm management is provided herein, which includes: determining the alarm level of the original index data and marking the alarm information corresponding to the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold; and alarming according to the alarm reminding mode matched with the alarm level.
The degree that the original index data exceeds the corresponding second data alarm threshold value reflects the alarm severity, the alarm level of the original index data is determined based on the original index data, the alarm can be configured with a plurality of alarm reminding modes such as mails, short messages, telephones and the like, and at least one alarm reminding mode can be selected for alarming according to different alarm levels.
The embodiment provides a method for routing inspection treatment, which can be implemented in detail in two aspects, namely, the treatment auditing function, namely, the time limit for releasing the alarm information is determined; thereby enabling the data marked with the alarm information to be resolved within a set time limit; meanwhile, in the time limit, an alarm convergence function is configured to prohibit the alarm information from being marked again in the time limit, so that the alarm flooding is prevented. If the alarm is resolved within the time limit, the flagged alarm information is dismissed; if the alarm is not resolved by the time limit, the alarm information is marked again. On the other hand, aiming at the data of which the alarm information is released, files are established and classified for subsequent duplication, so that the same risk is prevented from appearing again.
To sum up, the data inspection method provided by the above embodiment implements data inspection from at least two levels of automated inspection and data visualization inspection for basic index data and service index data in cloud manufacturers and self-established clusters, and can independently monitor and alarm important service index data such as SQL records, and in addition, provides inspection management methods such as management and audit functions, alarm management and inspection management, and prevents the risk caused by overlooking of alarm problems. Therefore, the inspection efficiency and quality can be improved, and the labor cost is reduced.
Referring to fig. 3, an embodiment of the present disclosure provides a database inspection apparatus, which is used to implement the database inspection method in the foregoing embodiment, and the apparatus includes:
a data pulling module 302, configured to pull original index data from a data source; the original index data includes: base index data related to the instances and business index data related to the database;
a parameter obtaining module 304, configured to obtain a preconfigured automatic inspection parameter; the automatic inspection parameters include a plurality of the following: polling period, performance polling item and data analysis parameter;
the inspection data acquisition module 306 is used for acquiring inspection data from the original index data according to an inspection period; the polling data comprises first index data corresponding to each performance polling item;
and the data analysis module 308 is configured to analyze the inspection data according to the data analysis parameters, and generate an inspection report of the inspection data.
In one embodiment, the data analysis parameters include: comparing the analysis parameters, the comparison period of the comparison analysis parameters and a first data alarm threshold;
the data analysis module 308 is specifically configured to:
analyzing the first index data corresponding to each performance inspection item according to the comparative analysis parameters and the comparative period thereof to obtain a first change trend of each first index data; determining the trend type and the variation amplitude of the first variation trend according to the first data alarm threshold; determining the risk level of each first index data according to a preset amplitude range and the trend type and the change amplitude of the first change trend, wherein the amplitude range and the risk level have a corresponding relation; and determining the health degree of the inspection data in the current inspection period according to the risk level of each first index data.
In one embodiment, the automatic routing inspection parameter further comprises: at the critical point in time, the time of day,
the inspection data obtaining module 306 is further configured to:
and at a key time point, acquiring second index data corresponding to at least one preset performance inspection item from the original index data, and taking the second index data and the first index data together as inspection data.
In an embodiment, the database inspection device further includes a visualization module, which is configured to:
and mapping the original index data according to the data generation time aiming at the original index data corresponding to each performance inspection item to form a visual data chart, wherein the visual data chart is used for displaying a second change trend of the original index data.
In one embodiment, the database inspection device further includes an alarm management module, which includes:
the threshold value obtaining unit is used for obtaining a second data alarm threshold value corresponding to each performance inspection item;
and the alarm unit is used for responding to the original index data corresponding to each performance inspection item, determining that the original index data exceeds the corresponding second data alarm threshold value, and performing alarm management on the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold value.
In an embodiment, the alarm unit is specifically configured to:
determining the alarm level of the original index data and marking the alarm information corresponding to the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold; and alarming according to the alarm reminding mode matched with the alarm level.
In one embodiment, the basic index data includes: one or more of central processor utilization, memory utilization, master-slave delay thresholds, and network utilization; the service index data includes: one or more of a query rate per second, a number of transactions per second, and a number of inputs and outputs.
In one embodiment, the service indicator data includes a structured query language record,
the database inspection device further comprises a structured query language record inspection module, which is used for:
analyzing the structured query language record to obtain a structured query language template and the execution time of the structured query language template; and marking the alarm information corresponding to the structured query language in response to the fact that the execution time exceeds the preset time threshold.
In an embodiment, the database inspection device further includes an alarm convergence module, which is configured to:
Determining a time limit for releasing the alarm information; the alarm convergence function is configured to prohibit re-tagging of alarm information for a time period.
The device provided by the embodiment has the same implementation principle and technical effect as the method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the method embodiments without reference to the device embodiments.
An exemplary embodiment of the present disclosure also provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program, when executed by the at least one processor, is for causing the electronic device to perform a method according to an embodiment of the disclosure.
The exemplary embodiments of the present disclosure also provide a computer program product comprising a computer program, wherein the computer program, when executed by a processor of a computer, is adapted to cause the computer to perform a method according to an embodiment of the present disclosure.
Referring to fig. 4, a block diagram of a structure of an electronic device 400, which may be a server or a client of the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Electronic device is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 4, the electronic device 400 includes a computing unit 401 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 402 or a computer program loaded from a storage unit 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
A number of components in the electronic device 400 are connected to the I/O interface 405, including: an input unit 406, an output unit 407, a storage unit 408, and a communication unit 409. The input unit 406 may be any type of device capable of inputting information to the electronic device 400, and the input unit 406 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. Output unit 407 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 404 may include, but is not limited to, a magnetic disk, an optical disk. The communication unit 409 allows the electronic device 400 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth (TM) devices, WiFi devices, WiMax devices, cellular communication devices, and/or the like.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
The foregoing are merely exemplary embodiments of the present disclosure, which enable those skilled in the art to understand or practice the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (12)
1. A database inspection method is characterized by comprising the following steps:
pulling raw index data from a data source, wherein the raw index data comprises: base index data related to the instances and business index data related to the database;
acquiring a preconfigured automatic inspection parameter, wherein the automatic inspection parameter comprises: polling period, performance polling item and data analysis parameter;
Acquiring polling data from the original index data according to the polling period, wherein the polling data comprises first index data corresponding to each performance polling item;
and analyzing the routing inspection data according to the data analysis parameters.
2. The method of claim 1, wherein the data analysis parameters comprise: comparing the analysis parameters, the comparison period of the comparison analysis parameters and a first data alarm threshold;
the analyzing the routing inspection data according to the data analysis parameters comprises:
analyzing the first index data corresponding to each performance inspection item according to the comparative analysis parameters and the comparative period thereof to obtain a first change trend of each first index data;
determining the trend type and the variation amplitude of the first variation trend according to the first data alarm threshold;
determining the risk level of each first index datum according to a preset amplitude range and the trend type and the variation amplitude of the first variation trend, wherein the amplitude range and the risk level have a corresponding relation;
and determining the health degree of the inspection data in the current inspection period according to the risk level of each first index data.
3. The method of claim 1, wherein the automatic routing inspection parameters further comprise: at the critical point in time, the time of day,
the method further comprises the following steps:
and at the key time point, acquiring second index data corresponding to at least one preset performance inspection item from the original index data, and taking the second index data and the first index data together as the inspection data.
4. The method of claim 1, further comprising:
and mapping the original index data according to data generation time aiming at the original index data corresponding to each performance inspection item to form a visual data chart, wherein the visual data chart is used for displaying a second change trend of the original index data.
5. The method of claim 1, further comprising:
acquiring a second data alarm threshold corresponding to each performance inspection item;
and aiming at the original index data corresponding to each performance inspection item, responding to the fact that the original index data exceeds the corresponding second data alarm threshold value, and carrying out alarm management on the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold value.
6. The method of claim 5, further comprising:
determining the alarm level of the original index data and marking the alarm information corresponding to the original index data according to the degree that the original index data exceeds the corresponding second data alarm threshold;
and alarming according to the alarm reminding mode matched with the alarm level.
7. The method of claim 1, wherein the base metric data comprises: one or more of central processor utilization, memory utilization, master-slave delay thresholds, and network utilization;
the service index data comprises: one or more of a query rate per second, a number of transactions per second, and a number of inputs and outputs.
8. The method of claim 1, wherein the business metric data comprises a structured query language record,
the method further comprises the following steps:
analyzing the structured query language record to obtain a structured query language template and the execution time of the structured query language template;
and marking the alarm information corresponding to the structured query language in response to the fact that the execution time exceeds a preset time threshold value.
9. The method according to claim 6 or 8, characterized in that the method further comprises:
determining a time limit for releasing the alarm information;
the alarm convergence function is configured to prohibit the alarm information from being marked again during the time period.
10. The utility model provides a database inspection device which characterized in that includes:
the data pulling module is used for pulling original index data from a data source, wherein the original index data comprises: base index data related to the instances and business index data related to the database;
the parameter acquisition module is used for acquiring preconfigured automatic inspection parameters, wherein the automatic inspection parameters comprise: polling period, performance polling item and data analysis parameter;
the inspection data acquisition module is used for acquiring inspection data from the original index data according to the inspection period, wherein the inspection data comprises first index data corresponding to each performance inspection item;
and the data analysis module is used for analyzing the routing inspection data according to the data analysis parameters.
11. An electronic device, characterized in that the electronic device comprises:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
Wherein the program comprises instructions which, when executed by the processor, cause the processor to carry out the method according to any one of claims 1-9.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-9.
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