Distributed database management method, device, equipment and medium

Abstract

The present disclosure provides a method for managing a distributed database, which can be applied to the fields of information security and big data technology, including: determining abnormal indicators in current monitoring data in a distributed database; troubleshooting root cause indicator information corresponding to the abnormal indicators; and performing optimization operations on the abnormal indicators based on the root cause indicator information to achieve management of the distributed database. Therefore, compared with the situation in which a large amount of human operation and maintenance is relied upon in the prior art, the management autonomy of the distributed database is further achieved, the degree of automation and intelligence is higher, the manpower and time costs of cluster operation and maintenance of the distributed database are reduced, and the operation and maintenance efficiency is improved. In addition, the present disclosure also provides a management device, an electronic device, and a computer-readable storage medium for a distributed database.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a distributed database management method, device, electronic device and computer-readable storage medium. Background Art

[0002] As the amount of business data continues to grow, single-machine databases are increasingly unable to meet current needs due to the limitations of single-machine configurations, so distributed databases (DDB) are widely used. Distributed database systems usually use smaller computer systems, each computer can be stored in a separate place, each computer may have a complete copy or a partial copy of the database management system (DBMS), and have its own local database. Many computers located in different locations are interconnected through the network to form a complete, global, logically centralized, and physically distributed large database to support. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] In order to solve at least one of the technical problems existing in the distributed database in the prior art, the present disclosure provides a distributed database management method, a distributed database management device, an electronic device and a computer-readable storage medium.

[0005] (II) Technical solution

[0006] One aspect of the present disclosure provides a method for managing a distributed database, which includes: determining abnormal indicators in current monitoring data in the distributed database; checking root cause indicator information corresponding to the abnormal indicators; and performing optimization operations on the abnormal indicators according to the root cause indicator information to achieve management of the distributed database.

[0007] According to an embodiment of the present disclosure, before determining the abnormal index in the current monitoring data in the distributed database, the method further includes: querying the current monitoring data in the distributed database in response to a data retrieval instruction.

[0008] According to an embodiment of the present disclosure, before determining abnormal indicators in the current monitoring data in the distributed database, it also includes: obtaining the original monitoring data in the distributed database, and obtaining the baseband by performing big data training on the original monitoring data, wherein the baseband is the area where each monitoring indicator in the current monitoring data is located under normal circumstances.

[0009] According to an embodiment of the present disclosure, determining abnormal indicators in current monitoring data in a distributed database includes: judging the correspondence between each indicator in the current monitoring data and the baseband; and determining abnormal indicators in the current monitoring data based on the correspondence.

[0010] According to an embodiment of the present disclosure, in checking the root cause indicator information corresponding to the abnormal indicator, it includes: matching the abnormal indicator with a preset fault troubleshooting indicator group; and checking the root cause indicator information corresponding to the abnormal indicator based on the matching result and the root cause indicator mapping relationship generated by the matching.

[0011] According to an embodiment of the present disclosure, in checking the root cause indicator information corresponding to the abnormal indicator based on the matching result and the root cause indicator mapping relationship generated by the matching, it includes: when the matching result is that the abnormal indicator is completely matched with at least one indicator group in the fault troubleshooting indicator group, determining the impact value of the abnormal indicator; according to the root cause indicator mapping relationship, checking the root cause indicator information corresponding to the impact value.

[0012] According to an embodiment of the present disclosure, performing optimization operations on abnormal indicators according to root cause indicator information includes: generating corresponding optimization operation instructions according to the root cause indicator information and preset abnormal optimization corresponding rules; and executing the optimization operation instructions.

[0013] According to an embodiment of the present disclosure, the method further includes: determining feedback data corresponding to the optimization operation; and performing self-operation and maintenance operations for abnormal indicators based on the feedback data.

[0014] Another aspect of the present disclosure provides a management device for a distributed database, which includes an indicator determination module, a root cause investigation module, and an optimization execution module. The indicator determination module is used to determine abnormal indicators in current monitoring data in the distributed database; the root cause investigation module is used to investigate root cause indicator information corresponding to the abnormal indicators; and the optimization execution module is used to perform optimization operations on the abnormal indicators according to the root cause indicator information to achieve management of the distributed database.

[0015] Another aspect of the present disclosure provides an electronic device, which includes one or more processors and a memory; the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement the above-mentioned method.

[0016] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the instructions are used to implement the above method when executed.

[0017] (III) Beneficial effects

[0018] The present disclosure provides a method for managing a distributed database, which includes: determining abnormal indicators in current monitoring data in the distributed database; checking the root cause indicator information corresponding to the abnormal indicators; and performing optimization operations on the abnormal indicators according to the root cause indicator information to achieve management of the distributed database. Therefore, compared with the situation in which a large amount of human operation and maintenance is relied upon in the prior art, the management autonomy of the distributed database is further achieved, the degree of automation and intelligence is higher, the manpower and time costs of cluster operation and maintenance of the distributed database are reduced, and the operation and maintenance efficiency is improved. In addition, the present disclosure also provides a management device, an electronic device, and a computer-readable storage medium for a distributed database. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] For a more complete understanding of the present disclosure and its advantages, reference will now be made to the following description taken in conjunction with the accompanying drawings, in which:

[0020] Figure 1 An exemplary system architecture of a distributed database cluster according to an embodiment of the present disclosure is schematically shown;

[0021] Figure 2 An exemplary system architecture to which the distributed database management method according to an embodiment of the present disclosure can be applied is schematically shown;

[0022] Figure 3 A flowchart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0023] Figure 4 Another exemplary system architecture to which the distributed database management method according to an embodiment of the present disclosure can be applied is schematically shown;

[0024] Figure 5 Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0025] Figure 6 Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0026] Figure 7 Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0027] Figure 8 Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0028] Fig. 9 Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0029] Fig.10Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0030] Fig.11 Another flow chart schematically illustrates a method for managing a distributed database according to an embodiment of the present disclosure;

[0031] Fig.12 A block diagram schematically shows a distributed database management device according to an embodiment of the present disclosure; and

[0032] Fig.13 A block diagram of an electronic device according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0033] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0034] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "include", "comprising", etc. used herein indicate the existence of the above-mentioned features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0035] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0036] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0037] Some block diagrams and / or flow charts are shown in the accompanying drawings. It should be understood that some boxes or combinations thereof in the block diagrams and / or flow charts can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that these instructions can create a device for implementing the functions / operations described in these block diagrams and / or flow charts when executed by the processor. The technology of the present disclosure can be implemented in the form of hardware and / or software (including firmware, microcode, etc.). In addition, the technology of the present disclosure can take the form of a computer program product on a computer-readable storage medium storing instructions, which can be used by an instruction execution system or used in conjunction with an instruction execution system.

[0038] Figure 1 An exemplary system architecture of a distributed database cluster according to an embodiment of the present disclosure is schematically shown.

[0039] like Figure 1 As shown, the distributed database 100 refers to a database with multiple copies working simultaneously and following the distributed consistency protocol, wherein each distributed database 100 includes at least three servers 1-3, and each server is generally divided into three main modules: computing module, management module, and storage module, such as computing module 1, management module 1, and storage module 1 included in server 1; similarly, computing module 2, management module 2, and storage module 2 included in server 2, and computing module 3, management module 3, and storage module 3 included in server 3. Among them, computing modules 1-3 are stateless nodes, responsible for receiving SQL requests from the application end, processing SQL-related logic, and interacting with corresponding storage modules 1-3 to obtain data, and finally returning results to the application terminal. Management modules 1-3 are stateful nodes, responsible for storing metadata and managing the information of the entire cluster. Storage modules 1-3 are also stateful nodes, responsible for storing data of the entire database cluster. The so-called stateless node refers to a node that does not store critical data and is ready to use. On the contrary, a stateful node refers to a node that stores critical data and needs to be synchronized and pulled for normal service when restarted.

[0040] As the scale of distributed database clusters expands, more and more problems arise in the actual operation and maintenance process of distributed databases, and most of these problems in existing technologies can only be solved by manpower. In order to solve these problems more efficiently, the manpower and time costs consumed by the operation and maintenance of distributed databases will also gradually increase. Therefore, how to further improve the autonomy of distributed databases and reduce the burden of operation and maintenance has become a technical problem that urgently needs to be solved.

[0041] In order to solve at least one of the technical problems existing in the distributed database in the prior art, such as the situation that the autonomy of the current distributed database cannot match the increasing scale of its cluster, resulting in increasing operation and maintenance costs and decreasing operation and maintenance efficiency of the distributed database, the present disclosure provides a distributed database management method, a distributed database management device, an electronic device and a computer-readable storage medium.

[0042] It should be noted that the distributed database management method and device provided by the present disclosure can be applied to the fields of information security technology, big data technology and financial technology, and can also be applied to any technical field other than the above-mentioned technical fields. The application field of the distributed database management method and device provided by the present disclosure is not specifically limited.

[0043] Figure 2 An exemplary system architecture to which a distributed database management method according to an embodiment of the present disclosure can be applied is schematically shown.

[0044] It should be noted that Figure 2 What is shown is merely an application example to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the distributed database management method of the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0045] like Figure 2As shown, the system architecture 200 according to this embodiment may include a data request system 210, and a server system 220 that establishes data communication with the data request system 210, wherein the server system includes servers M, 221, 222, 223, 224, and 225 that establish data transmission channels with the data request system 210, wherein server M is a primary access server (i.e., a main server) that can obtain instruction information from users (such as operation and maintenance personnel of the server system). Servers 221, 222, 223, 224, and 225 are secondary access servers (i.e., branch servers), and the data request system 110 and servers M, 221, 222, 223, 224, and 225 can be implemented based on an internal cloud network server C. Alternatively, when the main server M among the servers M, 221, 222, 223, 224 and 225 is a network server, that is, relative to the intranet of other terminal devices 211, 212, 213, 214 and 215, the main server M of the server system 220 can be located in an external network. At this time, the cloud network server C is used here as a medium for providing a communication link between other terminal devices 211, 212, 213, 214 and 215. The data transmission channel between the server system 220 and multiple terminal devices can be specifically implemented through various communication connection types, such as wired, wireless communication links or optical fiber cables, etc. Among them, the cloud network server C can be a web server to provide a graphical display and input interface to the user.

[0046] It should be noted that, according to the embodiments of the present disclosure, the servers 221, 222, 223, 224 and 225 can be interconnected without encryption and applied to management services of large-scale distributed databases that can ensure information security.

[0047] The user can use the terminal devices 211, 212, 213, 214 and 215 to interact with the server system 120 to receive or send messages, etc., to achieve the management of the distributed database, specifically involving the access to the database in the main server M in the server system. For example, the terminal device 211 sends the access request content such as business data to the terminal device 212. After receiving the data request of the terminal device 211, the server system 220 will forward the corresponding business data and encrypt the business data under specific needs, so that the business data that finally reaches the terminal device 211 is secure. Various communication client applications can be installed on the terminal devices 211, 212, 213, 214 and 215, such as management applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0048] The terminal devices 211 , 212 , 213 , 214 and 215 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and various application servers.

[0049] The server system 220 may include various types of firewalls that provide various services, such as a filtering firewall (only an example) that provides support for websites browsed by users using terminal devices 211, 212, 213, 214, and 215. The filtering firewall may analyze and process received data such as user requests, and analyze based on the address of the data source and the flag features such as the protocol type to determine whether the request can pass, thereby filtering or blocking unsafe factors.

[0050] It should be noted that the distributed database management method provided in the embodiment of the present disclosure can generally be executed by the server system 220. Accordingly, the distributed database management device provided in the embodiment of the present disclosure can generally be set in the server system 220. The distributed database management method provided in the embodiment of the present disclosure can also be executed by other server systems that are different from the server system 120 and can communicate with the terminal devices 211, 212, 213, 214, 215 and / or the server system 220. Accordingly, the distributed database management device provided in the embodiment of the present disclosure can also be set in other server systems that are different from the server system 220 and can communicate with the terminal devices 211, 212, 213, 214, 215 and / or the server system 220.

[0051] It should be understood that Figure 2 The number of terminal devices and servers in the embodiment is only for illustration. Any number of terminal devices and servers may be provided according to implementation requirements.

[0052] The following combination Figure 3-Figure 13 , the distributed database management method, distributed database management device, electronic device and computer-readable storage medium provided by the present disclosure are further described in detail.

[0053] Figure 3 The flowchart of the distributed database management method according to the embodiment of the present disclosure is schematically shown.

[0054] One aspect of the present disclosure provides a distributed database management method, which includes steps S301-S303.

[0055] In step S301, abnormal indicators in current monitoring data in the distributed database are determined;

[0056] In step S302, root cause indicator information corresponding to the abnormal indicator is checked; and

[0057] In step S303, an optimization operation is performed on the abnormal indicator according to the root cause indicator information to achieve management of the distributed database.

[0058] Figure 4 Another exemplary system architecture to which the distributed database management method according to an embodiment of the present disclosure can be applied is schematically shown.

[0059] like Figure 4 As shown, the self-sensing unit 410 can realize the discovery and location of anomalies in the current monitoring data, and can mainly include two components: a monitoring subunit 411 and a troubleshooting subunit 412.

[0060] The monitoring subunit 411 can be used to obtain the current monitoring data in the distributed database, and analyze and process the current monitoring data to determine the abnormal indicator data in the current monitoring data. The current monitoring data is the operation log data generated by the current operation status of each server in the distributed database, such as the current operation log data of different indicators such as the CPU and memory of the corresponding server, wherein the current monitoring data can be stored in a data storage device or storage module in the distributed database.

[0061] When a log data item in the aforementioned current monitoring data is abnormal, the indicator corresponding to the log data item is abnormal. The indicator abnormality usually directly or indirectly affects the program associated with the indicator to varying degrees within a certain time range, thereby easily making the data storage or processing functions of the entire distributed database unable to operate normally, resulting in an operation failure. Therefore, the monitoring subunit 411 can confirm and analyze the specific log data in the entire current monitoring data item by item, so that the abnormal indicators with abnormal operating status can be screened out.

[0062] The troubleshooting subunit 412 can perform database problem troubleshooting operations on the abnormal indicators determined above. For abnormal indicators, each abnormality of an indicator has a root cause that causes it. Through the preset indicator abnormality data and root cause indicator information, the root cause indicator information of the abnormal indicators can be checked and determined one by one according to the indicator abnormality data, so as to obtain the root cause indicator information corresponding to the above abnormal indicators, and the root cause indicator information can be understood as the data formed by the root cause of the abnormality corresponding to the above abnormal indicators. Therefore, compared with the method of directly fixing the optimization operation according to the indicator, the root cause indicator information of the abnormality can be more accurately checked and located through the abnormal indicators at the first time, thereby improving the confirmation efficiency and accuracy of the optimization operation, improving the operating efficiency and accuracy of the self-perception-self-optimization, and making the self-management of the distributed database cluster more efficient and accurate.

[0063] Furthermore, the self-optimization unit 420 can be used to automatically optimize the corresponding faults or problems through the optimization operation corresponding to the root cause indicator information for the abnormal indicators, so that the distributed database of the embodiment of the present disclosure can optimize the operation problems monitored and checked by the self-sensing unit 410, so that the abnormal indicators can be processed in time, that is, the root cause indicators are optimized. Therefore, after the abnormal indicators are optimized by the self-optimization unit 420, effective management of the distributed database is achieved.

[0064] Therefore, compared with the existing technology that relies heavily on manual operation and maintenance, the management autonomy of distributed databases is further realized, with a higher degree of automation and intelligence, which reduces the manpower and time costs of cluster operation and maintenance of distributed databases and improves operation and maintenance efficiency.

[0065] Figure 5 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0066] like Figure 5 As shown, according to an embodiment of the present disclosure, before determining abnormal indicators in current monitoring data in a distributed database in step S301, step S501 is also included.

[0067] In step S501, in response to a data retrieval instruction, current monitoring data in a distributed database is queried.

[0068] The data retrieval instruction is a request instruction for retrieving monitoring data issued by a user (such as the management or operation and maintenance personnel of a distributed database) through a terminal device, or a request instruction for preset monitoring data sent by the system to the distributed database within a fixed period according to a preset instruction retrieval rule. Monitoring data is usually generated and stored in a storage module or a corresponding storage server in a distributed database in real time. Specifically, different log data can be grouped according to their generation time to form current monitoring data. According to the request instruction responded to by the data retrieval instruction, the corresponding query operation of the current monitoring data can be executed to obtain the current monitoring data.

[0069] In this way, the current monitoring data can be acquired purposefully, or the current monitoring data can be acquired automatically and regularly, so that the management method of the distributed database of the embodiment of the present disclosure is more automated and intelligent.

[0070] Figure 6 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0071] like Figure 6As shown, according to an embodiment of the present disclosure, before determining abnormal indicators in current monitoring data in a distributed database in step S301, steps S601 and S602 are also included.

[0072] In step S601, the original monitoring data in the distributed database is obtained.

[0073] In step S602, a baseband is obtained by performing big data training on the original monitoring data, wherein the baseband is the area where each monitoring indicator in the current monitoring data is located under normal circumstances.

[0074] Before determining the abnormal indicators, it is first necessary to obtain the basis for judging the abnormal indicators.

[0075] In addition to the current monitoring data, the storage server or storage module corresponding to the distributed database stores other historical monitoring data generated during the operation of the distributed database, and the historical monitoring data constitutes the original monitoring data of the distributed database. By querying and calling the original monitoring data, all the original monitoring data can be obtained.

[0076] Among them, performing a big data training operation on the original monitoring data can obtain the normal operating value range of each indicator in the normal operating state, that is, a value area, which constitutes the "baseband" mentioned in the above step S602. Therefore, by performing big data training on a large amount of original monitoring data, the area where each monitoring indicator should be normally located is obtained, which is called the "baseband", and the baseband is used as the basis for judging the abnormality of the indicator in the embodiment of the present disclosure. Among them, if a certain monitoring data exceeds this baseband, the indicator corresponding to the monitoring data is abnormal, which can be used to determine the abnormal indicator.

[0077] Therefore, by constructing a judgment standard for abnormal indicators through the baseband, rapid judgment of indicator abnormalities can be achieved.

[0078] Figure 7 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0079] like Figure 7 As shown, according to an embodiment of the present disclosure, in step S301, determining abnormal indicators in current monitoring data in a distributed database includes steps S701 and S702.

[0080] In step S701, the corresponding relationship between each indicator in the current monitoring data and the baseband is determined;

[0081] In step S702, the abnormal indicators in the current monitoring data are determined according to the corresponding relationship.

[0082] The monitoring value of each indicator of the current monitoring data is compared with the standard value of the baseband data to form a corresponding relationship between the indicator monitoring value and the standard value of the baseband data.

[0083] Through the above correspondence, if the monitoring value of the corresponding indicator exceeds the numerical range defined by the standard value (i.e., the normal value range), an alarm can be generated, constituting a problem abnormality, and determining the monitoring indicator corresponding to the abnormal monitoring value. On the contrary, if the monitoring value does not exceed the numerical range defined by the standard value, it does not constitute a problem abnormality.

[0084] Based on the corresponding relationship of the above abnormal judgment, the determination data of the abnormal indicators in the current monitoring data can be formed.

[0085] Figure 8 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0086] like Figure 8 As shown, according to an embodiment of the present disclosure, in step S302, root cause indicator information corresponding to the abnormal indicator is checked, including steps S801 and S802.

[0087] In step S801, the abnormality index is matched with a preset troubleshooting index group;

[0088] In step S802, root cause indicator information corresponding to the abnormal indicator is checked according to the matching result and the root cause indicator mapping relationship generated by the matching.

[0089] As for the abnormal indicators obtained, some indicators will have a direct impact on the overall operation status of the distributed database, which may easily cause the operation failure of the distributed database and affect the normal operation function; some indicators will not affect the overall operation status of your distributed database, but only affect some non-core operation modules such as auxiliary modules; some indicators will not affect the core operation status of the distributed database within a certain time range, but may affect the normal operation status of the distributed database beyond a certain time. Therefore, different abnormal indicators have different impacts on the operation status of the distributed database. The greater the impact, the greater the impact value of the abnormal indicator on the entire distributed database, and the more critical the role of the indicator in the distributed database. On the contrary, the smaller the impact value.

[0090] The troubleshooting indicator group is the matching control data set for all key or important abnormal indicators. If the indicators involved in the abnormal indicator match the troubleshooting indicator group, the abnormal indicator is determined to be a key indicator, and the optimization operation needs to be performed as soon as possible, in order to solve the system problem corresponding to the abnormal indicator as soon as possible. If the abnormal indicator is determined to be a non-critical indicator, it can be temporarily shelved, or it can be processed by other self-feedback operations. Therefore, the troubleshooting indicator group actually provides a basis for judging the abnormalities of the core indicators of the distributed database, so that the method of the embodiment of the present disclosure can determine the abnormal indicators that affect the core operating functions as soon as possible, and obtain the corresponding abnormal indicator optimization configuration accordingly, in order to better and more accurately solve the operating failure.

[0091] When the determined abnormal indicator can match the fault troubleshooting indicator group (i.e., matching result), it is determined that the abnormal indicator involves the normal execution of the key operating state, and a fault optimization operation is required. Prior to this, it is further necessary to use the abnormal indicator and the preset root cause indicator mapping relationship to perform a root cause troubleshooting operation on the abnormal indicator, and finally determine the root cause indicator information.

[0092] The preset root cause indicator mapping relationship involves mapping data between the root cause of the abnormality of the key indicator and the corresponding key indicator, that is, based on the key indicator and the abnormal data that appears, the corresponding abnormal root cause, that is, the root cause indicator information, can be determined.

[0093] Therefore, the method of the embodiment of the present disclosure can further automatically determine the root cause of the anomaly based on the anomaly indicator, thereby providing a judgment basis for the next step of optimizing the operation for the anomaly and completing the location of the root cause of the anomaly.

[0094] Fig. 9 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0095] like Fig. 9 As shown, according to an embodiment of the present disclosure, in step S802, according to the matching result generated by the matching and the root cause indicator mapping relationship, the root cause indicator information corresponding to the abnormal indicator is checked, including steps S901 and S902.

[0096] In step S901, when the matching result is that the abnormal indicator completely matches at least one indicator group in the troubleshooting indicator group, the impact value of the abnormal indicator is determined;

[0097] In step S902, root cause indicator information corresponding to the impact value is checked according to the root cause indicator mapping relationship.

[0098] For the above-mentioned troubleshooting indicator group, it can include multiple sub-indicator groups, each of which includes multiple key core indicators. Among them, each sub-indicator group can involve at least one key operating function of the distributed database, which can involve multiple key operating indicators. Among them, the operating impact involved in the key operating function in the entire distributed database is also different. Therefore, according to the key operating function, the different sub-indicator groups involving the key operating indicators can be divided into the degree of influence, which can be specifically reflected in the impact value, thereby forming a corresponding relationship between the impact value and the operating indicator. Among them, the larger the impact value, the higher the impact level, the more important the sub-indicator group corresponding to the key operating indicator, and the greater the impact of the abnormal situation on the normal operation of the entire distributed database. Therefore, when all indicators in the abnormal indicator completely match and correspond to the key operating indicators in at least one indicator group in the troubleshooting indicator group, the key operating function corresponding to the abnormal indicator is determined, and the size of its impact value is determined at the same time.

[0099] The preset root cause indicator mapping relationship can be used to confirm the root cause of the abnormality of the abnormal indicator. Specifically, the preset root cause indicator mapping relationship is actually the mapping relationship between the root cause of the abnormality of the key indicator and the impact value of the corresponding key indicator. Therefore, according to the root cause indicator mapping relationship and the corresponding impact value, the root cause indicator information directly corresponding to the impact value can be directly determined, thereby confirming the root cause of the abnormality of the key indicator.

[0100] Therefore, based on the above-mentioned scheme of the embodiment of the present disclosure, the root cause of the failure of the key indicator can be directly determined, so that the distributed database can locate the key problem indicator more accurately in the first time, and perform rapid optimization processing and other response operations on the indicator abnormalities or operations that affect the core operating functions, so as to prevent the key functions of the distributed database from being affected, so as to avoid the abnormal expansion of the server cluster, thereby effectively ensuring the normal operation of the entire distributed database, which is fast, accurate, and effective, with a higher degree of automation and more efficient management.

[0101] Fig.10 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0102] like Fig.10 As shown, according to an embodiment of the present disclosure, in step S303, performing optimization operations on abnormal indicators according to root cause indicator information includes steps S1001 and S1002.

[0103] In step S1001, a corresponding optimization operation instruction is generated according to the root cause indicator information and the preset abnormal optimization corresponding rules;

[0104] In step S1002, the optimization operation instruction is executed.

[0105] When an abnormality occurs in each indicator, the root cause of each abnormality (i.e., root cause indicator information) in the various abnormalities of the indicator requires a corresponding abnormal solution, i.e., an optimization operation plan, to optimize the abnormality or failure of the indicator. Among them, the preset abnormal optimization corresponding rules can be used to determine the mapping relationship between the root cause indicator information of the corresponding abnormal indicator and the specific optimization operation. Among them, the optimization operation needs to be implemented by executing the corresponding operation execution instruction. Therefore, the preset abnormal optimization corresponding rules can specifically be the mapping relationship between the optimization operation instruction and the root cause indicator information.

[0106] After the root cause indicator information of the corresponding abnormal indicator is obtained, the optimization operation instruction can be determined according to the preset abnormal optimization corresponding rule. The optimization operation instruction is a request instruction data for the execution of an optimization operation. After the optimization operation instruction is executed, the above-mentioned optimization operation for the abnormal indicator can be directly implemented. For example, if the root cause indicator information of the abnormal indicator involves the relevant problem of inefficient SQL, the optimization operation instruction determined by the preset abnormal optimization corresponding rule can be to call the SQL optimizer, and the SQL optimizer performs optimization on the problem of inefficient SQL. Specifically, the root cause indicator information of the inefficient SQL related problem is that the database has a full table scan SQL with many large tables. Then, according to the root cause indicator information, the corresponding SQL optimizer can be called, and the SQL optimizer can be used to detect the execution plan of this statement, and the optimization plan of adjusting the access index and establishing a new index can be targeted, and it can be optimized to a statement with fewer scan lines and higher efficiency, thereby completing the optimization of the abnormal SQL indicator.

[0107] Therefore, the method of the embodiment of the present disclosure can achieve self-perception and self-optimization of abnormal indicators, automatically complete the process of abnormal optimization, prevent the impact of abnormal indicators on the overall operating status from deepening or expanding, and require almost no human cost, which is efficient and low-cost.

[0108] Fig.11 Another flow chart of the distributed database management method according to an embodiment of the present disclosure is schematically shown.

[0109] like Fig.11 As shown, according to an embodiment of the present disclosure, the method further includes steps S1101 and S1102.

[0110] In step S1101, feedback data corresponding to the optimization operation is determined;

[0111] In step S1102, self-operation and maintenance operations are performed on abnormal indicators based on the feedback data.

[0112] like Figure 4 As shown, after the self-optimization unit 420 performs the optimization operation on the abnormal index, the self-operation and maintenance unit 430 can receive the generated corresponding optimization feedback data. The optimization feedback data can determine whether the abnormal index at the current moment is the same as the abnormal index at the optimization operation moment by comparing the monitoring data between the current moment and the optimization operation moment, and then determine whether the optimization operation of the self-optimization unit 420 is successful or not, thereby forming feedback data.

[0113] In the case where the feedback data indicates that the optimization operation failed (i.e., the self-optimization unit 420 cannot optimize the abnormal indicators to solve the abnormality or failure), the server cluster of the distributed database will be in a fault sudden state where the health state is affected or threatened, and the self-operation and maintenance unit 430 can perform self-operation and maintenance operations without manual intervention for the fault sudden state. Specifically, different self-operation and maintenance operations can be performed based on the root cause indicator information of different abnormal indicators, such as pulling up downtime nodes, limiting problematic SQL resources, killing problematic connection threads, etc.

[0114] Therefore, the above-mentioned distributed database management method of the embodiment of the present disclosure can perform autonomous maintenance of the database cluster through self-perception, self-optimization, and self-operation and maintenance, realize the basic autonomy of the cluster, reduce the burden on operation and maintenance personnel, and ensure the normal operation of the cluster.

[0115] Fig.12 A block diagram of a distributed database management device according to an embodiment of the present disclosure is schematically shown.

[0116] like Fig.12 As shown, another aspect of the present disclosure provides a management device 1200 for a distributed database, which includes an indicator determination module 1210, a root cause investigation module 1220, and an optimization execution module 1230. The indicator determination module 1210 is used to determine abnormal indicators in current monitoring data in the distributed database; the root cause investigation module 1220 is used to investigate the root cause indicator information corresponding to the abnormal indicator; and the optimization execution module 1230 is used to perform optimization operations on the abnormal indicator according to the root cause indicator information, so as to realize the management of the distributed database.

[0117] It should be noted that Fig.12 The embodiment of the distributed database management device 1200 shown is similar to the embodiment of the distributed database management method described above, and the technical effects achieved are also similar, which will not be repeated here.

[0118] Fig.13 The block diagram of the electronic device according to the embodiment of the present disclosure is schematically shown. Fig.13The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0119] Another aspect of the present disclosure provides an electronic device, including one or more processors and a memory; the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of the embodiment of the present disclosure.

[0120] like Fig.13 As shown, the computer system 1300 according to the embodiment of the present disclosure includes a processor 1301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1302 or the program loaded from the storage part 1308 to the random access memory (RAM) 1303. The processor 1301 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 1301 may also include an onboard memory for caching purposes. The processor 1301 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0121] In RAM 1303, various programs and data required for the operation of system 1300 are stored. Processor 1301, ROM 1302 and RAM 1303 are connected to each other through bus 1304. Processor 1301 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1302 and / or RAM 1303. It should be noted that the program can also be stored in one or more memories other than ROM 1302 and RAM 1303. Processor 1301 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0122] According to an embodiment of the present disclosure, the system 1300 may further include an input / output (I / O) interface 1305, which is also connected to the bus 1304. The system 1300 may further include one or more of the following components connected to the I / O interface 1305: an input section 1306 including a keyboard, a mouse, etc.; an output section 1307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1308 including a hard disk, etc.; and a communication section 1309 including a network interface card such as a LAN card, a modem, etc. The communication section 1309 performs communication processing via a network such as the Internet. A drive 1310 is also connected to the I / O interface 1308 as needed. A removable medium 1311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1310 as needed, so that a computer program read therefrom is installed into the storage section 1308 as needed.

[0123] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1309, and / or installed from the removable medium 1311. When the computer program is executed by the processor 1301, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0124] According to an embodiment of the present disclosure, at least one of the indicator determination module 1210, the root cause investigation module 1220, and the optimization execution module 1230 may be implemented as a reference. Fig.13 The described computer program module, when executed by a processor, can implement the corresponding operations of the above described distributed database management method.

[0125] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method of the embodiment of the present disclosure when executed.

[0126] Specifically, the computer-readable storage medium may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system.

[0127] The computer-readable storage medium carries one or more programs. When the one or more programs are executed, the distributed database management method according to the embodiment of the present disclosure is implemented.

[0128] Alternatively, the computer-readable storage medium may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system.

[0129] The computer-readable storage medium carries one or more programs. When the one or more programs are executed, the distributed database management method according to the embodiment of the present disclosure is implemented.

[0130] Another aspect of the present disclosure provides a computer program, which includes computer executable instructions. When the instructions are executed, they are used to implement the distributed database management method of the embodiment of the present disclosure.

[0131] So far, the embodiments of the present disclosure have been described in detail with reference to the accompanying drawings.

[0132] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0133] It will be appreciated by those skilled in the art that, although the present disclosure has been shown and described with reference to specific exemplary embodiments of the present disclosure, it will be appreciated by those skilled in the art that, without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents, various changes in form and detail may be made to the present disclosure. Therefore, the scope of the present disclosure should not be limited to the above-described embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims.

[0134] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for managing a distributed database, wherein: include: Determining abnormal indicators in the current monitoring data in the distributed database; Checking the root cause indicator information corresponding to the abnormal indicator; as well as Performing optimization operations on the abnormal indicators according to the root cause indicator information to achieve management of the distributed database; The step of checking the root cause indicator information corresponding to the abnormal indicator includes: Matching the abnormal indicator with a preset troubleshooting indicator group; According to the matching result generated by the matching and the root cause indicator mapping relationship, the root cause indicator information corresponding to the abnormal indicator is checked; Wherein, the step of checking the root cause indicator information corresponding to the abnormal indicator according to the matching result and the root cause indicator mapping relationship generated by the matching includes: When the matching result is that the abnormal indicator completely matches at least one indicator group in the troubleshooting indicator group, determining the impact value of the abnormal indicator, wherein the troubleshooting indicator group includes matching control data set for key abnormal indicators; According to the root cause indicator mapping relationship, root cause indicator information corresponding to the impact value is checked.

2. The method according to claim 1, wherein: Before determining the abnormal index in the current monitoring data in the distributed database, the method further includes: In response to the data retrieval instruction, the current monitoring data in the distributed database is queried.

3. The method according to claim 1, wherein: Before determining the abnormal index in the current monitoring data in the distributed database, the method further includes: Obtaining the original monitoring data in the distributed database, The baseband is obtained by performing big data training on the original monitoring data, wherein the baseband is the area where each monitoring indicator in the current monitoring data is located under normal circumstances.

4. The method according to claim 3, wherein: The determining of abnormal indicators in the current monitoring data in the distributed database includes: Determine the corresponding relationship between each indicator in the current monitoring data and the baseband; According to the corresponding relationship, an abnormal indicator in the current monitoring data is determined.

5. The method according to claim 1, wherein: In performing the optimization operation on the abnormal indicator according to the root cause indicator information, the method includes: Generate corresponding optimization operation instructions according to the root cause indicator information and preset abnormal optimization corresponding rules; Execute the optimization operation instruction.

6. The method according to claim 5, wherein: Also includes: Determining feedback data corresponding to the optimization operation; According to the feedback data, self-operation and maintenance operations are performed on the abnormal indicators.

7. A distributed database management device, wherein: include: An indicator determination module, used to determine abnormal indicators in the current monitoring data in the distributed database; A root cause investigation module is used to investigate the root cause indicator information corresponding to the abnormal indicator; as well as An optimization execution module, used to perform optimization operations on the abnormal indicators according to the root cause indicator information to achieve management of the distributed database; Wherein, the root cause investigation module is used to: Matching the abnormal indicator with a preset troubleshooting indicator group; When the matching result is that the abnormal indicator completely matches at least one indicator group in the troubleshooting indicator group, determining the impact value of the abnormal indicator, wherein the troubleshooting indicator group includes matching control data set for key abnormal indicators; According to the root cause indicator mapping relationship, the root cause indicator information corresponding to the impact value is checked.

8. An electronic device, wherein: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing computer-executable instructions, wherein: When the instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 6.

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