CN112131068A - Data monitoring method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a data monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of big data. The data monitoring method comprises the following steps: acquiring data to be monitored of a target data cluster; calculating health degree data according to the data to be monitored, and storing the health degree data into a corresponding monitoring alarm table; based on the monitoring alarm table, drawing a health degree trend graph corresponding to the data to be monitored so as to visually display the health degree data corresponding to the target data cluster; and acquiring a monitoring alarm threshold value, and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph. The technical scheme of the embodiment of the invention not only can carry out three-dimensional and visual intelligent monitoring on the data cluster and provide the resource utilization rate of the data cluster, but also has strong expandability, can carry out personalized and diversified setting on the monitoring platform and improves the use experience of users.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a data monitoring method, a data monitoring device, electronic equipment and a computer-readable storage medium.
Background
With the rapid development of big data technology in recent years, big data technology is more and more popular, and the basic storage and security related to big data are more and more important.
At present, a basic storage and computation framework of big Data is a Hadoop (the Hadoop is a distributed system infrastructure developed by the Apache foundation), and a mainstream integrated monitoring Platform of a Hadoop cluster is an open-source big Data monitoring framework such as CDH (cloud's Distribution adding Apache Hadoop, a Hadoop distributed Data management Platform of the cloud company) and HDP (Data management Platform of the hotspot Data Platform). When the Hadoop cluster is monitored through the open-source monitoring platforms, the problems of various uncontrollable factors exist, for example, the monitoring platforms cannot be quickly positioned when finding problems; the monitoring provided by the open source framework can not meet the diversified and personalized requirements of a user using a Hadoop platform, the expandability is low, and the use experience of the user is reduced; and when the data volume of Hadoop storage is continuously increased, the open source monitoring platform can generate performance bottleneck, and the operation efficiency of the Hadoop cluster is influenced.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
Embodiments of the present invention provide a data monitoring method, a data monitoring apparatus, an electronic device, and a computer-readable storage medium, so as to overcome, at least to a certain extent, the problems that when a problem is found in an existing monitoring platform for monitoring a data cluster, the existing monitoring platform cannot be quickly located, a performance bottleneck occurs, diversified and personalized requirements of a user cannot be met, and the extensibility is low.
Additional features and advantages of the invention will be set forth in the detailed description which follows, or may be learned by practice of the invention.
According to a first aspect of the embodiments of the present invention, there is provided a data monitoring method, including: acquiring data to be monitored of a target data cluster; calculating health degree data according to the data to be monitored, and storing the health degree data into a corresponding monitoring alarm table; based on the monitoring alarm table, drawing a health degree trend graph corresponding to the data to be monitored so as to visually display the health degree data corresponding to the target data cluster; and acquiring a monitoring alarm threshold value, and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph.
In some exemplary embodiments of the present invention, based on the foregoing scheme, obtaining a monitoring alarm threshold, and performing monitoring alarm according to the monitoring alarm threshold and the health degree trend graph further includes: responding to monitoring alarm information of health degree data, and acquiring a plurality of historical health degree data related to the health degree data through the health degree trend graph; regulating and controlling a monitoring alarm threshold value of the health degree data according to the plurality of historical health degree data; and monitoring and alarming according to the regulated monitoring and alarming threshold value and the health degree trend graph.
In some example embodiments of the present invention, based on the foregoing scheme, the obtaining a monitoring alarm threshold, and performing monitoring alarm according to the monitoring alarm threshold and the health degree trend graph further includes: responding to alarm information of health degree data, and acquiring an input monitoring alarm threshold; and monitoring and alarming according to the input monitoring and alarming threshold value and the health degree trend graph.
In some example embodiments of the present invention, based on the foregoing solution, the data to be monitored includes monitoring basic data and a storage hierarchy, and the method further includes: acquiring monitoring basic data of a target data cluster in a preset mode; calculating first health degree data according to the monitoring basic data, and storing the first health degree data into a corresponding monitoring alarm table; calculating second health degree data corresponding to the storage hierarchy corresponding to the target data cluster, and storing the second health degree data into the corresponding monitoring alarm table; drawing the monitoring basic data and a health degree trend graph corresponding to the storage hierarchy based on the monitoring alarm table so as to visually display the first health degree data and the second health degree data corresponding to the target data cluster; and alarming according to the adjustable monitoring alarm threshold value and the health degree trend graph.
In some example embodiments of the present invention, based on the foregoing solution, the monitoring basic data at least includes task amount data, queue resource data, and storage resource data, and the obtaining the monitoring basic data of the target data cluster in a preset manner includes: calling a target interface to acquire the task amount data in a command mode; acquiring the queue resource data through a web crawler; and acquiring the storage resource data from the data warehouse model corresponding to the target data cluster.
In some example embodiments of the present invention, based on the foregoing solution, after obtaining the data to be monitored of the target data cluster, the method further includes: and storing the data to be monitored into a relational database with a designed table structure.
In some example embodiments of the present invention, based on the foregoing solution, the setting of the monitoring alarm table in the relational database, and the drawing of the health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table to visually display the health degree data corresponding to the target data cluster further includes: obtaining health data stored in the relational database; drawing a health degree trend graph corresponding to the data type according to the data type of the data to be monitored corresponding to the health degree data; and sending the health degree trend graphs of different data types to a front end for visual display.
According to a second aspect of the embodiments of the present invention, there is provided a data monitoring apparatus including: the data acquisition unit is used for acquiring data to be monitored of the target data cluster; the data calculation unit is used for calculating health degree data according to the data to be monitored and storing the health degree data into a corresponding monitoring alarm table; the data display unit is used for drawing a health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table so as to visually display the health degree data corresponding to the target data cluster; and the data monitoring alarm unit is used for acquiring a monitoring alarm threshold value and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing, the data monitoring alarm unit is configured to: responding to monitoring alarm information of health degree data, and acquiring a plurality of historical health degree data related to the health degree data through the health degree trend graph; regulating and controlling a monitoring alarm threshold value of the health degree data according to the plurality of historical health degree data; and monitoring and alarming according to the regulated monitoring and alarming threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing, the data monitoring alarm unit is configured to: responding to alarm information of health degree data, and acquiring an input monitoring alarm threshold; and monitoring and alarming according to the input monitoring and alarming threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing solution, the data monitoring apparatus further includes: the monitoring basic data acquisition unit is used for acquiring monitoring basic data of the target data cluster in a preset mode; the first health degree data calculation unit is used for calculating first health degree data according to the monitoring basic data and storing the first health degree data into a corresponding monitoring alarm table; the second health degree data calculation unit is used for calculating second health degree data corresponding to the storage hierarchy corresponding to the target data cluster and storing the second health degree data into the corresponding monitoring alarm table; the health degree data display unit is used for drawing the monitoring basic data and a health degree trend graph corresponding to the storage hierarchy based on the monitoring alarm table so as to visually display the first health degree data and the second health degree data corresponding to the target data cluster; and the monitoring alarm unit is used for alarming according to the adjustable monitoring alarm threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing, the monitoring-base-data obtaining unit is configured to: calling a target interface to acquire the task amount data in a command mode; acquiring the queue resource data through a web crawler; and acquiring the storage resource data from the data warehouse model corresponding to the target data cluster.
In an exemplary embodiment of the present invention, based on the foregoing, the data monitoring apparatus is configured to: and storing the data to be monitored into a relational database with a designed table structure.
In an exemplary embodiment of the present invention, based on the foregoing, the data display unit is configured to: obtaining health data stored in the relational database; drawing a health degree trend graph corresponding to the data type according to the data type of the data to be monitored corresponding to the health degree data; and sending the health degree trend graphs of different data types to a front end for visual display.
According to a third aspect of embodiments of the present invention, there is provided an electronic apparatus, including: a processor; and a memory having computer readable instructions stored thereon, the computer readable instructions when executed by the processor implementing any of the data monitoring methods described above.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a data monitoring method according to any one of the above.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
in the data monitoring method in the example embodiment of the invention, health degree data of a target data cluster is calculated according to data to be monitored of the target data cluster, and the health degree data is stored in a corresponding monitoring alarm table; drawing a health degree trend graph corresponding to the health degree data according to the monitoring alarm table and carrying out visual display; and monitoring and alarming according to the monitoring and alarming threshold value and the health degree trend graph. On one hand, a plurality of data to be monitored of the target data cluster are calculated and converted into health degree data, the health degree data are stored in a monitoring alarm table and drawn into a health degree trend graph for displaying, so that the monitoring of the target data cluster is more three-dimensional and visual, the health degree data are stored through the monitoring alarm table, and when the target data cluster has problems, the problem points can be quickly and conveniently located; on the other hand, monitoring alarm is carried out according to the monitoring alarm threshold value and the health degree trend graph, and a user can regulate and control the monitoring alarm threshold value according to the health degree trend graph so as to enable the target data cluster to reasonably distribute resources, improve the resource utilization rate of the target data cluster, meet the requirements of the user on individuation and diversification of the use monitoring platform, and improve the use experience of the user.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
FIG. 1 schematically illustrates a schematic diagram of a data monitoring method according to some embodiments of the invention;
FIG. 2 schematically illustrates a schematic diagram of health data of a target data cluster, according to some embodiments of the invention;
FIG. 3 schematically illustrates a schematic diagram of a partial effect graph with a health trend graph presented at the front end, in accordance with some embodiments of the present invention;
FIG. 4 is a schematic diagram that schematically illustrates an occupied memory to allocated memory ratio monitoring alarm and a post-monitoring call in a queue, in accordance with some embodiments of the present invention;
FIG. 5 schematically illustrates a schematic of health data calculation for a storage hierarchy according to some embodiments of the invention;
FIG. 6 schematically illustrates a schematic diagram of a monitoring structure of a target data cluster, in accordance with some embodiments of the present invention;
FIG. 7 schematically illustrates a schematic diagram of a data monitoring apparatus according to some embodiments of the invention;
FIG. 8 schematically illustrates a structural diagram of a computer system of an electronic device, in accordance with some embodiments of the present invention;
FIG. 9 schematically illustrates a schematic diagram of a computer-readable storage medium according to some embodiments of the invention.
In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations or operations have not been shown or described in detail to avoid obscuring aspects of the invention.
Furthermore, the drawings are merely schematic illustrations and are not necessarily drawn to scale. The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
In the present exemplary embodiment, a data monitoring method is first provided, which can be applied to a Hadoop cluster (bazaar). FIG. 1 schematically illustrates a schematic diagram of a data monitoring method according to some embodiments of the invention. Referring to fig. 1, the data monitoring method may include the steps of:
step S110, acquiring data to be monitored of a target data cluster;
step S120, calculating health degree data according to the data to be monitored, and storing the health degree data into a corresponding monitoring alarm table;
step S130, drawing a health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table so as to visually display the health degree data corresponding to the target data cluster;
step S140, acquiring a monitoring alarm threshold value, and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph.
According to the data monitoring method in the embodiment, on one hand, a plurality of data to be monitored of the target data cluster are calculated and converted into health degree data, the health degree data are stored in the monitoring alarm table and are drawn into the health degree trend graph to be displayed, so that the monitoring of the target data cluster is more three-dimensional and visual, the health degree data are stored through the monitoring alarm table, and when the target data cluster has problems, the problem points can be quickly and conveniently located; on the other hand, monitoring alarm is carried out according to the monitoring alarm threshold value and the health degree trend graph, and a user can regulate and control the monitoring alarm threshold value according to the health degree trend graph so as to enable the target data cluster to reasonably distribute resources, improve the resource utilization rate of the target data cluster, meet the requirements of the user on individuation and diversification of the use monitoring platform, and improve the use experience of the user.
Next, the data monitoring method in the present exemplary embodiment will be further explained.
In step S110, data to be monitored of the target data cluster is acquired.
In an example embodiment of the present invention, the target data cluster may refer to a data cluster that needs to perform data monitoring, for example, in the example embodiment, the target data cluster may be a Hadoop cluster, and of course, the target data cluster may also be a Kafka (Kafka is an open source stream processing platform developed by the Apache software foundation), which is not particularly limited in this example embodiment. The data to be monitored may refer to data that needs to be monitored and alarmed in the target data cluster, for example, the number of tasks to be processed in the message queue, the resource occupancy rate, the task timeout, and the like, which is not particularly limited in this exemplary embodiment.
Further, after the data to be monitored of the target data cluster is obtained, the system stores the data to be monitored into a relational database with a designed table structure. The relational database may refer to a database composed of a plurality of two-dimensional row-column tables capable of being connected to each other, for example, in the present exemplary embodiment, the relational database may be mySQL (which is a relational database that stores data in different tables), and of course, the present exemplary embodiment is not limited thereto. The developer can design a corresponding table structure in the relational database in advance according to requirements, and after the data to be monitored of the target data cluster is obtained, the data to be monitored is stored in the relational database with the designed table structure. The data to be monitored is stored in the table structure of the relational database, so that the data can be read more conveniently, and meanwhile, when the data are in problems, the data can be quickly inquired and positioned through the table structure, and the processing efficiency of the system is improved.
In step S120, health degree data is calculated according to the data to be monitored, and the health degree data is stored in the corresponding monitoring alarm table.
In an exemplary embodiment of the present invention, the health data may refer to data (or may refer to an index for performing a monitoring alarm on the data to be monitored) calculated according to the data to be monitored, and is used for characterizing a health degree of the data to be monitored (for example, the health data may refer to a ratio of occupied memory resources in a message queue to a total memory allocated to the message queue, and when the ratio is smaller than a threshold, the message queue is characterized to be healthy, and when the ratio is larger than a threshold, the message queue is characterized to be unhealthy. The monitoring alarm table may refer to a table structure which is previously constructed in a relational database by a developer and is used for storing health degree data corresponding to data to be monitored.
FIG. 2 schematically illustrates a schematic diagram of health data of a target data cluster, according to some embodiments of the invention.
Referring to fig. 2, the health data (which may also be referred to as a monitoring alarm indicator) 201 may include a ratio 202 of occupied memory in the queue to allocated memory in the queue, a CPU monitoring alarm 203 in the queue, a task source ratio 204, a task progress monitoring alarm 205, a task timeout monitoring alarm 206, and a number 207 of tasks to be processed in the queue. It is to be readily understood that the health data in the present disclosure and the schematic drawings are illustrative only, and the present exemplary embodiment is not limited thereto.
Specifically, the system acquires the health degree data stored in the relational database, draws a health degree trend graph corresponding to the data type according to the data type of the data to be monitored corresponding to the health degree data, and sends the health degree trend graphs of different data types to the front end for visual display. The data type may refer to a type corresponding to data to be monitored, for example, the data type may be a number of tasks corresponding to a message queue, a storage resource occupied by the message queue, a task timeout duration, and the like, which is not particularly limited in this example embodiment. The health degree trend graph is generated according to the health degree data corresponding to the data types of the different data to be monitored, the different data are displayed in a classified mode, a user can accurately and quickly search the data to be monitored, and the user experience is improved.
In step S130, based on the monitoring alarm table, a health degree trend graph corresponding to the data to be monitored is drawn to visually display the health degree data corresponding to the target data cluster.
In an example embodiment of the present invention, the health degree trend graph may refer to a data graph drawn according to health degree data corresponding to data to be monitored, and data changes and health states of the target data cluster are presented to a user in an intuitive manner. For example, the health degree trend graph may be a data line graph corresponding to the health degree data, the time and the data amount, and of course, the health degree trend graph may also be a bar graph or a pie graph, which is not particularly limited in this example embodiment. The system draws a health degree trend graph corresponding to the data to be monitored according to the health degree data stored in the monitoring alarm table, and sends the health degree trend graph to a front end (client) to be displayed to a user. The health degree data are drawn into the health degree trend graph to be presented to the user, so that the monitoring of the target data cluster by the user can be three-dimensional and visual, and the use experience of the user is improved.
FIG. 3 schematically illustrates a schematic diagram of a partial effect diagram with a health trend diagram presented at the front end, according to some embodiments of the invention.
Referring to fig. 3, a graph 301 may refer to a health degree trend graph corresponding to "average running time of completed tasks in a queue" of data to be monitored, a graph 302 may refer to a health degree trend graph corresponding to "usage of memory allocated in a queue" of data to be monitored, and a graph 303 may refer to a health degree trend graph corresponding to "usage of CPU in a queue" of data to be monitored, and the relationship between the usage of data in a target data cluster and time and an occupied amount can be visually displayed through the health degree trend graph, so that data monitoring is more three-dimensional, visual and accurate, and the usage experience of a user is improved.
In step S140, a monitoring alarm threshold is obtained, and a monitoring alarm is performed according to the monitoring alarm threshold and the health degree trend graph.
In an exemplary embodiment of the present invention, the monitoring alarm threshold may refer to a value that is automatically controlled or input by a user and is used to trigger an alarm for abnormal data, for example, an alarm is performed when a proportion of occupied memory resources in the message queue to a total memory allocated to the message queue exceeds 80%, or an alarm may be performed when a task amount to be processed in the message queue exceeds 10, although the monitoring alarm threshold may also be another value used to trigger an alarm for abnormal data, which is not particularly limited in this exemplary embodiment. A standard line is set in the health degree trend graph according to the obtained monitoring alarm threshold, and an alarm is given when the data in the health degree trend graph exceeds or is lower than the standard line (for example, the display color of the abnormal point data may be modified, or a message may be sent to remind, which is not specially limited in this example embodiment).
Specifically, the system responds to monitoring alarm information of health degree data, and obtains a plurality of historical health degree data related to the health degree data through a health degree trend graph; regulating and controlling a monitoring alarm threshold value of the health degree data according to a plurality of historical health degree data; and monitoring and alarming according to the regulated monitoring and alarming threshold value and the health degree trend graph. The monitoring alarm information may refer to notification information generated when health data at a certain time exceeds or falls below a monitoring alarm threshold. The plurality of historical health data may refer to other health data associated with a data type of data to be monitored corresponding to the health data at which an alarm occurs, for example, when a proportion of occupied memory resources in a message queue to a total memory allocated to the message queue exceeds a monitoring alarm threshold, the plurality of historical health data may refer to a proportion of occupied memory resources in other message queues to the total memory allocated to the message queue, which is only schematically illustrated here, and this is not limited in this example embodiment. When the system receives monitoring alarm information of health degree data, the system acquires a plurality of historical health degree data related to the health degree data, judges the health states corresponding to the plurality of historical health degree data, and adjusts the monitoring alarm threshold corresponding to the health degree data according to the health states of the plurality of historical health degree data. And the system continues to monitor and alarm according to the regulated and controlled health degree data and the health degree trend graph.
Optionally, the system responds to an alarm message of health degree data to obtain an input monitoring alarm threshold; and monitoring and alarming according to the input monitoring and alarming threshold value and the health degree trend graph. The input monitoring alarm threshold value can be that after a user checks or receives monitoring alarm information, the monitoring alarm threshold value is input through a preset input port, and the system adjusts the original monitoring alarm threshold value according to the monitoring alarm threshold value input by the user. The original monitoring alarm threshold value is adjusted through the monitoring alarm threshold value input by the user, the user can independently regulate and control the monitoring alarm threshold value to enable the target data cluster to reasonably distribute resources, the resource utilization rate of the target data cluster is improved, the requirements of the user on individuation and diversification of the monitoring platform are met, and the use experience of the user is improved.
Fig. 4 is a schematic diagram illustrating a monitoring alarm and a monitoring post-call for a ratio of occupied memory to allocated memory in a queue according to some embodiments of the invention.
Referring to fig. 4, data monitoring is performed on memory usage of a queue a, a queue B, and a queue C in a target data cluster, where each small box represents a memory resource in the queue, a dark small box 401 represents that a memory is occupied, and a light small box 402 represents that a memory is unoccupied. Suppose that the occupied memory in queue a accounts for 100% of the allocated memory of the queue, the occupied memory in queue B accounts for 60% of the allocated memory of the queue, and the occupied memory in queue a accounts for 0% of the allocated memory of the queue. At this time, the system detects that the health degree data of the queue A exceeds the original monitoring alarm threshold value and alarms, and the system or the user knows that the queue C occupies less memory according to the historical health degree data of the queue B and the queue C associated with the queue A, so that the system or the user can redistribute the total memory of the queue A and the queue C by adjusting the monitoring alarm threshold values of the queue A and the queue C. The monitoring alarm threshold value is regulated and controlled independently, so that resources are reasonably distributed to the target data cluster, the resource utilization rate of the target data cluster is improved, the requirements of users on individuation and diversification of the monitoring platform are met, and the use experience of the users is improved.
In another example embodiment of the present invention, the data to be monitored may include monitoring basic data and a storage hierarchy, and the system obtains the monitoring basic data of the target data cluster in a preset manner; calculating first health degree data according to the monitoring basic data, and storing the first health degree data into a corresponding monitoring alarm table; calculating second health degree data corresponding to a storage hierarchy corresponding to the target data cluster, and storing the second health degree data into a corresponding monitoring alarm table; based on the monitoring alarm table, drawing monitoring basic data and a health degree trend graph corresponding to a storage hierarchy so as to visually display first health degree data and second health degree data corresponding to a target data cluster; and alarming according to the adjustable monitoring alarm threshold value and the health degree trend graph.
The monitoring basic data may refer to basic data to be monitored in the target data cluster (in the present exemplary embodiment, the monitoring basic data is relative to the storage hierarchy), for example, the monitoring basic data may be occupied memory resources in the message queue and total memory allocated to the message queue, the number of tasks to be processed in the message queue, and the total number of tasks in the message queue, which is not particularly limited in the present exemplary embodiment. The storage hierarchy may refer to the data storage structure of the database in the target data cluster (in this example embodiment, the storage hierarchy is with respect to the monitoring base data). The first health degree data can refer to health degree data corresponding to the monitoring basic data, and the second health degree data can refer to health degree data corresponding to the storage hierarchy.
FIG. 5 schematically illustrates a schematic of health data calculation for a storage hierarchy according to some embodiments of the invention.
Referring to fig. 5, in step S510, a cluster storage resource (which may be considered as a common responsible person) in the storage hierarchy of the target data cluster specifies a storage directory, transparentizes the storage resource, and distributes the storage resource to a third-level directory storage resource;
step S520, merging small files by using three-level directory storage resources (which can be regarded as three-level directory responsible persons) in the storage hierarchy, clearing cold data, summarizing table-level storage resources, and returning data to the cluster storage resources;
in step S530, the cluster storage resource calculates health degree data (data to be monitored) corresponding to the storage hierarchy according to data returned by the tertiary directory storage resource, for example, the health degree data corresponding to the storage hierarchy may include a data storage period, a data size, a small file number (limited by the storage period), and the like. It is to be understood that this is by way of illustration only and is not to be taken by way of any particular limitation in the present disclosure.
Further, the monitoring basic data may at least include task quantity data, queue resource data, and storage resource data, and the system obtaining the monitoring basic data of the target data cluster in a preset manner may include calling the target interface to obtain the task quantity data in a command manner, obtaining the queue resource data by a web crawler, and obtaining the storage resource data from a data warehouse model corresponding to the target data cluster, which is not limited in this example embodiment.
FIG. 6 schematically illustrates a schematic diagram of a monitoring structure of a target data cluster, according to some embodiments of the invention.
Referring to fig. 6, the monitoring modules of the target data cluster may include a task monitoring module 601, a queue resource monitoring module 602, a storage monitoring module 603, and a health data calculation module 604. The task monitoring module 601 may obtain the task amount data in a command manner by calling a target interface; the queue resource monitoring module 602 may obtain queue resource data in a web crawler manner; the storage monitoring module 603 may obtain storage resource data from a data warehouse model corresponding to the target data cluster; the health degree data calculation module 604 obtains the data to be monitored acquired by the task monitoring module 601, the queue resource monitoring module 602, and the storage monitoring module 603, and calculates to obtain health degree data corresponding to the data to be monitored.
It is noted that although the steps of the methods of the present invention are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
In addition, in the present exemplary embodiment, a data monitoring apparatus is also provided. Referring to fig. 7, the data monitoring apparatus 700 includes: the data obtaining unit 710 is configured to obtain data to be monitored of a target data cluster; the data calculation unit 720 is used for calculating health degree data according to the data to be monitored and storing the health degree data into a corresponding monitoring alarm table; the data display unit 730 is configured to draw a health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table, so as to visually display the health degree data corresponding to the target data cluster; the data monitoring alarm unit 740 is configured to obtain a monitoring alarm threshold, and perform monitoring alarm according to the monitoring alarm threshold and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing scheme, the data monitoring alarm unit 740 is configured to: responding to monitoring alarm information of health degree data, and acquiring a plurality of historical health degree data related to the health degree data through the health degree trend graph; regulating and controlling a monitoring alarm threshold value of the health degree data according to the plurality of historical health degree data; and monitoring and alarming according to the regulated monitoring and alarming threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing scheme, the data monitoring alarm unit 740 is configured to: responding to alarm information of health degree data, and acquiring an input monitoring alarm threshold; and monitoring and alarming according to the input monitoring and alarming threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing solution, the data monitoring apparatus 700 further includes: the monitoring basic data acquisition unit is used for acquiring monitoring basic data of the target data cluster in a preset mode; the first health degree data calculation unit is used for calculating first health degree data according to the monitoring basic data and storing the first health degree data into a corresponding monitoring alarm table; the second health degree data calculation unit is used for calculating second health degree data corresponding to the storage hierarchy corresponding to the target data cluster and storing the second health degree data into the corresponding monitoring alarm table; the health degree data display unit is used for drawing the monitoring basic data and a health degree trend graph corresponding to the storage hierarchy based on the monitoring alarm table so as to visually display the first health degree data and the second health degree data corresponding to the target data cluster; and the monitoring alarm unit is used for alarming according to the adjustable monitoring alarm threshold value and the health degree trend graph.
In an exemplary embodiment of the present invention, based on the foregoing, the monitoring-base-data obtaining unit is configured to: calling a target interface to acquire the task amount data in a command mode; acquiring the queue resource data through a web crawler; and acquiring the storage resource data from the data warehouse model corresponding to the target data cluster.
In an exemplary embodiment of the present invention, based on the foregoing scheme, the data monitoring apparatus 700 is configured to: and storing the data to be monitored into a relational database with a designed table structure.
In an exemplary embodiment of the present invention, based on the foregoing scheme, the data display unit 730 is configured to: obtaining health data stored in the relational database; drawing a health degree trend graph corresponding to the data type according to the data type of the data to be monitored corresponding to the health degree data; and sending the health degree trend graphs of different data types to a front end for visual display.
The specific details of each module of the data monitoring device have been described in detail in the corresponding data monitoring method, and therefore are not described herein again.
It should be noted that although in the above detailed description several modules or units of the data monitoring device are mentioned, this division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the data monitoring method is also provided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 800 according to such an embodiment of the invention is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present invention.
As shown in fig. 8, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, a bus 830 connecting different system components (including the memory unit 820 and the processing unit 810), and a display unit 840.
Wherein the storage unit stores program code that is executable by the processing unit 810 to cause the processing unit 810 to perform steps according to various exemplary embodiments of the present invention as described in the "exemplary methods" section above in this specification. For example, the processing unit 810 may execute step S110 shown in fig. 1 to obtain data to be monitored of a target data cluster; step S120, calculating health degree data according to the data to be monitored, and storing the health degree data into a corresponding monitoring alarm table; step S130, drawing a health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table so as to visually display the health degree data corresponding to the target data cluster; step S140, acquiring a monitoring alarm threshold value, and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph.
The storage unit 820 may include readable media in the form of volatile storage units, such as a random access storage unit (RAM)821 and/or a cache storage unit 822, and may further include a read only storage unit (ROM) 823.
The electronic device 800 may also communicate with one or more external devices 870 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 850. Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above-mentioned "exemplary methods" section of the present description, when said program product is run on the terminal device.
Referring to fig. 9, a program product 900 for implementing the above-described data monitoring method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program codes, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, 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.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method for monitoring data, comprising:
acquiring data to be monitored of a target data cluster;
calculating health degree data according to the data to be monitored, and storing the health degree data into a corresponding monitoring alarm table;
based on the monitoring alarm table, drawing a health degree trend graph corresponding to the data to be monitored so as to visually display the health degree data corresponding to the target data cluster;
and acquiring a monitoring alarm threshold value, and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph.
2. The data monitoring method according to claim 1, wherein obtaining a monitoring alarm threshold and performing monitoring alarm according to the monitoring alarm threshold and the health degree trend graph further comprises:
responding to monitoring alarm information of health degree data, and acquiring a plurality of historical health degree data related to the health degree data through the health degree trend graph;
regulating and controlling a monitoring alarm threshold value of the health degree data according to the plurality of historical health degree data;
and monitoring and alarming according to the regulated monitoring and alarming threshold value and the health degree trend graph.
3. The data monitoring method according to claim 2, wherein the obtaining a monitoring alarm threshold and performing monitoring alarm according to the monitoring alarm threshold and the health degree trend graph further comprises:
responding to alarm information of health degree data, and acquiring an input monitoring alarm threshold;
and monitoring and alarming according to the input monitoring and alarming threshold value and the health degree trend graph.
4. The data monitoring method of claim 1, wherein the data to be monitored comprises monitoring base data and a storage hierarchy, the method further comprising:
acquiring monitoring basic data of a target data cluster in a preset mode;
calculating first health degree data according to the monitoring basic data, and storing the first health degree data into a corresponding monitoring alarm table;
calculating second health degree data corresponding to the storage hierarchy corresponding to the target data cluster, and storing the second health degree data into the corresponding monitoring alarm table;
drawing the monitoring basic data and a health degree trend graph corresponding to the storage hierarchy based on the monitoring alarm table so as to visually display the first health degree data and the second health degree data corresponding to the target data cluster;
and alarming according to the adjustable monitoring alarm threshold value and the health degree trend graph.
5. The data monitoring method according to claim 4, wherein the monitoring basic data at least includes task amount data, queue resource data, and storage resource data, and the obtaining the monitoring basic data of the target data cluster in a preset manner includes:
calling a target interface to acquire the task amount data in a command mode;
acquiring the queue resource data through a web crawler; and
and acquiring the storage resource data from the data warehouse model corresponding to the target data cluster.
6. The data monitoring method of claim 1, wherein after obtaining the data to be monitored of the target data cluster, the method further comprises:
and storing the data to be monitored into a relational database with a designed table structure.
7. The data monitoring method according to any one of claims 1 to 6, wherein the monitoring alarm table is disposed in the relational database, and the drawing a health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table to visually display the health degree data corresponding to the target data cluster further comprises:
obtaining health data stored in the relational database;
drawing a health degree trend graph corresponding to the data type according to the data type of the data to be monitored corresponding to the health degree data;
and sending the health degree trend graphs of different data types to a front end for visual display.
8. A data monitoring device, comprising:
the data acquisition unit is used for acquiring data to be monitored of the target data cluster;
the data calculation unit is used for calculating health degree data according to the data to be monitored and storing the health degree data into a corresponding monitoring alarm table;
the data display unit is used for drawing a health degree trend graph corresponding to the data to be monitored based on the monitoring alarm table so as to visually display the health degree data corresponding to the target data cluster;
and the data monitoring alarm unit is used for acquiring a monitoring alarm threshold value and carrying out monitoring alarm according to the monitoring alarm threshold value and the health degree trend graph.
9. An electronic device, comprising:
a processor; and
a memory having stored thereon computer readable instructions which, when executed by the processor, implement a data monitoring method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a data monitoring method according to any one of claims 1 to 7.
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