CN112559128A - Apache Kylin hosting system and method based on cloud computing - Google Patents
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Abstract
The invention provides an Apache Kylin hosting system and method based on cloud computing.A management module is arranged on a virtual machine and is responsible for application and creation of infrastructure on a cloud, and the management module automatically creates required computing, storage and network resources in a cloud platform account of a user by calling a public interface provided by a cloud platform; nodes in the calculation and storage separation cluster only provide calculation resources, and object storage is used as storage resources; apache Kylin is taken as an OLAP engine, and data visualization software is built in the OLAP engine. Based on the invention, an OLAP analysis platform with low threshold, low cost and high performance can be quickly constructed on the cloud, and the data analysis requirements of enterprises on the cloud are met.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to an Apache Kylin hosting system and method based on cloud computing.
Background
At present, Apache Kylin is an open-source distributed analysis engine, provides an SQL (structured query language) query interface and multidimensional analysis (OLAP) capability above Hadoop/Spark, supports sub-second-level query on super-large-scale data, and is adopted by thousands of enterprises in the world at present. At present, when an enterprise performs data analysis by adopting Apache Kylin, three problems are mainly encountered, firstly, Apache Kylin needs to be operated on a Hadoop cluster, and for the enterprise without the Hadoop cluster, the difficulty of deploying an operation and maintenance cluster is high, the use threshold is also high, and a corresponding big data talent is needed. Secondly, in the face of increasing mass data and access flow, IT is necessary to continuously increase IT infrastructure, and the investment is large. Thirdly, compared with the traditional data center, cloud computing has many advantages such as low cost, expandability and safety, cloud on an IT infrastructure is a current trend, and enterprises must consider a data analysis solution after the cloud on data.
Disclosure of Invention
In view of this, the present disclosure provides a cloud computing-based Apache Kylin hosting system and method for the pain point and demand encountered when an enterprise uses Apache Kylin at present, and the technical scheme is as follows:
in one aspect, the invention provides an Apache Kylin hosting system based on cloud computing, which comprises a management module, a computing module, an application module and a monitoring module, wherein the management module is arranged on a virtual machine, the application and the creation of infrastructure on the cloud are applied and created by using button operation, the Apache Kylin and a cluster are deployed and used for managing the deployment, the operation and the maintenance of the computing module, the application module and the monitoring module, the computing module is a distributed computing cluster consisting of a plurality of at least 4 nodes and used for providing computing and storage resources for the application module, and has the capability of automatic expansion and contraction, the application module is used for providing OLAP analysis capability and data visualization capability, and the monitoring module is used for monitoring the computing module and the application module.
Further, the management module automatically creates needed infrastructure on the cloud in the cloud platform account of the user, including computing, storage and network resources, by calling a public interface provided by the cloud platform, deploys computing module programs on at least 4 nodes, constructs a computing module, deploys application module programs on at least 1 node, constructs an application module, deploys monitoring programs on the computing module and the application module nodes, and constructs a monitoring module of the full platform.
Furthermore, the computing module adopts a framework with separated computing and storage, nodes in the cluster only provide computing resources, and object storage is used as storage resources.
Furthermore, the computing module has the automatic scaling capability, and according to the load state of the current cluster and a corresponding scaling strategy, when the cluster has computing tasks and is in a waiting state due to insufficient resources, the computing module automatically increases the computing load of the computing nodes, and when the cluster has nodes without tasks and is in an idle state, the computing module automatically releases idle computing nodes.
Furthermore, the application module submits the calculation task to the calculation module, and after the calculation module completes the calculation, the result is returned to the application module or persistently stored.
Furthermore, the application module takes Apache Kylin as an OLAP engine and is internally provided with data visualization software.
Furthermore, the application module provides full-link one-stop data analysis capability from data access and modeling to report display and provides docking capability with mainstream BI software.
Further, the monitoring operation of the monitoring module includes monitoring system indexes of all nodes and setting threshold values of all indexes for email alarm, and also includes collecting system logs of all modules and displaying and querying support logs.
In another aspect, the present invention provides an Apache Kylin hosting method based on cloud computing, where the method is applied to the above-mentioned Apache Kylin hosting system based on cloud computing, and includes the following steps:
step 1: the management module applies for and creates infrastructure on the cloud, and deploys a computing module, an application module and a monitoring module;
step 2: the application module takes Apache Kylin as an OLAP engine to submit a calculation task to the calculation module;
and step 3: the computing module automatically stretches computing nodes and executes computing tasks;
and 4, step 4: the calculation module returns the calculation result to the application module and stores the calculation result in an object storage of the calculation module;
and 5: the monitoring module monitors the operation process of the computing module and the application module;
step 6: and outputting index monitoring alarm and collecting monitoring logs.
The invention provides an Apache Kylin hosting system and method based on cloud computing, wherein the mode of deploying Apache Kylin on the cloud is matched with the trend of an enterprise IT facility and the cloud on the data, an OLAP analysis platform based on Apache Kylin can be quickly constructed on the cloud, the requirement of large data analysis on the cloud of the enterprise is met, a management module is used, a plurality of buttons can be simply clicked to complete application and creation of infrastructure on the cloud, Apache Kylin and a cluster are deployed, the deployment and the operation of the computing module, the application module and a monitoring module are further managed, the difficulty of operation and maintenance deployment is greatly reduced, and the use threshold is reduced; the automatic telescopic function of the computing module can automatically increase computing nodes when the computing load is large, the requirement of increasing the nodes when the flow is increased is met, meanwhile, after the flow is reduced, the computing nodes can be automatically reduced, and unnecessary resource waste is avoided.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
FIG. 1 is a schematic diagram of an Apache Kylin hosting system based on cloud computing according to the present invention;
fig. 2 is a schematic diagram of an Apache Kylin hosting method based on cloud computing according to the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
In addition, the term "plurality" shall mean two as well as more than two.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Example one
An embodiment of the present invention provides an Apache Kylin hosting system based on cloud computing, as shown in fig. 1, which includes a management module, a computing module, an application module, and a monitoring module, where the management module is set on a virtual machine, and is responsible for application and creation of infrastructure on the cloud, and is used to manage deployment, operation, and maintenance of the computing module, the application module, and the monitoring module, the computing module is a distributed computing cluster composed of at least 4 nodes and is used to provide computing and storage resources for the application module, the application module is used to provide OLAP analysis capability and data visualization capability, and the monitoring module is used to monitor the computing module and the application module.
The management module runs on an independent virtual machine, and automatically creates required infrastructure on the cloud including computing, storage and network resources in a cloud platform account of a user by calling a public interface provided by a cloud platform, wherein the created infrastructure includes but is not limited to the virtual machine, a database and the like during specific implementation. The management module is responsible for deploying computing modules, application modules and monitoring modules, deploying computing module programs on at least 4 nodes by the management module based on the created infrastructure on the cloud, constructing the computing modules, deploying application module programs on at least 1 node, constructing the application modules, deploying the monitoring programs on the computing modules and the nodes of the application modules, constructing the monitoring modules of a full platform, and managing the operation and maintenance of the computing modules, the application modules and the monitoring modules.
The computing module adopts a structure with separated computing and storage, nodes in the cluster only provide computing resources, and object storage is used as storage resources. The architecture with the separated computing and storage greatly improves the expandability of a computing module, the storage uses the object storage provided on the cloud, and compared with the traditional HDFS, the cloud-based HDFS has higher stability and lower cost, theoretically has no capacity limitation, and can store mass data. The computing module has the automatic expansion capability, and according to the load state of the current cluster and a corresponding expansion strategy, when the cluster has computing tasks and is in a waiting state due to insufficient resources, computing nodes are automatically increased to deal with the computing loads, when the cluster has nodes without tasks, and when the cluster is in an idle state, idle computing nodes are automatically released, so that resource waste is avoided. The computing module improves the expandability of the whole system and reduces the use cost through the design of separation of computing and storage and automatic expansion.
And the application module submits the calculation task to the calculation module, and after the calculation module finishes calculation, the result is returned to the application module or persistently stored.
The application module takes Apache Kylin as an OLAP engine, and is internally provided with data visualization software, so that the full-link one-stop data analysis capability from data access and modeling to report display is provided, the docking capability with mainstream BI software is provided, and the seamless docking with the mainstream BI software such as Microsoft Power BI and Tableau is supported. In specific implementation, desktop applications of Tableau and Microsoft Power BI are connected by installing a Kylin ODBC driver and a Kylin data source connector.
Monitoring work of the monitoring module is to monitor system indexes of all nodes, wherein in specific implementation, the monitored indexes comprise information such as a CPU (central processing unit), a memory and the like, and can set threshold values of all indexes to carry out mail alarming, and on the other hand, system logs of all modules are collected to display and inquire support logs, so that problems are conveniently checked.
Example two
An embodiment of the present invention provides a cloud-computing-based Apache Kylin hosting method, which is applied to the cloud-computing-based Apache Kylin hosting system, as shown in fig. 2, and includes the following steps:
step 1: the management module applies for and creates infrastructure on the cloud, and deploys a computing module, an application module and a monitoring module;
during implementation, the management module is used for simply clicking a plurality of buttons to deploy the Apache Kylin and the clusters on the cloud, so that the difficulty of operation and maintenance deployment is greatly reduced, and the use threshold is lowered.
Step 2: the application module takes Apache Kylin as an OLAP engine to submit a calculation task to the calculation module;
and step 3: the computing module automatically stretches computing nodes and executes computing tasks;
during specific implementation, according to the load state of the current cluster and a corresponding expansion strategy, the corresponding calculation load of the calculation node is automatically increased when the cluster load is heavy, and the idle calculation node is automatically released when the cluster load is low, so that resource waste is avoided.
And 4, step 4: the calculation module returns the calculation result to the application module and stores the calculation result in an object storage of the calculation module;
when the method is implemented specifically, visual software is arranged in the application module, the report shows the calculation result, and the calculation result can also be shown through mainstream BI software.
And 5: the monitoring module monitors the operation process of the computing module and the application module;
step 6: and outputting index monitoring alarm and collecting monitoring logs.
In specific implementation, on one hand, system indexes of all nodes are monitored, the monitored indexes comprise information such as a CPU (central processing unit), a memory and the like, threshold values of all indexes can be set for mail alarming, and on the other hand, system logs of all modules are collected, display and query of support logs are carried out, and problems are conveniently checked.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. An Apache Kylin hosting system based on cloud computing is characterized by comprising a management module, a computing module, an application module and a monitoring module, wherein the management module is arranged on a virtual machine, a button is used for operating and applying and creating infrastructure on the cloud, Apache Kylin and a cluster are deployed and used for managing deployment, operation and maintenance of the computing module, the application module and the monitoring module, the computing module is a distributed computing cluster consisting of at least 4 nodes and used for providing computing and storage resources for the application module, the computing module has automatic stretching capacity, the application module is used for providing OLAP analysis capacity and data visualization capacity, and the monitoring module is used for monitoring the computing module and the application module.
2. The cloud-computing-based Apache Kylin hosting system of claim 1, wherein the management module automatically creates required on-cloud infrastructure, including computing, storage, and network resources, within a user's cloud platform account by invoking a public interface provided by the cloud platform.
3. The cloud-computing-based Apache Kylin hosting system of claim 1, wherein the management module deploys computing module programs on at least 4 nodes to build a computing module, deploys application module programs on at least 1 node to build an application module, deploys monitoring programs on the nodes of the computing module and the application module to build a full-platform monitoring module.
4. The cloud-computing-based Apache Kylin hosting system of claim 1, wherein the computing modules employ a separate computing and storage architecture, nodes in a cluster provide only computing resources, and object storage is used as storage resources.
5. The cloud computing-based Apache Kylin hosting system of claim 1, wherein the computing modules automatically increase the computing nodes to handle the computing load when a cluster has a computing task in a waiting state due to insufficient resources, and automatically release idle computing nodes when the cluster has no task and is in an idle state, according to a load state of a current cluster and a corresponding scaling strategy.
6. The cloud-computing-based Apache Kylin hosting system according to claim 1, wherein the application module submits computing tasks to the computing module, and after the computing module completes computing, the results are returned to the application module or persistently stored.
7. The cloud-based Apache Kylin hosting system of claim 1, wherein the application module uses Apache Kylin as an OLAP engine and is embedded with data visualization software.
8. The cloud-computing-based Apache Kylin hosting system of claim 1, wherein the application module provides full-link one-stop data analysis capability from data access, modeling to report presentation, providing interfacing capability with mainstream BI software.
9. The cloud-computing-based Apache Kylin hosting system according to claim 1, wherein the monitoring of the monitoring modules includes monitoring system metrics of all nodes and setting thresholds of each metric for email alert, and further includes collecting system logs of all modules, and displaying and querying support logs.
10. A cloud-based Apache Kylin hosting method applied to the cloud-based Apache Kylin hosting system according to any one of claims 1 to 9, comprising the steps of:
step 1: the management module applies for and creates infrastructure on the cloud, and deploys a computing module, an application module and a monitoring module;
step 2: the application module takes Apache Kylin as an OLAP engine to submit a calculation task to the calculation module;
and step 3: the computing module automatically stretches computing nodes and executes computing tasks;
and 4, step 4: the calculation module returns the calculation result to the application module and stores the calculation result in an object storage of the calculation module;
and 5: the monitoring module monitors the operation process of the computing module and the application module;
step 6: and outputting index monitoring alarm and collecting monitoring logs.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117009038A (en) * | 2023-10-07 | 2023-11-07 | 之江实验室 | Graph computing platform based on cloud native technology |
| CN117009038B (en) * | 2023-10-07 | 2024-02-13 | 之江实验室 | Graph computing platform based on cloud native technology |
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