CN110968749A - Visual display device and method based on big data containerized dispatching center system - Google Patents
Visual display device and method based on big data containerized dispatching center system Download PDFInfo
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- 238000012800 visualization Methods 0.000 description 3
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9035—Filtering based on additional data, e.g. user or group profiles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9038—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F3/0486—Drag-and-drop
Abstract
The invention provides a visual display device and method based on a big data containerization dispatching center system, wherein the device comprises the following steps: the workflow creating module creates at least one workflow according to business needs, manually drags each module operation in the big data processing process to the workflow, and self-defines the dependency relationship among each module operation in the workflow; the positioning module positions required content according to the input search content; the filtering module filters the content according to the positioned content; the display module displays the positioned content and the filtered content to a user in real time; and the highlight module highlights all the dependency relations related to the contents when a mouse is arranged on the displayed contents and pops up the detailed information of the current contents. The invention realizes clear, concise and telescopic panoramic display in a big data containerization dispatching center system and describes the job dependency relationship in the workflow.
Description
Technical Field
The invention relates to the field of communication, in particular to a visual display device and method based on a big data containerization dispatching center system.
Background
The directed Acyclic Graph (Direct Acyclic Graph) supports asynchronous concurrency, can form a topological tree structure, and can greatly improve expansibility. Directed acyclic graphs are widely applied to complex data relation graph display.
The workflow of the Apache Oozie big data scheduling framework is a set of actions (Hadoop map/reduce operation, pig operation and other operations), and is controlled by a control dependency DAG (direct Acyclic graph), but the interface has no user interaction, and the establishment of the operation dependency relationship is not flexible.
The Airflow is a platform for arranging, scheduling and monitoring the workflow, the Airflow arranges the workflow into DAGs formed by tasks, a scheduler executes the tasks according to a specified dependency relationship in a group of running programs, and the execution sequence of all the tasks in the workflow and the dependency relationship among the tasks can be described. But is limited to a single workflow and does not have a panoramic description of the data relationships of all the workflows of the system.
The button is a data integration module in the whole Pentaho product system, and a user can create and define a job or conversion in a dragging mode and provide execution conditions of the job or conversion of each child node. Jobs in a workflow are executed in a serial fashion. A Job comprises one or more Job items, and the Job items are connected by a Hop (Job Hop), namely a connecting line with arrows between steps. The execution sequence of the jobs is determined by jump and the execution result of each job item, and the user can customize the operation. However, when too many jobs are performed in the workflow and the nesting relationship between the jobs and the job items is too complex, the display of the dependency relationship between the jobs and the job items becomes not friendly enough, and a clear, concise and telescopic panoramic display does not exist.
Based on this, the existing visualization interface of the big data dispatching center system mainly has the following defects: the interactive experience of the visual interface of the existing big data scheduling center system is poor; a clear, concise and telescopic panoramic display is lacked to describe the job dependency relationship in the workflow; and there is no panoramic presentation of all workflows and all jobs across the system level of the workflow.
Disclosure of Invention
In order to solve the technical problems, the invention provides a visual display device and method based on a big data containerized dispatching center system, so as to realize clear, concise and telescopic panoramic display in the big data containerized dispatching center system and describe the job dependency relationship in the workflow.
According to an embodiment of the present invention, the present invention provides a visual display device based on a big data containerized dispatch center system, the device includes:
the workflow creating module is used for creating at least one workflow according to the business requirements;
the positioning module is used for positioning needed contents according to the input search contents;
the filtering module is used for filtering the content according to the positioned content;
the display module is used for displaying the positioned content and the filtered content to a user in real time;
and the highlight module is used for highlighting when the mouse is arranged on the displayed content and popping up detailed information of the current content.
Further, the workflow creating module is configured to create at least one workflow according to the service requirement, where the creating includes adding a Sqoop job, a Hive job, a Spark job, a data conversion job, or a custom job, manually dragging each module job to the workflow in the big data processing process, and custom-defining a dependency relationship between each module of the workflow.
Further, the filtered content includes the time consumed by the job and the CPU occupation ratio.
Further, the display module is used for displaying the positioned content and the filtered content to a user in real time, wherein the displaying includes displaying the directed acyclic graph DAG in a force-directed graph mode so as to clearly display a relation panorama among all data sources and operations of the system.
Further, the highlighting module is used for highlighting when the mouse is arranged on the displayed content and popping up detailed information of the current content, and comprises the steps of placing the mouse on a content node, highlighting upstream and downstream dependent nodes and clicking the highlighted node to pop up the detailed information.
Further, the detailed information includes specific information of the node where the content is located, node dependency information, and all upstream and downstream dependency details of the node.
Further, the displaying module is configured to display the located content and the filtered content to the user in real time, where the displaying includes displaying in a manner of a star-shaped graph or a single directed acyclic graph DAG.
Further, the shape, the size and the dimension of the operation presentation are set in a custom mode.
Furthermore, the display module also includes setting the node configuration, connection color, size and shape of the content when displaying the content.
According to an embodiment of the present invention, the present invention further provides a visualization display method based on a big data containerization scheduling center system, where the method includes:
s1, creating one or more workflows based on business requirements, wherein the workflows comprise Sqoop adding operation, Hive operation, Spark operation, data conversion operation or custom operation, and manually dragging to establish relationship dependence;
s2, inputting contents to be searched, positioning the contents, and displaying the directed acyclic graph in a force-directed graph mode to clearly display a panoramic graph of the relationship between all data sources and the operation of the system;
s3, filtering out contents meeting conditions, wherein the filtered contents comprise operation time consumption and a CPU occupation ratio;
s4, placing a mouse on a node of the content through all workflow contents and upstream and downstream dependency relations in the directed acyclic graph panorama display system, and enabling upstream and downstream dependency nodes to be highlighted;
s5, clicking the highlight node to pop up detailed information of the node, wherein the detailed information comprises specific information, node dependence information and all upstream and downstream dependence details of the node.
The invention provides a visual display device and method based on a big data containerization dispatching center system, which have the following beneficial effects:
(1) the method supports the manual dragging and adding of the dependency relationship of the data processing operation of the big data containerized dispatching center system by the user;
(2) the method takes a data source as a center, and radiates Sqoop operation, Hive operation, Spark operation, data conversion operation, custom operation and the like of a big data platform around the data source;
(3) according to the method, the operation/data source is clicked, the upstream and downstream dependency relationship can be observed, and the operation can be filtered according to the condition;
(4) the invention supports star graphs and single DAG graphs, configuration nodes, connection line colors, shapes, sizes and the like, positioning, zooming and checking the related connection of single nodes.
Drawings
Fig. 1 is a frame diagram of a visual display device based on a big data containerization dispatching center system provided by the invention;
fig. 2 is a flowchart of a visual display method based on a big data containerization scheduling center system according to the present invention.
Detailed Description
For the convenience of understanding, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
As shown in fig. 1, the visual display device based on the big data containerized dispatch center system provided by the present invention includes:
the workflow creating module is used for creating at least one workflow according to business requirements, creating the workflow, adding Sqoop operation, Hive operation, Spark operation, data conversion operation or custom operation, manually dragging each module operation in the big data processing process to the workflow, and custom-defining the dependency relationship among each module of the workflow; according to the invention, a plurality of workflows can be created according to requirements; as jobs and workflows increase, clarifying relationships between data sources and jobs becomes increasingly important.
The display device is provided with a search box, so that the required content is input through the search box of the instrument panel, and the specific node based on the content is further positioned.
The filtering module is used for filtering the content according to the positioned content, and in the invention, the content is filtered through the filtering module of the instrument panel, so that content nodes meeting conditions, such as time consumption of operation, CPU occupation proportion and the like, are filtered.
And the display module is used for displaying the positioned content and the filtered content to a user in real time. In the invention, the display module plays the positioned content and the filtered content, and the specific display mode comprises displaying the directed acyclic graph DAG in a force-directed graph mode so as to clearly display the relation panoramic graph between all data sources and the operation of the system. Of course, the display mode also includes a mode of a star map or a single DAG map for displaying, and meanwhile, in the invention, the display modes of various jobs can customize the contents of the display shape, size and the like of the jobs. Meanwhile, the nodes of the required content can be configured based on the workflow in the display module, and the colors, the sizes and the shapes of the connecting lines can be set, so that personalized display is realized.
And the highlight module is used for highlighting when the mouse is arranged on the displayed content and popping up detailed information of the current content. In the embodiment of the invention, the highlight module realizes corresponding functions based on the cooperation of a mouse, specifically, the mouse is placed on a content node, the upstream and downstream dependent nodes are highlighted, and detailed information is popped up by clicking the highlighted node. The detailed information comprises specific information of a node where the content is located, node dependency information and all upstream and downstream dependency details of the node.
According to another embodiment of the present invention, as shown in fig. 2, the present invention further provides a visualization display method based on a big data containerization dispatch center system, where the method includes:
s1, creating one or more workflows based on business requirements, wherein the workflows comprise Sqoop adding operation, Hive operation, Spark operation, data conversion operation or custom operation, and manually dragging to establish relationship dependence;
s2, inputting contents to be searched, positioning the contents, and displaying the directed acyclic graph in a force-directed graph mode to clearly display a panoramic graph of the relationship between all data sources and the operation of the system;
s3, filtering out the content meeting the conditions and displaying the content, wherein the filtered content comprises the time consumed by the operation and the proportion occupied by a CPU;
s4, placing a mouse on a node of the content through all workflow contents and upstream and downstream dependency relations in the directed acyclic graph panorama display system, and enabling upstream and downstream dependency nodes to be highlighted;
s5, clicking the highlight node to pop up detailed information of the node, wherein the detailed information comprises specific information, node dependence information and all upstream and downstream dependence details of the node.
The operation assembly line provided by the invention supports the interactive experience of users on the manual free dragging of the dependence relationship of the large data containerization data processing operation and the data source. Meanwhile, the task panorama of the invention displays the chart by receiving a specific data structure. Icons support two types: a. the star-shaped graph supports two forms of a center form and a centerless form, and a center point can be configured; b. and the single DAG graph displays the upstream and downstream relations of the single node and displays the details of the node. Node and connecting line design among the icons supports node color configuration, style when a hover mouse is suspended, highlighted style, shape, size and the like. The graph operation supports the enlargement and the reduction, the node aggregation, the highlight and the node connection behaviors are controlled by clicking self-definition, and the number and the positioning of the initial nodes of the window are controlled.
It will be evident to those skilled in the art that the embodiments of the present invention are not limited to the details of the foregoing illustrative embodiments, and that the embodiments of the present invention are capable of being embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the embodiments being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Several units, modules or means recited in the system, apparatus or terminal claims may also be implemented by one and the same unit, module or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the embodiments of the present invention and not for limiting, and although the embodiments of the present invention are described in detail with reference to the above preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the embodiments of the present invention without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A visual display device based on a big data containerized dispatching center system is characterized by comprising:
the workflow creating module is used for creating at least one workflow according to the business requirements;
the positioning module is used for positioning needed contents according to the input search contents;
the filtering module is used for filtering the content according to the positioned content;
the display module is used for displaying the positioned content and the filtered content to a user in real time;
and the highlight module is used for highlighting when the mouse is arranged on the displayed content and popping up detailed information of the current content.
2. The visual display device based on the big data containerization dispatching center system according to claim 1, wherein the workflow creating module is configured to create at least one workflow according to business requirements, and includes adding an Sqoop job, a Hive job, a Spark job, a data conversion job, or a custom job, manually dragging each module job to the workflow in the big data processing process, and custom-defining a dependency relationship between each module of the workflow.
3. The visual display device of the big data containerization-based dispatch center system of claim 1, wherein the filtered content comprises job time consumption and CPU occupation ratio.
4. The big-data containerization scheduling center system-based visual display device of claim 1, wherein the display module is configured to display the positioned content and the filtered content to the user in real time, and the display module is configured to display the directed acyclic graph DAG in a force-directed graph manner to clearly display a panoramic view of relationships between all data sources and jobs of the system.
5. The visual display device of the big data containerization based dispatch center system of claim 1, wherein the highlighting module is configured to highlight when a mouse is placed on the displayed content and pop up the detailed information of the current content, and the highlighting module is configured to place the mouse on the content node, highlight the dependent nodes upstream and downstream, and pop up the detailed information by clicking the highlighted node.
6. The big data containerization based dispatch center system visual display of claim 1, wherein the detailed information comprises specific information of a node where the content is located, node dependency information, and all upstream and downstream dependency details of the node.
7. The visual display device of the big-data containerized scheduling center system according to claim 4, wherein the display module for displaying the located content and the filtered content to the user in real time further comprises displaying by means of a star-shaped graph or a single directed acyclic graph DAG.
8. The big data containerization based dispatch center system visual display of claim 2, wherein the job presentation shape, size, dimensions are set in a custom manner.
9. The visual display device of the big data containerization-based dispatch center system of claim 7, wherein the display module further comprises a configuration, a connection color, a size and a shape of the nodes of the content when displaying the content.
10. A visual display method based on a big data containerization dispatching center system is characterized by comprising the following steps:
s1, creating one or more workflows based on business requirements, wherein the workflows comprise Sqoop adding operation, Hive operation, Spark operation, data conversion operation or custom operation, and manually dragging to establish relationship dependence;
s2, inputting contents to be searched, positioning the contents, and displaying the directed acyclic graph in a force-directed graph mode to clearly display a panoramic graph of the relationship between all data sources and the operation of the system;
s3, filtering out contents meeting conditions, wherein the filtered contents comprise operation time consumption and a CPU occupation ratio;
s4, placing a mouse on a node of the content through all workflow contents and upstream and downstream dependency relations in the directed acyclic graph panorama display system, and enabling upstream and downstream dependency nodes to be highlighted;
s5, clicking the highlight node to pop up detailed information of the node, wherein the detailed information comprises specific information, node dependence information and all upstream and downstream dependence details of the node.
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