KR102358735B1 - The data relation generating system for graph database - Google Patents

Abstract

The present invention relates to a system for generating data associations in a graph database and a user interface method for generating data associations in a graph database.
The present invention establishes a correlation between fields based on a user's request given in real time through a user interface, and analyzes the correlation between the established fields. And it is a system and method that extracts connection information of data and turns it into a graph database. Users can easily create data correlation queries by drag and drop through the metadata provided by the system, and extract data connection relationships based on the query to generate data results in the form of graphs.

Description

Data Relations Generation System in Graph Database

The present invention relates to graph database technology.

In the era of the so-called 4th industrial revolution, changes in the computing environment such as big data, artificial intelligence, and machine learning have changed the paradigm of data utilization. In the past, it was important to obtain objective information through statistical analysis of data. However, there is a need for a system that can more intuitively find hidden meanings through relationship analysis between data and visualization of the relationship analysis and make inferences more easily through it. Graph database solutions are attracting attention in response to these needs.

A graph database basically consists of a storage for storing graph data, a graph processing engine for real-time processing of graph data, and a supported language for efficiently storing and processing graph data. The graph database of this configuration can be used for all tasks where expression and processing based on relationships between data are important. In the existing relational database environment, various data such as purchase and human information are stored in the form of a table and then graphed and analyzed through a separate data visualization technology, whereas in a graph database solution, the data itself is stored in the form of a graph of points and lines, Specific patterns and anomalies can be quickly traced along a line, and analysis is facilitated by visualizing them. Through this, the user company can analyze the correlation of data more intuitively and quickly.

However, there is an entry barrier for usability because users have to learn the queries related to each database.

The inventors of the present invention have researched and made efforts to solve the above problems. As part of such an effort, the Ministry of Science and ICT participated in the national R&D project and continued research and development, and ended up completing the present invention as a result.

It is an object of the present invention to make associations by establishing relationships between data based on metadata so that data analysts (these data analysts who are data science experts are referred to herein as "users") can easily track relationships between data. It's about providing a relationship. In particular, in the present invention, a user can easily create a query using a drag-and-drop method, and can view a relationship in a customized graph form related to a user request. At this time, data in graph form is generated by extracting related data based on the correlation between fields created by the user in a drag-and-drop method.

The data system according to the present invention displays extracted metadata information on a user interface to help establish a correlation between data. Meta information extracted from the table includes data creation time, storage location, data type, etc., and the user can set the correlation between fields based on this metadata information.

On the other hand, other objects not specified in the present invention will be additionally considered within the range that can be easily inferred from the following detailed description and effects thereof.

In order to achieve the above object, a first aspect of the present invention is a user interface method for creating a data relation in a graph database:

When a user computer terminal accesses a database made of a set of a plurality of tables having a field, which is an item for storing data, a first database table and one or more second database tables, the first database table and one or more second database tables through the user interface of the user computer terminal. a plurality of fields included in the first database table, a plurality of fields included in the second database table, and metadata for the databases are displayed;

The input means of the user computer terminal selects a specific field of the first database table from the user interface and drags and drops it to a specific field of the second database table, or selects a specific field of the second database table and selects the When dragging and dropping to a specific field of the first database table, a step of automatically generating an affinity query corresponding to the drag and drop event;

It is characterized in that the data corresponding to the correlation query is collected from the database, and the collected data is converted into graph data and visualized.

In the user interface method for generating data correlation in a graph database according to a preferred embodiment of the present invention, an indicator of the input means of the user computer terminal is placed in a field of the first database table or a field of the second database table. Once located, it is good to visualize the metadata of the field.

In addition, in the user interface method for creating a data correlation relationship in a graph database according to a preferred embodiment of the present invention, the user interface includes a relation setting screen and a table view screen, and the drag and drop in the table view screen It is preferable that an event occurs, and a relation of graph-type data corresponding to the data correlation generated by the drag-and-drop event is determined according to a setting event on the relation setting screen.

A second preferred aspect of the present invention is a data relation creation system in a graph database, in which input means in a user interface of a user computer terminal accessing the database creates a data relation query by drag-and-drop events on fields of different database tables. If the:

causes the metadata generation module to generate metadata for the database tables and display them in the user interface;

The data collection module accesses the database and selects and collects data stored in the field selected in the drag-and-drop event,

It characterized in that the graph generating module converts the data collected by the data collection module into graph data and visualizes it with the user interface.

In the data correlation generating system in the graph database according to a preferred embodiment of the present invention, if the indicator of the input means of the user computer terminal is located in a certain field of the database table, it is good to visualize the metadata of the corresponding field .

In addition, in the data correlation creation system in the graph database according to a preferred embodiment of the present invention, the user interface includes a relation setting screen and a table view screen, and the drag-and-drop event occurs in the table view screen, It is preferable that a relation of graph-type data corresponding to the data correlation generated by the drag-and-drop event is determined according to a setting event on the relation setting screen.

According to the present invention, there is an advantage in that it is possible to lower the barrier to entry regarding usability, in which a user has to learn a query related to each database by dragging and dropping a query from the user interface of the database. In addition, since the result is received in the form of a graph, it is easy to understand the relationship between data.

On the other hand, even if it is an effect not explicitly mentioned herein, it is added that the effects described in the following specification expected by the technical features of the present invention and their potential effects are treated as described in the specification of the present invention.

1 conceptually shows a configuration example of a graph data structure used in the present invention.
FIG. 2 schematically shows a configuration example of a neighbor list configured according to the relation of FIG. 1 .
3 shows a configuration example of the database structure of the present invention.
4 schematically shows the configuration of a system for generating data associations according to a preferred embodiment of the present invention.
5 schematically shows an overall configuration example of a method for generating data associations according to a preferred embodiment of the present invention.
6 shows a scenario for explaining the configuration of a data association relationship generating system according to a preferred embodiment of the present invention.
7 shows an example of the configuration of the user interface 200 in the system for generating data associations according to a preferred embodiment of the present invention.
8 is a diagram schematically illustrating a relationship between a database and a data relationship creation module in a data relationship creation system according to another preferred embodiment of the present invention.
※ It is revealed that the accompanying drawings are exemplified as a reference for understanding the technical idea of the present invention, and the scope of the present invention is not limited thereby.

Hereinafter, the configuration of the present invention guided by various embodiments of the present invention and effects resulting from the configuration will be described with reference to the drawings. In the description of the present invention, if it is determined that related known functions are obvious to those skilled in the art and may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted.

A graph data structure is a data structure composed of vertices (vertex or nodes) and edges (edges or relations) connecting vertices. It is easy to understand the relational network between data and it is easy to visualize for analysis. Since a graph can be expressed as a set of vertices and edges, it is expressed as G(V, E).

1 and 2 conceptually explain a graph data structure in which the database is expressed as graph data in the present invention. The elements of this graph include vertices and edges as shown in FIG. 1 . Vertices (1, 2, 3, 4) represent data to be stored in the graph. Edges 10, 20, 30, and 40, which mean lines connecting vertices, represent relationships between data.

An Adjacent List can be expressed as shown in FIG. 2 through the expressions shown in FIG. 1 of these vertices 1, 2, 3, and 4 and the edges 10, 20, 30, and 40. As shown in FIG. The neighbor list of FIG. 2 stores which nodes are connected by which relation. Graphs can be stored and searched through adjacency lists that express adjacency relationships between nodes.

Meanwhile, in the present invention, a user can make a data-related query using metadata provided by the database system. Metadata is structured data about data, and is data that describes data. Metadata can be viewed as attribute information and consists of data elements that can identify data. For example, Date, Type, Format, Identifier, Availability, etc. that created the data are applicable. And, by using the properties of such metadata, users can easily find specific data they want.

3 schematically shows a configuration example of a database 50 according to a preferred embodiment of the present invention. A database is a collection of related data. Since several tables 51 , 52 , 53 may exist in one database 50 , they may be displayed as a set of tables 51 , 52 , 53 .

In the present invention, the database is composed of fields (Field: 51a), records (Record: 51b), and tables (Tables: 51, 52, 53). A field 51a is an item for storing data, a record 51b is each row stored in a table, and the tables 51, 52, and 53 function as an aggregate of data composed of fields.

4 schematically shows the configuration of a database association relationship creation system according to a preferred embodiment of the present invention. The system includes a database 50 , a data association creation module 100 , and a user interface 200 . And the processor that manages and processes this system is installed in the server. The server is composed of one or more hardware/software equipment, and the user computer terminal accesses the server to access the database 50 , and then the user interface 200 is displayed on the display of the user computer terminal as a database screen.

The user interface 200 displays the table list, field contents, and metadata stored in the database in a preset screen configuration. As will be described later, based on the metadata information displayed on the screen by the input means of the user's computer terminal, the fields of the table for which the correlation analysis is desired are connected by drag and drop to complete the data correlation query.

The data correlation generation module 100 includes a metadata generation module 110 , a data collection module 120 , and a graph data generation module 13 .

The metadata generation module 110 is a module that generates metadata for a database table. This can include the time the data was created, the storage location (ip, path, etc.), and the data type and scope.

The data collection module 120 selects and collects data stored in the field selected by the user from the database 50 . This data collection module 120 includes a database connector and SQL query that can access the database.

The graph data generation module 130 converts the collected data into graph data.

Among the data selectively collected by the data collection module 120, if the field value bounded by a relation: <--> matches the range set by the correlation query, it is left and the remaining record data is deleted. Vertex, Relation, and Adjacent List are processed as follows.

- Node: The record data stored in the table is saved as a node of the graph and a unique ID is given.

- Relation: The relation requested by the user is designated as a relation in the graph and a unique id is given.

- Adjacent List: The association found in the data collection module 120 is stored in the adjacency list.

In the illustrated example, the database 50 presents three databases, but this is for convenience of description. It goes without saying that fewer databases can be configured, and more databases can be configured. In this specification, a plurality of databases will be classified into “a first database” and a “second database.” This is not to say that the technical configuration of the present invention does not include the classification procedure, but in order to better understand the technical idea of the present invention. The second database refers to one or more databases other than the first database. The database structure consisting of fields, records, and tables as described above is the same. For example, in the example shown, database 1 (59 ) can be classified as the first database, then the remaining databases 2 (58) and 3 (57) become the second database.

The input means of the user computer terminal selects a specific field of the table of the first database 59 in the user interface 200 and drags and drops it to a specific field of the table of the second database 58 or 57, or Alternatively, if a specific field in the table of the second database 58 or 57 is selected and dragged and dropped to a specific field in the table of the first database 59, an affinity query corresponding to this drag and drop event is automatically created. will be.

That is, in the method of creating a database relationship of the present invention, as shown in FIG. 5 , the drag-and-drop event is executed in the user interface of the user computer terminal accessing the database ( S100 ). The drag-and-drop event will be described again.

When a drag-and-drop event is generated on the user interface of step S100, the data collection module selects and collects data stored in the field selected by the user from the database (S200).

Then, based on the collected data, the graph data generation module creates graph-type data that is visualized as nodes and relations.

Referring to FIG. 6 , this will be described in more detail.

In the illustrated embodiment, the first database (database A, 54) has two tables (Table A, Table B), and the second database (database B, 55) has one table (Table C). Table A contains 4 fields, Table B contains 3 fields, and Table C contains 4 fields.

When the user computer terminal accesses the database having this structure, the user interface 200 displays a list of tables and fields in the database. Although not shown, the metadata of each field is also displayed through the user interface. The user creates a relationship based on the information displayed on this user interface screen.

The data correlation creation module 100 automatically generates the correlation query by simply selecting the fields of each table by the user using an input means of the user's computer terminal, for example, a mouse and connecting them by drag and drop.

In the illustrated example, field 3 in table A is selected and dragged and dropped to field 2 in table B. Then, in response to the drag-and-drop, the data association relationship creation module creates an association relationship between field 3 of table A and field 2 of table B. Similarly, as field 2 was selected in table B, it was dragged and dropped to field 2 and field 4 in table C, respectively. Then, in response to this drag-and-drop, the data association relationship creation module creates an association relationship between field 3 of table A and field 2 of table B.

The query generated in FIG. 6 can be represented by two key and value pairs as follows.

Key: TableA.Field3 | Value: TableB.Field2

Key: TableB.Field2 | Value: {TableC.Field2, TableC.Field4}

The relationship between fields can be set as an n:n relationship. That is, a field list can be entered in the value value paired with the field name corresponding to the key value.

7 shows an example of a screen configuration of the user interface 200 according to a preferred embodiment of the present invention.

In this embodiment, as shown, the user interface 200 includes a relation setting screen 210 and a table view screen 220 . A drag and drop event occurs on the table view screen 220 .

In order to effectively create drag and drop, information about the data contained in the field is required. Therefore, when the indicator 201 of the input means (eg, a mouse cursor) is located in a specific field, metadata for the field corresponding to the corresponding position is displayed in such a way that the mouse is over. In the illustrated example, the indicator 201 is located in field 4 of table A 54a, and then metadata for field 4 of this table A is displayed as a mouse-over screen 221 . For example, although the data type and the range of values that can be stored are displayed as metadata, this is not necessarily the only metadata displayed.

Users look at this metadata to determine if it is a required field. In the scenario, you saw the metadata for field 4, but it wasn't the field you needed. As a result of checking other metadata, field 3 of table A 54a is selected, dragged, and dropped to field 2 of table B 54b to establish an association.

The user may set the range of graph-type data received as a result by using the relation setting screen 210 . For example, if you select only the case where the field values are the same, you can receive only the cases where the field values exactly match when you create an association query on the table. If you input as a range setting, the result is received together until there is an overlapping value within the entered range.

That is, according to a setting event on the relation setting screen 210 , a relation of graph-type data corresponding to a data correlation according to a drag-and-drop event may be determined.

Finally, let's summarize the data relation creation system of the database of the present invention once again.

The present invention is a system and method for establishing a relationship between fields based on a user's request given in real time through a user interface, analyzing the relationship between the set fields, extracting connection information of data, and then converting it into a graph database. Users can easily create data-related queries by drag and drop through the metadata provided by the system, and based on this query, extract data connection relationships to create graph-type data results.

In order to realize the above functions and configurations, the data correlation creation module 100 operates. As shown in FIG. 8 , as described above, the metadata generating module 110 generates metadata having information about data when data is stored. The generated metadata information may be stored in the metadata database 56 . Metadata mainly includes data type and table information. Therefore, the data type (int, long, double, string, boolean) can be extracted based on the value stored in the field. The table information includes a database location, a table name/field name, and a table creation time.

The data collection module 120 includes a connector for inquiring a connected database table and a database query. Creates a select query that can inquire the values of the table in which the association relationship is set. Also, in the illustrated example, since the user has selected all fields in Table A, Table B, and Table C, a query that can access DatabaseA (54) and DatabaseB (55) is created. The record data stored in the table is collected by the query generated by the data collection module 120 .

The graph data generation module 130 extracts only data in which the relationship input by the user is established based on the connection relationship query passed through the user interface. Save the field value and the path of the field (database name-table name-record id value) as a node of the graph and give it a unique id value. In addition, the relationship information is saved as a graph relation and a unique id value is given. The resulting data in the form of a graph is visualized through the user interface.

For reference, the user interface method for generating data correlation in a graph database according to an embodiment of the present invention may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the present invention, or may be known and available to those skilled in the art of computer software.

Examples of computer-readable media include hard disks, magnetic media such as floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floppy disks, and ROM, RAM, A hardware device specifically configured to store and execute program instructions, such as flash memory, may be included. Examples of program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

The protection scope of the present invention is not limited to the description and expression of the embodiments explicitly described above. In addition, it is added once again that the protection scope of the present invention cannot be limited due to obvious changes or substitutions in the technical field to which the present invention pertains.

Claims (6)

(a) accessing, by the user computer terminal, one or more databases made of a set of a plurality of tables having a plurality of fields, which are items for storing data;
(b) displaying, by the server, one or more tables of the first database and one or more tables of the second database through the user interface of the user computer terminal (the tables of the first database and the tables of the second database are each make the field visible);
(c), by the server, when the indicator of the input means of the user computer terminal is located in a specific field, displaying metadata for the field corresponding to the corresponding position in a mouse-over manner;
(d) the input means of the user computer terminal selects a specific field of the table of the first database from the user interface and drags and drops it to a specific field of the table of the second database, or dragging and dropping a specific field to a specific field in the table of the first database by selecting a specific field;
(e) causing the data affinity creation module to automatically generate an affinity query corresponding to the drag-and-drop event;
(f) collecting, by the data collection module, data stored in the field selected according to the correlation query from the database;
(g) A user interface method for creating a data correlation in a graph database, further comprising the step of generating graph-type data expressed by nodes and relations based on the data collected by the graph data generation module. delete delete delete delete delete

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