KR100413967B1 - Method of interpretation and transformation of nested dataset on navigation-based data model - Google Patents

Abstract

1. TECHNICAL FIELD OF THE INVENTION

The present invention relates to a method for interpreting and converting a superimposed data set according to a navigational data model and a computer readable recording medium having recorded thereon a program for realizing the method.

2. Technical problem to be solved by the invention

The present invention provides a method for interpreting and converting a nested dataset according to a navigation-based data model that can effectively provide a sequential access to a dataset having a nested structure satisfying a condition in a storage system. It is an object of the present invention to provide a computer-readable recording medium having recorded thereon a program for realizing the method.

3. Summary of Solution to Invention

The present invention relates to a method for interpreting and converting a nested dataset applied to an apparatus for converting a nested dataset in a navigation-based cursor, comprising: extracting a group from a path expression specified in a search clause and applying the group to a specification list to be used by the cursor; ; A second step of performing a navigation based on the applied specification list to form a standardized data set; And a third step of accessing actual data through a catalog based on the configured specification list.

4. Important uses of the invention

The present invention is used for communication service control and the like.

Description

Method of interpretation and transformation of nested dataset on navigation-based data model

The present invention relates to a method for interpreting and converting a superstructure dataset according to a navigation-based data model. More particularly, the present invention relates to a dataset having a superimposed structure existing within a searched result in a two-dimensional structure. The present invention relates to a method for interpreting and converting a nested-structured dataset based on a navigational data model that can provide a formalized approach and interface to nested datasets.

In general, a cursor is a structure used for sequential access operations on a dataset, which is a collection of data that meets a given query condition. Here, the sequential access operation is necessary because the database system basically handles a set of data, whereas the general-purpose programming language does not support or support a separate means of dealing with a set. Because there are many restrictions. In other words, general-purpose programming languages use a cursor scheme to solve the limitation of not being able to directly maintain / access the entire result obtained as a result of operations on the dataset. In addition, some solutions have been proposed when the structure of a dataset is a combination-structured structure with a basic type. However, a structure that can repeatedly include other datasets within itself, such as the dataset, is very complicated. . Thus, in general-purpose programming languages, it is very difficult to specify their size or limit for structures in which datasets can overlap.

In recent years, there have been a number of ways to solve this problem. First, there may be a way to support this in programming languages that use datasets. However, this method places a heavy burden on the user on memory limitations and operational algorithms. In other words, there is a problem in that the efficiency of storage space is reduced by operating separate memory allocation and writing of algorithms for operating datasets of unknown size and structure.

The second way is to create a temporary dataset to store this structure in the database and provide it as a unit at the user's request. Currently, there is a general method for dealing with multiple datasets, but this method also has a problem in that space utilization for additional memory allocation is reduced.

Finally, there is a way to navigate using related catalogs without physically storing nested datasets. Because this method does not physically store the nested datasets, it does not use additional memory and also reduces the time cost for doing so. However, in order for this method to be effective, all datasets must be directly accessible, and the complexity of the application program due to the configuration of pointers increases.

Accordingly, the present invention has been proposed to solve a conventional problem, and is used to provide sequential access to a dataset that satisfies a condition in a storage system that resides in the main memory and guarantees the referential integrity to the object identifier. It is an object of the present invention to provide a method of interpreting and converting a superimposed structure dataset in a navigation-based data model and a computer-readable recording medium recording a program for realizing the method.

1A to 1B are diagrams illustrating an embodiment of a system for interpreting and converting a superstructure dataset in a navigation-based data model to which the present invention is applied.

2 is a diagram illustrating an embodiment of a dataset configuration and a result of a user query in a method for interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

3A to 3C are flowcharts illustrating one embodiment of performing a dataset related query in a method of interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

4 is a flow diagram of an embodiment of a main function for structured dataset in a method of interpretation and transformation of a superstructure dataset in a navigational data model according to the present invention.

5 is a flow diagram of an embodiment of navigation control of a group in a method for interpreting and converting a superstructure dataset in a navigation based data model according to the present invention.

6 is a flowchart illustrating an embodiment of reconstruction control of an aggregate element in a method of interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

7 is an embodiment flow diagram for the calculation of the next navigation position in a method of interpretation and transformation of a superstructure dataset in a navigation based data model in accordance with the present invention.

In order to achieve the above object, the present invention provides a method for interpreting and converting a superstructure dataset applied to an apparatus for interpreting and converting a superstructure dataset in a navigation-based cursor, and extracting a group from a path expression specified in a search clause. A first step of applying the specification list to be used by the cursor; A second step of performing a navigation based on the applied specification list to form a standardized data set; And a third step of accessing actual data through a catalog based on the configured specification list.

Meanwhile, the present invention provides a first function of extracting a set group from a path expression specified in a search clause and applying it to a specification list to be used by a cursor in a dataset analysis and conversion system having a processor for interpretation and conversion of a superstructure dataset. ; A second function of performing a navigation based on the applied specification list to form a standardized data set; And a computer readable recording medium having recorded thereon a program for realizing a third function of accessing actual data through the catalog based on the configured specification list.

The objects, features and advantages described above will become more apparent from the following detailed description taken in conjunction with the accompanying drawings. Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1A to 1B are exemplary embodiments of a system for interpreting and converting a superstructure dataset in a navigation-based data model to which the present invention is applied.

As shown in FIGS. 1A and 1B, the data application program 101 performs a query through a client terminal. At this time, the query is transmitted to the data server 103 via the Internet. Here, the data server 103 includes a cursor 108 to access the data set as mounted in the main memory 104 of the system 102. That is, the data server 103 receives a query from the data application program 101, at which time the query is parsed through the query processor 107. Here, the parsed query is analyzed by the data server 103 and the result is extracted from the main memory 104 and forwarded to the data application program 101.

In this case, when the result transmitted to the data application program 101 is several objects, the data is divided into several times through the cursor 108.

In this case, the cursor 108 checks whether the condition specified by the specification list 111 and the application program 105, which is meta information about the data sets maintained by the cursor, is satisfied and checks all the conditions presented. Evaluate condition evaluator 112 to evaluate, dataset accessor 110 to provide access to dataset 114, and dataset extraction to formalize and deliver the atypical result dataset to application 105 Section 109.

Herein, the information in the specification list 111 indicates a name, an attribute number, an alias, etc. of a dataset or table related to the information between the datasets. These are extracted from the catalog 115 which maintains meta information for all datasets in the main memory 104.

2 is a diagram illustrating an embodiment of a dataset configuration and a result of a user query in a method of interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

As shown in FIG. 2, the first dataset 220 is configured to have an object identifier type that refers to an object in the data set 221, 222 that is different from the primitive data type. In addition, the single object identifier type 202 in the first data set 220 refers to one object in another or its own data set, and the set object identifier type 204 refers to a plurality of objects.

Here, the reference through the object identifier type means joining with the data set, and uses the path operator 207 to refer to another object through the object identifier.

In this case, the path operator 207 is used to refer to an object of another data set not included in its own data set, and may also be used to repeatedly refer to another object through object identifiers 202 and 204 in the object. Can be. These details are stored in the dataset catalog 115. At this time, the catalog information is used after extracting the information required when configuring the cursor is stored in the specification list (111).

User queries are defined to use navigational modeling, to easily access and obtain results from multiple datasets residing on main memory, and to be extended based on standard SQL'92. The user query is defined to have one basic dataset, that is, the first dataset 220. Here, the first dataset 220 is a starting point of all object references.

In addition, the first dataset 220 has a comparison clause 206 for selecting an object to be extracted and a search clause 203 for obtaining a specific attribute of the selected object. The comparison clause 206 is a set of expressions having a comparison operator and a value to be compared, and only data that satisfies all of them becomes a result of the query. Here, the module for verifying and evaluating the expression is not the main content of the present invention, but the main content of the present invention is how to format the data set obtained as a result of the evaluation. Therefore, the comparison clause is not mentioned separately.

That is, when the operator 204 for the nested structure is used in the search clause 203, the result is that it is another dataset or a set of datasets 202. For example, a dataset α that satisfies all the conditions of the comparison clause 206 has two datasets 207 in the second dataset 221 as values, and again the dataset β 208 is another dataset. You can have them as values.

Therefore, the specification list 111 has a result of parsing a query, and the main information includes an input path to an object (or data) in the dataset and an output path to another dataset object, and the current information in the dataset. The object identifier that is the target of the task (if the target of the current task in the first dataset has the object identifier α in the first dataset, it also contains information about whether it was used in the comparison or search clauses), The dataset, route ID, and alias are the main information used when navigating the dataset. In addition, the superimposition structure in the basic data set is designated by a set group (a2 or a3 of?) 209, and the other superimposition structure by the set element (b2 of? Or c2, d2, etc.) 210.

Hereinafter, with reference to the accompanying Figures 3 to 7 will be described in detail with respect to the analysis and conversion method of the superimposed structure data set according to the navigation-based data model according to the present invention.

3A to 3C are flowcharts illustrating one embodiment of performing a dataset related query in a method of interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

As shown in FIG. 3A, first, when a query is input to the data server 103 (301), it is determined whether the query is a fetch command (302). If it is determined in step 302 that the query is not an extraction operation, a basic data set for the query is extracted (303), and it is determined whether the query requires a cursor (305).

As a result of the determination in step 302, when a cursor is required, a cursor having general information about a comparison clause / search clause is generated (307). When the generation of the cursor is completed in step 307, initialization for executing a query is performed (308).

On the other hand, as a result of the determination in step 305, if the query does not require a cursor, the query is executed directly (306), and the loop ends.

On the other hand, if it is determined in step 302 that the query is an extraction operation, that is, if the query type is an extraction operation for an already initialized cursor, the data application program 105 after reconstructing the result data set using the initialized cursor (304).

Here, the process of [re] configuring the result data set using the initialized cursor and returning it to the data application 105 will be described in detail with reference to FIG. 3B.

As shown in FIG. 3B, when performing a return to the data application 105 after reconstructing the result data set (304), it is first determined whether a set group exists (309). As a result of the determination in step 309, if there is a set group, the set group is navigated to extract a result data set suitable for the condition (310). If the set group does not exist, the comparison clause [E] is used to determine the current state. Extract the dataset of 312. The result extracted in the processes 312 and 310 is given to the user after the preprocessing operation to return (311).

Meanwhile, a process of generating a cursor having general information about the comparison clause / search clause in the process 307 will be described in detail with reference to FIG. 3C.

As shown in FIG. 3C, in order to generate a cursor, a basic data set is first extracted (313), and information about expressions in the comparison clause is extracted using the extracted basic data set and added to the specification list (314). . At this time, it is determined whether there is a search clause in the information extracted in step 314 (315).

As a result of the determination in step 315, if there is a search clause, attribute information is extracted from the search clause, that is, entry information is extracted and added to the specification list (316). Here, the added result specification list includes information such as a data set ID, a path ID, and an alias as information used in FIGS. 5 to 7 to be described later. In this case, if there is an analysis result set group of the search clause, it is reflected in the cursor (317).

FIG. 4 is a flow diagram of an embodiment of a main function for structured dataset in a method for interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

That is, FIG. 4 is a detailed flowchart of the main process 310 for extracting a result data set suitable for a condition. First, a final group set is extracted for a configured cursor (401). The group indicator is calculated from the extracted group set (402), and the navigation is performed to extract a suitable data set on the set group using the current group indicator (403). Then, it is determined whether the post-navigation state is a state of finding a suitable data set (404).

As a result of the determination in step 404, if the extracted dataset is currently found to be a suitable dataset, the dataset of the current state is returned, and as a result, the dataset is returned to the user (405).

As a result of the determination in step 404, if the extracted dataset is not currently in a state of finding a suitable dataset, that is, in a state in which it is necessary to search the previous aggregation group, it means that navigation to the previous aggregation group is required. Therefore, it is determined whether the previous aggregation group exists (406).

As a result of the determination in step 406, if the previous set group does not exist, it returns a state indicating that all possible navigation to the current data set is completed (407). The result is reflected in the specification list for the path to be initialized for the aggregate element in the aggregation group (408), and the initialization is performed again to the situation before the voyage (409). The new group will then begin sailing. To this end, the process returns to step 420 again to repeat the loop.

FIG. 5 is a flow chart of an embodiment of a navigation control of a group in a method for interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

That is, FIG. 5 is a detailed flow of navigation performance for dataset extraction described in the above-described process 403. First, a dataset and a path are extracted from a given group indicator (501). In operation 502, it is determined whether the type of the extracted route, that is, the target route to be navigated is the object identifier format DB_REF.

As a result of the determination in step 502, since the current route cannot be navigated when the route is in the form of an object identifier, the next position to be navigated is calculated at the present time (504). In operation 505, it is determined whether the navigation of the previous aggregation group is necessary based on the result of the calculated position. As a result of the determination in step 505, if the navigation of the previous aggregation group is required, the previous aggregation group returns a necessary state (506), and if the navigation of the previous aggregation group is not necessary, whether navigation is possible within the current group. Determine (507).

As a result of the determination in step 507, if the navigation is possible within the current group, the result extraction is returned (508), and if the navigation is not possible within the current group, the group indicator obtained is set again (509). In step 501, the loop is repeated to calculate the next navigation position.

Here, iterative execution of the loop ends by either navigating in the current group or returning a voyage request for the previous group.

That is, as a result of the determination in step 502, if the path is not in the form of an object identifier, it is again determined whether there is an element to navigate by examining the number of elements in the set. As a result of the determination in step 503, if there is no element to navigate, as in the case where the object to be navigated was the object identifier, the process proceeds to step 504 to find the next position to sail at the present time (504). If there is, it is determined whether the navigation of all elements is completed (510).

As a result of the determination in step 510, when the navigation of all elements is completed, the data set and the path are reinitialized again (511), and it is determined whether the initialized set exists in the path shared with the condition clause (512). ).

As a result of the determination in the process 512, if it exists in the path shared with the condition clause, the navigation cannot proceed. Therefore, the process proceeds to the process 506 and requests the navigation through the initialization of the previous set group, and if it exists in the path shared with the condition clause. If not, the process proceeds to step 504 to find the next position to sail and performs the process of sailing.

On the other hand, as a result of the determination in the process 510, if all the elements are completed navigation means that there is an object that has not yet been approached, after initializing the elements (513), the process proceeds to the process (508) is successful Returns status.

6 is a flowchart illustrating an embodiment of reconstruction control of an aggregate element in a method of interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

That is, FIG. 6 is a detailed flowchart of performing initialization for the aggregation element described in operation 513 in FIG. 5. First, an alias is extracted from the aggregation element to perform initialization, and the format of the extracted alias is performed. Determine (602).

As a result of the determination in step 602, if the extracted alias is in the form of an object identifier, an object identifier in the alias is extracted (608). If the extracted alias is in the form of an object identifier set type (DB_SET), the object is extracted from the alias. The object identifier set is opened with the identifier (603). At this time, the state of the object identifier set opened in step 603 is examined to determine whether the object identifier set is currently open for the first time (604).

As a result of the determination in step 604, in the case of the object identifier set currently opened for the first time, the number of elements of the object identifier set is read and set, and the element index to be accessed is initialized to 1 (605), which is indicated by the current element index. The object identifier is extracted (606), and if it is not the first set of currently opened object identifiers, an object identifier indicated by the current element index is immediately extracted (606).

Meanwhile, the individual identifier extracted in step 606 increases the current element index number by 1 for the next navigation (607). Once the object identifiers have been extracted (607, 608), the target dataset to be initialized from the alias and the alias is extracted (609), using them to initialize all the paths associated with the alias of the dataset (610).

Meanwhile, the process 608 also extracts the object identifier in the alias and proceeds to process 609 to extract the target dataset and the alias to be initialized (609), and uses them to all paths related to the alias of the dataset. In operation 610, the initialization is performed.

7 is a flowchart illustrating a method of calculating a next navigation position in a method of interpreting and converting a superstructure dataset in a navigation-based data model according to the present invention.

That is, FIG. 7 is a detailed flowchart of a process 504 of calculating a next position to navigate from the present time of FIG. 5. First, a dataset and a path are extracted from a given group indicator (701), and the extracted dataset and The alias is extracted from the route information (702). Then, it is determined whether the extracted alias is shared with the conditional clause (703).

As a result of the determination in step 703, if the extracted nickname is shared with the condition clause, it is not the object of navigation but there is a new route starting in the nickname, and thus it is determined whether there is a route not yet approached (704).

If it is determined in the process 704 that there is no route yet to be approached, that is, if all the routes are all approached, it is impossible to navigate in the current aggregation group. Therefore, the navigation request for the previous aggregation group is requested (705). If there is a path that does not exist, after initializing the aggregated elements on the corresponding path (705), it is determined whether there is an object to be searched (707).

As a result of the determination in step 707, if there is an object to be searched, it returns a state that there was an object to be searched (708). Returns a status to let the other group begin sailing.

On the other hand, as a result of the determination in step 703, if the nickname of the data set is not shared with the conditional clause, the path index is increased by one step (709), and the target path to be considered next is extracted (710). In operation 711, it is determined whether the target path is in the form of an object identifier.

If it is determined in step 711 that the target route is an object identifier type, the process proceeds to step 702 to repeat the process of finding the next navigation position, and if the determination result is not the object identifier type (ie, the object Identifier set type), and determine whether all paths have been accessed (712).

As a result of the determination in step 712, if there is an element that is not yet approached, after initializing the corresponding path (713), the process proceeds to the step 702 to find the next navigation position along with the calculated path. Repeat again.

In addition, if it is determined in the process 712 that there is no accessible path, that is, if there is a result data set, the final state is reflected in the specification list (714), and the process proceeds to the process (708). Returns a status that the extraction was successful.

The method of the present invention as described above may be implemented as a program and stored in a computer-readable recording medium (CD-ROM, RAM, ROM, floppy disk, hard disk, magneto-optical disk, etc.).

The present invention described above is not limited to the stated embodiments and the accompanying drawings, and it is common in the art that various substitutions, modifications, and changes can be made without departing from the technical spirit of the present invention. It will be evident to those who have knowledge of.

As described above, the present invention can be used as a method for guaranteeing real-time for query processing having complex and nested data structures in communication applications. For this purpose, all databases must reside in main memory, and When creating a cursor needed for a query, instead of creating an additional temporary dataset, a navigation method using an object identifier for an object is used to prevent the waste of storage space caused by building an additional dataset, thereby effectively using the storage space. It has the effect of shortening the time.

Claims (7)

A method of interpreting and converting a dataset in a navigation-based cursor to be rescued to ensure real-time based on overlapping / inherited datasets and catalog information thereof that reside in the main memory, A first step of extracting a set group from a path expression specified in a search clause from a relationship between data sets having an overlap / inheritance structure and generating a specification list for use by a cursor; A second step of constructing a standardized data set by performing an optimized voyage according to an approach on the main memory to ensure real-time based on the applied specification list; And A third step of accessing the actual data residing in the main memory through the catalog based on the configured list of specifications Analysis and transformation method of the superstructure dataset according to the navigation-based data model comprising a. The method of claim 1, wherein the first step, Parsing the comparison result search clause, extracting path information from the overlapping / inheritance structure between the datasets, and adding an additional attribute of the alias to the specification list according to the format of the path and whether or not it is shared with the comparison clause; And A fifth step of extracting a set group and its number based on the added additional attributes and applying the same to a specification list to be used for a cursor supporting a navigation-based model; Analysis and transformation method of the superstructure dataset according to the navigation-based data model comprising a. The method of claim 1, wherein the second step, A fourth step of determining a target group to navigate by optimizing access to a data set on the main memory; And A fifth step of constructing the most recent data shape that satisfies all the conditional clauses as a formalized data set by recursively navigating the data set according to the overlapping / inheritance structure for each of the determined target group groups Analysis and transformation method of the superstructure dataset according to the navigation-based data model comprising a. The method of claim 1, wherein the third step, A fourth step of obtaining an actual object identifier from an alias in the specification list; And Extracting an offset and a size of an attribute obtained from a catalog specification list and combining the object identifier with the object identifier to access actual data of the data set on the main memory; Analysis and transformation method of the superstructure dataset according to the navigation-based data model comprising a. The method of claim 3, wherein the fourth step, A sixth step of extracting an object identifier set having one or more elements present in the basic data set from the navigation-based model allowing the overlapping structure to determine the aggregation group; And Step 7 of Determining a Set Group by Extracting an Object Identifier That Has One or More Output Paths to an Object Identifier Set That Is More Than One Object Identifier Set Analysis and transformation method of the superstructure dataset according to the navigation-based data model comprising a. The method of claim 3, wherein the step 5, A sixth step of terminating the navigation and storing the state of the cursor when the navigation is possible for the current aggregation group; A seventh step of extracting the next navigable group group if the navigator is not available for the current group group; An eighth step of initializing an aggregate element while actually navigating in the extracted aggregate group; And The ninth step of finding a next navigation time within the group group and repeatedly performing the sixth to eighth steps to form a standardized data set Analysis and transformation method of the superstructure dataset according to the navigation-based data model comprising a. delete