CN103678590A - Report collecting device and report collecting method based on OLAP - Google Patents
Report collecting device and report collecting method based on OLAP Download PDFInfo
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Abstract
The invention provides a report collecting device based on OLAP. The report collecting device based on the OLAP comprises a multi-dimensional model fast establishing module, a multi-dimensional model and report area mapping module and a data extracting module. According to the multi-dimensional model fast establishing module, service operation is selected, and a multi-dimensional model is generated fast according to selected service operation information. According to the multi-dimensional model and report area mapping module, based on the established multi-dimensional model, the mapping between the multi-dimensional model and a report area is set through a dragging mode, and a mapping area is generated according to a mapping relation set through the mapping. According to the data extracting module, based on the generated mapping area, the mapping area is converted into multi-dimensional inquiry statements to carry out multi-dimensional inquiry, and inquiry results are filled in a report. The invention further provides a report collecting method based on the OLAP. By means of the technical scheme, based on the existing report collecting modes, the report collection of multi-object data can be completed by fully utilizing single-object data, and a general and uniform collecting concept is established, wherein multi-object data are involved in the general and uniform collecting concept, and the general and uniform collecting concept is oriented to scattered data report collection and independent data report collection.
Description
Technical field
The present invention relates to field of computer technology, particularly, relate to a kind of form harvester and a kind of form acquisition method based on OLAP based on OLAP.
Background technology
At present, most medium-and-large-sized enterprises and institutions have set up the Back ground Information systems such as fairly perfect ERP, CRM, OA, and these systems are all typical OLTP system substantially, for enterprise has accumulated a large amount of data.But these data be disperse, separate, stored in database, for business personnel, these data are the books from heaven that cannot understand.How these data are integrated and are converted to data analysis or the collection of business meaning? for this point, existing product is mostly to solve by multi-dimensional query, but the subject matter existing has:
(1) build multidimensional model too complicated: multidimensional model building process is too complicated, and the technology and concept that multidimensional model is related to is exposed to user, can not go out fast multidimensional model;
(2) multidimensional model can not be applied to collection form: existing product mainly lays particular emphasis on analytical statement, and multi-dimensional query technology is applied to, does not gather in form.
How by dispersion, independently data are integrated, and by the data rapid extraction after integrating to gathering form? solution need to be proposed.
Therefore, need a kind of new form acquisition technique based on OLAP, can be on existing form acquisition mode basis, make full use of the form collection that single object data complete multi-object data, set up general, the unified thinking that gathers gathering towards dispersion, independent data form that multi-object data participate in.
Summary of the invention
The present invention is just based on the problems referred to above, a kind of new form acquisition technique based on OLAP has been proposed, can be on existing form acquisition mode basis, make full use of the form collection that single object data complete multi-object data, set up general, the unified thinking that gathers gathering towards dispersion, independent data form that multi-object data participate in.
In view of this, the present invention proposes a kind of form harvester based on OLAP, comprise: multidimensional model rapid build module, for the business operation of selecting to comprise service profile, accounting period, tolerance, Data Source, generates multidimensional model fast according to the business operation information of selecting; Multidimensional model and form region mapping block, for the multidimensional model based on described multidimensional model rapid build module construction, carry out the mapping settings in multidimensional model and form region by pulling mode, according to the mapping relations of mapping settings, generate mapping area; Data extraction module, the mapping area for based on described multidimensional model and the generation of form region mapping block, is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled in form.In this technical scheme, by the mode rapid build multidimensional model of service-oriented, by multidimensional model and collection form region mapping mode, data are extracted and gathered in form, can reduce the complexity that multidimensional model builds.
In technique scheme, preferably, described multidimensional model rapid build module, specifically comprises: interface arranges module, for the business operation of selecting to comprise service profile, accounting period, tolerance and Data Source; Multidimensional model builds module, for obtaining described interface, the business operation that module is selected is set, and the business operation based on obtaining builds multidimensional model.
In technique scheme, preferably, described multidimensional model builds the operation that the business operation of module based on obtaining builds multidimensional model, specifically comprises: according to the service profile in described business operation, generate dimension, and automatically generate level and the rank of dimension; The corresponding data table of described service profile forms dimension table, the value on the Major key dimension of service profile, the displayed value on the name-value dimension of service profile; According to the rise time accounting period dimension in described business operation, and a plurality of ranks of rise time dimension; According to the tolerance in described business operation, generate tolerance; According to the service profile in described business operation, tolerance and Data Source, generate fact table; According to the described dimension, time dimension, tolerance and the fact table that generate, generate cube.
In technique scheme, preferably, described multidimensional model and form region mapping block, specifically comprise: mapping settings module, for obtaining multidimensional model and the predefined collection form of described multidimensional model rapid build module construction, by pulling mode, the mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form are arranged; Mapping area generation module, for the mapping relations that arrange based on described mapping settings module, generates mapping area.
In technique scheme, preferably, the operation that described mapping settings module arranges the mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form by pulling mode, specifically comprise: pull the dimension member of multidimensional model and tolerance to left side or the top of the storage unit setting in advance, be fixed mapping area; Pull the dimension member of multidimensional model and tolerance to the top of the storage unit setting in advance, mapping area is expanded; Dimension in described expansion mapping area and multidimensional model is shone upon to the foundation that described dimension is expanded for expansion mapping area; And the mapping relations that described mapping area generation module arranges based on described mapping settings module, generate the operation of mapping area, specifically comprise: the set of obtaining the mapping relations that arrange in described mapping settings module and all storage unit that set in advance; From the set of described all storage unit, choose a storage unit that index cell is corresponding, from described mapping relations, choose the ranks dimension of this storage unit mapping, and whether this ranks dimension of verification is legal: if legal, obtain already present mapping area list, and judge whether this mapping area list to join existing mapping area: if add, respective memory unit added to mapping area and regenerate regional extent; If do not add, generate new mapping area, add mapping area list corresponding to this new mapping area; If illegal, judge whether all to travel through storage unit; If all traversal, finishes the operation that this generates mapping area; If all do not travel through, choose storage unit corresponding to next index cell and process from the set of described all storage unit; And/or, described data extraction module is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled into the operation in form, specifically comprise and calculate the operation of fixed area and the operation of calculating extended area, wherein: the operation of described calculating fixed area, comprise according to row dimension corresponding to mapping area or the row dimension rule of classification of coupling whether completely, mapping area is divided into groups, and carry out data extraction by group; In described rule of classification, if row dimension is mated completely, while splicing multi-dimensional query statement, row dimension is expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension is expanded; The described operation of carrying out data extraction by group, specifically comprises: a plurality of mapping area are merged into a computing unit; Splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; Query Result is split by mapping area; Executing data is filled; The operation of described calculating extended area, specifically comprises: obtain the dimension of shining upon in extended area; Splicing multi-dimensional query statement: mapping area is mapped in to the dimension that lists as row dimension, using all member's dimensions of shining upon in extended area as row dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; The expansion of execution extended area; Executing data is filled.
According to a further aspect of the invention, a kind of form acquisition method based on OLAP has also been proposed, comprise: step 202: the business operation that selection comprises service profile, accounting period, tolerance, Data Source, generates multidimensional model fast according to the business operation information of selecting; Step 204: the multidimensional model building based on described step 202, the mapping area of carrying out the generation in multidimensional model and form region by pulling mode, is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled in form.In this technical scheme, by the mode rapid build multidimensional model of service-oriented, by multidimensional model and collection form region mapping mode, data are extracted and gathered in form, can reduce the complexity that multidimensional model builds.Mapping settings, generates mapping area according to the mapping relations of mapping settings; Step 206: based on described step 204
In technique scheme, preferably, described step 202, specifically comprises: the business operation that selection comprises service profile, accounting period, tolerance and Data Source; Obtain the business operation of above-mentioned selection, the business operation based on obtaining builds multidimensional model.
In technique scheme, preferably, the described business operation based on obtaining builds the operation of multidimensional model, specifically comprises: according to the service profile in described business operation, generate dimension, and automatically generate level and the rank of dimension; The corresponding data table of described service profile forms dimension table, the value on the Major key dimension of service profile, the displayed value on the name-value dimension of service profile; According to the rise time accounting period dimension in described business operation, and a plurality of ranks of rise time dimension; According to the tolerance in described business operation, generate tolerance; According to the service profile in described business operation, tolerance and Data Source, generate fact table; According to the described dimension, time dimension, tolerance and the fact table that generate, generate cube.
In technique scheme, preferably, described step 204, specifically comprises: obtain described multidimensional model and the predefined collection form of structure, by pulling mode, the mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form are arranged; Described mapping relations based on arranging, generate mapping area.
In technique scheme, preferably, the described operation mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form being arranged by pulling mode, specifically comprise: pull the dimension member of multidimensional model and tolerance to left side or the top of the storage unit setting in advance, be fixed mapping area; Pull the dimension member of multidimensional model and tolerance to the top of the storage unit setting in advance, mapping area is expanded; Dimension in described expansion mapping area and multidimensional model is shone upon to the foundation that described dimension is expanded for expansion mapping area; And the described mapping relations that arrange based on described mapping settings module, generate the operation of mapping area, specifically comprise: the set of obtaining mapping relations with all storage unit that set in advance of setting; From the set of described all storage unit, choose a storage unit that index cell is corresponding, from described mapping relations, choose the ranks dimension of this storage unit mapping, and whether this ranks dimension of verification is legal: if legal, obtain already present mapping area list, and judge whether this mapping area list to join existing mapping area: if add, respective memory unit added to mapping area and regenerate regional extent; If do not add, generate new mapping area, add mapping area list corresponding to this new mapping area; If illegal, judge whether all to travel through storage unit; If all traversal, finishes the operation that this generates mapping area; If all do not travel through, choose storage unit corresponding to next index cell and process from the set of described all storage unit; And/or, describedly mapping area is converted to multi-dimensional query statement carries out multi-dimensional query, and query results is filled into the operation in form, specifically comprise and calculate the operation of fixed area and the operation of calculating extended area, wherein: the operation of described calculating fixed area, specifically comprise: according to row dimension corresponding to mapping area or the row dimension rule of classification of coupling whether completely, mapping area is divided into groups, and carry out data extraction by group; In described rule of classification, if row dimension is mated completely, while splicing multi-dimensional query statement, row dimension is expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension is expanded; The described operation of carrying out data extraction by group, specifically comprises: a plurality of mapping area are merged into a computing unit; Splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; Query Result is split by mapping area; Executing data is filled; The operation of described calculating extended area, specifically comprises: obtain the dimension of shining upon in extended area; Splicing multi-dimensional query statement: mapping area is mapped in to the dimension that lists as row dimension, using all member's dimensions of shining upon in extended area as row dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; The expansion of execution extended area; Executing data is filled.
By above technical scheme, can on existing form acquisition mode basis, make full use of the form collection that single object data complete multi-object data, set up general, the unified thinking that gathers gathering towards dispersion, independent data form that multi-object data participate in.
Accompanying drawing explanation
Fig. 1 shows the block diagram of the form harvester based on OLAP according to an embodiment of the invention;
Fig. 2 shows the process flow diagram of the form acquisition method based on OLAP according to an embodiment of the invention;
Fig. 3 shows the principle schematic of the form harvester based on OLAP according to an embodiment of the invention;
Fig. 4 shows the principle schematic of Multidimensional Data Model example according to an embodiment of the invention;
Fig. 5 shows the principle schematic of the ranks dimension example that obtains according to an embodiment of the invention storage unit mapping from mapping relations;
Fig. 6 shows the process flow diagram of mapping area generation module according to an embodiment of the invention;
Fig. 7 shows the process flow diagram that data are extracted according to an embodiment of the invention;
Fig. 8 shows according to an embodiment of the invention by multidimensional model rapid build module construction multidimensional model exemplary plot;
Fig. 9 shows mapping relations exemplary plot is set according to an embodiment of the invention in mapping settings module;
Figure 10 shows according to an embodiment of the invention by multidimensional model rapid build module construction multidimensional model exemplary plot;
Figure 11 shows according to an embodiment of the invention and extracts data instance figure by data extraction module;
Figure 12 shows balance sheet Mapping Examples figure according to an embodiment of the invention;
Figure 13 shows inner according to an embodiment of the invention credit and debt detail list Mapping Examples figure.
Embodiment
In order more clearly to understand above-mentioned purpose of the present invention, feature and advantage, below in conjunction with the drawings and specific embodiments, the present invention is further described in detail.It should be noted that, in the situation that not conflicting, the application's embodiment and the feature in embodiment can combine mutually.
A lot of details have been set forth in the following description so that fully understand the present invention; but; the present invention can also adopt other to be different from other modes described here and implement, and therefore, protection scope of the present invention is not subject to the restriction of following public specific embodiment.
Fig. 1 shows the block diagram of the form harvester based on OLAP according to an embodiment of the invention.
As shown in Figure 1, form harvester 100 based on OLAP according to an embodiment of the invention, comprise: multidimensional model rapid build module 102, for the business operation of selecting to comprise service profile, accounting period, tolerance, Data Source, according to the business operation information of selecting, generate fast multidimensional model; Multidimensional model and form region mapping block 104, for the multidimensional model based on multidimensional model rapid build module construction, carry out the mapping settings in multidimensional model and form region by pulling mode, according to the mapping relations of mapping settings, generate mapping area; Data extraction module 106, the mapping area for based on multidimensional model and the generation of form region mapping block, is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled in form.In this technical scheme, by the mode rapid build multidimensional model of service-oriented, by multidimensional model and collection form region mapping mode, data are extracted and gathered in form, can reduce the complexity that multidimensional model builds.
In technique scheme, preferably, multidimensional model rapid build module 102, specifically comprises: interface arranges module, for the business operation of selecting to comprise service profile, accounting period, tolerance and Data Source; Multidimensional model builds module, for obtaining interface, the business operation that module is selected is set, and the business operation based on obtaining builds multidimensional model.
In technique scheme, preferably, multidimensional model builds the operation that the business operation of module based on obtaining builds multidimensional model, specifically comprises: according to the service profile in business operation, generate dimension, and automatically generate level and the rank of dimension; The corresponding data table of service profile forms dimension table, the value on the Major key dimension of service profile, the displayed value on the name-value dimension of service profile; According to the rise time accounting period dimension in business operation, and a plurality of ranks of rise time dimension; According to the tolerance in business operation, generate tolerance; According to the service profile in business operation, tolerance and Data Source, generate fact table; According to the dimension, time dimension, tolerance and the fact table that generate, generate cube.
In technique scheme, preferably, multidimensional model and form region mapping block 104, specifically comprise: mapping settings module, for obtaining multidimensional model and the predefined collection form of multidimensional model rapid build module construction, by pulling mode, the mapping relations in the multidimensional model obtaining and the form region corresponding with gathering form are arranged; Mapping area generation module, for the mapping relations that arrange based on mapping settings module, generates mapping area.
In technique scheme, preferably, the operation that mapping settings module arranges the mapping relations in the multidimensional model obtaining and the form region corresponding with gathering form by pulling mode, specifically comprise: pull the dimension member of multidimensional model and tolerance to left side or the top of the storage unit setting in advance, be fixed mapping area; Pull the dimension member of multidimensional model and tolerance to the top of the storage unit setting in advance, mapping area is expanded; Dimension in expansion mapping area and multidimensional model is shone upon to the foundation that dimension is expanded for expansion mapping area; And the mapping relations that mapping area generation module arranges based on mapping settings module, generate the operation of mapping area, specifically comprise: the set of obtaining the mapping relations that arrange in mapping settings module and all storage unit that set in advance; From the set of all storage unit, choose a storage unit that index cell is corresponding, from mapping relations, choose the ranks dimension of this storage unit mapping, and whether this ranks dimension of verification is legal: if legal, obtain already present mapping area list, and judge whether this mapping area list to join existing mapping area: if add, respective memory unit added to mapping area and regenerate regional extent; If do not add, generate new mapping area, add mapping area list corresponding to this new mapping area; If illegal, judge whether all to travel through storage unit; If all traversal, finishes the operation that this generates mapping area; If all do not travel through, choose storage unit corresponding to next index cell and process from the set of all storage unit; And/or, data extraction module 106 is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled into the operation in form, specifically comprise and calculate the operation of fixed area and the operation of calculating extended area, wherein: the operation of calculating fixed area, comprise according to row dimension corresponding to mapping area or the row dimension rule of classification of coupling whether completely, mapping area is divided into groups, and carry out data extraction by group; In rule of classification, if row dimension is mated completely, while splicing multi-dimensional query statement, row dimension is expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension is expanded; By group, carry out the operation of data extraction, specifically comprise: a plurality of mapping area are merged into a computing unit; Splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; Query Result is split by mapping area; Executing data is filled; The operation of calculating extended area, specifically comprises: obtain the dimension of shining upon in extended area; Splicing multi-dimensional query statement: mapping area is mapped in to the dimension that lists as row dimension, using all member's dimensions of shining upon in extended area as row dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; The expansion of execution extended area; Executing data is filled.
Fig. 2 shows the process flow diagram of the form acquisition method based on OLAP according to an embodiment of the invention.
As shown in Figure 2, form acquisition method based on OLAP according to an embodiment of the invention, comprise: step 202: the business operation that selection comprises service profile, accounting period, tolerance, Data Source, generates multidimensional model fast according to the business operation information of selecting; Step 204: the multidimensional model building based on step 202, the mapping area of carrying out the generation in multidimensional model and form region by pulling mode, is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled in form.In this technical scheme, by the mode rapid build multidimensional model of service-oriented, by multidimensional model and collection form region mapping mode, data are extracted and gathered in form, can reduce the complexity that multidimensional model builds.Mapping settings, generates mapping area according to the mapping relations of mapping settings; Step 206: based on step 204
In technique scheme, preferably, step 202, specifically comprises: the business operation that selection comprises service profile, accounting period, tolerance and Data Source; Obtain the business operation of above-mentioned selection, the business operation based on obtaining builds multidimensional model.
In technique scheme, preferably, the business operation based on obtaining builds the operation of multidimensional model, specifically comprises: according to the service profile in business operation, generate dimension, and automatically generate level and the rank of dimension; The corresponding data table of service profile forms dimension table, the value on the Major key dimension of service profile, the displayed value on the name-value dimension of service profile; According to the rise time accounting period dimension in business operation, and a plurality of ranks of rise time dimension; According to the tolerance in business operation, generate tolerance; According to the service profile in business operation, tolerance and Data Source, generate fact table; According to the dimension, time dimension, tolerance and the fact table that generate, generate cube.
In technique scheme, preferably, step 204, specifically comprises: obtain multidimensional model and the predefined collection form of structure, by pulling mode, the mapping relations in the multidimensional model obtaining and the form region corresponding with gathering form are arranged; Mapping relations based on arranging, generate mapping area.
In technique scheme, preferably, the operation mapping relations in the multidimensional model obtaining and the form region corresponding with gathering form being arranged by pulling mode, specifically comprise: pull the dimension member of multidimensional model and tolerance to left side or the top of the storage unit setting in advance, be fixed mapping area; Pull the dimension member of multidimensional model and tolerance to the top of the storage unit setting in advance, mapping area is expanded; Dimension in expansion mapping area and multidimensional model is shone upon to the foundation that dimension is expanded for expansion mapping area; And the mapping relations that arrange based on mapping settings module, generate the operation of mapping area, specifically comprise: the set of obtaining mapping relations with all storage unit that set in advance of setting; From the set of all storage unit, choose a storage unit that index cell is corresponding, from mapping relations, choose the ranks dimension of this storage unit mapping, and whether this ranks dimension of verification is legal: if legal, obtain already present mapping area list, and judge whether this mapping area list to join existing mapping area: if add, respective memory unit added to mapping area and regenerate regional extent; If do not add, generate new mapping area, add mapping area list corresponding to this new mapping area; If illegal, judge whether all to travel through storage unit; If all traversal, finishes the operation that this generates mapping area; If all do not travel through, choose storage unit corresponding to next index cell and process from the set of all storage unit; And/or, mapping area is converted to multi-dimensional query statement and carries out multi-dimensional query, and query results is filled into the operation in form, specifically comprise and calculate the operation of fixed area and the operation of calculating extended area, wherein: the operation of calculating fixed area, specifically comprise: according to row dimension corresponding to mapping area or the row dimension rule of classification of coupling whether completely, mapping area is divided into groups, and carry out data extraction by group; In rule of classification, if row dimension is mated completely, while splicing multi-dimensional query statement, row dimension is expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension is expanded; By group, carry out the operation of data extraction, specifically comprise: a plurality of mapping area are merged into a computing unit; Splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; Query Result is split by mapping area; Executing data is filled; The operation of calculating extended area, specifically comprises: obtain the dimension of shining upon in extended area; Splicing multi-dimensional query statement: mapping area is mapped in to the dimension that lists as row dimension, using all member's dimensions of shining upon in extended area as row dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; The expansion of execution extended area; Executing data is filled.
For example, as shown in Figure 3, the automatic processing procedure of technical solution of the present invention, mainly comprises three parts that are equipped with: multidimensional model rapid build module, multidimensional model and form region mapping block, data extraction module.Be described as follows:
(i) multidimensional model rapid build module
Multidimensional model rapid build module completes the rapid build of multidimensional model, and it is divided into again: interface arranges module, multidimensional model builds module.Interface arranges in module and selects the business operations such as service profile, accounting period, tolerance, Data Source, and the information that multidimensional model structure module arranges in module according to interface generates multidimensional model fast.
The operating process that interface arranges module is as follows: (1) select service profile; (2) select accounting period; (3) select tolerance; (4) select Data Source.
As shown in Figure 4, to build the operating process of module as follows for multidimensional model: (1) obtain interface the information such as service profile in module, accounting period, tolerance, Data Source are set; (2) according to the information architecture multidimensional model of obtaining: 1. generate dimensional information; According to the service profile of selecting, generate dimension, and automatically generate level and the rank of dimension; Dimension table is the tables of data that these archives are corresponding, and the value in dimension is the Major key of these archives, and the displayed value in dimension is the name-value of these archives; 2. rise time dimension; According to rise time accounting period dimension, and a plurality of ranks of rise time dimension; 3. generate tolerance; 4. generate fact table; According to the service profile of selecting, tolerance and Data Source, generate fact table; 5. generate cube.
(ii) multidimensional model and form region mapping block
Multidimensional model and form region mapping block complete the mapping in multidimensional model and form region, and it is divided into again: mapping settings module, mapping area generation module.Mapping settings module is a kind of interface module, first obtains the multidimensional model of multidimensional model rapid build module construction, then by pulling mode, carries out the mapping settings in multidimensional model and form region; Mapping area generation module is a kind of background process device, according to the mapping relations that arrange in mapping settings module, generates mapping area.
The operating process of mapping settings module is as follows: the multidimensional model of (1) obtaining multidimensional model rapid build module construction; (2) obtain defined collection form; (3) carry out the mapping settings in multidimensional model and form region:
1. fixed area: pull the dimension member of multidimensional model and tolerance to left side or the top of storage unit.2. extended area: pull the dimension member of multidimensional model and tolerance to the top of storage unit; By dimension mapping in extended area and multidimensional model, the foundation that this dimension is expanded as expansion area.
As shown in Figure 6, the operating process of mapping area generation module is as follows:
(1) obtain the mapping relations that arrange in mapping settings module; (2) obtain all storage unit set; (3) from set, get a storage unit; (4) from mapping relations, obtain as shown in Figure 5, the ranks dimension of storage unit mapping: 1. row dimension: from this storage unit position, search row dimension left; 2. row dimension: upwards search row dimension from this storage unit position; (5) whether the ranks dimension of verification mapping is legal: 1.: to the (6) step; 2. no: to the (8) step; (6) obtain and had mapping area list; (7) whether can join existing mapping area: 1.: this storage unit is added to mapping area and regenerates regional extent; 2. no: to generate new mapping area, add mapping area list; (8) whether storage unit all travels through: 1.: generate mapping area and finish; 2. no: to the (3) step get next index cell and process.
(iii) data extraction module
First data extraction module obtains the mapping area generating in multidimensional model and form region mapping block, mapping area is converted to multi-dimensional query statement and carries out multi-dimensional query, and query results is filled in form.
The operating process of data extraction module is as follows:
(1) obtain the mapping area generating in multidimensional model and form region mapping block; (2) calculate fixed area:
1. mapping area is divided into groups
A) rule of classification: row dimension or row dimension that mapping area is corresponding are mated completely; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension can be expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension can be expanded.
2. by group, carry out data extraction, as shown in Figure 7:
A) a plurality of mapping area are merged into a computing unit; B) splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; C) multidimensional model secondary processing, rejects useless dimensional information; D) by OLAP engine, carrying out MDX inquires about; E) Query Result is split by mapping area; F) executing data is filled;
(3) calculate extended area;
1. obtain the dimension of shining upon in extended area; 2. splice multi-dimensional query statement: a) mapping area is mapped in to the dimension that lists as axle (row) dimension; B) using the dimension of shining upon in extended area (all members) as axle (OK) dimension; C) will gather the unit of form own, during etc. dimension as food slicer dimension; 3. multidimensional model secondary processing, rejects useless dimensional information; 4. by OLAP engine, carrying out MDX inquires about; 5. carry out extended area expansion; 6. executing data is filled.
And for example, the realization of technical solution of the present invention flows into as follows:
(1) by multidimensional model rapid build module construction multidimensional model, example as shown in Figure 8.
(2) by multidimensional model and form region mapping block, shine upon:
1. mapping relations are set in mapping settings module: as shown in Figure 9, represent dimension member or the tolerance of setting with the cell of words identification, the cell identifying with ' 123 ' represents storage unit.
2. by generating mapping area in mapping area generation module: as shown in figure 10, obtain storage unit set: [B4, C4, D4, E4, B5, C5, D5, E5], according to generating mapping area principle, finally generates two mapping area: B4:C5, E4:E5.
(3) by data extraction module, extract data: as shown in figure 11, B4:C5, E4:E5 mapping area are merged, splicing MDX statement, carries out MDX by OLAP engine and inquire about, and after Query Result is filled, represents.
For another example, as shown in figure 12, inner credit and debt detail list Mapping Examples as shown in figure 13 for the balance sheet Mapping Examples of application technical solution of the present invention.
Technical scheme of the present invention, take a large amount of dispersions that enterprise exists, independently data are basis, rapid build multidimensional model, and fast data are extracted to collection form by multidimensional engine.Adopt technical scheme of the present invention, on the one hand the data of dispersion have been carried out to quick integration and extraction; Also strengthened on the other hand the mode that form carries out data acquisition that gathers.Technical scheme difference with the prior art part of the present invention:
(1) mostly existing report data collection technology is based on formula, storing process, formula is set and sets up that storing process workload is large, difficulty is high, and for disperseing the data of storage to integrate.And technical scheme of the present invention can be integrated existing data of disperseing, and use multi-dimensional query technology that the data after integrating are extracted to collection form; Moreover, technical scheme of the present invention than traditional formula being set, set up the modes such as storing process and be simple and easy to use, can reduce in a large number report data collection workload is set;
(2) the existing product based on OLAP technology mainly lays particular emphasis on statement analysis, and multidimensional technology and concept are come out and increased the complexity that builds multidimensional model.And technical scheme of the present invention has been done structure multidimensional model the encapsulation of service-oriented, based on business operation, generate fast multidimensional model, and multidimensional model and multidimensional technology can be applied to and in form collection, carry out data acquisition, reduce the structure complexity of multidimensional model, and strengthened the mode of report data collection.
Technical scheme of the present invention, can be applicable in form product, by the method, will disperse independently data rapid extraction to arrive collection form.Technical scheme of the present invention, the feature having is: (1), by the mode rapid build multidimensional model of service-oriented, the technology and concept no longer multidimensional model being related to comes out, and only need to carry out simple business operation and can complete multidimensional model structure; Can reduce the complexity that multidimensional model builds; (2) by multidimensional model and collection form region mapping mode, data are extracted and gathered in form; Can so that multidimensional model no longer only for analyzing, and can be for form collection.
More than be described with reference to the accompanying drawings technical scheme of the present invention, considered and in correlation technique, there is no easy, the unified solution gathering for multi-object data sheet.Existing form collection cannot complete the form gatherer process of dispersion, independent data participation.Therefore, the present invention proposes a kind of form harvester and a kind of form acquisition method based on OLAP based on OLAP, can be on existing form acquisition mode basis, make full use of the form collection that single object data complete multi-object data, set up general, the unified thinking that gathers gathering towards dispersion, independent data form that multi-object data participate in.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (10)
1. the form harvester based on OLAP, is characterized in that, comprising:
Multidimensional model rapid build module, for the business operation of selecting to comprise service profile, accounting period, tolerance, Data Source, generates multidimensional model fast according to the business operation information of selecting;
Multidimensional model and form region mapping block, for the multidimensional model based on described multidimensional model rapid build module construction, carry out the mapping settings in multidimensional model and form region by pulling mode, according to the mapping relations of mapping settings, generate mapping area;
Data extraction module, the mapping area for based on described multidimensional model and the generation of form region mapping block, is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled in form.
2. the form harvester based on OLAP according to claim 1, is characterized in that, described multidimensional model rapid build module, specifically comprises:
Interface arranges module, for the business operation of selecting to comprise service profile, accounting period, tolerance and Data Source;
Multidimensional model builds module, for obtaining described interface, the business operation that module is selected is set, and the business operation based on obtaining builds multidimensional model.
3. the form harvester based on OLAP according to claim 2, is characterized in that, described multidimensional model builds the operation that the business operation of module based on obtaining builds multidimensional model, specifically comprises:
According to the service profile in described business operation, generate dimension, and automatically generate level and the rank of dimension; The corresponding data table of described service profile forms dimension table, the value on the Major key dimension of service profile, the displayed value on the name-value dimension of service profile;
According to the rise time accounting period dimension in described business operation, and a plurality of ranks of rise time dimension;
According to the tolerance in described business operation, generate tolerance;
According to the service profile in described business operation, tolerance and Data Source, generate fact table;
According to the described dimension, time dimension, tolerance and the fact table that generate, generate cube.
4. according to the form harvester based on OLAP described in any one in claims 1 to 3, it is characterized in that, described multidimensional model and form region mapping block, specifically comprise:
Mapping settings module, for obtaining multidimensional model and the predefined collection form of described multidimensional model rapid build module construction, by pulling mode, the mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form are arranged;
Mapping area generation module, for the mapping relations that arrange based on described mapping settings module, generates mapping area.
5. the form harvester based on OLAP according to claim 4, it is characterized in that, the operation that described mapping settings module arranges the mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form by pulling mode, specifically comprises:
Pull the dimension member of multidimensional model and tolerance to left side or the top of the storage unit setting in advance, be fixed mapping area;
Pull the dimension member of multidimensional model and tolerance to the top of the storage unit setting in advance, mapping area is expanded; Dimension in described expansion mapping area and multidimensional model is shone upon to the foundation that described dimension is expanded for expansion mapping area; And,
The mapping relations that described mapping area generation module arranges based on described mapping settings module, generate the operation of mapping area, specifically comprise:
Obtain the set of the mapping relations that arrange in described mapping settings module and all storage unit that set in advance;
From the set of described all storage unit, choose a storage unit that index cell is corresponding, from described mapping relations, choose the ranks dimension of this storage unit mapping, and whether this ranks dimension of verification be legal:
If legal, obtain already present mapping area list, and judge whether this mapping area list to join existing mapping area: if add, respective memory unit added to mapping area and regenerate regional extent; If do not add, generate new mapping area, add mapping area list corresponding to this new mapping area;
If illegal, judge whether all to travel through storage unit; If all traversal, finishes the operation that this generates mapping area; If all do not travel through, choose storage unit corresponding to next index cell and process from the set of described all storage unit; And/or,
Described data extraction module is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled into the operation in form, and specifically comprise and calculate the operation of fixed area and the operation of calculating extended area, wherein:
Whether completely the operation of described calculating fixed area, comprise according to row dimension corresponding to mapping area or the row dimension rule of classification of coupling, mapping area divided into groups, and carry out data extraction by group; In described rule of classification, if row dimension is mated completely, while splicing multi-dimensional query statement, row dimension is expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension is expanded;
The described operation of carrying out data extraction by group, specifically comprises: a plurality of mapping area are merged into a computing unit; Splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; Query Result is split by mapping area; Executing data is filled;
The operation of described calculating extended area, specifically comprises: obtain the dimension of shining upon in extended area; Splicing multi-dimensional query statement: mapping area is mapped in to the dimension that lists as row dimension, using all member's dimensions of shining upon in extended area as row dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; The expansion of execution extended area; Executing data is filled.
6. the form acquisition method based on OLAP, is characterized in that, comprising:
Step 202: the business operation that selection comprises service profile, accounting period, tolerance, Data Source, generates multidimensional model fast according to the business operation information of selecting;
Step 204: the multidimensional model building based on described step 202, carries out the mapping settings in multidimensional model and form region, according to the mapping relations generation mapping area of mapping settings by pulling mode;
Step 206: the mapping area generating based on described step 204, is converted to multi-dimensional query statement by mapping area and carries out multi-dimensional query, and query results is filled in form.
7. the form acquisition method based on OLAP according to claim 6, is characterized in that, described step 202, specifically comprises:
The business operation that selection comprises service profile, accounting period, tolerance and Data Source;
Obtain the business operation of above-mentioned selection, the business operation based on obtaining builds multidimensional model.
8. the form acquisition method based on OLAP according to claim 7, is characterized in that, the described business operation based on obtaining builds the operation of multidimensional model, specifically comprises:
According to the service profile in described business operation, generate dimension, and automatically generate level and the rank of dimension; The corresponding data table of described service profile forms dimension table, the value on the Major key dimension of service profile, the displayed value on the name-value dimension of service profile;
According to the rise time accounting period dimension in described business operation, and a plurality of ranks of rise time dimension;
According to the tolerance in described business operation, generate tolerance;
According to the service profile in described business operation, tolerance and Data Source, generate fact table;
According to the described dimension, time dimension, tolerance and the fact table that generate, generate cube.
9. according to the form acquisition method based on OLAP described in any one in claim 6 to 8, it is characterized in that, described step 204, specifically comprises:
Obtain described multidimensional model and the predefined collection form of structure, by pulling mode, the mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form are arranged;
Described mapping relations based on arranging, generate mapping area.
10. the form acquisition method based on OLAP according to claim 9, it is characterized in that, the described operation mapping relations in the described multidimensional model obtaining and the form region corresponding with described collection form being arranged by pulling mode, specifically comprises:
Pull the dimension member of multidimensional model and tolerance to left side or the top of the storage unit setting in advance, be fixed mapping area;
Pull the dimension member of multidimensional model and tolerance to the top of the storage unit setting in advance, mapping area is expanded; Dimension in described expansion mapping area and multidimensional model is shone upon to the foundation that described dimension is expanded for expansion mapping area;
And,
The described mapping relations that arrange based on described mapping settings module, generate the operation of mapping area, specifically comprise:
The set of all storage unit of obtaining the mapping relations of setting and setting in advance;
From the set of described all storage unit, choose a storage unit that index cell is corresponding, from described mapping relations, choose the ranks dimension of this storage unit mapping, and whether this ranks dimension of verification be legal:
If legal, obtain already present mapping area list, and judge whether this mapping area list to join existing mapping area: if add, respective memory unit added to mapping area and regenerate regional extent; If do not add, generate new mapping area, add mapping area list corresponding to this new mapping area;
If illegal, judge whether all to travel through storage unit; If all traversal, finishes the operation that this generates mapping area; If all do not travel through, choose storage unit corresponding to next index cell and process from the set of described all storage unit;
And/or,
Describedly mapping area is converted to multi-dimensional query statement carries out multi-dimensional query, and query results is filled into the operation in form, specifically comprise and calculate the operation of fixed area and the operation of calculating extended area, wherein:
Whether completely the operation of described calculating fixed area, specifically comprises: according to row dimension corresponding to mapping area or the row dimension rule of classification of coupling, mapping area is divided into groups, and carry out data extraction by group; In described rule of classification, if row dimension is mated completely, while splicing multi-dimensional query statement, row dimension is expanded; If row dimension is mated completely, while splicing multi-dimensional query statement, just row dimension is expanded;
The described operation of carrying out data extraction by group, specifically comprises: a plurality of mapping area are merged into a computing unit; Splicing multi-dimensional query statement: mapping area is mapped in to dimension in rows and columns as axle dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; Query Result is split by mapping area; Executing data is filled;
The operation of described calculating extended area, specifically comprises: obtain the dimension of shining upon in extended area; Splicing multi-dimensional query statement: mapping area is mapped in to the dimension that lists as row dimension, using all member's dimensions of shining upon in extended area as row dimension, will gather the unit of form own, during etc. dimension as food slicer dimension; Multidimensional model secondary processing, rejects useless dimensional information; By OLAP engine, carrying out MDX inquires about; The expansion of execution extended area; Executing data is filled.
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