CN113486092B - Time constraint-based time chart approximate query method and device - Google Patents

Time constraint-based time chart approximate query method and device Download PDF

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CN113486092B
CN113486092B CN202110872412.4A CN202110872412A CN113486092B CN 113486092 B CN113486092 B CN 113486092B CN 202110872412 A CN202110872412 A CN 202110872412A CN 113486092 B CN113486092 B CN 113486092B
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query
time
result set
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CN113486092A (en
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黄金晶
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Suzhou Vocational Institute of Industrial Technology
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462—Approximate or statistical queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2474—Sequence data queries, e.g. querying versioned data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention discloses a time chart approximate query method based on time constraint, which comprises the following steps: s1: and receiving a plurality of query graphs, and placing the query graphs into a query waiting queue according to the time sequence. S2: and sequentially taking out a plurality of query graphs from the query waiting queue, and receiving the corresponding limited hop count h. S3: and performing approximate matching of the query graph in the range of the limited hop count h in a pre-stored time graph to obtain an approximate query result set. S4: and screening according to the time constraint relation between the approximate query result set and the query graph to obtain a final query result set. S5: and outputting a final query result set, and ending the approximate query of the time chart. The invention can perform approximate query of time diagram with time constraint, the time constraint relation is set in the query diagram, sub-diagram matching is performed within a specified hop range by using sub-diagram simulation technology, the approximate query result of the query diagram is found in the data diagram, and the query result meets the preset time constraint relation in the query diagram.

Description

Time constraint-based time chart approximate query method and device
Technical Field
The invention belongs to the field of data analysis, and particularly relates to a time chart approximate query method and device based on time constraint.
Background
Graph pattern matching is to find all matching results according to a given query graph in one data graph, and plays an important role in many aspects, such as matching of chemical molecular structures, analysis of social relations in a social network, and the like. In recent years, how to perform efficient graph matching in large-scale data graphs is a hot spot problem for academic and industrial research. In the past, most research has focused on static graphs, but data in the fields of social networks, biochemistry and the like in life are dynamically changed, and some documents begin to pay attention to the inquiry of dynamic time charts. In the time chart, time information is arranged on the edges of the connecting nodes, a time constraint relation can be added according to a semantic relation in the query process, for example, a traveler flies to Guangzhou from Beijing, the traveler wants to stay on the sea for one day, the traveler needs to check flights flying to Shanghai from Beijing and flights flying to Guangzhou from Shanghai in the flight query process, and the two flights need to have a time interval of one day. Graph pattern matching on a dynamic time graph can reflect the relationship between query results and time.
At present, the time-constrained query is performed in the time diagram, and the main problem is that in the prior art, the time-constrained query is performed on the time diagram, and the query result completely consistent with the query diagram is obtained mainly by using an accurate matching mode, so that the practical application is difficult to form.
Disclosure of Invention
The technical aim of the invention is to provide a time chart approximate query method and a device based on time constraint so as to provide the technical effect of practical application.
In order to solve the problems, the technical scheme of the invention is as follows:
a time chart approximate query method based on time constraint comprises the following steps:
s1: and receiving a plurality of query graphs, and placing the query graphs into a query waiting queue according to the time sequence.
S2: and sequentially taking out a plurality of query graphs from the query waiting queue, and receiving the corresponding limited hop count h.
S3: and performing approximate matching of the query graph in the range of the limited hop count h in a pre-stored time graph to obtain an approximate query result set.
S4: and screening according to the time constraint relation between the approximate query result set and the query graph to obtain a final query result set.
S5: and outputting a final query result set, and ending the approximate query of the time chart.
The time constraint relationship is a relationship of two time intervals, and the time constraint relationship comprises preceding time, partial overlapping time and inclusion time.
Further preferably, the time constraint relation further comprises a time constraint value deltat, { ΔtαT|α ε { <, +.ltoreq, =, >,. Gtoreq }, where T is a time threshold.
The preceding time interval under the preceding relation between the two time intervals is coherent with the time constraint value deltat.
The overlapping time region in the partially overlapping relationship between the two time intervals is coherent with the time constraint value Δt.
Wherein, the step S3 specifically comprises the following steps of
S31: reading the first entry Q of the query graph 0 Obtaining item Q 0 And matching the node values and the access degree values with the time chart to obtain a point matching result set result V and an edge matching result set result E.
S32: and (3) merging according to the edge matching result set resultants in the step (S31), putting the merging result into a result set resultants, updating the point matching result set resultants, and then clearing the edge matching result set resultants after merging.
S33: reading the next entry Q of the query graph 1 Obtaining item Q 1 And the node value and the access degree value of the node (B) are matched with the time diagram to update a point matching result set result V and an edge matching result set result E.
S34: and (3) merging according to the edge matching result set resultants in the step (S33), putting the merging result into a result set resultants, updating the point matching result set resultants V, and then clearing the edge matching result set resultants.
S35: and repeating the step S33 and the step S34 until all the table items in the query graph are read, so as to obtain an approximate query result set.
Specifically, step S31 specifically includes the steps of
S311: reading the first entry Q of the query graph 0 Obtaining item Q 0 Node values and access values of (a).
S312: finding the AND table entry Q from the time diagram 0 Corresponding data blocks, reading each data item of the data block,
if the entry and exit value recorded in the data item is greater than or equal to the table item Q 0 And updating the point matching result set ResultV according to the data item.
If each data item of the data block is read, the point matching result set ResultV is not updated, and the process jumps to step S5, NULL is output, and the query is ended.
S313: reading table item Q 0 Chain list item of (1) to obtain item Q 0 Pointing to another entry Q x 。
S314: reading an item Q in a point matching result set result V 0 Corresponding to the data items, and sequentially matching the data items in the range of limited hop number h in the time chart to find the table item Q 0 To item Q x Reachable path acquisition Q of (1) 0 Q x Edge matching results and will match table entry Q x Updating the corresponding matching result to the point matching result set result V, Q 0 Q x And updating the edge matching result into an edge matching result set result.
S315: repeating step S314, updating the point matching result set resultV and the edge matching result set resultE until the point matching result set resultV and the edge matching result set resultE are matched with the table item Q 0 And jumps to step S32 after all linked list items match.
Specifically, step S33 specifically includes the steps of
S331: reading the next entry Q of the query graph 1 Obtaining item Q 1 Searching whether an item Q exists in a point matching result set result V or not 1 If yes, go to step S332, if no, go to step S31 for entry Q 1 And matching is carried out, and the result is updated to a point matching result set result V.
S332: reading table item Q 1 Chain list item of (1) to obtain item Q 1 Pointing to another entry Q y Find out if there is an item Q in the result set result V of point matching y If so, the process proceeds to step S333, and if not, the process proceeds to step S334.
S333: reading an item Q in a point matching result set result V 1 And Q y And in turn to item Q 1 Matching the matching result of the table entry Q in the range of limited hop number h in the time chart 1 To item Q y Reachable path acquisition Q of (1) 1 Q y Edge matching results and will Q 1 Q y The edge matching result is updated to the edge matching result set result, and the process goes to step S335.
S334: reading an item Q in a point matching result set result V 1 And in turn to item Q 1 Matching the matching result of the table entry Q in the range of limited hop number h in the time chart 1 To item Q y Reachable path acquisition Q of (1) 1 Q y Edge matching results and will match table entry Q y Updating the corresponding matching result to the point matching result set result V, Q 1 Q y The edge matching result is updated to the edge matching result set result, and the process goes to step S335.
S335: repeating steps S332-S334, updating the point matching result set resultV and the edge matching result set resultE until the point matching result set resultV and the edge matching result set resultE are matched with the table item Q 1 And jumps to step S34 after all linked list items of the table are matched.
Specifically, step S4 specifically includes the steps of
S41: the time constraint relation of the query graph is read.
S42: and sequentially reading the matching results of the result set resultQ, and removing the matching results which do not accord with the time constraint based on the time constraint relation of the query graph to obtain a final query result set.
A time diagram approximate query device based on time constraint comprises a query diagram receiver, a first memory, a query diagram analyzer, a query diagram matching processor, a time constraint processor and a second memory,
the query graph receiver is used for receiving a plurality of query graphs, and placing the query graphs into the first memory according to time sequence.
The query graph analyzer sequentially fetches a plurality of query graphs from the first memory and receives the corresponding limited hop count h.
The query graph matching processor is used for receiving the query graph and the limited hop count h, and performing approximate matching on the query graph within the range of the limited hop count h in the pre-stored time graph to obtain an approximate query result set.
The time constraint processor is used for receiving the time constraint relation between the approximate query result set and the query graph, and screening the time constraint relation to obtain a final query result set.
The second memory is used for receiving and storing the final query result set and can output the final query result set.
Specifically, the query graph matching processor is configured to read a plurality of entries of the query graph, obtain node values and access values of the entries, and match the entries with the time graph in sequence to obtain a point matching result set result v and an edge matching result set result e. And merging the edge matching result sets resultants, putting the merged results into a result set resultants, updating the point matching result sets resultants, and then clearing the merged edge matching result sets resultants to obtain the approximate query result set.
Specifically, the time constraint processor is used for receiving the time constraint relation of the query graph from the query graph matching processor, sequentially reading the matching results of the result set result Q, and removing the matching results which do not accord with the time constraint based on the time constraint relation of the query graph to obtain a final query result set.
By adopting the technical scheme, the invention has the following advantages and positive effects compared with the prior art: the invention can perform approximate query of time diagram with time constraint, the time constraint relation is set in the query diagram, sub-diagram matching is performed within a specified hop range by using sub-diagram simulation technology, the approximate query result of the query diagram is found in the data diagram, and the query result meets the preset time constraint relation in the query diagram. Graph pattern matching on the dynamic time graph can reflect the relation between the query result and time, and optimal time arrangement is achieved.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
FIG. 1 is a schematic flow chart of a time diagram approximate query method based on time constraint;
FIG. 2 is a schematic diagram of a timing diagram according to the present invention;
FIG. 3 is a schematic diagram of reachable paths based on the time diagram of FIG. 2;
FIG. 4 is a schematic diagram of a time constraint relationship according to the present invention;
FIG. 5 is a schematic diagram of a time chart of the logic structure of the present invention;
FIG. 6 is a schematic diagram of a time chart of the memory structure of the present invention;
FIG. 7 is a schematic diagram of a time-chart query logic structure of the present invention;
FIG. 8 is a schematic diagram of a query graph storage structure according to the present invention;
FIG. 9 is a block diagram of a time-constrained time-graph approximation query device of the present invention;
FIG. 10 is an example query graph of the present invention;
FIG. 11 is another query example of the present invention;
FIG. 12 is a schematic diagram of the present invention prior to relationship screening rules;
FIG. 13 is a schematic diagram of the inclusion relationship filtering rules of the present invention;
FIG. 14 is a schematic diagram of a partial overlap relationship screening rule according to the present invention
FIG. 15 is a schematic diagram of an edge matching result set result of the present invention;
FIG. 16 is a schematic diagram of a final query result set of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will explain the specific embodiments of the present invention with reference to the accompanying drawings. It is evident that the drawings in the following description are only examples of the invention, from which other drawings and other embodiments can be obtained by a person skilled in the art without inventive effort.
For the sake of simplicity of the drawing, the parts relevant to the present invention are shown only schematically in the figures, which do not represent the actual structure thereof as a product. Additionally, in order to simplify the drawing for ease of understanding, components having the same structure or function in some of the drawings are shown schematically with only one of them, or only one of them is labeled. Herein, "a" means not only "only this one" but also "more than one" case.
The invention provides a time-constraint-based time chart approximate query method and a time-constraint-based time chart approximate query device, which are further described in detail below with reference to the accompanying drawings and the specific embodiments. Advantages and features of the invention will become more apparent from the following description and from the claims.
Example 1
Referring to fig. 1, the present embodiment provides a time map approximate query method based on time constraint, which includes the following steps. S1: and receiving a plurality of query graphs, and placing the query graphs into a query waiting queue according to the time sequence. S2: and sequentially taking out a plurality of query graphs from the query waiting queue, and receiving the corresponding limited hop count h. S3: and performing approximate matching of the query graph in the range of the limited hop count h in a pre-stored time graph to obtain an approximate query result set. S4: and screening according to the time constraint relation between the approximate query result set and the query graph to obtain a final query result set. S5: and outputting a final query result set, and ending the approximate query of the time chart.
First, a description will be given of what is a time chart, and referring specifically to fig. 2, fig. 2 is merely an illustrative example of a time chart, and is not limited thereto. In fig. 1, a total of 4 nodes are included, each node is connected to each other in an edge, and there is time information consisting of a series of time intervals (s 1 ,e 1 )、(s 2 ,e 2 )、……、(s i ,e i ) Composition, wherein s i Represents the start time, e i Representing the expiration time. If it is necessary to start from one node to reach another node, the time on the node edge passing on the way is ordered, and the path is a time reachable path. In FIG. 1, A 1 B 2 The time interval of the side is (1, 5), B 2 C 1 The time interval of the edge has two segments (3, 7) and (6, 10). Wherein since the start time 3 of (3, 7) is less than A 1 B 2 The end time 5 of edge (1, 5) thus from A 1 To C 1 There is only one time reachable path, as shown in fig. 3.
Next, referring to fig. 4, as described above, there are time intervals between two adjacent nodes in the time chart, there are time constraint relationships between two adjacent nodes, and the time constraint relationships are 13 in total, and in this embodiment, the 13 relationships are integrated and are summarized into 3 types, namely, prior (before), overlapping (overlap) and containing (contacts). When the time constraint relation is prior to or partially overlapped, the time constraint relation is also provided with a time constraint value delta T, { ΔtαT|α ε { <, +.ltoreq, =, >,. Gtoreq }, where T is a time threshold.
Illustrating time constraint relationships
1) Assume two time intervals (t 1 ,t 2 ) And (t) 3 ,t 4 ) Both satisfy "(t) 1 ,t 2 )before(t 3 ,t 4 ) And Deltat.gtoreq.2' represents the time interval (t 1 ,t 2 ) To be before (t) 3 ,t 4 ) And the preceding time interval is at least 2.
2) Assume two time intervals (t 1 ,t 2 ) And (t) 3 ,t 4 ) Both satisfy "(t) 1 ,t 2 )overlaps(t 3 ,t 4 ) And Deltat is<2 "indicates the time interval (t 1 ,t 2 ) Part of the time interval is overlapped with (t) 3 ,t 4 ) And the overlapping time zone is less than 2.
3) Assume two time intervals (t 1 ,t 2 ) And (t) 3 ,t 4 ) Both satisfy "(t) 1 ,t 2 )contains(t 3 ,t 4 ) "then means the time interval (t 1 ,t 2 ) Comprises (t) 3 ,t 4 )。
Referring to fig. 5 and 6, in the present embodiment, nodes having the same tag value in the time chart are distinguished by subscripts, and in particular, referring to fig. 5, a 1 、A 2 、A 3 The distinction is made by means of subscripts. Referring specifically to fig. 5, in the storing of the time chart, a multi-level index structure is adopted, and the outbound degree and inbound degree of each node, and other nodes pointed to by the node, are recorded for each node. In A way 1 For example, in FIG. 4, from A 1 The node has two edge partsPoint to B 1 And D 1 Nodes, thus record A 1 The node has an outbound degree of 2, an inbound degree of 0, A 1 Next pointer of node points to B 1 And D 1 In the nodes and record A respectively 1 B 1 Edge sum A 1 D 1 Edge time intervals.
Referring to fig. 7 and 8, a query graph is next presented. Fig. 7 shows three query graphs. Fig. 7 (1) shows a query diagram of the "before" relationship, where the time interval on the AB side is earlier than the time interval on the AC side, and the earlier time interval is greater than 2. Fig. 7 (2) expresses an "overlap" relationship, where the time interval on AB is to overlap with the time interval on CA partially, and the overlapping time is 3. Fig. 7 (3) shows that the time interval on the AB side includes the time interval on the AC side, the time interval on the BC side is earlier than the time interval on the AB side, and the earlier time interval is 1 or less. Fig. 8 is a diagram of storing a query graph in an adjacency list according to the present embodiment, and records a time constraint relationship using an array C, and fig. 8 is a diagram of storing a query graph shown in fig. 7 (1). Each entry of the adjacency table records the node value, the access degree value and the node pointed to by each node in the query graph. The time constraint relation among edges in the query graph is recorded in the time constraint array, and each unit in the time constraint array is a time constraint relation.
With reference to fig. 1, the implementation of the present embodiment will now be described stepwise.
In step S1, a plurality of query graphs are received, and the query graphs are placed in a query waiting queue in the time sequence of receiving the query graphs.
Then in step S2, the query graph is sequentially fetched from the query waiting queue, and the corresponding limited hop count h is received to enter step S3 for matching.
In step S3, the query graph and the preset time graph are approximately matched within the range of the limited hop count h, so as to obtain an approximate query result set, and specifically, step S3 includes the following steps.
First, in step S31, the first entry of the read query graph is denoted as Q 0 Obtaining item Q 0 Node values and access values of (a) and time chartAnd carrying out matching to obtain a point matching result set resultV and an edge matching result set resultE.
In particular, it can be subdivided into the following steps
First, in step S311, the first entry Q of the query graph is read 0 Obtaining item Q 0 For convenience of description of subsequent steps, it is assumed that the table entry Q 0 The node value of (a) is a, which may also be referred to as a node.
Next, in step S312, a data block corresponding to the node value a is found from the memory structure of the time chart, each data item of the data block is sequentially read, and if the node access value recorded in the data item is greater than or equal to the table item Q in the query chart obtained in step S311 0 The node recorded in the data item is a matching result of the A node, and is put into a point matching result set result V= { A (A) a ,A b ,…)}，A a 、A b Is the table item Q in the time chart 0 Corresponding to the node values in the data block. If the entire data block is queried, resultv=null, which indicates that no corresponding node is matched, the process proceeds to step S5 directly, and the query is ended.
Then, in step S313, the entry Q is read 0 Linked list item L pointed to by Next pointer of (C) 0 Linked list item L 0 The node to which the stored a node points is denoted B for convenience of description.
Next, in step S314, a matching result a (a a ,A b …), take out the first matching result a of node a a Finding the data block where A is located in the storage structure of the time chart, and finding A a Corresponding data item, from A a Starting from the node, finding out B which can be matched with the B node of the query graph in all h-hop ranges in the time graph m 、B n … node, i.e. from A a Node goes to B m 、B n … node has a time reachable path, records the matching result of the node B into a point matching result set result V, and records the edge matching result into an edge matching result set result E= { AB: (the following)<A a B m ,T>；<A a C i ,T；C i D k ,T；…；F m B n ,T>)}，<A a B m ,T>Expression edge A a B m Can be matched with the side AB, and the side A a B m The time interval of (2) is T;<A a C i ,T；C i D k ,T；…；F m B n ,T>expression from A a Node departure, pathway node C i 、D k …F m Finally arrive at B n Node, the whole process is in the range of h hops, and the node is from A a To B n There is a time reachable path between. The same method is used for the residual matching result { A of the A node b … find B reachable within h-hops in time chart m 、B n … nodes, while also requiring the point match result set ResultV and the edge match result set ResultE to be updated continuously.
In step S315, the entries Q are read sequentially 0 The matching in the h-hop range is carried out according to the step S314 on the remaining linked list items pointed by the Next pointer of (2), and the point matching result set ResultV and the edge matching result set ResultE are updated until the point matching result set ResultV and the edge matching result set ResultE are matched with the list item Q 0 If all the linked list items match, the linked list item is NULL, and the process goes to step S32.
Next, step S32 is performed to obtain an entry Q 0 Combining the matching results of the A node and the node B, C … pointed by the A node, putting the combined result into a result set resultaq, and updating the matching result in the point matching result set resultav. In addition, the matching result of the edge matching result set resultate needs to be emptied so as to match the next entry of the adjacency list of the query graph.
Referring to fig. 10, step S32 is illustrated. According to the above steps, the A node is matched first, and the matching result of the A node is set as A 1 And A 2 Then resultv= { a (a 1 ,A 2 ) Then respectively from A 1 And A 2 B nodes are matched in the range of the departure h hops, and the matching result of the AB edges in the time diagram is set as result = { { AB: (-) AB:<A 1 B 1 ,T>、<A 2 B 1 ,T>) }, then match the node B's match junctionFruit addition ResultV, resultV = { A (A) 1 ,A 2 )、B(B 1 ) -a }; then matching the AC edges, and setting the matching result of the AC edges as<A 1 C 1 ,T>Then result= { AB:. Times.<A 1 B 1 ，T>、<A 2 B 1 ，T>)}、{AC:(<A 1 C 1 ,T>)}}，ResultV＝{A(A 1 ,A 2 )、B(B 1 )、C(C 1 ) -a }; the matching results of the AB edge and the AC edge are then combined, since the matching result of the AC edge is not obtained from A 2 The matching result of the starting point is removed, thereby removing one matching result of the AB edge<A 2 B 1 ,T>The matching result of ResultV is updated simultaneously, resultv= { a (a 1 ，)、B(B 1 )、C(C 1 ) And putting the combined result into a result set resultQ, wherein the result set resultQ= { AB:. The result set resultQ = { AB:. The result set resultQ }<A 1 B 1 ,T>)、{AC:(<A 1 C 1 ,T>)}。
Next, step S33 specifically includes the following steps,
first, in step S331, the next entry Q of the query graph is read 1 Obtaining item Q 1 For convenience of description of subsequent steps, it is assumed that the table entry Q 1 The node value of (2) is D, which may also be referred to as the D node. Find if there is an entry Q in the point match result set result V 1 If yes, go to step S332, if no, go to step S31 for entry Q 1 And matching is carried out, and the result is updated to a point matching result set result V.
Next, step S332 is performed to read the entry Q 1 The first linked list item L of the linked list items pointed to by the Next pointer of (2) 0 For convenience of description, let the linked list item L 0 If yes, go to step S333, and if no, go to step S334.
If the process proceeds to step S333, the matching result D (D 1 ,D 2 …), for each matching result of D, find whether there is a node out of that nodeTime available path in the range of sending h hops reaches V i Node (V) i A matching result V (V 1 ,V 2 …) and records the DV edge matching result into result, and then jumps to step S335.
If step S334 is entered, since the V node has not been matched in the foregoing step, the matching result of the D node in the resultav is directly read, for each matching result of D, a node that can be matched with the V node in the query graph in the h-hop range is found in the time chart according to the method in step S314, the matching result of the V node is recorded into the point matching result set resultav, and meanwhile, the matching result of the DV edge is recorded into the edge matching result set resultae, and then step S335 is skipped.
Finally, in step S335, steps S332 to S334 are repeated to update the point matching result set ResultV and the edge matching result set ResultE until it matches the entry Q 1 And jumps to step S34 after all linked list items of the table are matched.
Step S34 is similar to step S32, and the item Q is specified in step S34 1 The D node and the pointed node matching result are combined according to the step S32, the combined result is added into a result set result Q, and the matching result which does not meet the requirements is removed in the combining process; and then the resultE edge matching result set is emptied to prepare for the next matching.
Referring to fig. 11, another combination is specifically described. The query graph shown in fig. 11 has more BC edges than fig. 10, and after matching AB and AC edges according to the foregoing steps, the matching results are merged and then put into the result set ResultQ. Next, the edge BC is matched, and since the node B and the node C have been matched as described above, the edge BC is matched from the matching result B (B i …) starting to find C reachable within h-hops k Node, and C k The node is a matching result of the C node in the previous step, and finally the matching result of the BC edge is combined into the ResultQ.
And repeating the step S33 and the step S34 until all the table items in the query graph are read, so as to obtain an approximate query result set.
And then entering S4, screening according to the time constraint relation between the approximate query result set and the query graph to obtain a final query result set. In particular to
First, in step S41, the time constraint relation of the query graph is read, and referring to FIG. 8, the first element C in the time constraint relation array is read 0 Taking out two edges e with time constraint relation 1 And e 2 Time constraint relationship type R c Time constraint value T c 。
Next, in step S42, the matching results in the result set ResultQ are sequentially read, if there is a sum e 1 、e 2 Matched edge e' 1 And e' 2 (e’ 1 And e' 2 It is also possible to have h-hop in-range with e 1 、e 2 Matched path), let e' 1 The time intervals on the edges in the upper h-hop range are (t) a1 ,t b1 ),(t a2 ,t b2 )…，e’ 2 The time intervals on the edges in the upper h-hop range are (t) c1 ,t d1 ),(t c2 ,t d2 ) …, further screening out the results conforming to the time constraint relation, and removing the results not conforming to the time constraint relation to obtain a final query result set.
The specific rules are that
1) Before relationship
Referring to FIG. 12, (t) a1 ,t b1 )…(t an ,t bn ) To sum e 1 Matched path e 'within h hops' 1 Time interval above, (t) c1 ,t d1 )…(t cn ,t dn ) To sum e 2 Matched path e 'within h hops' 2 The beform rule requires path e 'for the time interval above' 1 The last time interval also precedes e' 2 The first time interval above, t bn <t c1 And t c1 -t bn Satisfy the time constraint value T c 。
2) Contains relationship
Referring to FIG. 13, the relationship requires e' 2 Each time interval on the path is contained in e' 1 Is within a certain time interval of (1);i.e. pair e' 2 Each time interval (t ci ,t di ) Sequentially inquiring e' 1 Is set to be equal to (t) a1 ,t b1 )…(t an ,t bn ) See if there is a time interval (t ak ,t bk ) Conform to t ci ≥t ak And t di ≤t bk 。
3) overlap relation
Referring to FIG. 14, the overlap relationship requires e' 1 The first time interval on the path starts earlier than e' 2 The start time, e ', of the first time interval on the path' 1 The end time of the last time interval on the path is earlier than e' 2 End time of last time interval on path, and e' 1 And e' 2 The overlapping interval values are to satisfy the time constraint value T c 。
And finally, outputting a final query result set in the step S5 to obtain a desired result and ending the approximate query of the time diagram.
Example 2
Referring to fig. 2, the present embodiment provides a time-constraint-based time map approximation query apparatus based on embodiment 1, which employs the time-constraint-based time map approximation query method as claimed in any one of embodiment 1.
Referring to fig. 9, the present embodiment includes a query graph receiver, a first memory, a query graph analyzer, a query graph matching processor, a time constraint processor and a second memory,
the query graph receiver is used for receiving a plurality of query graphs, and placing the query graphs into the first memory according to time sequence.
The query graph analyzer sequentially fetches a plurality of query graphs from the first memory and receives the corresponding limited hop count h.
The query graph matching processor is used for receiving the query graph and the limited hop count h, and performing approximate matching on the query graph within the range of the limited hop count h in the pre-stored time graph to obtain an approximate query result set.
The time constraint processor is used for receiving the time constraint relation between the approximate query result set and the query graph, and screening the time constraint relation to obtain a final query result set.
The second memory is used for receiving and storing the final query result set and can output the final query result set.
Fig. 5 is a time chart, fig. 7 (1) is a query chart, and the entire query process will be described in connection with this embodiment.
The query graph receiver is used for receiving the query graph submitted by the user and placing the query graph into the first memory according to the time sequence.
The query graph analyzer fetches the query graph from the first memory and receives a limited number of hops h, in this case let h=2, which is fed into the query graph matching processor.
The query graph matching processor performs approximate matching within a 2-hop range in the data graph according to the structure of the query graph, and the matching process is as follows:
1) Reading the first entry Q of the query graph adjacency table 0 And obtaining the node value A, the outbound value 2 and the inbound value 0 of the table entry.
2) In the storage structure of the time chart, a data block corresponding to an A node is found, and a first item set in the data block is read to obtain A 1 The node corresponding to the output degree value 2 and the input degree value 0 is due to A 1 The access degree value of the node is equal to that of the node of the query graph A, and the matching result ResultV= { A (A 1 ) }. Continuing to read the second item set in the data block to obtain A 2 Node-corresponding out-degree value 4, in-degree value 0, and A 1 After comparing the node access degree values, the matching result is recorded into result v= { a (a 1 ,A 2 ) }. Continuing to read the third item set in the data block to obtain A 3 The node corresponding to the output degree value 1 and the input degree value 2 is due to A 3 The node's out-degree value is smaller than the out-degree value of the A node in the query graph, thus A 3 The node cannot match the a node.
3) Reading a first entry Q in a query graph 0 Linked list item L pointed to by Next pointer of (C) 0 The node value is B, and the step (4) is carried out to match the AB edge in the 2-hop range；
4) Find matching result a (a 1 ,A 2 ) Finding the data block of A in the storage structure of the time chart and matching the data block to A 1 Corresponding data item, from A 1 The data item of the node starts, the Next pointer points to the linked list, the first node value is B 1 Meet the matching of AB edge in 2-hop range, and B is 1 Node record entry matching result set result v= { a (a 1 ,A 2 )，B(B 1 ) Simultaneously recording the matching result into an edge matching result set result= { AB: (<A 1 B 1 ,(1,2)>) } dueto A 1 To B 1 Only 1 jump between, so continue to find the data block where B is located, find B 1 The item set where B is located is found 1 The edge not pointed out, for B 1 The matching of the nodes is terminated. At A 1 The Next node of the linked list pointed by Next is continuously read in the data block, and the node value is D 1 Find the data block where D is located and match to D 1 Data item where D is found 1 The pointed node is C 1 Cannot match B in the 2-hop range, thus from A 1 The node starts, and the node B is matched with the node B in the range of 2 hops<A 1 B 1 ,(1,2)>. Next, another match to node A results in A 2 Matching AB edge in 2-hop range, and recording the matching result of the time-reachable path, in this case, only<A 2 B 1 ,(3,4)(8,19)>Can be matched with the AB edge, and the path A 2 →E 1 →B 2 The time reachable path is not met. Thus in this step, the matching result of the final AB edge formed is result= { AB: (<A 1 B 1 ,(1,2)>、<A 2 B 1 ,(3,4)>、<A 2 B 1 ,(8,19)>}；
5) Reading table Q in query graph 0 Next pointer to the Next entry L of the linked list 1 Matching the AC edges within the 2-hop range by the method in the step 4), and recording the matching result of the C node into result V= { A (A) 1 ,A 2 ),B(B 1 ),C(C 1 ) Edge-matched junctionFruit record into result= { AC: (<A 1 D 1 ,(5,6)；D 1 C 1 ,(9,11)>、<A 1 D 1 ,(7,8)；D 1 C 1 ,(9,11)>、<A 2 C 1 ,(6,8)>、<A 2 E 2 ,(7,9)；E 2 C 1 ,(11,15)>}。
6) Repeating step 5) to read item Q 0 The Next pointer of (2) points to the Next entry of the linked list, due to L 1 The next entry in (a) is NULL, so for Q 0 The matching of the relevant nodes of the table entry ends.
7) Referring to FIG. 15, item Q 0 Combining the matching results of the node A and the node B and the node C pointed by the node A, and putting the combined result into a resultQ. Resultq= { (AB:<A 1 B 1 ,(1,2)>),(AC：<A 1 D 1 ,(5,6)；D 1 C 1 ,(9,11)>)}、{(AB：<A 1 B 1 ,(1,2)>),(AC：<A 1 D 1 ,(7,8)；D 1 C 1 ,(9,11)>)}、{(AB：<A 2 B 1 ,(3,4)>),(AC：<A 2 C 1 ,(6,8)>)}、{(AB：<A 2 B 1 ,(8,19)>),(AC：<A 2 C 1 ,(6,8)>)}、{(AB：<A 2 B 1 ,(3,4)>),(AC：<A 2 E 2 ,(7,9)；E 2 C 1 ,(11,15)>)}、{(AB：<A 2 B 1 ,(8,19)>),(AC：<A 2 E 2 ,(7,9)；E 2 C 1 ,(11,15)>)}}。
8) Reading the next entry Q of the query graph adjacency table 1 Entry Q 1 The node value of (2) is B, the node matching result of B node already exists in the node matching result ResultV, and the step 9 is entered.
9) Due to Q 1 The term Next pointer is NULL, for term Q 1 The matching of the relevant nodes ends.
10 Continuing to read the next entry Q of the query graph adjacency table 2 Entry Q 2 The node value of (2) is C, the node matching result of C node is already in the node matching result V, and the step is enteredStep 11).
11 Due to Q 2 Next pointer of item is NULL for Q 2 The matching of the entry correlation node ends.
12 Due to the last entry Q of the query graph adjacency table 2 After the matching is completed, the approximate query result of the query matching the 2-hop range and the time constraint array of the query graph are sent to a time constraint processor.
The time constraint processor carries out further screening on the query results according to the time constraint relation, selects the results conforming to the time constraint relation, and obtains a final query result set, wherein the process is as follows:
a) Reading the first element C in the time constraint relation array 0 Taking out two sides AB, AC with time constraint relation and time constraint relation type R c =before and time constraint value T c >2。
b) Reading the first matching result in result, R 1 ＝{(AB：<A 1 B 1 ,(1,2)>),(AC：<A 1 D 1 ,(5,6)；D 1 C 1 ,(9,11)>) } dueto R c ＝before、T c >2, then the time interval of the AB side in the matching result is required to be earlier than the time interval of the AC side, and the time interval is at least greater than 2. At R 1 In (A) 1 B 1 The time interval on the edge is (1, 2), the matching result of the AC edge is a time path of 2 hops, the time interval on the first hop is taken out for comparison according to the before relation, and the first hop A 1 D 1 The time interval on the side is (5, 6), A 1 D 1 The starting time of the time interval on the edge is 5, A 1 B 1 The end time on the edge is 2, it is evident that the time interval between 5 and 2 is greater than 2, and R is therefore 1 Is a query result satisfying the time constraint relationship.
c) Continuing to read the second matching result in result, R 2 ＝{(AB：<A 1 B 1 ,(1,2)>),(AC：<A 1 D 1 ,(7,8)；D 1 C 1 ,(9,11)>) -matching method as in b), R 2 Is a matching result.
d) ContinuingReading the third matching result in result, R 3 ＝{(AB：<A 2 B 1 ,(3,4)>),(AC：<A 2 C 1 ,(6,8)>) } dueto A 2 B 1 End time sum A of edge time interval 2 C 1 The starting times on the edges do not satisfy the time relationship preceding 2, and R 3 Not a match result.
e) Continuing to read the fourth match in result, as described in d), R 4 Nor is it a match result.
f) Continuing to read the fifth matching result in result, R 5 ＝{(AB：<A 2 B 1 ,(3,4)>),(AC：<A 2 E 2 ,(7,9)；E 2 C 1 ,(11,15)>) According to the method described above, A 2 B 1 Edge time intervals (3, 4) and A 2 E 2 The edge time intervals (7, 9) satisfy a time relation preceding 2, thus R 5 Is a matching result.
g) Continuing to read the last matching result in result, R 6 ＝{(AB：<A 2 B 1 ,(8,19)>),(AC：<A 2 E 2 ,(7,9)；E 2 C 1 ,(11,15)>) And the result is not a match result.
Referring to fig. 16, the final time constraint matching result r= { (AB) is output:<A 1 B 1 ,(1,2)>),(AC：<A 1 D 1 ,(5,6)；D 1 C 1 ,(9,11)>)}、{(AB：<A 1 B 1 ,(1,2)>),(AC：<A 1 D 1 ,(7,8)；D 1 C 1 ,(9,11)>)}、{(AB：<A 2 B 1 ,(3,4)>),(AC：<A 2 E 2 ,(7,9)；E 2 C 1 ,(11,15)>)}}。
the embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, it is within the scope of the appended claims and their equivalents to fall within the scope of the invention.

Claims (10)

1. The time chart approximate query method based on time constraint is characterized by comprising the following steps:
s1: receiving a plurality of inquiry graphs, and placing the inquiry graphs into an inquiry waiting queue according to a time sequence;
s2: sequentially taking out a plurality of query graphs from the query waiting queue, and receiving a corresponding limited hop count h;
s3: performing approximate matching of the query graph in the range of the limited hop count h in a pre-stored time graph to obtain an approximate query result set;
s4: screening according to the approximate query result set and the time constraint relation of the query graph to obtain a final query result set;
s5: and outputting a final query result set, and ending the approximate query of the time chart.
2. The time constraint-based time graph approximate query method according to claim 1, wherein a time interval is arranged between two adjacent nodes in the time graph, the time constraint relationship is a relationship between two time intervals, and the time constraint relationship comprises preceding, partial overlapping and containing.
3. The time constraint based time graph approximation query method of claim 2, wherein, the time constraint relationship further includes a time constraint value deltat, { ΔtαT|α ε { <, +.ltoreq, =, >. Gtoreq }, where T is a time threshold;
the prior time interval under the prior relation between the two time intervals is coherent with the time constraint value delta t;
the overlapping time region in the partial overlapping relationship between the two time intervals is coherent with the time constraint value Δt.
4. The time constraint-based time graph approximation query method as claimed in claim 1, wherein said step S3 comprises the steps of
S31: reading the first entry Q of the query graph 0 Obtaining the table item Q 0 The node value and the access degree value of (2) are matched with the time graph to obtain a point matching result set result V and an edge matching result set result E;
s32: merging according to the edge matching result set resultants in the step S31, putting the merging result into a result set resultants, updating the point matching result set resultants, and then clearing the edge matching result set resultants after merging;
s33: reading the next table item Q of the query graph 1 Obtaining the table item Q 1 Matching with the time graph to update the point matching result set result V and the edge matching result set result E;
s34: merging according to the edge matching result set resultants in the step S33, putting the merging result into the result set resultants, updating the point matching result set resultants, and then clearing the edge matching result set resultants;
s35: and repeating the step S33 and the step S34 until all the table items in the query graph are read, so as to obtain the approximate query result set.
5. The time constraint-based time map approximation query method as set forth in claim 4, wherein said step S31 comprises the steps of
S311: reading the first entry Q of the query graph 0 Obtaining the table item Q 0 Node values and access values of (a);
s312: finding the entry Q from the time map 0 Corresponding data blocks, reading each data item of the data blocks,
if the entry and exit degree value recorded in the data item is greater than or equal to the table item Q 0 Updating the point matching result set result V according to the data item;
if each data item of the data block is read, if the point matching result set result V is not updated, jumping to the step S5, outputting NULL and ending the query;
s313: reading the table item Q 0 Chain table item of (1) to obtain the table item Q 0 Pointing to another entry Q x ；
S314: reading the table item Q in the point matching result set ResultV 0 Corresponding to the data items, and sequentially matching the data items within the range of the limited hop number h in the time chart to find the table item Q 0 To the table item Q x Reachable path acquisition Q of (1) 0 Q x Edge matching results and will match the table entry Q x Updating the corresponding matching result into the point matching result set result V, wherein the Q 0 Q x Updating the edge matching result into the edge matching result set result;
s315: repeating the step S314, updating the point matching result set resultV and the edge matching result set resultE until the point matching result set resultV and the edge matching result set resultE are matched with the table item Q 0 And (3) jumping to the step S32 after all the linked list items are matched.
6. The time constraint-based time map approximation query method as set forth in claim 4, wherein said step S33 specifically comprises the steps of
S331: reading the next table item Q of the query graph 1 Obtaining the table item Q 1 Searching whether the table item Q exists in the point matching result set ResultV or not 1 If yes, go to step S332, if no, go to step S31 to get the table Q 1 Matching is carried out, and the point matching result set resultV is updated;
s332: reading the table item Q 1 Chain table item of (1) to obtain the table item Q 1 Pointing to another entry Q y Searching whether the item Q exists in the point matching result set ResultV y If yes, go to step S333, if no, go to step S334;
s333: reading the point matching resultThe entry Q in the set ResultV 1 And Q y And sequentially for the table item Q 1 Matching the matching result of the table entry Q in the range of the limited hop number h in the time chart 1 To the table item Q y Reachable path acquisition Q of (1) 1 Q y Edge matching results and matching the Q 1 Q y Updating the edge matching result into the edge matching result set result, and jumping to step S335;
s334: reading the table item Q in the point matching result set ResultV 1 And sequentially for the table item Q 1 Matching the matching result of the table entry Q in the range of the limited hop number h in the time chart 1 To the table item Q y Reachable path acquisition Q of (1) 1 Q y Edge matching results and will match the table entry Q y Updating the corresponding matching result into the point matching result set result V, wherein the Q 1 Q y Updating the edge matching result into the edge matching result set result, and jumping to step S335;
s335: repeating the steps S332 to S334, and updating the point matching result set resultV and the edge matching result set resultE until the point matching result set resultV and the edge matching result set resultE are matched with the table item Q 1 And (3) jumping to the step S34 after all the linked list items are matched.
7. The time constraint-based time graph approximation query method as claimed in claim 1, wherein said step S4 comprises the steps of
S41: reading the time constraint relation of the query graph;
s42: and sequentially reading the matching results of the result set resultQ, and removing the matching results which do not accord with time constraint based on the time constraint relation of the query graph to obtain the final query result set.
8. A time diagram approximate query device based on time constraint is characterized by comprising a query diagram receiver, a first memory, a query diagram analyzer, a query diagram matching processor, a time constraint processor and a second memory,
the query graph receiver is used for receiving a plurality of query graphs, and placing the query graphs into the first memory according to time sequence;
the query graph analyzer sequentially takes out a plurality of query graphs from the first memory and receives the corresponding limited hop count h;
the query graph matching processor is used for receiving the query graph and the limited hop count h, and performing approximate matching of the query graph in the range of the limited hop count h in a pre-stored time graph to obtain an approximate query result set;
the time constraint processor is used for receiving the time constraint relation between the approximate query result set and the query graph, and screening the time constraint relation to obtain a final query result set;
the second memory is configured to receive and store the final query result set, and to output the final query result set.
9. The time constraint based time graph approximation query device of claim 8, wherein,
the query graph matching processor is used for reading a plurality of table items of the query graph to obtain node values and access degree values of the table items, and sequentially matching the table items with the time graph to obtain a point matching result set resultV and an edge matching result set resultE; and merging the edge matching result set resultants, putting the merged results into a result set resultants, updating the point matching result set resultants, and then emptying the edge matching result set resultants after merging to obtain the approximate query result set.
10. The time constraint-based time graph approximation query device of claim 8, wherein the time constraint processor is configured to receive the time constraint relation of the query graph from the query graph matching processor, sequentially read matching results of the result set ResultQ, and remove matching results that do not meet a time constraint based on the time constraint relation of the query graph, to obtain the final query result set.
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