CN115098506A - Associated data storage method, device, equipment and storage medium - Google Patents

Abstract

The invention discloses a storage method, a device, equipment and a storage medium of associated data, wherein the storage method comprises the following steps: acquiring each data node and a plurality of node attributes corresponding to each data node in a target database, and determining attribute identifications corresponding to the node attributes for each data node according to a preset numerical value interval; constructing a node information table corresponding to each data node according to a plurality of node attributes corresponding to each data node and attribute identifications corresponding to each node attribute; acquiring an attribute identification set corresponding to each sample under different associated nodes according to the associated node attribute corresponding to each sample in the target database and each node information table; and constructing a sample association information table according to the attribute identification sets corresponding to the samples under different association nodes and the sample identifications of the samples. The technical scheme of the embodiment of the invention can reduce the storage space of the data table and improve the reading efficiency of the associated data.

Description

A storage method, device, device and storage medium for associated data

technical field

The present invention relates to the field of computer technology, and in particular, to a storage method, apparatus, device and storage medium for associated data.

Background technique

With the development of computer technology, databases have been commonly used to store sample data and multiple associated data corresponding to the sample data.

In the prior art, when storing the associated data corresponding to the sample data, there are usually the following two methods: the first method is to record the associated data corresponding to each sample identifier in the data table one by one in the form of recording log data. For the same sample identifier, there may be multiple associated data items corresponding to the sample identifier; the second method is to combine the multiple associated data identifiers corresponding to each sample according to the preset separator. For a certain sample identifier, there is a long string used to represent all associated data identifiers.

However, the storage space occupied by the data table in the first method is relatively large, and the data reading efficiency is low due to too many data items; in the second method, when reading data, it is necessary to The string is split, because the string is long, it also takes a long time to read the data, and the reading efficiency is low.

SUMMARY OF THE INVENTION

The present invention provides a storage method, device, device and storage medium for associated data, which can reduce the storage space of the data table and improve the reading efficiency of the associated data.

According to an aspect of the present invention, a method for storing associated data is provided, comprising:

Acquire each data node and a plurality of node attributes corresponding to each data node in the target database, and determine the attribute identifier corresponding to each node attribute for each data node according to a preset value interval;

constructing a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to the respective node attributes;

According to the attribute of the associated node corresponding to each sample in the target database and each of the node information tables, obtain the attribute identifier set corresponding to each sample under different associated nodes;

The sample association information table is constructed according to the attribute identification sets corresponding to each sample under different association nodes and the sample identification of each sample.

According to another aspect of the present invention, there is provided a storage device for associated data, the device comprising:

an attribute identifier determination module, configured to obtain each data node and a plurality of node attributes corresponding to each data node in the target database, and determine the attribute identifier corresponding to each node attribute for each data node according to a preset value interval;

a node information table construction module, configured to construct a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to each of the node attributes;

an identification set acquisition module, configured to acquire attribute identification sets corresponding to each sample under different associated nodes according to the associated node attributes corresponding to each sample in the target database and each of the node information tables;

The association information table building module is used for constructing the sample association information table according to the attribute identification sets corresponding to each sample under different association nodes and the sample identification of each sample.

According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform any of the embodiments of the present invention. The storage method of the associated data.

According to another aspect of the present invention, a computer-readable storage medium is provided, where computer instructions are stored in the computer-readable storage medium, and the computer instructions are used to cause a processor to implement any of the embodiments of the present invention when executed. The storage method of the associated data.

According to the technical solution provided by the embodiments of the present invention, by acquiring each data node and a plurality of node attributes corresponding to each data node in a target database, according to a preset value interval, the attribute corresponding to each node attribute is determined for each data node. Identification, according to the multiple node attributes corresponding to each data node, and the attribute identification corresponding to each node attribute, construct the node information table corresponding to each data node, according to the associated node attribute corresponding to each sample in the target database, and each node information Table, to obtain the attribute identification set corresponding to each sample under different associated nodes, and according to the corresponding attribute identification set of each sample under different associated nodes, as well as the sample identification of each sample, the technical means of constructing the sample association information table can reduce the data The storage space of the table improves the reading efficiency of the associated data.

It should be understood that the content described in this section is not intended to identify key or critical features of the embodiments of the invention, nor is it intended to limit the scope of the invention. Other features of the present invention will become readily understood from the following description.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 is a flowchart of a method for storing associated data according to an embodiment of the present invention;

2 is a flowchart of another method for storing associated data according to an embodiment of the present invention;

3 is a flowchart of another method for storing associated data according to an embodiment of the present invention;

4 is a schematic structural diagram of a storage device for associated data provided according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an electronic device implementing the method for storing associated data according to an embodiment of the present invention.

Detailed ways

In order to make those skilled in the art better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only Embodiments are part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having" and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

FIG. 1 is a flowchart of a method for storing associated data according to Embodiment 1 of the present invention. This embodiment is applicable to the case of storing sample associated data in a database. The method can be executed by a storage device for associated data. The storage device of the associated data may be implemented in the form of hardware and/or software, and the storage device of the associated data may be configured in an electronic device (such as a terminal or a server) with a data processing function. As shown in Figure 1, the method includes:

Step 110: Acquire each data node and a plurality of node attributes corresponding to each data node in the target database, and determine the attribute identifier corresponding to each node attribute for each data node according to a preset value interval.

In this embodiment, the target database may be a database for storing sample data and sample-related data. The data node can be understood as a data storage module in the target database, which is used to store the data table and data input by the user. Specifically, the data node may be a sample attribute, for example, assuming that the sample is a person, the data node may be a specific person attribute, such as hobbies, awards, and the like.

In a specific embodiment, each data node may correspond to multiple node attributes. Taking the data node as a hobby as an example, the corresponding node attributes may include swimming, painting, watching movies, reading, and singing. Taking data nodes as awards as an example, the corresponding node attributes may include academic awards, competition awards, sports awards, and photography awards.

After acquiring the multiple node attributes corresponding to each data node, the attribute identifier corresponding to each node attribute can be determined for each data node according to a fixed value interval.

In this step, taking a data node as an example, assuming that the preset value interval includes m (m>0) integers, each integer can be sequentially used as the attribute identifier corresponding to each node attribute in the data node.

Step 120 , constructing a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to the respective node attributes.

In this step, a node information table corresponding to each data node may be constructed according to the mapping relationship between node attributes and attribute identifiers in each data node.

In a specific embodiment, taking a data node as an example, the node information table corresponding to the data node may be as shown in Table 1:

Table 1

property ID Node properties 1 property A 2 property B 3 property C ... attribute L m attribute M

As shown in Table 1, in the node information table corresponding to the data node, each node attribute and the corresponding attribute identifier (ie, attribute ID) are stored.

Step 130 , according to the attribute of the associated node corresponding to each sample in the target database and each of the node information tables, obtain a set of attribute identifiers corresponding to each sample under different associated nodes.

In this step, the attribute of the associated node corresponding to the sample may be determined according to the associated data corresponding to each sample. For example, assuming that the sample is a person, the person likes to watch a certain type of movie, read books by a certain author, and has won the first prize for writing and photography, then the associated node corresponding to the person can be determined as "hobbies" and "Awards", the corresponding associated node attributes are "Watching Movies", "Readings", "Academic Awards" and "Photography Awards".

In this embodiment, taking a sample as an example, optionally, after obtaining the associated node attributes corresponding to the sample, the attribute identifiers (that is, association Node attribute identifier), and combine multiple associated node attribute identifiers corresponding to the sample under a specific associated node to obtain an attribute identifier set corresponding to the sample under the associated node. Using the same method, the corresponding attribute identification sets of the sample under different associated nodes can be obtained.

In a specific embodiment, it is assumed that the sample is a person, the associated node attributes corresponding to the person are "movie watching", "reading", "academic award" and "photography award", and it is assumed that the attribute identifier corresponding to "movie watching" is "a" and the attribute identifier corresponding to "reading" is "b", then it can be determined that the attribute identifier set of the person under the associated node "hobbies" is "a&b"; assuming that the attribute identifier corresponding to "academic award" is " c", and the attribute identifier corresponding to "Photography Award" is "d", then it can be determined that the attribute identifier set of the person under the associated node "Award" is "c&d".

Therefore, through the above method, the attribute identifier sets corresponding to each sample under different associated nodes can be obtained.

Step 140: Construct a sample association information table according to the attribute identifier sets corresponding to each sample under different association nodes and the sample identifier of each sample.

In this embodiment, a sample association information table can be constructed according to the mapping relationship between each sample identifier, each associated node, and the attribute identifier set corresponding to the sample under the associated node, as shown in Table 2:

Table 2

Sample ID Associated Node A Associated Node B 1 X₁ X₂ 2 Y₁ Y₂ ... ... ...

Among them, two associated nodes are taken as an example in Table 2, X ₁ represents the attribute identifier set corresponding to sample 1 under the associated node A, X ₂ represents the attribute identifier set corresponding to the sample 1 under the associated node B, and Y ₁ represents the sample 2 The attribute identification set corresponding to the association node A, Y ₂ represents the attribute identification set corresponding to the sample 2 under the association node B.

In a specific embodiment, after the associated data is stored in the above manner, if a user's query request for associated data for a certain sample is received, each attribute corresponding to the sample can be obtained in the above-mentioned sample association information table Identification set, then split each attribute identification set to obtain multiple node attribute identifications, and finally obtain the node attribute information corresponding to each node attribute identification according to the above node information table, and feed this node attribute information as the result data to the user.

In this embodiment, it is not necessary to record the associated data identifier corresponding to each sample identifier one by one, and by constructing a node information table and a sample associated information table, the storage space occupied by the data table can be reduced; Restricting the identifiers of node attributes can avoid the problem of complicated strings in attribute identifiers, resulting in a long time for data reading.

According to the technical solution provided by the embodiments of the present invention, by acquiring each data node and a plurality of node attributes corresponding to each data node in a target database, according to a preset value interval, the attribute corresponding to each node attribute is determined for each data node. Identification, according to the multiple node attributes corresponding to each data node, and the attribute identification corresponding to each node attribute, construct the node information table corresponding to each data node, according to the associated node attribute corresponding to each sample in the target database, and each node information Table, to obtain the attribute identification set corresponding to each sample under different associated nodes, and according to the corresponding attribute identification set of each sample under different associated nodes, as well as the sample identification of each sample, the technical means of constructing the sample association information table can reduce the data The storage space of the table improves the reading efficiency of the associated data.

FIG. 2 is a flowchart of a method for storing associated data according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above-mentioned embodiment. As shown in Figure 2, the method includes:

Step 201: Acquire each data node and multiple node attributes corresponding to each data node in the target database.

Step 202 : According to the value range of the integer data corresponding to the target database, determine a plurality of integer powers of 2 that conform to the value range.

In a specific embodiment, assuming that the range of integer data of the target database is -2^31-2^30, 31 positive integer powers of 2 can be taken in this range, such as 2^0, 2^1, 2^2...2^30 (1073741824).

Step 203: Arrange the multiple integer powers of 2, and sequentially use each integer power of 2 as an attribute identifier corresponding to each node attribute in each data node according to the arrangement result.

In this step, optionally, multiple integer powers of 2 can be arranged in ascending order, and each integer power of 2 can be used as the attribute of each node in each data node according to the arrangement result. The corresponding attribute identifier.

Step 204: Construct a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to each of the node attributes.

In a specific embodiment, taking the data node as "hobbies" as an example, the node information table corresponding to the data node may be as shown in Table 3:

table 3

Wherein, as shown in Table 3, the attribute identifier of each node attribute may be a corresponding integer power of 2.

Step 205: According to the associated node attribute corresponding to each sample in the target database, and the attribute identifier of each associated node attribute in the node information table, obtain the summation result of the integer power of 2 corresponding to each sample under different associated nodes, The result of summing the integer powers of 2 is taken as the attribute identification set.

In this embodiment, taking a sample as an example, optionally, after obtaining the associated node attribute corresponding to the sample, the attribute identifier corresponding to each associated node attribute can be obtained in the above-mentioned node information table, and then the Add the attribute identifiers of multiple associated nodes corresponding to the sample under a specific associated node to obtain the summation result of the integer power of 2 corresponding to the sample under the associated node, and use the summation result of the integer power of 2 as Property ID set. Using the same method, the corresponding attribute identification sets of the sample under different associated nodes can be obtained.

In a specific embodiment, it is assumed that the sample is a person, the associated node attributes corresponding to the person are "movie watching", "reading", "academic award" and "photography award", and it is assumed that the attribute identifier corresponding to "movie watching" is "4", and the attribute identification corresponding to "Reading" is "8", then it can be determined that the attribute identification set of the person under the associated node "Hobbies" is "12"; assuming that the attribute identification corresponding to "Academic Award" is " 16", and the attribute identification corresponding to "Photography Award" is "64", then it can be determined that the attribute identification set of the person under the associated node "Award" is "80".

Therefore, through the above method, the attribute identifier sets corresponding to each sample under different associated nodes can be obtained.

Step 206 , construct a sample association information table according to the attribute identifier sets corresponding to each sample under different association nodes and the sample identifier of each sample.

In a specific embodiment, taking the associated nodes "hobbies" and "awards" as examples, it is assumed that the attribute identifier set of Person 1 under the associated node "hobbies" is "12", and the attribute identifier set under the associated node "awards" is "12", The attribute identification set is "80", the attribute identification set of Person 2 under the association node "Hobbies" is "30", and the attribute identification set under the association node "Awards" is "20". The constructed sample association information table can be As shown in Table 4:

Table 4

Sample ID hobby Awards 1 12 80 2 30 20 ... ... ...

Among them, as shown in Table 4, the attribute identification set corresponding to each sample under different associated nodes may be the summation result of integer powers of 2.

Step 207: After receiving the associated data query request, acquire the target sample identifier and target associated node included in the associated data query request.

In this step, after receiving the associated data query request input by the user, the target sample identifier and the target associated node can be extracted from the request according to the preset identifier. The target sample identifier may be the identifier corresponding to the sample the user wants to query, and the target associated node may be the sample attribute that the user wants to query for the sample.

Step 208: Acquire a target attribute identifier set in the sample association information table according to the target sample identifier and the target associated node.

In this step, the attribute identification set (ie, the target attribute identification set) corresponding to the target associated node under the target sample identification can be obtained according to the sample association information table.

In a specific embodiment, assuming that the target sample identifier is 1 and the target associated node is "hobbies", the target attribute identifier set can be determined to be 12 in Table 4.

Step 209: Split the target attribute identification set according to the integer power of 2.

In this step, when the target attribute identification set is split according to the integer power of 2, the maximum integer power of 2 corresponding to the target attribute identification set can be calculated first, and then the target attribute identification set and the maximum integer power of 2 can be calculated. The difference between the powers. If the difference is greater than 0, continue to calculate the maximum integer power of 2 corresponding to the difference, and calculate the difference between the difference and the maximum integer power of 2 until the difference is equal to 0. .

Step 210: Obtain the node information table corresponding to the target associated node, and obtain the associated data corresponding to the query request from the node information table corresponding to the target associated node according to the split result of the target attribute identifier set .

In this step, after the target attribute identification set is split, multiple node attribute identifications can be obtained, and then the node attribute information corresponding to each node attribute identification is obtained according to the node information table, and the node attribute information is used as the corresponding node attribute information. Query the associated data corresponding to the request.

In a specific embodiment, assuming that the target sample identifier is 2 and the target associated node is "hobbies", the target attribute identifier set can be determined as 30 in Table 4, and then the target attribute identifier set is divided into 16, 8, 4 and 2, and the corresponding node attributes obtained in Table 3 are "painting", "watching a movie", "reading" and "singing".

In this embodiment, by taking the integer power of 2 as the attribute identifier, and using the summation result of the integer power of 2 as the attribute identifier set, it is possible to avoid the problem that the character string in the attribute identifier set is too long, resulting in time-consuming data reading. ; secondly, since any positive integer greater than zero can be split into a unique set of sets containing the largest power of 2, by splitting the attribute identifier set according to the power of 2, the performance of the string can be improved. Splitting efficiency, and the accuracy of splitting results.

According to the technical solution provided by the embodiment of the present invention, by acquiring each data node and a plurality of node attributes corresponding to each data node in the target database, and according to the value range of the integer data corresponding to the target database, determine the value range that conforms to the value range. Multiple integer powers of 2, arrange multiple integer powers of 2, and sequentially take each integer power of 2 as the attribute identifier corresponding to each node attribute, according to the multiple nodes corresponding to each data node. Attributes, as well as the attribute identifiers corresponding to the attributes of each node, construct a node information table. According to the associated node attributes and attribute identifiers corresponding to each sample in the target database, the summation results of the integer powers of 2 corresponding to each sample under different associated nodes are obtained as Attribute identification set, according to the attribute identification set corresponding to each sample under different association nodes, and the sample identification of each sample, construct the sample association information table, after receiving the associated data query request, according to the target sample identification and target association node, in the sample The technology of obtaining the target attribute identification set from the association information table, splitting the target attribute identification set according to the integer power of 2, and obtaining the association data in the node information table corresponding to the target association node according to the split result of the target attribute identification set The method can reduce the storage space of the data table and improve the reading efficiency of the associated data.

FIG. 3 is a flowchart of a method for storing associated data according to Embodiment 3 of the present invention. This embodiment is a further refinement of the above-mentioned embodiment. As shown in Figure 3, the method includes:

Step 301: Acquire each data node and multiple node attributes corresponding to each data node in the target database.

Step 302: According to the value range of the integer data corresponding to the target database, determine a plurality of integer powers of 2 that conform to the value range.

Step 303: Arrange the multiple integer powers of 2.

Step 304: Determine whether the total number of node attributes in each of the data nodes is greater than or equal to the target number of the multiple integer powers of 2; if so, execute steps 305-307; if not, execute step 308.

In this embodiment, the target number may be the entire number of integer powers of 2. Assuming that the range of integer data of the target database is -2^31-2^30, you can take 31 positive integer powers of 2 in this range, such as 2^0, 2^1, 2^2... ...2^30(1073741824), that is, the target number is 31.

Step 305: Obtain a target number of node attributes from the multiple node attributes of the data node, and sequentially use the integer power of 2 as the attribute identifier corresponding to each node attribute according to the arrangement result.

In this embodiment, if the total number of node attributes in a certain data node is greater than the target number, a part of the node attributes may be firstly extracted from all the node attributes. Specifically, a target number of node attributes may be sequentially acquired according to the number of arrangement of the node attributes, and each integer power of 2 may be used as the attribute identifier corresponding to each node attribute.

Step 306: Count the number of remaining node attributes in the data node, and determine whether the number is less than or equal to the target number, if so, go to step 307, if not, return to step 305 until the remaining node attributes in the data node The quantity is less than or equal to the target quantity.

Step 307: Acquire the integer powers of 2 equal to the number in sequence according to the arrangement result, and use each integer power of 2 as the attribute identifier corresponding to each remaining node attribute respectively.

Step 308 , according to the arrangement result, sequentially use the integer power of 2 as the attribute identifier corresponding to each node attribute in each data node.

In this embodiment, if the total number of node attributes in a certain data node is greater than the target number, after extracting some node attributes from all node attributes, the number of remaining node attributes can be counted. If the number is less than or equal to the target number, then From all the integer powers of 2, the integer power of 2 equal to the number can be extracted again, and each integer power of 2 can be used as the attribute identifier corresponding to each remaining node attribute; if the number is greater than the target number, Then, continue to extract a part of the node attributes from the remaining node attributes according to the target number until the number of the remaining node attributes is less than or equal to the target number.

Step 309: Determine a data item identifier corresponding to each of the node attributes according to the arrangement order of each attribute identifier in each of the data nodes and the number of occurrences of each attribute identifier.

In this step, if the same attribute identifier appears multiple times in the data node, the data item identifier can be determined for each node attribute corresponding to the attribute identifier according to the appearance order of the attribute identifier (ie, the arrangement order).

In a specific embodiment, it is assumed that in a data node, the attribute identifier "8" appears three times in total, the node attribute corresponding to the first time is "attribute D", and the node attribute corresponding to the second time is "attribute P" ”, the node attribute corresponding to the third time is “attribute Z”, then according to the arrangement order of the attribute identifier “8”, it can be determined that the data item identifier corresponding to “attribute D” is “1”, and the data item corresponding to “attribute P” The identifier is "2", and the data item corresponding to "attribute Z" is marked as "3".

Step 310: Build a node information table corresponding to each of the data nodes according to a plurality of node attributes corresponding to each of the data nodes, an attribute identifier corresponding to each node attribute, and a data item identifier.

In a specific embodiment, taking the data node as "hobbies" as an example, the node information table corresponding to the data node may be as shown in Table 5:

table 5

property ID data item id Node properties 1 1 swim 2 1 painting 4 1 See a movie 8 1 read 16 1 Sing ... ... ... 1 2 travel 2 2 play ball 4 2 shop ... ... ... 1 3 listen to music

As shown in Table 5, since the total number of node attributes in the data node is greater than the total number of integer powers of 2, the same attribute identifier can be assigned to multiple node attributes. When multiple node attributes correspond to the same attribute identifier, the data item identifiers may be sequentially determined for each node attribute according to the arrangement order of the attribute identifiers.

Step 311 , according to the associated node attributes corresponding to each sample in the target database and each of the node information tables, acquire attribute identifier sets corresponding to different data item identifiers of each sample under different associated nodes.

In this step, taking an associated node as an example, the attribute identifier sets corresponding to the samples under different data item identifiers can be obtained according to the node information table corresponding to the associated node. Taking Table 5 as an example, assuming that the associated node attributes corresponding to the sample are "painting", "watching a movie", "travel", "playing ball" and "listening to music", it can be determined that the sample corresponds to when the data item ID is 1. The attribute identification set is 6, when the data item ID is 2, the corresponding attribute identification set is 3, and when the data item ID is 3, the corresponding attribute identification set is 1.

Thus, in the above manner, attribute identification sets corresponding to different data item identifications of each sample under different associated nodes can be obtained.

Step 312 , construct a sample association information table corresponding to each association node according to the attribute identification sets corresponding to different data item identifications of each sample under different association nodes, and the sample identification of each sample.

In this step, optionally, taking the associated node "hobbies" as an example, the sample association information table corresponding to the associated node may be as shown in Table 6:

Table 6

As shown in Table 6, the sample association information table stores attribute identification sets corresponding to different data item identifications of each sample under a specific association node.

In this embodiment, a sample association information table corresponding to each association node may be constructed in the same manner as described above.

In a specific embodiment, after the associated data is stored in the above manner, if a user's associated data query request for a certain sample is received, the target sample identifier and target associated node included in the associated data query request can be obtained, Assuming that the target sample ID is 2 and the target associated node is "hobbies", the attribute ID set corresponding to each data item ID corresponding to the sample can be obtained in the sample association information table (such as Table 6), such as 123, 118, 328…28 etc.

After acquiring each attribute identification set corresponding to the sample, each attribute identification set may be split according to the integer power of 2 to obtain multiple attribute identifications. Specifically: 123=64+32+16+8+2+1, 118=64+32+16+4+2, 328=256+64+8, ..., 28=16+8+4, then in The node attribute information corresponding to each attribute identifier under each data item ID is obtained from the node information table (eg, Table 5), as the associated data corresponding to the query request.

Specifically, taking the attribute identification set 123 of sample 2 when the data item ID is 1 as an example, the attribute identification set can be divided into the following attribute identifications: 64, 32, 16, 8, 2 and 1, then the attribute identification set can be divided into the following attribute marks: 64, 32, 16, 8, 2 and 1. In 5, when the ID of the acquired data item is 1, these attribute identifiers correspond to the node attribute information, namely: swimming, painting, reading, singing, etc.

According to the technical solution provided by the embodiment of the present invention, by acquiring each data node and multiple node attributes corresponding to each data node in the target database, and according to the value range of the integer data corresponding to the target database, a plurality of nodes that meet the value range are determined. Integer power of 2, arrange multiple integer powers of 2 to determine whether the total number of node attributes in each data node is greater than or equal to the target number. Each integer power of 2 is used as the attribute identifier corresponding to each node attribute, and the number of remaining node attributes is counted to determine whether the number is less than or equal to the target number. Each integer power of 2 is used as the attribute identifier corresponding to each remaining node attribute respectively, and according to the arrangement order of each attribute identifier in each data node, and the number of occurrences of each attribute identifier, the data item identifier corresponding to each described node attribute is determined, Construct the node information table corresponding to each data node, and obtain the attribute identifier sets corresponding to different data item identifiers under different associated nodes for each sample according to the associated node attributes corresponding to each sample in the target database and each node information table. The set of attribute identifiers corresponding to different data item identifiers under different associated nodes, as well as the sample identifiers of each sample, are the technical means of constructing sample associated information tables corresponding to each associated node, which can reduce the storage space of the data table and improve the associated data. read efficiency.

FIG. 4 is a schematic structural diagram of a storage device for associated data according to Embodiment 4 of the present invention. As shown in FIG. 4 , the device includes: an attribute identification determination module 410, a node information table construction module 420, an identification set acquisition module 430 and Association information table building module 440 .

The attribute identification determination module 410 is used to obtain each data node and a plurality of node attributes corresponding to each data node in the target database, and determine the corresponding attribute of each node attribute for each data node according to a preset value interval identification;

The node information table construction module 420 is configured to construct a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to the respective node attributes;

The identification set obtaining module 430 is configured to obtain attribute identification sets corresponding to each sample under different associated nodes according to the associated node attributes corresponding to each sample in the target database and each of the node information tables;

The association information table construction module 440 is configured to construct a sample association information table according to the attribute identification sets corresponding to each sample under different association nodes and the sample identification of each sample.

According to the technical solution provided by the embodiments of the present invention, by acquiring each data node and a plurality of node attributes corresponding to each data node in a target database, according to a preset value interval, the attribute corresponding to each node attribute is determined for each data node. Identification, according to the multiple node attributes corresponding to each data node, and the attribute identification corresponding to each node attribute, construct the node information table corresponding to each data node, according to the associated node attribute corresponding to each sample in the target database, and each node information Table, to obtain the attribute identification set corresponding to each sample under different associated nodes, and according to the corresponding attribute identification set of each sample under different associated nodes, as well as the sample identification of each sample, the technical means of constructing the sample association information table can reduce the data The storage space of the table improves the reading efficiency of the associated data.

On the basis of the above embodiment, the attribute identification determination module 410 includes:

an integer power determination unit, configured to determine, according to the value range of the integer data corresponding to the target database, a plurality of integer powers of 2 that conform to the value range;

an integer power arranging unit, used for arranging the multiple integer powers of 2, and sequentially taking each integer power of 2 as the attribute identifier corresponding to each node attribute in each data node according to the arrangement result;

The attribute quantity judgment unit is used to judge whether the total quantity of node attributes in each of the data nodes is greater than or equal to the target quantity of the multiple integer powers of 2; , obtain the node attributes of the target number, and sequentially use the integer power of 2 as the attribute identifier corresponding to each node attribute according to the arrangement result;

The remaining attribute quantity statistics unit is used to count the quantity of the remaining node attributes in the data node, and judge whether the quantity is less than or equal to the target quantity; , and each integer power of 2 is used as the attribute identifier corresponding to each remaining node attribute.

The node information table building module 420 includes:

a data item identification determining unit, configured to determine the data item identification corresponding to each described node attribute according to the arrangement order of each attribute identification in each described data node, and the number of occurrences of each attribute identification;

An information table construction unit is configured to construct a node information table corresponding to each of the data nodes according to a plurality of node attributes corresponding to each of the data nodes, an attribute identifier corresponding to each node attribute, and a data item identifier.

The identity set acquisition module 430 includes:

The summation result obtaining unit is used to obtain the integer times of 2 corresponding to each sample under different associated nodes according to the associated node attributes corresponding to each sample in the target database and the attribute identifiers of the associated node attributes in the node information table The power summation result, and the integer power summation result of 2 is used as the attribute identification set;

The attribute identification set obtaining unit is configured to obtain attribute identification sets corresponding to different data item identifications of each sample under different associated nodes according to the associated node attributes corresponding to each sample in the target database and each of the node information tables.

The association information table building module 440 includes:

a query request receiving unit, configured to acquire the target sample identifier and the target associated node included in the associated data query request after receiving the associated data query request;

a target identification set obtaining unit, configured to obtain a target attribute identification set in the sample association information table according to the target sample identification and the target associated node;

an integer power splitting unit, used for splitting the target attribute identification set according to the integer power of 2;

an associated data acquisition unit, configured to acquire the node information table corresponding to the target associated node, and obtain the query request from the node information table corresponding to the target associated node according to the split result of the target attribute identifier set Corresponding Linked Data;

The sample association information table construction unit is used for constructing a sample association information table corresponding to each association node according to the attribute identification sets corresponding to different data item identifications of each sample under different association nodes, and the sample identification of each sample.

The above-mentioned apparatus can execute the methods provided by all the foregoing embodiments of the present invention, and has corresponding functional modules and beneficial effects for executing the above-mentioned methods. For technical details not described in detail in the embodiments of the present invention, reference may be made to the methods provided by all the foregoing embodiments of the present invention.

FIG. 5 shows a schematic structural diagram of an electronic device 10 that can be used to implement embodiments of the present invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (eg, helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are by way of example only, and are not intended to limit implementations of the inventions described and/or claimed herein.

As shown in FIG. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a read only memory (ROM) 12, a random access memory (RAM) 13, etc., connected in communication with the at least one processor 11, wherein the memory stores There is a computer program executable by at least one processor, and the processor 11 can be executed according to a computer program stored in a read only memory (ROM) 12 or loaded from a storage unit 18 into a random access memory (RAM) 13. Various appropriate actions and processes are performed. In the RAM 13, various programs and data necessary for the operation of the electronic device 10 can also be stored. The processor 11 , the ROM 12 and the RAM 13 are connected to each other through a bus 14 . An input/output (I/O) interface 15 is also connected to the bus 14 .

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc. etc.; and a communication unit 19, such as a network card, modem, wireless communication transceiver, and the like. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.

The processor 11 may be various general and/or special purpose processing components having processing and computing capabilities. Some examples of processors 11 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various specialized artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the storage method of the associated data.

In some embodiments, the storage method of associated data may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18 . In some embodiments, part or all of the computer program may be loaded and/or installed on the electronic device 10 via the ROM 12 and/or the communication unit 19 . When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the above-described storage method of associated data may be performed. Alternatively, in other embodiments, the processor 11 may be configured by any other suitable means (eg, by means of firmware) to perform the storage method of the associated data.

Various implementations of the systems and techniques described herein above may be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips system (SOC), load programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpretable on a programmable system including at least one programmable processor that The processor, which may be a special purpose or general-purpose programmable processor, may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device an output device.

Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/operations specified in the flowcharts and/or block diagrams to be carried out. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in connection with the instruction execution system, apparatus or device. Computer-readable storage media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), fiber optics, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having a display device (eg, a CRT (cathode ray tube) or an LCD (liquid crystal display)) for displaying information to the user monitor); and a keyboard and pointing device (eg, a mouse or trackball) through which a user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback); and can be in any form (including acoustic input, voice input, or tactile input) to receive input from the user.

The systems and techniques described herein may be implemented on a computing system that includes back-end components (eg, as a data server), or a computing system that includes middleware components (eg, an application server), or a computing system that includes front-end components (eg, a user's computer having a graphical user interface or web browser through which a user may interact with implementations of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system may be interconnected by any form or medium of digital data communication (eg, a communication network). Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the Internet.

A computing system can include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or a cloud host. It is a host product in the cloud computing service system to solve the traditional physical host and VPS services, which are difficult to manage and weak in business scalability. defect.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, the steps described in the present invention can be performed in parallel, sequentially or in different orders, and as long as the desired results of the technical solutions of the present invention can be achieved, no limitation is imposed herein.

The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. a storage method of associated data, is characterized in that, comprises: Acquire each data node and a plurality of node attributes corresponding to each data node in the target database, and determine the attribute identifier corresponding to each node attribute for each data node according to a preset value interval; constructing a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to the respective node attributes; According to the attribute of the associated node corresponding to each sample in the target database and each of the node information tables, obtain the attribute identifier set corresponding to each sample under different associated nodes; The sample association information table is constructed according to the attribute identification sets corresponding to each sample under different association nodes and the sample identification of each sample. 2. The method according to claim 1, wherein, according to a preset value interval, for each data node, determine the attribute identifier corresponding to each node attribute respectively, comprising: According to the value range of the integer data corresponding to the target database, determine a plurality of integer powers of 2 that conform to the value range; The multiple integer powers of 2 are arranged, and each integer power of 2 is sequentially used as the attribute identifier corresponding to each node attribute in each data node according to the arrangement result. 3. The method according to claim 2, wherein, according to the associated node attributes corresponding to each sample in the target database, and each described node information table, the attribute identification set corresponding to each sample under different associated nodes is obtained, comprising: : According to the associated node attribute corresponding to each sample in the target database and the attribute identifier of each associated node attribute in the node information table, obtain the result of summing the integer power of 2 corresponding to each sample under different associated nodes, The summation result of the integer power of 2 is used as the attribute identification set. 4. The method according to claim 3, characterized in that, after constructing the sample association information table according to the attribute identifier sets corresponding to each sample under different associated nodes and the sample identifiers of each sample, the method further comprises: After receiving the associated data query request, obtain the target sample identifier and target associated node included in the associated data query request; According to the target sample identifier and the target associated node, obtain the target attribute identifier set in the sample associated information table; splitting the target attribute identification set according to the integer power of 2; A node information table corresponding to the target associated node is acquired, and according to the split result of the target attribute identifier set, the associated data corresponding to the query request is acquired in the node information table corresponding to the target associated node. 5. The method according to claim 2, wherein, according to the arrangement result, the integer powers of 2 are successively used as the attribute identifiers corresponding to the attributes of each node in each data node, comprising: Judging whether the total number of node attributes in each of the data nodes is greater than or equal to the target number of the multiple integer powers of 2; If so, obtain a target number of node attributes from the multiple node attributes of the data node, and sequentially use the integer power of 2 as the attribute identifier corresponding to each node attribute according to the arrangement result; Count the number of remaining node attributes in the data node, and determine whether the number is less than or equal to the target number; If so, sequentially obtain the integer power of 2 equal to the number according to the arrangement result, and use each integer power of 2 as the attribute identifier corresponding to each remaining node attribute respectively. 6 . The method according to claim 5 , wherein a node information table corresponding to each of the data nodes is constructed according to a plurality of node attributes corresponding to each of the data nodes and an attribute identifier corresponding to each of the node attributes respectively. 7 . ,include: According to the arrangement order of each attribute identifier in each of the data nodes, and the number of occurrences of each attribute identifier, determine the data item identifier corresponding to each of the node attributes; A node information table corresponding to each of the data nodes is constructed according to a plurality of node attributes corresponding to each of the data nodes, an attribute identifier corresponding to each node attribute, and a data item identifier. 7. The method according to claim 6, wherein, according to the associated node attributes corresponding to each sample in the target database, and each of the node information tables, the attribute identifier sets corresponding to each sample under different associated nodes are obtained, comprising: : According to the attribute of the associated node corresponding to each sample in the target database and each of the node information tables, obtain the attribute identifier set corresponding to the different data item identifiers of each sample under different associated nodes; According to the attribute identification set corresponding to each sample under different association nodes, and the sample identification of each sample, construct the sample association information table, including: According to the attribute identifier sets corresponding to different data item identifiers of each sample under different associated nodes, and the sample identifiers of each sample, a sample association information table corresponding to each associated node is constructed. 8. A storage device for associated data, comprising: an attribute identifier determination module, configured to obtain each data node and a plurality of node attributes corresponding to each data node in the target database, and determine the attribute identifier corresponding to each node attribute for each data node according to a preset value interval; a node information table construction module, configured to construct a node information table corresponding to each of the data nodes according to the plurality of node attributes corresponding to each of the data nodes and the attribute identifiers corresponding to each of the node attributes; an identification set acquisition module, configured to acquire attribute identification sets corresponding to each sample under different associated nodes according to the associated node attributes corresponding to each sample in the target database and each of the node information tables; The association information table building module is used for constructing the sample association information table according to the attribute identification sets corresponding to each sample under different association nodes and the sample identification of each sample. 9. An electronic device, characterized in that the electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform any of claims 1-7 The storage method of the associated data. 10. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method described in any one of claims 1-7 when executed. The storage method of the associated data.

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