WO2019056958A1

WO2019056958A1 - Trending keyword acquisition method, device and server

Info

Publication number: WO2019056958A1
Application number: PCT/CN2018/104799
Authority: WO
Inventors: 刘欢; 朱国云; 陈梁; 钱龙
Original assignee: 阿里巴巴集团控股有限公司
Priority date: 2017-09-22
Filing date: 2018-09-10
Publication date: 2019-03-28
Also published as: CN109542612A

Abstract

The present application provides a trending keyword acquisition method, a device and a server. The method comprises: acquiring a keyword within a reference period and acquiring a view count of the keyword; determining a view count interval in which the view count is located, querying to get a linked list corresponding to the view count interval, wherein different view count intervals correspond to different linked lists; updating a position of the view count of the keyword in the linked list; and when needing to determine a trending keyword, reading a view count of the keyword from the linked list and determining a trending keyword according to the view count of the keyword. The technical solution of the present application can be used to realize balanced loading of a distributed system and to improve stability and effectiveness of the system, thereby increasing overall processing capability of data requests with respect to trending keywords.

Description

Hotkey keyword acquisition method, device and server

The present application claims the priority of the Chinese Patent Application No. 201710865548.6, entitled "A Hotspot Keys Acquisition Method, Apparatus, and Server", which is hereby incorporated by reference. .

Technical field

The present application relates to the field of the Internet, and in particular, to a hotkey keyword acquisition method, apparatus, and server.

Background technique

Distributed systems are one of the mainstream solutions to the current demand for big data storage. In a distributed system, multiple database servers can be deployed, and each database server is used to store the same data. After receiving the data request sent by the client, the application server determines the database server by using a hash algorithm, and sends a data request to the database server. After receiving the data request, the database server returns the data corresponding to the data request to the application server, so that the application server returns the data to the client.

Since the hash algorithm is fixed, the data request for acquiring the same data is located to the same database server, which results in load balancing and the stability of the distributed system is poor.

For example, the application server performs hash processing on the data identifier, and determines the database server according to the processing result. All data requests for the data identifier A are located to the database server A, and all data requests for the data identifier B are located to the database server B. . If the number of data requests of the data identifier A is much larger than the number of data requests of the data identifier B, the processing pressure of the database server A is large, and the processing pressure of the database server B is small, and load balancing cannot be implemented between the database servers.

Summary of the invention

The application provides a hotspot keyword acquisition method, which is applied to a database server, and includes:

In the statistical period, obtain a keyword and obtain the number of accesses of the keyword;

Determining a number of access times of the number of accesses, and querying a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists;

Updating the location of the number of accesses of the keyword in the linked list;

When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.

Obtaining a keyword, querying a hash table by using the keyword, and obtaining a data block location corresponding to the keyword; the hash table is configured to record a correspondence between a keyword and a data block location;

Querying the number of accesses from the data block corresponding to the data block location, obtaining the number of accesses of the keyword by using the number of accesses that are queried, and updating the number of accesses of the keyword to the data block;

When the content in the data block needs to be deleted, the linked list with the lowest priority is searched according to the correspondence between the access number interval and the linked list, and the content in the last data block of the lowest priority linked list is deleted; The lowest-level linked list is the linked list corresponding to the minimum number of access times;

The present application provides a hotspot keyword obtaining apparatus, which is applied to a database server, and includes:

An obtaining module, configured to acquire a keyword in a statistical period, and obtain the number of accesses of the keyword;

a determining module, configured to determine a number of access times of the number of accesses, and query a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists; and update access of the keywords The number of times in the linked list;

The determining module is further configured to: when the hotspot keyword needs to be determined, read the number of accesses of the keyword from the linked list, and determine the hotspot keyword according to the number of accesses of the keyword.

An obtaining module, configured to acquire a keyword in a statistical period, and query a hash table by using the keyword to obtain a corresponding data block position; the hash table is configured to record a correspondence between a keyword and a data block position; Querying the number of accesses in the data block corresponding to the location of the data block, obtaining the number of accesses of the keyword by using the number of accesses that are queried, and updating the number of accesses of the keyword to the data block;

The determining module is configured to read the number of accesses of the keyword from the linked list when the hotkey keyword needs to be determined, and determine the hotspot keyword according to the number of accesses of the read keyword.

The deleting module is configured to: when the content in the data block needs to be deleted, query the linked list with the lowest priority according to the correspondence between the access number interval and the linked list, and delete the content in the last data block of the lowest priority linked list. The lowest priority linked list is a linked list corresponding to the smallest number of access times;

The determining module is further configured to: when the hotspot keyword needs to be determined, read the number of accesses of the keyword from the linked list, and determine the hotspot keyword according to the number of accesses of the read keyword.

The application provides a database server, the database server comprising:

a processor, configured to acquire a keyword in a statistical period, and obtain a number of accesses of the keyword; determine a number of access times in which the number of accesses is located, and query a linked list corresponding to the number of access times; Different access times intervals correspond to different linked lists; update the position of the number of accesses of the keyword in the linked list; when the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and according to the keyword The number of visits determines the hotspot keyword.

The application provides a database server, the database server comprising:

a processor, configured to acquire a keyword in a statistical period, and query a hash table by using the keyword to obtain a data block location corresponding to the keyword; wherein the hash table is used to record a keyword and Corresponding relationship of the location of the data block; querying the number of accesses from the data block corresponding to the location of the data block, and obtaining the number of accesses of the keyword by using the number of accesses queried, and updating the number of accesses of the keyword to In the data block; when the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.

The application provides a database server, the database server comprising:

a processor, configured to acquire a keyword in a statistical period, and obtain a number of accesses of the keyword; determine a number of access times in which the number of accesses is located, and query a linked list corresponding to the number of access times; The different access times interval corresponds to different linked lists; the number of access times of the keywords is updated in the linked list; when the content in the data block needs to be deleted, the priority is queried according to the correspondence between the access times interval and the linked list a lowest linked list, and deleting content in a last data block of the lowest priority linked list; wherein the lowest priority linked list is a linked list corresponding to a minimum number of access times; when a hot keyword needs to be determined, The number of visits to the keyword is read from the linked list, and the hotspot keyword is determined based on the number of visits to the keyword.

Based on the foregoing technical solution, in the embodiment of the present application, the database server may collect the hotspot keyword and notify the application server of the hotspot keyword, so that the application server performs load balancing processing on the data request of the hotkey keyword, thereby implementing distributed Load balancing of the system improves the stability and efficiency of the system and improves the overall processing capability of data requests for hot keywords. Moreover, the most valuable data is retained by dividing a plurality of linked lists and deleting the contents of the data blocks of the lowest priority linked list.

DRAWINGS

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings to be used in the embodiments of the present application or the description of the prior art will be briefly described below. Obviously, the drawings in the following description For example, some of the embodiments described in the present application can be obtained by those skilled in the art from the drawings of the embodiments of the present application.

1 is a schematic diagram of an application scenario in an implementation manner of the present application;

2A and 2B are flowcharts of a method for acquiring a hotspot keyword in an embodiment of the present application;

3 is an example of a data structure of a hash table and a linked list in an embodiment of the present application;

4 is a flowchart of a method for acquiring a hotspot keyword in another embodiment of the present application;

FIG. 5 is a flowchart of a method for acquiring a hotspot keyword in another embodiment of the present application;

6 is a structural diagram of a hotspot keyword acquiring apparatus in an embodiment of the present application;

7 is a structural diagram of a hotspot keyword obtaining apparatus in another embodiment of the present application;

FIG. 8 is a structural diagram of a hotspot keyword acquiring apparatus in another embodiment of the present application.

Detailed ways

The terms used in the embodiments of the present application are for the purpose of describing the specific embodiments, and are not intended to limit the application. The singular forms "a", "the", and "the" It should also be understood that the term "and/or" as used herein refers to any and all possible combinations of one or more of the associated listed items.

It should be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present application, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, the first information may also be referred to as the second information without departing from the scope of the present application. Similarly, the second information may also be referred to as the first information. Depending on the context, in addition, the word "if" may be interpreted to mean "at time" or "when" or "in response to determination."

A hotspot keyword acquisition method is proposed in the embodiment of the present application, and the method can be applied to a distributed system. Referring to FIG. 1 , which is a schematic diagram of an application scenario of an embodiment of the present application, a distributed system may include multiple database servers and multiple application servers. Figure 1 shows two database servers and three application servers as examples. In practical applications, the number of database servers and the number of application servers can be more. There is no limit to the number of database servers and the number of application servers.

In order to implement load balancing between the database servers, the database server can obtain the hotspot keywords and notify the application server of the hotspot keywords, so that the application server performs load balancing processing on the data requests of the hotkey keywords, thereby implementing the database. The load balancing between servers avoids the processing pressure of some database servers, while the processing pressure of other database servers is small.

In the embodiment of the present application, in order to obtain a hotspot keyword, the database server may count the number of accesses of the keyword, and determine whether the keyword is a hotspot keyword based on the number of accesses of the keyword. For example, when the number of accesses of the keyword is greater than the preset number of thresholds, the keyword is determined to be a hotspot keyword. When the number of accesses of the keyword is not greater than the preset number of times, the keyword is determined to be not a hotspot keyword.

In the embodiment of the present application, the key (Key) is a unique identifier of the data stored in the database server. When the application server sends a data request to the database server, the data request may carry a keyword, and after receiving the data request, the database server receives the data request. With this keyword, the data corresponding to the keyword can be queried from the database server and returned to the application server. The keyword may include, but is not limited to, a data identifier, a user identifier, a product identifier, and the like. The keyword is not limited, and the database server may query the locally stored data based on the keyword. For example, based on the data identifier, the database server can query the data corresponding to the data identifier, and based on the user identifier, the database server can query the data corresponding to the user identifier. Based on the item identification, the database server can query the data corresponding to the item identification. And so on.

To count the number of visits to a keyword, the database server can set the statistics period and count the number of visits to the keyword in each statistical period. For example, the duration of the statistical period is 1 second, then 0-1 seconds is 1 statistical period, 1-2 seconds is 1 statistical period, and so on. In the statistical period of 0-1 seconds, the database server counts the number of accesses of the keyword, and determines whether the keyword is a hot keyword based on the number of accesses of the keyword. In the statistical period of 1-2 seconds, the database server re-counts the number of accesses of the keyword, and determines whether the keyword is a hotspot keyword based on the number of accesses of the keyword. And so on.

In one example, the database server may use the data block to store the number of accesses of the keyword, each keyword occupies one data block, such as data block 1 stores the number of accesses of keyword 1, and data block 2 stores the number of accesses of keyword 2, And so on. In addition, the database server may receive a large number of keyword data requests during the statistical period, such as hundreds of thousands or even millions. When each keyword occupies one data block, it occupies a large number of data blocks, that is, access for storing keywords. The number of times will occupy a large number of data blocks.

However, the hotkey keyword acquisition function is only an auxiliary function of the database server. The database server does not allocate a large number of data blocks for this function, that is, it cannot use a large number of data blocks to store the number of accesses of keywords, and then obtain hotspot keywords. To this end, an LRU (Least Recently Used) algorithm is proposed, which uses the LRU algorithm to store the number of accesses of keywords based on a small number of data blocks.

For example, the database server allocates 100 data blocks for the "hotkey keyword acquisition" function (for example, 100 data blocks are used as an example. In actual applications, more data blocks can be allocated, and no limitation is imposed on this).

In the statistical period, if the data request of the keyword 1 is received in the first to the first time, the number of accesses of the keyword 1 is recorded in the data block 1, and the data block 1 is updated to the first data block of the LRU linked list. . If the data request of the keyword 2 is received at the 102nd time, the number of accesses of the keyword 2 is recorded in the data block 2, and the data block 2 is updated to the first data block of the LRU linked list, and the data block 1 is updated to The second data block of the LRU list. By analogy, if the data request of the keyword 100 is received in the 200th time, the number of accesses of the keyword 100 is recorded in the data block 100, and the data block 100 is updated to the first data block of the LRU linked list, and the data is Block 99 is updated to the second data block of the LRU linked list, and so on, and data block 1 is updated to the 100th data block of the LRU linked list (the last data block of the LRU linked list).

If the data request of the keyword 101 is received in the 201st time, since there is no data block available, the database server deletes the content of the last data block record from the LRU linked list, that is, deletes the keyword 1 recorded in the data block 1. The number of accesses, the number of accesses of the keyword 101 is recorded in the data block 1, the data block 1 is updated to the first data block of the LRU linked list, and the data block 100 is updated to the second data block of the LRU linked list, and the data block 99 is Updated to the third data block of the LRU list, and so on.

Obviously, before receiving the data request of the keyword 101, the number of accesses of the keyword 1 recorded in the data block 1 is the largest, the keyword 1 may be a hotspot keyword, and after receiving the data request of the keyword 101, The number of accesses of the keyword 1 recorded in the data block 1 is deleted, and the number of accesses of the hot keyword cannot be retained until the end of the statistical period, and it is impossible to count that the keyword 1 is a hot keyword.

For the above findings, in the embodiment of the present application, multiple access times intervals may be divided, each access time interval corresponds to a linked list, and different access times intervals correspond to different linked lists. The linked list may include, but is not limited to, an LRU linked list. For convenience of description, the following takes a linked list as an example for description.

For example, the linked list 1 corresponds to the access number interval 1, and the access number interval 1 corresponds to (the number of accesses 1 - the number of accesses 100); the linked list 2 corresponds to the access number interval 2, and the access number interval 2 corresponds to (the number of accesses 101) - the number of accesses 200); the linked list 3 corresponds to the access number interval 3, and the access number interval 3 corresponds to (the number of accesses 201 - infinity), that is, the number of accesses 201 is greater than or equal to. Of course, the above example is described by taking three linked lists and three access times intervals as an example. In practical applications, the number of linked lists and the number of access times can be more, and the number is not limited. In addition, the numerical value corresponding to the above-mentioned access number interval is only an example of the present application, and no limitation is imposed thereon.

In the above application scenario, as shown in FIG. 2A, which is a flowchart of a method for acquiring a hotspot keyword according to an embodiment of the present application, the method may be applied to a database server, and the method may include:

In step 201, during the statistical period, the keyword is obtained, and the number of accesses of the keyword is obtained.

In an example, the database server can obtain the keyword and obtain the number of accesses of the keyword in each statistical period. For convenience of description, a statistical period is taken as an example for description.

In an example, after receiving the data request sent by the client, the application server (such as the APP server) may determine the database server by using a hash algorithm and send a data request to the database server. After receiving the data request, the database server parses the keyword from the data request.

The keyword may include, but is not limited to, a data identifier, a user identifier, a product identifier, and the like. The keyword is not limited, and the database server may query the locally stored data based on the keyword. For example, based on the data identifier, the database server can query the data corresponding to the data identifier, and based on the user identifier, the database server can query the data corresponding to the user identifier.

The client may be an APP of a terminal device (such as a PC (Personal Computer), a notebook computer, a mobile terminal, or the like), or may be a browser of the terminal device, and the type of the client is not limited, and all of the clients may be Clients accessing the application server are within the scope of this application.

The application server may be a server that provides services for the client, and the application server may obtain data requested by the client from the database server, and send the data to the client. For example, the application server may be a data platform, an e-commerce platform, etc., and the type of the application server is not limited.

The database server may be a server that stores data. After receiving the data request sent by the application server, the database server parses the keyword from the data request, and locally queries the data corresponding to the keyword, and sends the data. Give the application server and then return the data to the client.

Referring to FIG. 2B, the process of “acquiring the number of accesses of the keyword” may include:

Step 2011: Obtain a data block location corresponding to the keyword.

In an example, the process of “acquiring the location of the data block corresponding to the keyword” may include, but is not limited to, the following manner: mode 1. Since the data block can record the correspondence between the keyword and the number of accesses, the database server may Each data block is traversed in turn, and if the keyword is recorded in the traversed data block, the data block position of the data block is the data block position corresponding to the keyword. In the second method, the database server may store a hash table, where the hash table is used to record the correspondence between the keyword and the data block location; based on the hash table, the database server may query the hash table by using the keyword, if If the keyword exists in the hash table, the data block position corresponding to the keyword can be obtained.

In the second method, since the database server does not need to traverse each data block in turn, and only needs to store the hash table, the data block position corresponding to the keyword can be queried from the hash table, thereby avoiding the traversal operation of the database server. Reduce the processing pressure of the database server and save time in traversal operations.

Referring to FIG. 3, which is an example of a data structure of a hash table and a linked list, the hash table may include, but is not limited to, a HashMap table, which may include, but is not limited to, an N-level LRU linked list.

In an example, the hash table is used to record the correspondence between the keyword and the location of the data block. After receiving the data request, the database server can parse the keyword from the data request and query the hash table through the keyword. . If the keyword does not exist in the hash table, the database server selects a data block for the keyword, records the number of accesses of the keyword into the selected data block, and records the keyword and the selection in the hash table. The correspondence of the data block positions of the data blocks. If the keyword exists in the hash table, the database server can obtain the data block location corresponding to the keyword from the hash table.

In an example, the N-level linked list refers to N linked lists, and each linked list corresponds to an access number interval, such as the linked list corresponding access times interval 1 (the number of accesses 1 - the number of accesses 100), and the linked list 2 corresponds to the access times interval 2 (accesses The number of times 101 - the number of accesses 200), the linked list 3 corresponds to the access number interval 3 (the number of accesses 201 - infinity), which may indicate that when the number of accesses of the keywords recorded in the data block is located in the access number interval 1, then The data block belongs to the linked list 1; when the number of accesses of the keywords recorded in the data block is located in the access number interval 2, the data block belongs to the linked list 2; when the number of accesses of the keywords recorded in the data block is located in the access When the number of times is 3, the data block belongs to the linked list 3.

In one example, for mode one, the data block is used to record the keyword, the number of accesses of the keyword, and for the second mode, the data block is used to record the number of accesses of the keyword. Of course, the data block can also record the keyword. For convenience of description, the data block record keyword and the number of accesses of the keyword are taken as an example.

For the second method, the example of “acquiring the data block location corresponding to the keyword” may be: after receiving the data request of the keyword 1 , the database server queries the hash table by using the keyword 1 . If the keyword 1 does not exist in the hash table, the database server selects a data block for the keyword 1 (such as an unoccupied data block or a currently released data block; an unoccupied data block means that the data block has not been recorded yet) The number of accesses of the keyword and the keyword; the currently released data block means that the data block has recorded the keyword and the number of accesses of the keyword, but the content recorded in the data block is deleted, and the subsequent process introduces the deletion process).

Assuming that the data block 80 is selected for the keyword 1, the data block 80 is used to record the number of accesses of the keyword 1 and the keyword 1, and the correspondence relationship between the key 1 and the data block position of the data block 80 is recorded in the hash table.

After the database server receives the data request of the keyword 1 again, the hash table is queried by the keyword 1. Since the keyword 1 already exists in the hash table, the database server can directly obtain the keyword 1 from the hash table. The corresponding data block position, that is, the data block position of the data block 80.

In step 2012, the number of accesses is queried from the data block corresponding to the data block location.

Since the data block is used to record the number of accesses of the keyword and the keyword, the database server can query the number of accesses from the data block corresponding to the data block position after obtaining the data block position.

In step 2013, the number of accesses of the keyword is obtained by using the number of accesses queried.

The process for obtaining the number of accesses of the keyword by using the number of accesses queried may include, but is not limited to, the following method: determining the number of accesses of the keyword is a preset number of accesses (for example, 1); Alternatively, the resource information corresponding to the keyword is obtained, and the weight value of the keyword is determined according to the resource information, and the number of accesses of the keyword is determined to be a weighted value of the number of access times.

In step 2014, the number of accesses of the keyword is updated to the data block corresponding to the data block position.

The number of accesses queried from the data block is the number of times the keyword is recorded in the data block when the data block was last updated. For convenience of description, in the subsequent process, the number of accesses is called a keyword. The number of first visits. The number of accesses of the currently obtained keyword is the number of times the keyword is recorded in the data block when the data block is updated this time. For convenience of description, in the subsequent process, the number of accesses is referred to as the second keyword. The number of visits. Obviously, the next time the data block needs to be updated, the second number of accesses becomes the first number of accesses to the keywords recorded in the data block.

In one example, each time a keyword (such as keyword 1) is obtained, the first access number of the keyword 1 is read from the data block corresponding to the data block position (such as the data block 80), and the first access number is obtained. Add 1 to get the second number of visits. For example, after the keyword 1 is obtained for the 100th time, the first access number 99 of the keyword 1 is read from the data block 80, the first access number 99 is incremented by 1, the second access number 100 is obtained, and the second access is obtained. The number of times 100 is updated into data block 80. After obtaining the keyword for the 101st time, the first access number 100 of the keyword 1 is read from the data block 80, and the first access number 100 is incremented by 1, the second access number 101 is obtained, and the second access number 101 is obtained. Update to data block 80. And so on.

In another example, each time a keyword (such as keyword 1) is obtained, the first access number of the keyword 1 can be read from a data block corresponding to the data block location (such as the data block 80), and the The first number of visits weights the weight value to obtain the second number of accesses. For example, the weight value is 5 as an example. After the keyword 1 is obtained for the 100th time, the first access number 495 of the keyword 1 can be read from the data block 80, and the first access number 495 is weighted. 5. The second access number 500 is obtained, and the second access number 500 is updated to the data block 80. After obtaining the keyword for the 101st time, the first access number 500 of the keyword 1 can be read from the data block 80, and the first access number 100 is weighted by 5 to obtain the second access number 505, and the second is obtained. The number of accesses 505 is updated into data block 80. And so on.

In order to obtain the weight value of the keyword (such as the keyword 1) (such as the weight value 5 described above), after each keyword 1 is obtained, the resource information corresponding to the keyword 1 can be obtained, and the keyword 1 is determined according to the resource information. Weights. Alternatively, after the keyword 1 is obtained for the first time, the resource information corresponding to the keyword 1 may be acquired, and the weight value of the keyword 1 is determined according to the resource information; then, the weight value is recorded to the data block 80, and the key is obtained again. After word 1, the weight value can be read directly from data block 80.

In one example, the resource information may include, but is not limited to, a data size of the keyword corresponding data, and/or a processing time of the keyword corresponding request. Based on this, the process of determining the weight value of the keyword according to the resource information may include, but is not limited to, the following manner: if the resource information includes the data size of the keyword corresponding data, the relationship between the data size and the preset size may be Determine the weight value of the keyword. If the resource information includes the processing time of the keyword corresponding request, the weight value of the keyword may be determined according to the relationship between the processing time and the preset time. If the resource information includes the data size of the keyword corresponding data and the processing time of the keyword corresponding request, the first sub-weight value of the keyword may be determined according to the relationship between the data size and the preset size; according to the processing time and the preset time a relationship, determining a second sub-weight value of the keyword; determining a weight value of the keyword according to the first sub-weight value and the second sub-weight value.

The process of determining the weight value of the keyword according to the relationship between the data size and the preset size includes: configuring the preset size according to experience, and determining the keyword if the data size of the keyword corresponding data is less than or equal to the preset size. The weight value is 1. If the data size of the keyword corresponding data is greater than the preset size, determine the weight value of the keyword is “round the data size by the preset size.” If the data size is 8, and the preset size is 5, the weight value is "Right 8/5 up", that is, the weight value is 2; the data size is 11, and the preset size is 5, the weight value is "rounded up to 11/5", that is, the weight value is 3.

The process of determining the weight value of the keyword according to the relationship between the processing time and the preset time includes: configuring the preset time according to experience, and determining the keyword if the processing time of the keyword corresponding request is less than or equal to the preset time The weight value is 1. If the processing time of the keyword corresponding request is greater than the preset time, the weight of the keyword is determined to be “rounded by the preset time divided by the preset time”. For example, if the processing time is 8, and the preset time is 5, the weight value is "Right 8/5 up", that is, the weight value is 2; the processing time is 11, when the preset time is 5, the weight value is "rounded up to 11/5", that is, the weight value is 3.

The process of determining the first sub-weight value of the keyword according to the relationship between the data size and the preset size may include: determining the keyword if the data size of the keyword corresponding data is less than or equal to the preset size. The first sub-weight value is 1. If the data size of the keyword corresponding data is greater than the preset size, it is determined that the first sub-weight value of the keyword is “rounded up by dividing the data size by the preset size”.

The process of determining the second sub-weight value of the keyword according to the relationship between the processing time and the preset time may include: determining the keyword if the processing time of the keyword corresponding request is less than or equal to the preset time The second sub-weight value is 1. If the processing time of the keyword corresponding request is greater than the preset time, it is determined that the second sub-weight value of the keyword is “rounded up by the preset time divided by the preset time”.

The process of determining the weight value of the keyword according to the first sub-weight value and the second sub-weight value may include: determining a weight value of the keyword as the first sub-weight value plus the second sub-weight value.

For example, if the data size is 8, the preset size is 5, the processing time is 11, and the preset time is 5, the first sub-weight value is “rounded up to 8/5”, that is, the first sub-weight value is 2. The second sub-weight value is "rounded up to 11/5", that is, the second sub-weight value is 3; therefore, the weight value of the keyword is 2+3=5.

In the above embodiment, the data size of the keyword correspondence data means that, assuming that the application server requests the data A corresponding to the keyword 1, the data size of the data corresponding to the keyword 1 is the size of the data A. Since the database server stores data A, the database server can know the size of the data A.

In the above embodiment, the processing time of the keyword correspondence request is: if the application server requests the data A corresponding to the keyword 1, the processing time of the keyword 1 corresponding to the request is, and the keyword 1 is received from the database server. The data request, to the time when the database server returns a response carrying the data A to the application server, and the database server can analyze the size of the time.

Step 202: Determine the number of access times in which the number of accesses (ie, the number of accesses obtained in step 201) is located, and query a linked list (such as an LRU linked list, etc.) corresponding to the number of access times.

Assuming that the number of accesses of the acquired keywords is 105, it is determined that the number of accesses 105 is located in the access number interval 2, and the number of accesses interval 2 corresponds to the linked list 2. Assuming that the number of accesses of the acquired keywords is 260, it is determined that the number of accesses 206 is located in the access number interval 3, and the number of accesses interval 3 corresponds to the linked list 3.

Step 203: Update the position of the number of accesses of the keyword in the linked list (ie, the linked list corresponding to the access number interval), for example, the data block in which the number of access times of the keyword is located may be updated to the first data block of the linked list.

Assuming that the number of accesses of the keyword 1 is 105, the data block 80 in which the number of accesses 105 of the keyword 1 is located can be updated to the first data block of the linked list 2. Assuming that the number of accesses of the keyword 1 is 260, the data block 80 in which the number of accesses 260 of the keyword 1 is located can be updated to the first data block of the linked list 3.

It is assumed that the linked list 1 includes, in order, a data block 1, a data block 2, a data block 80, and a data block 3 - a data block 79. The linked list 2 sequentially includes a data block 81 - a data block 90, which in turn includes a data block 91 - a data block 100.

Further, in step 201, it is assumed that the number of accesses recorded by the data block 80 is updated from 100 to 105. In step 202, it is determined that the linked list is the linked list 2, and in step 203, the data block 80 can be updated to the linked list 2. The first data block. That is, the linked list 1 includes the data block 1 - the data block 79 in turn, and the linked list 2 includes the data block 80 - the data block 90 in turn, and the linked list 3 sequentially includes the data block 91 - the data block 100.

For another example, in step 201, it is assumed that the number of accesses recorded by the data block 60 is updated from 50 to 51. In step 202, it is determined that the linked list is the linked list 1, that is, the linked list of the data block 60 does not change, in step 203. The data block 60 can be updated to the first data block of the linked list 1. That is, the linked list 1 may sequentially include a data block 60, a data block 1 - a data block 59, a data block 61 - a data block 79, and the linked list 2 may sequentially include a data block 80 - a data block 90, and the linked list 3 may sequentially include the data block 91. - Data block 100.

For another example, in step 201, it is assumed that the number of accesses recorded by the data block 90 is updated from 199 to 208. In step 202, it is determined that the linked list is the linked list 3, that is, the linked list of the data block 90 has changed. In step 203, The data block 90 can be updated to the first data block of the linked list 3. That is, the linked list 1 may sequentially include a data block 60, a data block 1 - a data block 59, a data block 61 - a data block 79, and the linked list 2 may sequentially include a data block 80 - a data block 89, and the linked list 3 may include the data block 90 in sequence. - Data block 100.

In an example, if the content in the data block needs to be deleted in the statistical period, the linked list with the lowest priority may be queried, and the content in the last data block of the lowest priority linked list is deleted; The linked list with the lowest priority is a linked list corresponding to the smallest number of access times.

The database server receives the data request sent by the application server, if the keyword carried by the data request is a new keyword (that is, the number of accesses of the keyword is not recorded in all the data blocks), and all the data blocks are already If it is occupied, it is determined that the content in one data block needs to be deleted.

The linked list in the embodiment of the present application has a priority, and the lowest priority linked list is a linked list corresponding to the smallest access number interval, and the highest priority linked list is the linked list corresponding to the largest access number interval, and the access number interval The larger the score, the higher the priority of the linked list corresponding to the access number interval.

For example, since the access number interval 3 (the number of accesses 201 - infinity) is larger than the access number interval 2 (the number of accesses 101 - the number of accesses 200), it is determined that the priority of the linked list 3 corresponding to the access number interval 3 is higher than the access number interval 2 The priority of the linked list 2. Since the access number interval 2 is larger than the access number interval 1 (the number of accesses 1 - the number of accesses 100), it can be determined that the priority of the linked list 2 corresponding to the access number interval 2 is higher than the priority of the linked list 1 corresponding to the access number interval 1. In summary, the priority of the linked list 1 can be the lowest, the priority of the linked list 3 can be the highest, and the priority of the linked list 2 is in the middle.

It is assumed that the linked list 1 includes the data block 1 - the data block 79 in sequence, and the linked list 2 includes the data block 80 - the data block 90 in sequence, and the linked list 3 includes the data block 91 - the data block 100 in sequence, when the content in the data block needs to be deleted, The linked list 1 with the lowest priority is queried, and the content (such as the keyword, the number of accesses of the keyword, etc.) in the last data block of the linked list 1 (such as the data block 79) is deleted. Thus, data block 79 can record new keywords as well as the number of accesses to new keywords. The data block 79 is then updated to the first data block of the linked list 1. That is to say, the linked list 1 may sequentially include a data block 79, a data block 1 - a data block 78, and the linked list 2 sequentially includes a data block 80 - a data block 90, which in turn includes a data block 91 - a data block 100.

After the content (such as the keyword, the number of accesses of the keyword, etc.) in the data block 79 of the linked list 1 is deleted, the keyword in the data block 79 and the data block position of the data block 79 can also be deleted from the hash table. Correspondence relationship, and the correspondence between the new keyword and the data block position of the data block 79 is recorded in the hash table.

In summary, each data block of the linked list with high priority has a large number of access records, and each data block of the linked list with a low priority has a small number of access records, for example, the highest priority linked list 3 Each data block, wherein the number of accesses recorded is greater than or equal to 201, such as 10000, and the data block of the linked list 3 having the lowest priority, wherein the number of accesses recorded is less than or equal to 100, and may be 1, therefore, needs to be deleted. When the content in the data block is deleted, the keyword in the linked list 1 with the lowest priority is deleted, so that the keyword with a small number of accesses is deleted, and the keyword with a large number of accesses is not deleted, that is, the key of the hot keyword may be Words will not be deleted, so you can keep the number of visits to hot keywords to the end of the statistical period, so you can improve the validity of the statistics when counting hot keywords.

Step 204: When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list (eg, from the data block of the linked list), and the hotspot keyword is determined according to the number of accesses of the keyword.

After the statistics period ends, the hotspot keyword needs to be determined, and the process of determining the hotspot keyword according to the number of accesses of the keyword is performed, and then the next statistical period can be entered, and the above steps 201-203 are performed again. . Alternatively, when receiving an instruction for determining a hotspot keyword, it is necessary to determine a hotspot keyword, perform a process of "determining a hotspot keyword according to the number of accesses of the keyword", and then, proceed to the next statistical cycle, and re- Perform the above steps 201-203.

After determining the hotspot keyword, the hotspot keyword may also be notified to the application server.

For example, after the end of the statistical period, the database server may sequentially read the number of accesses of the keyword from each data block (such as data block 1 - data block 100), if the number of accesses of the keyword is greater than a preset number of thresholds (may be If the experience is configured, the keyword may be a hot keyword. If the number of accesses of the keyword is not greater than the preset threshold, the keyword may be determined to be not a hot keyword.

In one example, the process of "reading the number of accesses of a keyword from a linked list and determining a hotspot keyword according to the number of accesses of the keyword" may include, but is not limited to, according to the highest priority linked list to the lowest priority The order of the linked list sequentially traverses the data blocks of the linked list; the highest priority linked list is the linked list corresponding to the largest access number interval, and the lowest priority linked list is the linked list corresponding to the smallest access number interval. Then, if the number of accesses of the keywords recorded in the traversed data block is greater than the preset number of times threshold, it is determined that the keyword is a hotspot keyword; otherwise, it is determined that the keyword is not a hotspot keyword. After traversing to the linked list that is not a hotkey keyword, stop traversing the data block of the next linked list.

For example, suppose that the linked list 1 includes the data block 1 - the data block 79 in turn, the linked list 2 includes the data block 80 - the data block 90 in turn, and the linked list 3 includes the data block 91 - the data block 100 in sequence, and the preset number of thresholds is 210, then: The order of the highest priority linked list to the lowest priority linked list, the database server first traverses each data block of the linked list 3 (such as data block 91 - data block 100), and then traverses each data block of the linked list 2 (such as data block 80) - Data block 90), and then traverse each data block of the linked list 1 (e.g., data block 1 - data block 79).

Assuming that the number of accesses recorded in the data block 91-data block 99 is greater than the preset number of times threshold, and the number of accesses recorded in the data block 100 is not greater than the preset number of times threshold, the key recorded in the data block 91-data block 99 is a hotspot. The keyword, and the keyword recorded in the data block 100 is not a hot keyword. Moreover, since the traversal to the linked list 3 that is not a hotkey keyword, the traversal of the data block of the next linked list is stopped, that is, each data block of the linked list 2 is no longer traversed, and each data block of the linked list 1 is no longer traversed, and the end Traversing.

Obviously, in the above manner, only each data block of the linked list 3 is traversed, and each data block of the linked list 2 is no longer traversed, and each data block of the linked list 1 is no longer traversed, thereby reducing the processing pressure of the database server and saving the database. The server's resources can speed up the process of data block traversal and save processing time.

In an example, after the end of the statistical period, the contents of all the linked data blocks can be cleared, and all the contents of the hash table are cleared, so that the data block, the hash table, and the linked list are all returned to the initial state, that is, In the initial state, the above steps 201-203 are re-executed, and the process will not be described again.

In one example, the above-described execution order is only an example given for convenience of description. In an actual application, the execution order between the steps may also be changed, and the order of execution is not limited. Moreover, in other embodiments, the steps of the respective methods are not necessarily performed in the order shown and described herein, and the methods may include more or less steps than those described in this specification. In addition, the individual steps described in this specification may be decomposed into a plurality of steps for description in other embodiments; the various steps described in the present specification may be combined into a single step for description in other embodiments.

In an example, after the database server obtains the hotspot keyword, the hotspot keyword can be notified to the application server. After the application server obtains the hotspot keyword, the application server can cache the data corresponding to the hotkey keyword locally. In this way, after receiving the data request for the hotspot keyword sent by the client, the application server can locally query the data corresponding to the hotkey keyword, and send the data corresponding to the hotkey keyword to the client without using the database server. Get the data corresponding to the hot keyword.

In another example, after obtaining the hotspot keyword, the application server may also change the hash algorithm for the hotspot keyword, so as to avoid the data request for the hotkey keyword being located to the same database server, thereby achieving load balancing and improving The stability of the distributed system. For example, after receiving the data request for the hotspot keyword sent by the client, the application server periodically changes the hash algorithm, so that the data request 1 - the data request 100 is sent to the database server A, and the data request 101 - the data request 200 is sent to the database. Server B, and so on, to achieve load balancing between database servers.

For example, after receiving 100 data requests for hotspot keywords, the application server can change the hash algorithm to change the database server to achieve load balancing between the database servers.

In another example, after obtaining the hotspot keyword, the database server may also cache the data corresponding to the hotspot keyword in the HotZone storage area of the database server (ie, the pre-divided area for storing hotspot data). In this way, after receiving the data request for the hotspot keyword sent by the application server, the database server can directly query the data corresponding to the hotspot keyword from the HotZone storage area, and send the data corresponding to the hotspot keyword to the application server instead of using the data. The data storage medium to the database server obtains data corresponding to the hotkey keyword, thereby speeding up data acquisition.

In summary, an example of the data acquisition process may be: after receiving the data request carrying the keyword sent by the client, the application server first queries the data corresponding to the keyword locally; if the keyword exists locally, the keyword corresponds to The application server directly sends the data corresponding to the keyword to the client; if the data corresponding to the keyword does not exist locally, the application server sends a data request carrying the keyword to the database server. After receiving the data request of the keyword sent by the application server, the database server queries the data corresponding to the keyword from the HotZone storage area; if the data corresponding to the keyword exists in the HotZone storage area, the database server obtains the data from the HotZone storage area. The data corresponding to the keyword is sent to the application server; if the data corresponding to the keyword does not exist in the HotZone storage area, the data corresponding to the keyword may be obtained from the data storage medium of the database server, and Send the data corresponding to the keyword to the application server.

In an example, after the application server caches the data corresponding to the hotkey keyword locally, the application server may also set an expiration time for the data, and after the expiration time arrives, the cached data is deleted locally. After the database server caches the data corresponding to the hotkey keyword in the HotZone storage area, the database may also set an expiration time for the data. After the expiration time arrives, the cached data is deleted from the HotZone storage area.

Based on the foregoing technical solution, in the embodiment of the present application, the database server may collect the hotspot keyword and notify the application server of the hotspot keyword, so that the application server performs load balancing processing on the data request of the hotkey keyword, thereby implementing distributed Load balancing of the system improves the stability and efficiency of the system and improves the overall processing capability of data requests for hot keywords. Moreover, since the database server does not need to traverse each data block in turn, only need to store the hash table, the data block position corresponding to the keyword can be queried from the hash table, thereby avoiding the traversal operation of the database server and reducing the database server. The processing pressure saves time in traversing operations. When the content in the data block needs to be deleted, the keywords in the lowest priority linked list are deleted, so that the keywords with small access times are deleted, and the keywords with large access times are not deleted, that is, hot keywords may be deleted. The keywords will not be deleted, so the number of visits to the hot keywords can be retained until the end of the statistical period. When the hot keywords are counted, the validity of the statistics can be improved. It is possible to traverse only each data block of the linked list with high priority, and not to traverse each data block of the linked list with low priority, and then count the hotspot keywords, thereby alleviating the processing pressure of the database server and saving the resources of the database server. Save processing time.

Based on the same application concept as the above method, as shown in FIG. 4, which is a flowchart of another hotspot keyword acquisition method, the method may be applied to a database server, and the method may include:

Step 401: Acquire a keyword in a statistical period, and query a hash table by using the keyword to obtain a data block location corresponding to the keyword. The hash table is used to record the correspondence between the keyword and the data block position. Therefore, the data block position corresponding to the keyword can be obtained from the hash table.

Step 402: Query the number of accesses from the data block corresponding to the data block location, and obtain the number of accesses of the keyword by using the number of accesses queried, and update the number of accesses of the keyword into the data block.

Step 403: When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.

In an example, after the hash table is queried by the keyword, if the keyword does not exist in the hash table, the data block is selected for the keyword; the number of accesses of the keyword is recorded in the selected data block. And the correspondence between the keyword and the data block position of the selected data block is recorded in the hash table.

In an example, the process of obtaining the number of accesses of the keyword by using the number of accesses queried may include, but is not limited to, determining that the number of accesses of the keyword is a preset value of the number of accesses queried; or Obtaining resource information corresponding to the keyword, determining a weight value of the keyword according to the resource information, and determining that the number of access times of the keyword is a weighted value of the number of times of the query; wherein the resource information includes a data size of the keyword corresponding data, and / or, the keyword corresponds to the processing time of the request.

The flow shown in FIG. 4 is similar to the flow shown in FIG. 2A, and details are not repeated herein.

Based on the same application concept as the above method, as shown in FIG. 5, which is a flowchart of another hotspot keyword acquisition method, the method may be applied to a database server, and the method may include:

Step 501: Acquire a keyword in a statistical period, and obtain the number of accesses of the keyword.

Step 502: Determine a number of access times of the number of accesses, and query a linked list corresponding to the number of access times; wherein different access times intervals may correspond to different linked lists.

Step 503: Update the location of the number of accesses of the keyword in the linked list.

Step 504, when the content in the data block needs to be deleted, according to the correspondence between the access number interval and the linked list, query the lowest priority linked list, and delete the content in the last data block of the lowest priority linked list; The lowest priority linked list is the linked list corresponding to the smallest number of access times.

Step 505: When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.

In one example, the process of "reading the number of accesses of a keyword from a linked list and determining a hotspot keyword according to the number of accesses of the keyword" may include, but is not limited to, according to the highest priority linked list to the lowest priority The sequence of the linked list sequentially traverses the data blocks of the linked list; wherein, the highest priority linked list is the linked list corresponding to the largest access number interval, and the lowest priority linked list is the linked list corresponding to the smallest access number interval; if the traversed data block is traversed If the number of accesses of the recorded keyword is greater than the preset number threshold, it is determined that the keyword is a hotspot keyword; otherwise, it is determined that the keyword is not a hotspot keyword; after traversing to the linked list that is not a hotkey keyword, stopping traversing the next one The data block of the linked list.

The flow shown in FIG. 5 is similar to the flow shown in FIG. 2A, and details are not repeated herein.

Based on the same application concept as the above method, the embodiment of the present application further provides a hotspot keyword obtaining apparatus, which is applied to a database server, as shown in FIG. 6, which is a structural diagram of a hotspot keyword acquiring apparatus.

The obtaining module 601 is configured to acquire a keyword in a statistical period, and obtain a number of access times of the keyword;

a determining module 602, configured to determine an access number interval in which the number of accesses is located, and query a linked list corresponding to the access number interval; wherein different access times intervals correspond to different linked lists; and update the keyword The number of visits in the linked list;

The determining module 602 is further configured to: when the hotspot keyword needs to be determined, read the number of accesses of the keyword from the linked list, and determine the hotspot keyword according to the number of accesses of the keyword.

The obtaining module 601 is configured to: obtain a data block location corresponding to the keyword, and query the number of accesses from the data block corresponding to the data block location in the process of acquiring the number of accesses of the keyword, And obtaining the number of accesses of the keyword by using the number of accesses queried;

The obtaining module 601 is specifically configured to: when the location of the data block corresponding to the keyword is obtained, query the hash table by using the keyword to obtain a data block location corresponding to the keyword; The hash table is used to record a correspondence between a keyword and a data block position;

In the process of obtaining the number of accesses of the keyword by using the number of times of the query, the number of times of accessing the keyword is determined by adding a preset value to the number of times the query is accessed; or obtaining the resource information corresponding to the keyword. And determining, according to the resource information, a weight value of the keyword, and determining that the number of accesses of the keyword is the number of accesses that are queried plus the weight value; wherein the resource information includes: the keyword corresponding data The data size, and/or, the keyword corresponds to the processing time of the request.

In one example, the hotspot keyword acquisition means further includes (not shown in the figure):

a deleting module, configured to: when the content in the data block needs to be deleted, query the lowest priority linked list, and delete the content in the last data block of the lowest priority linked list;

The determining module 602 is specifically configured to: in the process of determining a hotspot keyword according to the number of accesses of the keyword, sequentially traversing the data block of the linked list according to the order of the highest priority linked list to the lowest priority linked list; if traversing If the number of accesses of the keywords recorded in the data block is greater than the preset number of thresholds, it is determined that the keyword is a hotspot keyword; otherwise, it is determined that the keyword is not a hotspot keyword; after traversing to the linked list that is not a hotkey keyword, stopping Traversing the data blocks of the next linked list;

The linked list with the highest priority is a linked list corresponding to the largest number of access times, and the linked list with the lowest priority is a linked list corresponding to the smallest number of access times.

Based on the same application concept as the above method, the embodiment of the present application further provides a database server, where the database server includes: a processor, configured to acquire a keyword in a statistical period, and obtain the number of accesses of the keyword. Determining the number of access times of the number of accesses, and querying a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists; updating the number of accesses of the keywords in the linked list The location; when the hotkey keyword needs to be determined, the number of visits to the keyword is read from the linked list, and the hotkey keyword is determined according to the number of visits to the keyword.

Based on the same application concept as the above method, the embodiment of the present application further provides a machine readable storage medium, which can be applied to a database server, where the computer readable storage medium stores a plurality of computer instructions, when the computer instructions are executed. Performing the following steps: acquiring a keyword in a statistical period, and obtaining the number of accesses of the keyword; determining a number of access times in which the number of accesses is located, and querying a linked list corresponding to the number of access times; different accesses The number of times interval corresponds to a different linked list; the number of access times of the keyword is updated in the linked list; when the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the number of accesses of the keyword is determined according to the number of accesses of the keyword Hot keywords.

Based on the same application concept as the above method, the embodiment of the present application further provides a hotspot keyword obtaining apparatus, which is applied to a database server, as shown in FIG. 7 , which is a structural diagram of a hotspot keyword acquiring apparatus.

The obtaining module 701 is configured to: acquire a keyword in the statistical period, query the hash table by using the keyword, and obtain a corresponding data block position; the hash table is configured to record a correspondence between the keyword and the data block position; Querying the number of accesses from the data block corresponding to the data block location, obtaining the number of accesses of the keyword by using the number of accesses that are queried, and updating the number of accesses of the keyword to the data block;

The determining module 702 is configured to read the number of accesses of the keyword from the linked list when the hotspot keyword needs to be determined, and determine the hotspot keyword according to the number of accesses of the read keyword.

Based on the same application concept as the above method, the embodiment of the present application further provides a database server, where the database server includes: a processor, configured to acquire a keyword in a statistical period, and query a hash by using the keyword a table, the data block location corresponding to the keyword is obtained; wherein the hash table is used to record a correspondence between a keyword and a data block location; and the number of accesses is queried from a data block corresponding to the data block location, And obtaining the number of accesses of the keyword by using the number of accesses queried, and updating the number of accesses of the keyword to the data block; when the hotkey keyword needs to be determined, reading the keyword from the linked list The number of times, and the hotspot keyword is determined based on the number of visits to the keyword.

Based on the same application concept as the above method, the embodiment of the present application further provides a machine readable storage medium, which can be applied to a database server, where the computer readable storage medium stores a plurality of computer instructions, when the computer instructions are executed. Performing a process of: acquiring a keyword in a statistical period, and querying a hash table by using the keyword to obtain a data block location corresponding to the keyword; the hash table is used to record a keyword and a data block location Corresponding relationship; querying the number of accesses from the data block corresponding to the location of the data block, and obtaining the number of accesses of the keyword by using the number of accesses queried, and updating the number of accesses of the keyword to the data In the block; when the hotkey keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotkey keyword is determined according to the number of accesses of the keyword.

Based on the same application concept as the above method, the embodiment of the present application further provides a hotspot keyword obtaining apparatus, which is applied to a database server, as shown in FIG. 8 , which is a structural diagram of a hotspot keyword acquiring apparatus.

The obtaining module 801 is configured to acquire a keyword and obtain the number of access times of the keyword in a statistical period;

a determining module 802, configured to determine an access number interval in which the number of accesses is located, and query a linked list corresponding to the access number interval; wherein different access times intervals correspond to different linked lists; and update the keyword The number of visits in the linked list;

The deleting module 803 is configured to: when the content in the data block needs to be deleted, query the lowest priority linked list according to the correspondence between the access number interval and the linked list, and select the content in the last data block of the lowest priority linked list. Delete; the lowest priority linked list is the linked list corresponding to the smallest number of access times;

The determining module 802 is further configured to: when the hotspot keyword needs to be determined, read the number of accesses of the keyword from the linked list, and determine the hotspot keyword according to the number of accesses of the read keyword.

Based on the same application concept as the above method, the embodiment of the present application further provides a database server, where the database server includes: a processor, configured to acquire a keyword in a statistical period, and obtain the number of accesses of the keyword. Determining the number of access times of the number of accesses, and querying a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists; updating the number of accesses of the keywords in the linked list Position; when the content in the data block needs to be deleted, according to the correspondence between the access number interval and the linked list, the lowest priority linked list is queried, and the content in the last data block of the lowest priority linked list is deleted; The lowest-priority linked list is a linked list corresponding to the minimum access number interval; when the hot-spot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hot-spot keyword is determined according to the number of accesses of the keyword.

Based on the same application concept as the above method, the embodiment of the present application further provides a machine readable storage medium, which can be applied to a database server, where the computer readable storage medium stores a plurality of computer instructions, when the computer instructions are executed. Performing the following steps: acquiring a keyword in a statistical period, and obtaining the number of accesses of the keyword; determining a number of access times in which the number of accesses is located, and querying a linked list corresponding to the number of access times; different accesses The time interval corresponds to a different linked list; the number of access times of the keyword is updated in the linked list; when the content in the data block needs to be deleted, the lowest priority linked list is searched according to the correspondence between the access number interval and the linked list And deleting the content in the last data block of the lowest priority linked list; wherein the lowest priority linked list is a linked list corresponding to the smallest access number interval; when the hotspot keyword needs to be determined, from the linked list Read the number of visits to the keyword and determine the hotspot key based on the number of visits to the keyword .

The system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function. A typical implementation device is a computer, and the specific form of the computer may be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver, and a game control. A combination of a tablet, a tablet, a wearable device, or any of these devices.

For the convenience of description, the above devices are described separately by function into various units. Of course, the functions of each unit may be implemented in the same software or software and/or hardware when implementing the present application.

Those skilled in the art will appreciate that embodiments of the present application can be provided as a method, system, or computer program product. Thus, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment in combination of software and hardware. Moreover, embodiments of the present application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the present application. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the production of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

Moreover, these computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The instruction means implements the functions specified in one or more blocks of the flowchart or in a flow or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

The above description is only an embodiment of the present application and is not intended to limit the application. Various changes and modifications can be made to the present application by those skilled in the art. Any modifications, equivalents, improvements, etc. made within the spirit and scope of the present application are intended to be included within the scope of the appended claims.

Claims

A hotspot keyword acquisition method, which is characterized by being applied to a database server, comprising:

In the statistical period, obtain a keyword and obtain the number of accesses of the keyword;

Determining a number of access times of the number of accesses, and querying a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists;

Updating the location of the number of accesses of the keyword in the linked list;

When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.
The method of claim 1 wherein

The process of obtaining the number of accesses of the keyword includes:

Obtaining a data block location corresponding to the keyword;

Querying the number of accesses from the data block corresponding to the data block location;

The number of visits to the keyword is obtained using the number of visits queried.
The method of claim 2 wherein:

The process of obtaining the location of the data block corresponding to the keyword includes:

Querying a hash table by using the keyword to obtain a data block location corresponding to the keyword;

The hash table is used to record a correspondence between a keyword and a data block position.
The method of claim 3 wherein:

After the hash table is queried by the keyword, the method further includes:

If the keyword does not exist in the hash table, selecting a data block for the keyword;

Recording the number of accesses of the keyword into the selected data block, and recording a correspondence between the keyword and the data block position of the selected data block in the hash table.
The method of claim 2 wherein:

The process of obtaining the number of accesses of the keyword by using the number of accesses that are queried includes:

Determining the number of accesses of the keyword is a preset value of the number of accesses queried; or

Obtaining resource information corresponding to the keyword, and determining a weight value of the keyword according to the resource information, and determining that the number of accesses of the keyword is the number of accesses that are queried plus the weight value.
The method according to claim 5, wherein the resource information comprises: a data size of the keyword corresponding data, and/or a processing time of the keyword corresponding request;

The process of determining the weight value of the keyword according to the resource information includes:

Determining a weight value of the keyword according to a relationship between the data size and a preset size; or

Determining a weight value of the keyword according to the relationship between the processing time and a preset time; or

Determining a first sub-weight value of the keyword according to a relationship between the data size and a preset size;

Determining, according to the relationship between the processing time and the preset time, a second sub-weight value of the keyword;

Determining a weight value of the keyword according to the first sub-weight value and the second sub-weight value.
The method according to claim 2, wherein after the obtaining the number of accesses of the keyword by using the number of accesses queried, the method further comprises:

Updating the number of accesses of the keyword to a data block corresponding to the data block location.
The method of claim 1 further comprising:

When the content in the data block needs to be deleted, the lowest priority list is queried;

Deleting the content in the last data block of the lowest priority linked list;

Among them, the list with the lowest priority is the linked list corresponding to the smallest number of access times.
The method of claim 1 wherein

The process of updating the location of the number of accesses of the keyword in the linked list includes:

The data block in which the number of accesses of the keyword is located is updated to the first data block of the linked list.
The method of claim 1 wherein

The process of determining a hotspot keyword according to the number of accesses of the keyword includes:

The data block of the linked list is sequentially traversed according to the order of the highest priority linked list to the lowest priority linked list; wherein the highest priority linked list is the linked list corresponding to the largest access number interval, and the lowest priority linked list is the smallest a linked list corresponding to the number of access times;

If the number of accesses of the keywords recorded in the traversed data block is greater than a preset number of times threshold, determining that the keyword is a hotspot keyword; otherwise, determining that the keyword is not a hotspot keyword;

After traversing to the linked list that is not a hotkey keyword, stop traversing the data block of the next linked list.
The method of claim 1 further comprising:

After the statistical period ends, the contents of the data blocks of all linked lists are cleared.
A hotspot keyword acquisition method, which is characterized by being applied to a database server, comprising:

Obtaining a keyword, querying a hash table by using the keyword, and obtaining a data block location corresponding to the keyword; the hash table is configured to record a correspondence between a keyword and a data block location;

Querying the number of accesses from the data block corresponding to the data block location, obtaining the number of accesses of the keyword by using the number of accesses that are queried, and updating the number of accesses of the keyword to the data block;

When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.
The method of claim 12 wherein:

After the hash table is queried by the keyword, the method further includes:

If the keyword does not exist in the hash table, selecting a data block for the keyword;

Recording the number of accesses of the keyword into the selected data block, and recording a correspondence between the keyword and the data block position of the selected data block in the hash table.
The method of claim 12 wherein:

The process of obtaining the number of accesses of the keyword by using the number of accesses that are queried includes:

Determining the number of accesses of the keyword is a preset value of the number of accesses queried; or

Obtaining resource information corresponding to the keyword, determining a weight value of the keyword according to the resource information, and determining that the number of accesses of the keyword is the number of accesses that are queried plus the weight value; the resource information includes The data size of the keyword corresponding data, and/or the processing time of the keyword corresponding request.
A hotspot keyword acquisition method, which is characterized by being applied to a database server, comprising:

In the statistical period, obtain a keyword and obtain the number of accesses of the keyword;

Determining a number of access times of the number of accesses, and querying a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists;

Updating the location of the number of accesses of the keyword in the linked list;

When the content in the data block needs to be deleted, the linked list with the lowest priority is searched according to the correspondence between the access number interval and the linked list, and the content in the last data block of the lowest priority linked list is deleted; The lowest-level linked list is the linked list corresponding to the minimum number of access times;

When the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.
The method of claim 15 wherein:

The process of determining a hotspot keyword according to the number of accesses of the keyword includes:

The data block of the linked list is sequentially traversed according to the order of the highest priority linked list to the lowest priority linked list; wherein the highest priority linked list is the linked list corresponding to the largest access number interval, and the lowest priority linked list is the smallest a linked list corresponding to the number of access times;

If the number of accesses of the keywords recorded in the traversed data block is greater than a preset number of times threshold, determining that the keyword is a hotspot keyword; otherwise, determining that the keyword is not a hotspot keyword;

After traversing to the linked list that is not a hotkey keyword, stop traversing the data block of the next linked list.
A hotspot keyword obtaining device, which is applied to a database server, and includes:

An obtaining module, configured to acquire a keyword in a statistical period, and obtain the number of accesses of the keyword;

a determining module, configured to determine a number of access times of the number of accesses, and query a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists; and update access of the keywords The number of times in the linked list;

The determining module is further configured to: when the hotspot keyword needs to be determined, read the number of accesses of the keyword from the linked list, and determine the hotspot keyword according to the number of accesses of the keyword.
The device of claim 17 wherein:

The obtaining module is configured to: obtain a data block position corresponding to the keyword, and query the number of accesses from the data block corresponding to the data block position in the process of acquiring the number of accesses of the keyword, and Obtaining the number of accesses of the keyword by using the number of visits queried;

The obtaining module is specifically configured to: when the location of the data block corresponding to the keyword is obtained, query the hash table by using the keyword to obtain a data block location corresponding to the keyword; The hash table is used to record the correspondence between the keyword and the location of the data block;

In the process of obtaining the number of accesses of the keyword by using the number of times of the query, the number of times of accessing the keyword is determined by adding a preset value to the number of times the query is accessed; or obtaining the resource information corresponding to the keyword. And determining, according to the resource information, a weight value of the keyword, and determining that the number of accesses of the keyword is the number of accesses that are queried plus the weight value; wherein the resource information includes: the keyword corresponding data The data size, and/or, the keyword corresponds to the processing time of the request.
The device according to claim 17, further comprising:

a deleting module, configured to: when the content in the data block needs to be deleted, query the lowest priority linked list, and delete the content in the last data block of the lowest priority linked list;

The determining module is specifically configured to: in the process of determining a hotspot keyword according to the number of accesses of the keyword, sequentially traversing the data block of the linked list according to the order of the highest priority linked list to the lowest priority linked list; if the traversed data is traversed If the number of accesses of the keywords recorded in the block is greater than the preset number of thresholds, it is determined that the keyword is a hotspot keyword; otherwise, it is determined that the keyword is not a hotspot keyword; after traversing to the linked list that is not a hotkey keyword, the traversal is stopped. The data block of the next linked list;

The linked list with the highest priority is a linked list corresponding to the largest number of access times, and the linked list with the lowest priority is a linked list corresponding to the smallest number of access times.
A hotspot keyword obtaining device, which is applied to a database server, and includes:

An obtaining module, configured to acquire a keyword in a statistical period, and query a hash table by using the keyword to obtain a corresponding data block position; the hash table is configured to record a correspondence between a keyword and a data block position; Querying the number of accesses in the data block corresponding to the location of the data block, obtaining the number of accesses of the keyword by using the number of accesses that are queried, and updating the number of accesses of the keyword to the data block;

The determining module is configured to read the number of accesses of the keyword from the linked list when the hotkey keyword needs to be determined, and determine the hotspot keyword according to the number of accesses of the read keyword.
A hotspot keyword obtaining device, which is applied to a database server, and includes:

An obtaining module, configured to acquire a keyword in a statistical period, and obtain the number of accesses of the keyword;

a determining module, configured to determine a number of access times of the number of accesses, and query a linked list corresponding to the number of access times; wherein different access times intervals correspond to different linked lists; and update access of the keywords The number of times in the linked list;

The deleting module is configured to: when the content in the data block needs to be deleted, query the linked list with the lowest priority according to the correspondence between the access number interval and the linked list, and delete the content in the last data block of the lowest priority linked list. The lowest priority linked list is a linked list corresponding to the smallest number of access times;

The determining module is further configured to: when the hotspot keyword needs to be determined, read the number of accesses of the keyword from the linked list, and determine the hotspot keyword according to the number of accesses of the read keyword.
A database server, characterized in that the database server comprises:

a processor, configured to acquire a keyword in a statistical period, and obtain a number of accesses of the keyword; determine a number of access times in which the number of accesses is located, and query a linked list corresponding to the number of access times; Different access times intervals correspond to different linked lists; update the position of the number of accesses of the keyword in the linked list; when the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and according to the keyword The number of visits determines the hotspot keyword.
A database server, characterized in that the database server comprises:

a processor, configured to acquire a keyword in a statistical period, and query a hash table by using the keyword to obtain a data block location corresponding to the keyword; wherein the hash table is used to record a keyword and Corresponding relationship of the location of the data block; querying the number of accesses from the data block corresponding to the location of the data block, and obtaining the number of accesses of the keyword by using the number of accesses queried, and updating the number of accesses of the keyword to In the data block; when the hotspot keyword needs to be determined, the number of accesses of the keyword is read from the linked list, and the hotspot keyword is determined according to the number of accesses of the keyword.
A database server, characterized in that the database server comprises:

a processor, configured to acquire a keyword in a statistical period, and obtain a number of accesses of the keyword; determine a number of access times in which the number of accesses is located, and query a linked list corresponding to the number of access times; The different access times interval corresponds to different linked lists; the number of access times of the keywords is updated in the linked list; when the content in the data block needs to be deleted, the priority is queried according to the correspondence between the access times interval and the linked list a lowest linked list, and deleting content in a last data block of the lowest priority linked list; wherein the lowest priority linked list is a linked list corresponding to a minimum number of access times; when a hot keyword needs to be determined, The number of visits to the keyword is read from the linked list, and the hotspot keyword is determined based on the number of visits to the keyword.