CN108897807B

CN108897807B - Method and system for carrying out hierarchical processing on data in mobile terminal

Info

Publication number: CN108897807B
Application number: CN201810624536.9A
Authority: CN
Inventors: 王梅
Original assignee: Anhui Shangrong Information Technology Co ltd
Current assignee: Anhui Shangrong Information Technology Co.,Ltd.
Priority date: 2018-06-16
Filing date: 2018-06-16
Publication date: 2021-06-29
Anticipated expiration: 2038-06-16
Also published as: CN108897807A

Abstract

The invention discloses a method and a system for carrying out hierarchical processing on data in a mobile terminal, wherein the method comprises the following steps: receiving an acquisition request for a target data group; determining a current compressed data segment and a current compressed data area where the target data group is located; determining a plurality of associated data groups of which the target data group needs to be operated in an associated manner during operation; scanning all compressed data areas in the current compressed data segment, and determining a decompression level; decompressing according to the decompressing stage in the current compressed data segment; while decompressing in the current compressed data segment according to the decompression level, marking a sub-region of high compression rate in the associated compressed data region of each associated compressed data segment as a second decompression level, and marking a sub-region of medium compression rate or low compression rate in the associated compressed data region of each associated compressed data segment as a third decompression level; and in response to completion of decompression within the current compressed data segment, decompressing within the associated compressed data segment at the decompression level.

Description

Method and system for carrying out hierarchical processing on data in mobile terminal

Technical Field

The present invention relates to the field of data processing, and more particularly, to a method and system for hierarchical processing of data in a mobile terminal.

Background

At present, as mobile terminals such as mobile phones are more and more widely used, devices such as processors, memories, cameras, etc. of the mobile terminals are greatly improved. However, as the user demands for the running speed, images, and the like of various applications are higher, the processing resources or the storage resources occupied by the applications are also higher. For this reason, while improvements are made to devices such as processors, memories, cameras, and the like, improvements in access performance of data in mobile terminals are also required to improve data processing capabilities of the mobile terminals.

Disclosure of Invention

According to an aspect of the present invention, there is provided a method of hierarchically processing data in a mobile terminal, the method including:

receiving an acquisition request for a target data set stored in a first memory in the mobile terminal;

based on the obtaining request, determining a current compressed data segment in which the target data group is located among a plurality of compressed data segments in the first memory and determining a current compressed data area in which the target data group is located among a plurality of compressed data areas in the current compressed data segment;

determining a plurality of associated data groups which need to be operated in an associated manner when the target data group is operated based on the associated statistical information of the target data group;

scanning all compressed data areas in the current compressed data segment, marking the current compressed data area as a first decompression stage, determining at least one associated compressed data area which is outside the current compressed data area and has an associated data group in the current compressed data segment, marking a sub-area with a high compression rate or a medium compression rate in the at least one associated compressed data area of the current compressed data segment as a second decompression stage, and marking a sub-area with a low compression rate in the at least one associated compressed data area of the current compressed data segment as a third decompression stage, wherein the compression degrees of the high compression rate, the medium compression rate and the low compression rate are sequentially increased; wherein the decompression order of the first decompression stage, the second decompression stage and the third decompression stage decreases in sequence;

decompressing according to a decompression level within the current compressed data segment: decompressing the sub-area marked as the second decompression stage in the at least one associated compressed data area after decompressing the current compressed data area marked as the first decompression stage, and then decompressing the sub-area marked as the third decompression stage in the at least one associated compressed data area;

determining at least one associated compressed data segment of the plurality of compressed data segments other than the current compressed data segment and having an associated data set while decompressing at a decompression level within the current compressed data segment, wherein the associated data set is stored in at least one associated compressed data region within each associated compressed data segment;

tagging a sub-region of high compression rate within the at least one associated compressed data region of each associated compressed data segment as a second decompression stage and a sub-region of medium or low compression rate within the at least one associated compressed data region of each associated compressed data segment as a third decompression stage; and

in response to completion of decompression within the current compressed data segment, decompressing within the at least one associated compressed data segment at a decompression level: the sub-region marked as the second decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed first, and then the sub-region marked as the third decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed.

When the processor or the controller of the mobile terminal needs to use the target data group stored in the first memory, sending an acquisition request for the target data group stored in the first memory in the mobile terminal.

When the operating system in the mobile terminal is detected to be loaded into the first memory and the starting of the operating system is completed, a plurality of applications to be loaded of the mobile terminal are determined according to a preset loading configuration file, and a file package associated with each application in the plurality of applications to be loaded is copied from a second memory into the first memory.

The first memory is a volatile memory and the second memory is a non-volatile memory.

Creating a plurality of compressed data segments for storing compressed data in the first memory after the operating system is started and before a plurality of applications to be loaded of the mobile terminal are determined according to a preset loading configuration file, wherein each compressed data segment comprises a plurality of compressed data areas, and each compressed data area comprises a plurality of sub-areas.

Wherein the file package associated with each application includes at least one data group that has been compressed, and in the first memory, the data group is used as a basic storage unit when data is compressed for storage.

Wherein the file package associated with each application includes at least one data group that has been compressed, and in the second storage, the file package is used as a basic storage unit when data is compressed for storage.

Wherein the compressed single data group is stored in a single compressed data area of the compressed data segment, and at least one compressed data group can be stored in the single compressed data area.

The acquisition request comprises an identifier of a target data group to be acquired;

based on the obtaining request, determining a current compressed data segment in which the target data group is located among a plurality of compressed data segments in the first memory and determining a current compressed data region in which the target data group is located among a plurality of compressed data regions in the current compressed data segment comprises:

analyzing the acquisition request to determine an identifier of a target data group;

inquiring a data segment index information table in the first storage according to the identifier of the target data group, and determining the current compressed data segment of the target data group in the plurality of compressed data segments in the first storage according to the inquiry result;

and inquiring a data area index information table in the directory area of the current compressed data segment according to the identifier of the target data group, and determining the current compressed data area in which the target data group is positioned in a plurality of compressed data areas in the current compressed data segment according to the inquiry result.

After determining a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file, copying an association statistical file from a second memory to a first memory, wherein the association statistical file comprises a plurality of pieces of association statistical information, and each piece of association statistical information is used for indicating a plurality of associated data groups of each data group.

Determining the content association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending order arrangement on each data group except the current data group based on the content association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

and determining the content relevance between any two data groups by carrying out content matching on the summary information of any two data groups according to the matching value.

The preset selection rule comprises the following steps: the content relevancy in the sorted list is larger than a relevancy threshold value, or the content relevancy in the sorted list is ranked before a preset ranking.

Determining the operation association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending order arrangement on each data group except the current data group based on the operation association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

the method comprises the steps of obtaining operation history information of each data group, determining statistical data of the data groups operated in each basic time unit according to the operation history information, determining the operation times of any two data groups in the same basic time unit, and determining the operation association degree between any two data groups based on the operation times in the same basic time unit.

The preset selection rule comprises the following steps: and running a plurality of data groups with the association degree larger than the association degree threshold value in the ordered list, or running a plurality of data groups with the association degree ranking before the preset name time in the ordered list.

Determining the feedback association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending order arrangement on each data group except the current data group based on the feedback association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

the initial value of the feedback association degree between any two data groups is set to be 0, preset association degree rules or dynamic operation data are analyzed to determine the data group pair which needs to be set by the feedback association degree in the multiple data group pairs, and the feedback association degree is set for two data groups in each data group pair which needs to be set by the feedback association degree according to the association degree rules or the dynamic operation data.

The preset selection rule comprises the following steps: the feedback association degree of the data groups in the sorted list is larger than the association degree threshold value, or the feedback association degree of the data groups in the sorted list is ranked before the preset ranking.

Determining the comprehensive association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending order arrangement on each data group except the current data group based on the comprehensive association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

the method comprises the steps that content matching is carried out on summary information of any two data groups to determine the content relevancy between the any two data groups;

acquiring operation history information of each data group, determining statistical data of the data groups operated in each basic time unit according to the operation history information, determining the operation times of any two data groups in the same basic time unit, and determining the operation association degree between any two data groups based on the operation times in the same basic time unit;

wherein the content relevance and the running relevance of each data group except the current data group in the plurality of data groups and the current data group are weighted to calculate to determine the comprehensive relevance.

The preset selection rule comprises the following steps: the comprehensive association degree in the sorted list is larger than a threshold value of the association degree, or the comprehensive association degree in the sorted list is ranked before a preset ranking.

Wherein the content relevance degree and the feedback relevance degree of each data group except the current data group in the plurality of data groups and the current data group are subjected to weighted calculation to determine the comprehensive relevance degree.

Wherein the running relevance and the feedback relevance of each data group except the current data group in the plurality of data groups and the current data group are subjected to weighted calculation to determine the comprehensive relevance.

Wherein the content relevance degree, the operation relevance degree and the feedback relevance degree of each data group except the current data group in the plurality of data groups and the current data group are subjected to weighted calculation to determine the comprehensive relevance degree.

The method further comprises the step of setting an association grade for each association data set in the association statistical information based on the association operation times, the association operation times and the synchronous starting times of each association data set in the plurality of association data sets and a target data set during the association operation, wherein the association grade comprises: strong associations and weak associations.

And acquiring the operation history information of each data group, and determining the associated operation times, the associated operation time and the synchronous starting times of each associated data group and the target data group during the associated operation according to the operation history information.

The correlation operation times are the times of correlation operation of the two data sets in a statistical time period;

the correlation operation time is the time length of the correlation operation of the two data sets in the statistical time period;

the synchronous starting times are the times of synchronous starting of the two data groups in a statistical time period;

the correlated operation means that the difference of the time for which the two data sets are respectively called or started to operate is larger than a first preset time interval and smaller than a second preset time interval;

wherein synchronous start means that the difference between the times at which the two data sets are respectively called or started to run is less than or equal to a first predetermined time interval.

Determining, based on the correlation statistical information of the target data group, a plurality of correlation data groups that the target data group needs to be run in correlation at runtime includes:

and determining a plurality of association data sets of which the association level is strong association and the target data set needs to be associated and operated at the operation time based on the association statistical information of the target data set.

and determining a plurality of association data groups of which the target data group needs to be associated and operated at the operation time and the association level is weak association based on the association statistical information of the target data group.

Each associated compressed data area has at least one associated data set therein.

The method comprises the steps that a region compression rate is appointed for each sub-region in a compressed data region according to a compression configuration file, wherein the region compression rate comprises a high compression rate, a medium compression rate or a low compression rate;

the data set stored in each sub-region is compressed using the specified region compression rate.

The compression profile comprises a plurality of compression information tables, wherein each compression information table is associated with one of the plurality of compressed data segments and comprises a plurality of area sub-tables for recording compression information for each compressed data area within the associated compressed data segment;

each region sub-table is used to record a region compression rate for each of a plurality of sub-regions within the compressed data region.

With a high compression ratio of 90%, a medium compression ratio of 80%, and a low compression ratio of 70% (actually, a range of compression ratios).

Wherein decompressing the sub-region labeled as the second decompression stage within the at least one associated compressed data region of the current compressed data segment comprises: the plurality of sub-areas are decompressed from a low address to a high address direction or from a high address to a low address direction.

Wherein decompressing the sub-region labeled as the third decompression stage within the at least one associated compressed data region of the current compressed data segment comprises: the plurality of sub-areas are decompressed from a low address to a high address direction or from a high address to a low address direction.

Storing data resulting from decompressing the current compressed data area of a current data segment in a first data area of the first memory; and

storing data resulting from decompressing sub-regions within at least one associated compressed data region of a current data segment in a second data region of the first memory.

A compressed data segment having at least one associated data group is selected as an associated compressed data segment, and a compressed data area having at least one associated data group within the associated compressed data segment is determined as an associated compressed data area.

Storing data resulting from decompressing sub-regions within at least one associated compressed data region within each associated compressed data segment in a second data region of the first memory.

Before decompression in the at least one associated compressed data segment according to the decompression level, marking an unassociated compressed data area without an associated data group in each associated compressed data segment as an unreadable area, and when decompression is performed in the at least one associated compressed data segment according to the decompression level, not performing any processing on the unassociated compressed data area marked as an unreadable area.

Before decompression in the current compressed data segment according to the decompression level, marking the non-associated compressed data area without the target data group or the associated data group in the current compressed data segment as an unreadable area, and when decompression is performed in the current compressed data segment according to the decompression level, not performing any processing on the non-associated compressed data area marked as the unreadable area.

According to another aspect of the present invention, there is provided a system for hierarchical processing of data in a mobile terminal, the system comprising:

a receiving unit that receives an acquisition request for a target data group stored in a first memory within the mobile terminal;

a first retrieval unit that determines, based on the acquisition request, a current compressed data segment in which the target data group is located among a plurality of compressed data segments in the first memory and determines a current compressed data area in which the target data group is located among a plurality of compressed data areas in the current compressed data segment;

the association unit is used for determining a plurality of association data sets which need to be associated and operated when the target data set is operated based on the association statistical information of the target data set;

a first scanning unit, configured to scan all compressed data areas in the current compressed data segment, mark the current compressed data area as a first decompression stage, determine at least one associated compressed data area that is outside the current compressed data area and has an associated data set in the current compressed data segment, mark a sub-area with a high compression rate or a medium compression rate in the at least one associated compressed data area of the current compressed data segment as a second decompression stage, and mark a sub-area with a low compression rate in the at least one associated compressed data area of the current compressed data segment as a third decompression stage, where compression degrees of the high compression rate, the medium compression rate, and the low compression rate increase sequentially; wherein the decompression order of the first decompression stage, the second decompression stage and the third decompression stage decreases in sequence;

a first decompression unit for decompressing in the current compressed data segment according to a decompression level: decompressing the sub-area marked as the second decompression stage in the at least one associated compressed data area after decompressing the current compressed data area marked as the first decompression stage, and then decompressing the sub-area marked as the third decompression stage in the at least one associated compressed data area;

a second retrieval unit that determines at least one associated compressed data segment of the plurality of compressed data segments other than the current compressed data segment and having an associated data group, while decompressing at a decompression level within the current compressed data segment, wherein the associated data group is stored in at least one associated compressed data area within each associated compressed data segment;

a second scanning unit labeling a sub-area of a high compression rate within the at least one associated compressed data area of each associated compressed data segment as a second decompression stage and labeling a sub-area of a medium compression rate or a low compression rate within the at least one associated compressed data area of each associated compressed data segment as a third decompression stage; and

a second decompression unit, responsive to completion of decompression within the current compressed data segment, to decompress at a decompression level within the at least one associated compressed data segment: the sub-region marked as the second decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed first, and then the sub-region marked as the third decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed.

When a processor or controller of the mobile terminal needs to use the target data set stored in the first memory, the processor or controller sends an acquisition request for the target data set stored in the first memory within the mobile terminal.

The loading unit is used for determining a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file and copying a file package associated with each application in the plurality of applications to be loaded from a second memory to the first memory when the fact that the operating system in the mobile terminal is loaded into the first memory and the starting of the operating system is completed is detected.

The method further comprises the step of creating a plurality of compressed data sections for storing compressed data in the first memory after the operating system is started and before a plurality of applications to be loaded of the mobile terminal are determined according to a preset loading configuration file, wherein each compressed data section comprises a plurality of compressed data areas, and each compressed data area comprises a plurality of sub-areas.

the first retrieval unit includes:

the analysis unit is used for analyzing the acquisition request to determine an identifier of a target data group;

the query unit is used for querying the data segment index information table in the first storage according to the identifier of the target data group and determining the current compressed data segment of the target data group in the plurality of compressed data segments in the first storage according to the query result;

and the determining unit is used for inquiring the data area index information table in the directory area of the current compressed data segment according to the identifier of the target data group and determining the current compressed data area in which the target data group is positioned in the plurality of compressed data areas in the current compressed data segment according to the inquiry result.

The data processing device further comprises a processing unit, wherein the processing unit is used for determining the content association degree of each data group except the current data group and the current data group in the plurality of data groups, performing descending arrangement on each data group except the current data group based on the content association degree to generate an ordered list, and selecting the plurality of data groups from the ordered list according to a preset selection rule to serve as the plurality of associated data groups of the current data group;

The data processing device further comprises a processing unit, wherein the processing unit is used for determining the operation association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending arrangement on each data group except the current data group based on the operation association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

The data processing device further comprises a processing unit, wherein the processing unit is used for determining the feedback association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending arrangement on each data group except the current data group based on the feedback association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

The data processing device further comprises a processing unit, wherein the processing unit is used for determining the comprehensive association degree of each data group except the current data group in the multiple data groups and the current data group, performing descending arrangement on each data group except the current data group based on the comprehensive association degree to generate an ordered list, and selecting the multiple data groups from the ordered list according to a preset selection rule to serve as the multiple associated data groups of the current data group;

The method further comprises a setting unit, wherein an association grade is set for each association data set in the association statistical information based on the association operation times, the association operation times and the synchronous starting times of each association data set in the plurality of association data sets and a target data set during the association operation, and the association grade comprises the following steps: strong associations and weak associations.

The setting unit acquires the operation history information of each data group, and determines the correlation operation times, the correlation operation time and the synchronous starting times of each correlation data group and the target data group during the correlation operation according to the operation history information.

The association unit determines a plurality of association data sets which need to be associated and operated when the target data set is operated based on the association statistical information of the target data set, and the association unit comprises:

the association unit determines a plurality of association data sets of which the association level is strong association and which need to be associated and operated at the time of operation of the target data set based on the association statistical information of the target data set.

The associating unit determines, based on the association statistical information of the target data group, that the target data group needs to be associated and run at the time of running, and includes:

the association unit determines a plurality of association data sets of which the target data set needs to be associated and operated at the time of operation and the association level is weak association based on the association statistical information of the target data set.

The distribution unit is used for appointing a region compression rate for each sub-region in the compressed data region according to the compression configuration file, wherein the region compression rate comprises a high compression rate, a medium compression rate or a low compression rate;

Before the second decompressing unit decompresses the at least one associated compressed data segment according to the decompressing level, marking the non-associated compressed data area without the associated data group in each associated compressed data segment as an unreadable area, and when decompressing the at least one associated compressed data segment according to the decompressing level, not performing any processing on the non-associated compressed data area marked as the unreadable area.

Before the decompression of the current compressed data segment according to the decompression level in the first decompression unit, marking an unassociated compressed data area, which does not have a target data group or an associated data group, in the current compressed data segment as an unreadable area, and when the decompression of the current compressed data segment is performed according to the decompression level, not performing any processing on the unassociated compressed data area marked as the unreadable area.

Drawings

A more complete understanding of exemplary embodiments of the present invention may be had by reference to the following drawings in which:

FIG. 1 is a flow diagram of a method of hierarchical processing of data according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a logical structure of a storage device according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a logical structure of a compressed data segment according to an embodiment of the present invention;

FIG. 4 is a flow chart of a method of determining a storage location of a target data set according to an embodiment of the present invention;

FIG. 5 is a flow chart of a method for determining an associated data set according to an embodiment of the present invention;

FIG. 6 is a flow chart of a method for determining an associated data set according to another embodiment of the present invention;

FIG. 7 is a flow diagram of a method for determining an associated data set in accordance with yet another embodiment of the present invention;

FIG. 8 is a flow chart of a method for determining an associated data set according to yet another embodiment of the present invention;

FIG. 9 is a block diagram of a system for hierarchical processing of data according to an embodiment of the present invention; and

fig. 10 is a schematic structural diagram of a first search unit according to an embodiment of the present invention.

Detailed Description

Fig. 1 is a flow diagram of a method 100 of hierarchical processing of data according to an embodiment of the present invention. As shown in fig. 1, method 100 begins at step 101.

In step 101, an acquisition request for a target data set stored in a first memory within the mobile terminal is received. Generally, when a processor, controller, communication interface, etc. of the mobile terminal needs to use the target data set stored in the first memory, an acquisition request for the target data set stored in the first memory within the mobile terminal is sent. When a mobile terminal performs data processing, data storage, data calculation, and the like according to a user request, it is generally necessary to read a plurality of data sets. The data sets are typically stored in a first memory and a second memory and are read and used by devices within the mobile terminal when needed. Generally, the present invention refers to a data set required to be used by a processor, a controller, a communication interface, etc., as a target data set.

When the operating system in the mobile terminal is detected to be loaded into the first memory and the starting of the operating system is completed, determining a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file. Subsequently, the bundle of files associated with each of the plurality of applications to be loaded is copied from the second memory into the first memory. Wherein the first memory is a volatile memory, such as a random access memory RAM, a memory, and the second memory is a non-volatile memory, such as a flash memory. The operating system is stored in the second memory when the mobile terminal is powered off, and is loaded from the second memory into the first memory when the mobile terminal is started to run. The loading of the configuration file may be preset at the time of factory shipment of the mobile terminal or may be preset by a user of the mobile terminal. The loading configuration file may record one or more applications that can be automatically started when the operating system is started, among the plurality of applications in the mobile terminal. Typically, each application has an associated or at least one file package, and each file package may include multiple sub-packages of files therein, i.e., the file structure of each application is constructed in a hierarchical manner.

After the booting of the operating system of the mobile terminal is completed (which refers to when the booting of the system service, the system application, the resource management, the network initialization, etc. of the operating system is completed, but the user application is not loaded), and before the plurality of applications to be loaded of the mobile terminal are determined according to the preset loading profile, a plurality of compressed data segments for storing compressed data are created in the first memory, as shown in fig. 2. FIG. 2 is a schematic diagram of a logical structure of a storage device 200 according to an embodiment of the present invention. In fig. 2, a storage device 200 (e.g., a first memory) includes: a boot area 201, a first data area 202, a second data area 203, a compressed storage area 204, and a reserved storage area 205. Wherein the boot area 201 is used to store system files associated with the booting of the operating system and directory files for indicating storage directory information within the storage device 200. The first data area 202 and the second data area 203 have a plurality of data segments and are each used to store an uncompressed data set, or a decompressed data set. Generally, the data sets stored in the first data area 202 and the second data area 203 are data sets that can be directly read, acquired, accessed, processed or calculated by a processor, a controller, a communication interface or the like.

The compressed storage area 204 is used to store the compressed data set. It should be appreciated that in the second memory, the data files associated with each application are typically stored as compressed files. In general, a single data file may include at least one data group. In the second memory, the data record or data file is therefore stored in the form of a compressed data file or compressed data record. In the second memory, the compressed data file is generally stored in units of compressed data files, and when the compressed data file is loaded into the first memory, the compressed data file is split (generally, the data file includes at least one data group) to generate a plurality of compressed data groups. It should be appreciated that in the second memory, multimedia files, such as pictures, video, audio, documents, etc., may be stored in compressed form or uncompressed form. The reserved storage area 205 includes a plurality of data segments and a plurality of compressed data segments, and is used for storing backup files, or for storing reserved resources of a system, or for storing emergency files, or for storing storage areas when emergency storage is performed by the mobile terminal.

Compressed storage area 204 includes a plurality of compressed data segments for storing compressed data, e.g., compressed data segment 204-1, compressed data segment 204-2, compressed data segment 204-3, compressed data segment 204-5, ·. The storage space (or capacity) of the compressed data segment 204-1, the compressed data segment 204-2, the compressed data segment 204-3, and the compressed data segment 204-5 are set differently in fig. 2, but it should be understood that the storage space (or capacity) of each compressed data segment may be the same or different, or partially the same.

Each of the plurality of compressed data segments includes a plurality of compressed data areas, and each of the compressed data areas includes a plurality of sub-areas, as shown in fig. 3. FIG. 3 is a diagram illustrating a logical structure of a compressed data segment 300 according to an embodiment of the present invention. In fig. 3, the compressed data segment 300 includes: compressed data area 301, compressed data area 302, compressed data area 303, a. The compressed data area 301 includes: a low compression ratio sub-region 301-1, a high compression ratio sub-region 301-2, and a medium compression ratio sub-region 301-3; the compressed data area 302 includes: a low compression ratio sub-region 302-1, a medium compression ratio sub-region 302-2, and a medium compression ratio sub-region 302-3; the compressed data area 303 includes: a low compression ratio sub-region 303-1, a high compression ratio sub-region 303-2.

The memory space (or capacity) of each compressed data region and each sub-region may be the same or different, or partially the same. Further, the compression rate of each sub-region within the same or different memory regions may be the same or different, and the compression rate of each sub-region may be a high compression rate, a medium compression rate, or a low compression rate. For example, the high compression ratio is 90%, the medium compression ratio is 80%, and the low compression ratio is 70%. Alternatively, the high compression ratio is a compression ratio of 89% to 99%, the medium compression ratio is a compression ratio of 79% to 89% (excluding 89%), and the low compression ratio is a compression ratio of less than 79%. Alternatively, the high compression ratio is a compression ratio of 85% -100% (excluding 100%), the medium compression ratio is a compression ratio of 70% -85% (excluding 85%), and the low compression ratio is a compression ratio of less than 70%. The above values are exemplary only, and one skilled in the art will appreciate that the compression ratio or range of values can be any reasonable value.

Wherein the package of files associated with each application includes at least one compressed data group, and in the first storage, the data group (compressed data group) is used as a basic storage unit when the data is compressed for storage. Alternatively, in the first memory, a data group (uncompressed data group) is used as a basic storage unit when storing data. That is, in the first memory, each application is stored in the form of a plurality of compressed data groups or uncompressed data groups.

The file package associated with each application includes at least one data group that has been compressed, and in the second storage, the file package is used as a basic storage unit when data is compressed for storage. That is, in the second storage, each application is stored in the form of a package of files.

Furthermore, any compressed data set can be stored in a single compressed data area of the compressed data segment. That is, there are no data groups stored across the compressed data area. The single compressed data area is capable of storing at least one compressed data set therein.

At step 102, based on the obtaining request, a current compressed data segment in which the target data group is located among the plurality of compressed data segments in the first memory is determined and a current compressed data area in which the target data group is located among the plurality of compressed data areas in the current compressed data segment is determined. In general, the present application refers to a compressed data segment in which the target data group is located as a current compressed data segment and refers to a compressed data area in which the target data group is located as a current compressed data area. In the present application, the target data set may also be referred to as a compressed target data set. Generally, the data or data sets stored in the compressed storage area (including a plurality of compressed data segments) are all compressed data or data sets.

FIG. 4 is a flow chart of a method 400 of determining a storage location of a target data set according to an embodiment of the present invention. Wherein the acquisition request comprises an identifier of the target data set to be acquired. As shown in fig. 4, determining, based on the obtaining request, a current compressed data segment in which the target data group is located among a plurality of compressed data segments in the first memory and determining a current compressed data region in which the target data group is located among a plurality of compressed data regions in the current compressed data segment includes:

step 401, parsing the acquisition request to determine an identifier of a target data group. The acquisition request includes: requestor identification, identifier of target data group, request priority, request time, etc.

Step 402, querying the data segment index information table in the first memory according to the identifier of the target data group, and determining the current compressed data segment of the target data group located in the plurality of compressed data segments in the first memory according to the query result. The first memory includes therein a data segment index information table, and the data segment index information table includes data segment index information for each of the first data area, the second data area, the compressed storage area, and the reserved storage area. For the compressed storage area, the data segment index information includes an identification, a start address, an end address, a storage capacity, and the like of each compressed data segment. The data segment index information includes, for the first data area and the second data area, an identification, a start address, an end address, a storage capacity, etc. of each (uncompressed) data segment. For the reserved storage area, the data segment index information includes an identification, a start address, an end address, a storage capacity, and the like of each compressed data segment or uncompressed data segment.

Preferably, the data piece index information of each of the first data area, the second data area, the compressed storage area, and the reserved storage area may constitute a single data piece index information table, and this single data piece index information table is stored in the boot area. Alternatively, the data piece index information of each of the first data area, the second data area, the compressed storage area, and the reserved storage area may be configured as a respective data piece index information table, and the data piece index information tables of the first data area, the second data area, the compressed storage area, and the reserved storage area may be stored in the respective storage areas. The data segment index information may include a tuple < identifier of data group, identifier of belonging data segment >.

Step 403, querying the index information table of the data area in the directory area of the current compressed data segment according to the identifier of the target data group, and determining the current compressed data area in which the target data group is located in the multiple compressed data areas in the current compressed data segment according to the query result. And the directory area of each data segment or compressed data segment stores a data area index information table. The data area index information table may include a doublet < identifier of data group, identifier of belonging (compressed) data area >.

In step 103, a plurality of associated data sets that the target data set needs to be associated to run at the run time are determined based on the associated statistical information of the target data set. And after determining a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file, copying the associated statistical file from the second memory to the first memory. The association statistic file includes a plurality of pieces of association statistic information, wherein each piece of association statistic information is used to indicate a plurality of associated data groups (i.e., compressed data groups) of each data group (i.e., compressed data group). In addition, the association statistical information of the specific data group further includes a content association degree, a running association degree, a feedback association degree or a comprehensive association degree of each of the plurality of associated data groups of the specific data group with the specific data group.

Fig. 5 is a flow chart of a method 500 for determining an associated data set according to an embodiment of the present invention. As shown in fig. 5, method 500 begins at step 501. In step 501, a content association degree of each of the plurality of data sets (i.e., the compressed data sets) other than the current data set with the current data set is determined. By taking each of the plurality of data sets as a current data set, the content association degree between any two of the plurality of data sets can be determined.

At step 502, each data group other than the current data group is sorted in descending order based on content relevance to generate a sorted list. By taking each data group in the multiple data groups as a current data group, the application can obtain a respective sorted list of each data group, wherein each data group except the current data group in the multiple data groups in the sorted list is sorted in a descending order according to the content relevance. For example, in the sorted list of the current data group, the data group having the greatest degree of association with the content of the current data group is sorted first, and the data group having the smallest degree of association with the content of the current data group is sorted last. And when at least two data groups with the same content relevance degree as the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

In step 503, a plurality of data groups are selected from the ordered list according to a preset selection rule to serve as a plurality of associated data groups of the current data group. The preset selection rule comprises the following steps: the content relevancy in the sorted list is larger than a relevancy threshold, or the content relevancy in the sorted list is ranked before a predetermined ranking, and the like. In general, the relevancy threshold may be determined based on user input or system settings, such as 70%, 80%, 85%, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

The matching value of content matching of the summary information of any two data groups is used as the content association degree between any two data groups. The summary information is determined for each data group according to the content, action, source and the like of each data group, and is used for describing various relevant characteristics of the data group. The matching value of the summary information of any two data groups is determined through text comparison and semantic comparison peer-to-peer content matching modes.

Fig. 6 is a flow chart of a method 600 for determining an associated data set according to another embodiment of the present invention. As shown in fig. 6, method 600 begins at step 601. At step 601, a running relevance of each of the plurality of data sets other than the current data set to the current data set is determined. By taking each of the plurality of data sets as a current data set, the application can determine the operational association between any two of the plurality of data sets.

At step 602, each data group other than the current data group is sorted in descending order based on the running relevance to generate a sorted list. By taking each data group in the multiple data groups as a current data group, the application can obtain a respective sorted list of each data group, wherein each data group except the current data group in the multiple data groups in the sorted list is sorted in a descending order according to the operation association degree. For example, in the sorted list of the current dataset, the dataset having the greatest degree of operational association with the current dataset is sorted first, and the dataset having the least degree of operational association with the current dataset is sorted last. And when at least two data groups with the same operation association degree as the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

In step 603, a plurality of data groups are selected from the ordered list according to a preset selection rule to serve as a plurality of associated data groups of the current data group. The preset selection rule comprises the following steps: and running a plurality of data groups with the association degree larger than the association degree threshold value in the ordered list, or running a plurality of data groups with the association degree ranking before the preset name time in the ordered list. In general, the relevancy threshold may be determined based on user input or system settings, such as 5 times, 8 times, 10 times, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

The method comprises the steps of obtaining operation history information of each data group, wherein the operation history information comprises operation time, read time, write time, decompression time and the like of each data group. Then, the statistical data of the data sets operated in each basic time unit, that is, which data sets operated in each basic time unit, is determined according to the operation history information. In general, the basic time unit may be determined from user input or system settings, e.g., 5 minutes, 10 minutes, 15 minutes, etc. The method divides time into continuous basic time units, and takes the basic time units as basic statistical units. Then, the number of times that any two data sets are operated in the same basic time unit is determined, and the operation association degree between any two data sets is determined based on the number of times that any two data sets are operated in the same basic time unit. For example, if the first data set is run in the 1 st, 3 rd, 5 th, 6 th, 7 th, 8 th, and 9 th basic time units and the second data set is run in the 2 nd, 3 th, 4 th, 6 th, 7 th, 8 th, and 9 th basic time units, the number of times the first data set and the second data set are run in the same basic time units is 5. When any data set is operated for multiple times in the same basic time unit, the relevance calculation is only recorded as 1 time. It should be appreciated that, when determining the operational association degree, the length of the statistical time is generally predetermined, i.e., the operational association degree is calculated according to a predetermined number of basic time units, such as 30 basic time units, 50 basic time units, 60 basic time units, etc.

Fig. 7 is a flow chart of a method 700 for determining an associated data set according to yet another embodiment of the present invention. As shown in fig. 7, method 700 begins at step 701. In step 701, a feedback association degree of each data group of the plurality of data groups except the current data group with the current data group is determined. By taking each of the plurality of data sets as a current data set, the feedback association degree between any two of the plurality of data sets can be determined.

At step 702, each data group other than the current data group is sorted in descending order based on the feedback relevance to generate a sorted list. By taking each data group in the multiple data groups as the current data group, the application can obtain the respective sorted list of each data group, wherein each data group except the data group in the multiple data groups in the sorted list is sorted in a descending order according to the feedback relevance. For example, in the sorted list of the current data group, the data group having the greatest degree of association with the feedback of the current data group is sorted first, and the data group having the smallest degree of association with the feedback of the current data group is sorted last. And when at least two data groups with the same feedback relevance degree as the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

In step 703, a plurality of data groups are selected from the ordered list according to a preset selection rule as a plurality of associated data groups of the current data group. The preset selection rule comprises the following steps: the feedback association degree of the data groups in the sorted list is larger than the association degree threshold value, or the feedback association degree of the data groups in the sorted list is ranked before the preset ranking. In general, the relevancy threshold may be determined based on user input or system settings, such as relevancy thresholds of 15, 25, 35, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

The initial value of the feedback association degree between any two data groups is set to be 0, preset association degree rules or dynamic operation data are analyzed to determine the data group pair which needs to be set by the feedback association degree in the multiple data group pairs, and the feedback association degree is set for two data groups in each data group pair which needs to be set by the feedback association degree according to the association degree rules or the dynamic operation data. The preset association degree rule is, for example, an association degree rule set in advance by a user, an operating system, a system application, a user application, or the like. The association degree rule may be used to indicate a degree of association between any two data groups of the plurality of data groups. For example, the association rule indicates that the association of the first data group and the fifth data group is high, e.g., the feedback association is 20, indicates that the association of the first data group and the second data group is medium, e.g., the feedback association is 15, and indicates that the association of the first data group and the third data group is low, e.g., the feedback association is 10. The dynamic operation data is, for example, a degree of association between any two data groups of the plurality of data groups determined by an operating system, a system application, a user application, and the like based on the operation data of the data groups. For example, the dynamic operational data indicates that the association between the second data set and the fifth data set is high, e.g., the feedback association is 25, indicates that the association between the second data set and the third data set is medium, e.g., the feedback association is 15, and indicates that the association between the second data set and the sixth data set is low, e.g., the feedback association is 5. Wherein, the format of the data group pair is < data group name, data group name > and is used for indicating the feedback relevance between two different data groups. For example, the association degree rule indicates that the association degree of the first data group and the fifth data group is high, for example, the feedback association degree is 15, and the feedback association degree of the data group pair < the first data group and the fifth data group > is 15.

Further, the feedback correlation may be a cumulative sum of a plurality of values. For example, when the system application determines that the feedback association degree of the first data group and the second data group is 5 according to the dynamic operation data, the first user application determines that the feedback association degree of the first data group and the second data group is 10 according to the dynamic operation data, and the second user application determines that the feedback association degree of the first data group and the second data group is 15 according to the dynamic operation data, the feedback association degree of the first data group and the second data group is 30.

Fig. 8 is a flow chart of a method 800 for determining an associated data set according to yet another embodiment of the present invention. As shown in fig. 8, method 800 begins at step 801. At step 801, a comprehensive degree of association of each of the plurality of data sets other than the current data set with the current data set is determined. By taking each of the plurality of data sets as a current data set, the application can determine the comprehensive association degree between any two of the plurality of data sets.

At step 802, each data group other than the current data group is sorted in descending order based on the composite relevance to generate a sorted list. By taking each data group in the multiple data groups as the current data group, the application can obtain the respective sorted list of each data group, wherein each data group except the data group in the multiple data groups in the sorted list is sorted in a descending order according to the comprehensive association degree. For example, in the sorted list of the current data group, the data group having the largest degree of association with the feedback of the current data group is sorted first, and the data group having the smallest degree of overall association with the current data group is sorted last. And when at least two data groups with the same comprehensive association degree with the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

In step 803, a plurality of data groups are selected from the ordered list according to a preset selection rule as a plurality of associated data groups of the current data group. The preset selection rule comprises the following steps: the comprehensive association degree in the sorted list is larger than a threshold value of the association degree, or the comprehensive association degree in the sorted list is ranked before a preset ranking. In general, the relevancy threshold may be determined based on user input or system settings, such as 70%, 80%, 85%, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

In the following, the manner of determining the content relevance, running relevance and feedback relevance refers to the contents of fig. 5-7 above.

First embodiment

And performing content matching on the summary information of any two data groups to serve as the content relevance (in percentage form) between any two data groups.

Wherein the content relevance and the running relevance of each data group except the current data group in the plurality of data groups and the current data group are weighted to calculate to determine the comprehensive relevance. Specifically, the maximum value of the operational association degrees of each of the plurality of data sets other than the current data set with the current data set, that is, the maximum operational association degree, is determined. Then, the operational association of each of the plurality of data sets other than the current data set with the current data set is divided by the maximum operational association to determine an operational association of each data set as a percentage of the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the running state, the content relevance and the running relevance (in percentage). And according to the determined weight value, performing weighted calculation on the content association degree and the running association degree (in percentage form) of each data group except the current data group in the plurality of data groups and the current data group to determine the comprehensive association degree.

Second embodiment

Wherein, the summary information of any two data groups is subjected to content matching as the content relevance (in percentage form) between the any two data groups;

Wherein the content relevance degree and the feedback relevance degree of each data group except the current data group in the plurality of data groups and the current data group are subjected to weighted calculation to determine the comprehensive relevance degree. Specifically, the maximum value of the feedback association degrees of each of the plurality of data groups except the current data group with the current data group, that is, the maximum feedback association degree is determined. The feedback relevance of each of the plurality of data sets other than the current data set to the current data set is then divided by the maximum feedback relevance to determine the feedback relevance as a percentage of each data set to the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the operating state, the content relevance and the feedback relevance (in percentage form). And according to the determined weight value, performing weighted calculation on the content relevance and the feedback relevance (in percentage form) of each data group except the current data group in the plurality of data groups and the current data group to determine the comprehensive relevance.

Third embodiment

Wherein the running relevance and the feedback relevance of each data group except the current data group in the plurality of data groups and the current data group are subjected to weighted calculation to determine the comprehensive relevance. Specifically, the maximum value of the operational association degrees of each of the plurality of data sets other than the current data set with the current data set, that is, the maximum operational association degree, is determined. Then, the operational association of each of the plurality of data sets other than the current data set with the current data set is divided by the maximum operational association to determine an operational association of each data set as a percentage of the current data set. And determining the maximum value of the feedback relevance of each data group except the current data group in the plurality of data groups and the current data group, namely the maximum feedback relevance. The feedback relevance of each of the plurality of data sets other than the current data set to the current data set is then divided by the maximum feedback relevance to determine the feedback relevance as a percentage of each data set to the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the operating state, such as the operating association degree (in the form of a percentage) and the feedback association degree (in the form of a percentage). And according to the determined weight values, performing weighted calculation on the running relevance (in percentage form) and the feedback relevance (in percentage form) of each data group except the current data group in the plurality of data groups and the current data group to determine the comprehensive relevance.

Fourth embodiment

Wherein the content relevance degree, the operation relevance degree and the feedback relevance degree of each data group except the current data group in the plurality of data groups and the current data group are subjected to weighted calculation to determine the comprehensive relevance degree. Specifically, the maximum value of the operational association degrees of each of the plurality of data sets other than the current data set with the current data set, that is, the maximum operational association degree, is determined. Then, the operational association of each of the plurality of data sets other than the current data set with the current data set is divided by the maximum operational association to determine an operational association of each data set as a percentage of the current data set. And determining the maximum value of the feedback relevance of each data group except the current data group in the plurality of data groups and the current data group, namely the maximum feedback relevance. The feedback relevance of each of the plurality of data sets other than the current data set to the current data set is then divided by the maximum feedback relevance to determine the feedback relevance as a percentage of each data set to the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the operating state, such as content relevance (in the form of a percentage), operating relevance (in the form of a percentage), and feedback relevance (in the form of a percentage). According to the determined weight values, the content relevance (in percentage form), the running relevance (in percentage form) and the feedback relevance (in percentage form) of each data set except the current data set in the plurality of data sets and the current data set are subjected to weighted calculation to determine the comprehensive relevance. For example, the weight values for the content relevance (in percent form), the running relevance (in percent form), and the feedback relevance (in percent form) are 1/3, 1/3, and 1/3; 1/2, 1/4, and 1/4; 1/4, 1/4, and 1/2, and the like.

According to another embodiment, the application sets an association grade for each associated data set in the association statistical information based on the number of association operations, the association operation time and the number of synchronization startup times of each associated data set in the plurality of associated data sets with the target data set during the association operation. The association levels include: strong associations and weak associations. Heretofore, operation history information of each data group (the operation history information is generally stored in an operation history file and may be obtained by recording information such as a log file, for example) is acquired, and the number of associated operations, the associated operation time, and the number of synchronization starts of each associated data group with the target data group at the time of performing the associated operation are determined from the operation history information.

Wherein the number of associated runs is the number of associated runs (e.g., 5, 6, 8, etc.) made by the two data sets over a statistical time period (e.g., 10 minutes, 20 minutes, 30 minutes, etc.); wherein the correlation runtime is a length of time (e.g., 2 minutes, 3 minutes, 5 minutes, etc.) for which the correlation run is performed for the two data sets within the statistical time period; wherein the number of synchronous starts is the number of times (e.g., 3 times, 4 times, 5 times, etc.) that two data sets are synchronously started within a statistical time period; wherein the associated operation means that the difference between the times at which the two data sets are respectively called or started to operate is greater than a first predetermined time interval and less than a second predetermined time interval. Wherein synchronous start means that the difference between the times at which the two data sets are respectively called or started to run is less than or equal to a first predetermined time interval. Wherein the second predetermined time interval is greater than the first predetermined time interval, for example the second predetermined time interval is 30 seconds and the first predetermined time interval is 5 seconds.

After determining the association level of the data sets, the present application may filter or filter the associated data sets of the target data set (or any data set) according to the association level. For example, determining, based on the correlation statistics of the target data set, a plurality of correlation data sets that the target data set needs to be run in correlation at runtime includes: and determining a plurality of association data sets of which the association level is strong association and the target data set needs to be associated and operated at the operation time based on the association statistical information of the target data set. Determining, based on the correlation statistical information of the target data group, a plurality of correlation data groups that the target data group needs to be run in correlation at runtime includes: and determining a plurality of association data groups of which the target data group needs to be associated and operated at the operation time and the association level is weak association based on the association statistical information of the target data group.

At step 104, scanning all compressed data areas in the current compressed data segment, marking the current compressed data area as a first decompression stage, determining at least one associated compressed data area which is outside the current compressed data area and has an associated data set in the current compressed data segment, marking a sub-area with a high compression rate or a medium compression rate in each associated compressed data area of the at least one associated compressed data area of the current compressed data segment as a second decompression stage, and marking a sub-area with a low compression rate in each associated compressed data area of the at least one associated compressed data area of the current compressed data segment as a third decompression stage, wherein the compression degrees of the high compression rate, the medium compression rate and the low compression rate are sequentially increased; wherein the decompression order of the first, second and third decompression stages decreases in sequence. It should be appreciated that the first decompression stage, the second decompression stage, and the third decompression stage may be used to indicate a sequential level of decompressing the data set, such as the first batch, the second batch, the third batch, and so on. Alternatively, two or more decompression stages are determined to be the same batch. Wherein each associated compressed data area has/stores therein at least one associated data set (compressed data set). Wherein a region compression rate is specified for each sub-region in the compressed data region according to the compression configuration file, wherein the region compression rate comprises a high compression rate, a medium compression rate or a low compression rate. The data set stored in each sub-region is compressed by using the specified region compression rate, namely, the compression rate of the data set in the sub-region is the same as the region compression rate of the sub-region.

And inquiring a data area index information table in the directory area of the current compressed data segment according to the identifier of each associated data group, and determining that a plurality of compressed data areas in the current compressed data segment have associated compressed data areas of the associated data groups according to the inquiry result. And the directory area of each data segment or compressed data segment stores a data area index information table. The data area index information table may include a doublet < identifier of data group, identifier of belonging (compressed) data area >. The compression profile includes a plurality of compression information tables, wherein each compression information table is associated with one of the plurality of compressed data segments and includes a plurality of region sub-tables for recording compression information for each compressed data region within the associated compressed data segment. Each region sub-table is used to record a region compression rate for each of a plurality of sub-regions within the compressed data region.

In step 105, decompressing is performed in the current compressed data segment according to a decompression level: after decompressing the current compressed data area marked as the first decompression stage, decompressing the sub-area marked as the second decompression stage in the at least one associated compressed data area, and then decompressing the sub-area marked as the third decompression stage in the at least one associated compressed data area. Wherein decompressing the sub-region labeled as the second decompression stage within the at least one associated compressed data region of the current compressed data segment comprises: the plurality of sub-areas are decompressed from a low address to a high address direction or from a high address to a low address direction. Wherein decompressing the sub-region labeled as the third decompression stage within the at least one associated compressed data region of the current compressed data segment comprises: the plurality of sub-areas are decompressed from a low address to a high address direction or from a high address to a low address direction. Storing data resulting from decompressing the current compressed data area of a current data segment in a first data area of the first memory. And storing data resulting from decompressing sub-regions within at least one associated compressed data region of the current data segment in a second data region of the first memory.

At step 106, at least one associated compressed data segment of the plurality of compressed data segments other than the current compressed data segment and having an associated data set is determined while decompressing at a decompression level within the current compressed data segment, wherein the associated data set is stored in at least one associated compressed data region within each associated compressed data segment.

And inquiring a data segment index information table in the first memory according to the identifier of each associated data group, and determining the compressed data segment in which each associated data group is positioned in the plurality of compressed data segments in the first memory according to the inquiry result. A compressed data segment having at least one associated data set is determined as an associated compressed data segment. And inquiring the data area index information table in the directory area of each associated compressed data segment according to the identifier of each associated data group, and determining an associated compressed data area with an associated data group in a plurality of compressed data areas in each associated compressed data segment according to the inquiry result. And the directory area of each data segment or compressed data segment stores a data area index information table. The data area index information table may include a doublet < identifier of data group, identifier of belonging (compressed) data area >.

At step 107, the sub-region of high compression ratio within the at least one associated compressed data region of each associated compressed data segment is labeled as a second decompression stage and the sub-region of medium compression ratio or low compression ratio within the at least one associated compressed data region of each associated compressed data segment is labeled as a third decompression stage. It should be appreciated that the first decompression stage, the second decompression stage, and the third decompression stage may be used to indicate a sequential level of decompressing the data set, such as the first batch, the second batch, the third batch, and so on. Alternatively, two or more decompression stages are determined to be the same batch. Wherein each associated compressed data area has/stores therein at least one associated data set (compressed data set).

In step 108, in response to completion of decompression within the current compressed data segment, decompressing within the at least one associated compressed data segment at a decompression level: the sub-region marked as the second decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed first, and then the sub-region marked as the third decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed. A compressed data segment having at least one associated data group is selected as an associated compressed data segment, and a compressed data area having at least one associated data group within the associated compressed data segment is determined as an associated compressed data area. Storing data resulting from decompressing sub-regions within at least one associated compressed data region within each associated compressed data segment in a second data region of the first memory. Before decompression in the at least one associated compressed data segment according to the decompression level, marking an unassociated compressed data area without an associated data group in each associated compressed data segment as an unreadable area, and when decompression is performed in the at least one associated compressed data segment according to the decompression level, not performing any processing on the unassociated compressed data area marked as an unreadable area. Before decompression in the current compressed data segment according to the decompression level, marking the non-associated compressed data area without the target data group or the associated data group in the current compressed data segment as an unreadable area, and when decompression is performed in the current compressed data segment according to the decompression level, not performing any processing on the non-associated compressed data area marked as the unreadable area.

Fig. 9 is a schematic structural diagram of a system 900 for hierarchical processing of data according to an embodiment of the present invention. As shown in fig. 9, the system 900 includes: a receiving unit 901, a first retrieving unit 902, an associating unit 903, a first scanning unit 904, a first decompressing unit 905, a second retrieving unit 906, a second scanning unit 907, a second decompressing unit 908, a loading unit 909, an initializing unit 910, a processing unit 911, a setting unit 912, and an allocating unit 913.

A receiving unit 901, receiving an acquisition request for a target data set stored in a first memory in the mobile terminal. Generally, when a processor, controller, communication interface, etc. of the mobile terminal needs to use the target data set stored in the first memory, an acquisition request for the target data set stored in the first memory within the mobile terminal is sent. When a mobile terminal performs data processing, data storage, data calculation, and the like according to a user request, it is generally necessary to read a plurality of data sets. The data sets are typically stored in a first memory and a second memory and are read and used by devices within the mobile terminal when needed. Generally, the present invention refers to a data set required to be used by a processor, a controller, a communication interface, etc., as a target data set.

A loading unit 909 that determines a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file when it is detected that an operating system within the mobile terminal is loaded into the first memory and the start of the operating system is completed, and then copies a file package associated with each of the plurality of applications to be loaded from a second memory into the first memory. Wherein the first memory is a volatile memory, such as a random access memory RAM, a memory, and the second memory is a non-volatile memory, such as a flash memory. The operating system is stored in the second memory when the mobile terminal is powered off, and is loaded from the second memory into the first memory when the mobile terminal is started to run. The loading of the configuration file may be preset at the time of factory shipment of the mobile terminal or may be preset by a user of the mobile terminal. The loading configuration file may record one or more applications that can be automatically started when the operating system is started, among the plurality of applications in the mobile terminal. Typically, each application has an associated or at least one file package, and each file package may include multiple sub-packages of files therein, i.e., the file structure of each application is constructed in a hierarchical manner.

An initialization unit 910, which creates a plurality of compressed data segments for storing compressed data in the first memory after the operating system is started and before a plurality of applications to be loaded of the mobile terminal are determined according to a preset loading configuration file, wherein each compressed data segment comprises a plurality of compressed data areas, and each compressed data area comprises a plurality of sub-areas.

The first retrieving unit 902, based on the obtaining request, determines a current compressed data segment where the target data group is located among the plurality of compressed data segments in the first memory and determines a current compressed data area where the target data group is located among the plurality of compressed data areas in the current compressed data segment. In general, the present application refers to a compressed data segment in which the target data group is located as a current compressed data segment and refers to a compressed data area in which the target data group is located as a current compressed data area. In the present application, the target data set may also be referred to as a compressed target data set. Generally, the data or data sets stored in the compressed storage area (including a plurality of compressed data segments) are all compressed data or data sets.

Fig. 10 is a schematic structural diagram of a first search unit 1000 according to an embodiment of the present invention. As shown in fig. 10, the first retrieval unit 1000 (i.e., the first retrieval unit 902 in fig. 9) includes: parsing unit 1001, querying unit 1002, and determining unit 1003. The parsing unit 1001 parses the acquisition request to determine an identifier of a target data group. The acquisition request includes: requestor identification, identifier of target data group, request priority, request time, etc.

The querying unit 1002 queries the data segment index information table in the first memory according to the identifier of the target data group, and determines, according to a query result, a current compressed data segment of the target data group located in the plurality of compressed data segments in the first memory. The first memory includes therein a data segment index information table, and the data segment index information table includes data segment index information for each of the first data area, the second data area, the compressed storage area, and the reserved storage area. For the compressed storage area, the data segment index information includes an identification, a start address, an end address, a storage capacity, and the like of each compressed data segment. The data segment index information includes, for the first data area and the second data area, an identification, a start address, an end address, a storage capacity, etc. of each (uncompressed) data segment. For the reserved storage area, the data segment index information includes an identification, a start address, an end address, a storage capacity, and the like of each compressed data segment or uncompressed data segment.

The determining unit 1003 queries the data area index information table in the directory area of the current compressed data segment according to the identifier of the target data group, and determines the current compressed data area in which the target data group is located in the multiple compressed data areas in the current compressed data segment according to the query result. And the directory area of each data segment or compressed data segment stores a data area index information table. The data area index information table may include a doublet < identifier of data group, identifier of belonging (compressed) data area >.

The associating unit 903 determines a plurality of associated data sets that need to be associated and run when the target data set runs, based on the associated statistical information of the target data set. And determining a plurality of associated data groups which need to be operated in an associated manner when the target data group is operated based on the associated statistical information of the target data group. And after determining a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file, copying the associated statistical file from the second memory to the first memory. The association statistic file includes a plurality of pieces of association statistic information, wherein each piece of association statistic information is used to indicate a plurality of associated data groups (i.e., compressed data groups) of each data group (i.e., compressed data group). In addition, the association statistical information of the specific data group further includes a content association degree, a running association degree, a feedback association degree or a comprehensive association degree of each of the plurality of associated data groups of the specific data group with the specific data group.

The processing unit 911 determines the degree of association of each of the plurality of data sets (i.e., the compressed data set) other than the current data set with the content of the current data set. By taking each of the plurality of data sets as a current data set, the content association degree between any two of the plurality of data sets can be determined.

The processing unit 911 arranges each data group other than the current data group in descending order based on the content relevance to generate an ordered list. By taking each data group in the multiple data groups as a current data group, the application can obtain a respective sorted list of each data group, wherein each data group except the current data group in the multiple data groups in the sorted list is sorted in a descending order according to the content relevance. For example, in the sorted list of the current data group, the data group having the greatest degree of association with the content of the current data group is sorted first, and the data group having the smallest degree of association with the content of the current data group is sorted last. And when at least two data groups with the same content relevance degree as the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

The processing unit 911 selects a plurality of data sets from the ordered list as a plurality of associated data sets of the current data set according to a preset selection rule. The preset selection rule comprises the following steps: the content relevancy in the sorted list is larger than a relevancy threshold, or the content relevancy in the sorted list is ranked before a predetermined ranking, and the like. In general, the relevancy threshold may be determined based on user input or system settings, such as 70%, 80%, 85%, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

The processing unit 911 determines a degree of operational association of each of the plurality of data sets other than the current data set with the current data set. By taking each of the plurality of data sets as a current data set, the application can determine the operational association between any two of the plurality of data sets.

The processing unit 911 arranges each data group other than the current data group in a descending order based on the running association degree to generate an ordered list. By taking each data group in the multiple data groups as a current data group, the application can obtain a respective sorted list of each data group, wherein each data group except the current data group in the multiple data groups in the sorted list is sorted in a descending order according to the operation association degree. For example, in the sorted list of the current dataset, the dataset having the greatest degree of operational association with the current dataset is sorted first, and the dataset having the least degree of operational association with the current dataset is sorted last. And when at least two data groups with the same operation association degree as the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

The processing unit 911 selects a plurality of data sets from the ordered list as a plurality of associated data sets of the current data set according to a preset selection rule. The preset selection rule comprises the following steps: and running a plurality of data groups with the association degree larger than the association degree threshold value in the ordered list, or running a plurality of data groups with the association degree ranking before the preset name time in the ordered list. In general, the relevancy threshold may be determined based on user input or system settings, such as 5 times, 8 times, 10 times, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

The processing unit 911 determines a feedback association degree of each data set other than the current data set from among the plurality of data sets with the current data set. By taking each of the plurality of data sets as a current data set, the feedback association degree between any two of the plurality of data sets can be determined.

The processing unit 911 arranges each data group other than the current data group in a descending order based on the feedback association degree to generate an ordered list. By taking each data group in the multiple data groups as the current data group, the application can obtain the respective sorted list of each data group, wherein each data group except the data group in the multiple data groups in the sorted list is sorted in a descending order according to the feedback relevance. For example, in the sorted list of the current data group, the data group having the greatest degree of association with the feedback of the current data group is sorted first, and the data group having the smallest degree of association with the feedback of the current data group is sorted last. And when at least two data groups with the same feedback relevance degree as the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

The processing unit 911 selects a plurality of data sets from the ordered list as a plurality of associated data sets of the current data set according to a preset selection rule. The preset selection rule comprises the following steps: the feedback association degree of the data groups in the sorted list is larger than the association degree threshold value, or the feedback association degree of the data groups in the sorted list is ranked before the preset ranking. In general, the relevancy threshold may be determined based on user input or system settings, such as relevancy thresholds of 15, 25, 35, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

The processing unit 911 determines a comprehensive degree of association of each of the plurality of data sets other than the current data set with the current data set. By taking each of the plurality of data sets as a current data set, the application can determine the comprehensive association degree between any two of the plurality of data sets.

The processing unit 911 arranges each data group other than the current data group in descending order based on the comprehensive association degree to generate an ordered list. By taking each data group in the multiple data groups as the current data group, the application can obtain the respective sorted list of each data group, wherein each data group except the data group in the multiple data groups in the sorted list is sorted in a descending order according to the comprehensive association degree. For example, in the sorted list of the current data group, the data group having the largest degree of association with the feedback of the current data group is sorted first, and the data group having the smallest degree of overall association with the current data group is sorted last. And when at least two data groups with the same comprehensive association degree with the current data group exist, determining the sequence according to the identifiers of the at least two data groups, or determining the sequence of the at least two data groups according to a random mode.

The processing unit 911 selects a plurality of data sets from the ordered list as a plurality of associated data sets of the current data set according to a preset selection rule. The preset selection rule comprises the following steps: the comprehensive association degree in the sorted list is larger than a threshold value of the association degree, or the comprehensive association degree in the sorted list is ranked before a preset ranking. In general, the relevancy threshold may be determined based on user input or system settings, such as 70%, 80%, 85%, etc. Alternatively, the predetermined ranking is determined based on user input or system settings, e.g., the first 20, 30, 35, etc.

First embodiment

The processing unit 911 performs content matching on the summary information of any two data sets as the content association degree (in percentage) between the any two data sets.

The processing unit 911 obtains the operation history information of each data set, determines statistical data of the data sets operated in each basic time unit according to the operation history information, determines the number of times any two data sets are operated in the same basic time unit, and determines the operation association degree between any two data sets based on the number of times the any two data sets are operated in the same basic time unit.

The processing unit 911 performs a weighted calculation on the content association degree and the operation association degree of each of the plurality of data sets other than the current data set with the current data set to determine a comprehensive association degree. Specifically, the maximum value of the operational association degrees of each of the plurality of data sets other than the current data set with the current data set, that is, the maximum operational association degree, is determined. Then, the operational association of each of the plurality of data sets other than the current data set with the current data set is divided by the maximum operational association to determine an operational association of each data set as a percentage of the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the running state, the content relevance and the running relevance (in percentage). And according to the determined weight value, performing weighted calculation on the content association degree and the running association degree (in percentage form) of each data group except the current data group in the plurality of data groups and the current data group to determine the comprehensive association degree.

Second embodiment

The processing unit 911 performs content matching on the summary information of any two data sets as the content association degree (in percentage form) between any two data sets;

the processing unit 911 sets an initial value of a feedback association degree between any two data sets to 0, and analyzes a preset association degree rule or dynamic operation data to determine a data set pair that needs to be set for the feedback association degree among a plurality of data set pairs, and sets a feedback association degree for each two data sets in the data set pair that needs to be set for the feedback association degree according to the association degree rule or the dynamic operation data.

The processing unit 911 performs weighted calculation on the content association degree and the feedback association degree of each data set other than the current data set among the plurality of data sets with the current data set to determine a comprehensive association degree. Specifically, the maximum value of the feedback association degrees of each of the plurality of data groups except the current data group with the current data group, that is, the maximum feedback association degree is determined. The feedback relevance of each of the plurality of data sets other than the current data set to the current data set is then divided by the maximum feedback relevance to determine the feedback relevance as a percentage of each data set to the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the operating state, the content relevance and the feedback relevance (in percentage form). And according to the determined weight value, performing weighted calculation on the content relevance and the feedback relevance (in percentage form) of each data group except the current data group in the plurality of data groups and the current data group to determine the comprehensive relevance.

Third embodiment

The processing unit 911 obtains the operation history information of each data set, determines the statistical data of the data sets operated in each basic time unit according to the operation history information, determines the number of times that any two data sets are operated in the same basic time unit, and determines the operation association degree between any two data sets based on the number of times that the any two data sets are operated in the same basic time unit;

The processing unit 911 performs a weighted calculation on the operation association degree and the feedback association degree of each data set except the current data set among the plurality of data sets with the current data set to determine a comprehensive association degree. Specifically, the maximum value of the operational association degrees of each of the plurality of data sets other than the current data set with the current data set, that is, the maximum operational association degree, is determined. Then, the operational association of each of the plurality of data sets other than the current data set with the current data set is divided by the maximum operational association to determine an operational association of each data set as a percentage of the current data set. And determining the maximum value of the feedback relevance of each data group except the current data group in the plurality of data groups and the current data group, namely the maximum feedback relevance. The feedback relevance of each of the plurality of data sets other than the current data set to the current data set is then divided by the maximum feedback relevance to determine the feedback relevance as a percentage of each data set to the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the operating state, such as the operating association degree (in the form of a percentage) and the feedback association degree (in the form of a percentage). And according to the determined weight values, performing weighted calculation on the running relevance (in percentage form) and the feedback relevance (in percentage form) of each data group except the current data group in the plurality of data groups and the current data group to determine the comprehensive relevance.

Fourth embodiment

The processing unit 911 performs weighted calculation on the content association degree, the operation association degree, and the feedback association degree of each of the plurality of data sets other than the current data set with the current data set to determine the comprehensive association degree. Specifically, the maximum value of the operational association degrees of each of the plurality of data sets other than the current data set with the current data set, that is, the maximum operational association degree, is determined. Then, the operational association of each of the plurality of data sets other than the current data set with the current data set is divided by the maximum operational association to determine an operational association of each data set as a percentage of the current data set. And determining the maximum value of the feedback relevance of each data group except the current data group in the plurality of data groups and the current data group, namely the maximum feedback relevance. The feedback relevance of each of the plurality of data sets other than the current data set to the current data set is then divided by the maximum feedback relevance to determine the feedback relevance as a percentage of each data set to the current data set. The same or different weight values are determined according to user settings or system settings, or according to dynamic settings of the operating state, such as content relevance (in the form of a percentage), operating relevance (in the form of a percentage), and feedback relevance (in the form of a percentage). According to the determined weight values, the content relevance (in percentage form), the running relevance (in percentage form) and the feedback relevance (in percentage form) of each data set except the current data set in the plurality of data sets and the current data set are subjected to weighted calculation to determine the comprehensive relevance. For example, the weight values for the content relevance (in percent form), the running relevance (in percent form), and the feedback relevance (in percent form) are 1/3, 1/3, and 1/3; 1/2, 1/4, and 1/4; 1/4, 1/4, and 1/2, and the like.

A setting unit 912 configured to set an association level for each associated data group in the association statistical information based on the number of association operations, the association operation time, and the number of synchronization starts of each associated data group in the plurality of associated data groups with the target data group at the time of performing the association operation. The association levels include: strong associations and weak associations. Heretofore, operation history information of each data group (the operation history information is generally stored in an operation history file and may be obtained by recording information such as a log file, for example) is acquired, and the number of associated operations, the associated operation time, and the number of synchronization starts of each associated data group with the target data group at the time of performing the associated operation are determined from the operation history information.

A first scanning unit 904, which scans all compressed data areas in the current compressed data segment, marks the current compressed data area as a first decompression stage, determines at least one associated compressed data area which is outside the current compressed data area and has an associated data set in the current compressed data segment, marks a sub-area with a high compression rate or a medium compression rate in each associated compressed data area of the at least one associated compressed data area of the current compressed data segment as a second decompression stage, and marks a sub-area with a low compression rate in each associated compressed data area of the at least one associated compressed data area of the current compressed data segment as a third decompression stage, wherein the compression degrees of the high compression rate, the medium compression rate and the low compression rate are sequentially increased; wherein the decompression order of the first, second and third decompression stages decreases in sequence. It should be appreciated that the first decompression stage, the second decompression stage, and the third decompression stage may be used to indicate a sequential level of decompressing the data set, such as the first batch, the second batch, the third batch, and so on. Alternatively, two or more decompression stages are determined to be the same batch. Wherein each associated compressed data area has/stores therein at least one associated data set (compressed data set).

The allocating unit 913 specifies a region compression rate for each sub-region in the compressed data region according to the compression profile, where the region compression rate includes a high compression rate, a medium compression rate, or a low compression rate. The data set stored in each sub-region is compressed by using the specified region compression rate, namely, the compression rate of the data set in the sub-region is the same as the region compression rate of the sub-region.

A first decompression unit 905 that decompresses within the current compressed data segment at a decompression level: after decompressing the current compressed data area marked as the first decompression stage, decompressing the sub-area marked as the second decompression stage in the at least one associated compressed data area, and then decompressing the sub-area marked as the third decompression stage in the at least one associated compressed data area. Wherein decompressing the sub-region labeled as the second decompression stage within the at least one associated compressed data region of the current compressed data segment comprises: the plurality of sub-areas are decompressed from a low address to a high address direction or from a high address to a low address direction. Wherein decompressing the sub-region labeled as the third decompression stage within the at least one associated compressed data region of the current compressed data segment comprises: the plurality of sub-areas are decompressed from a low address to a high address direction or from a high address to a low address direction. Storing data resulting from decompressing the current compressed data area of a current data segment in a first data area of the first memory. And storing data resulting from decompressing sub-regions within at least one associated compressed data region of the current data segment in a second data region of the first memory.

A second retrieving unit 906 that determines at least one associated compressed data segment of the plurality of compressed data segments other than the current compressed data segment and having an associated data group while decompressing at a decompression level within the current compressed data segment, wherein the associated data group is stored in at least one associated compressed data area within each associated compressed data segment.

A second scanning unit 907 marks a sub-area of high compression ratio within the at least one associated compressed data area of each associated compressed data segment as a second decompression stage, and marks a sub-area of medium compression ratio or low compression ratio within the at least one associated compressed data area of each associated compressed data segment as a third decompression stage. It should be appreciated that the first decompression stage, the second decompression stage, and the third decompression stage may be used to indicate a sequential level of decompressing the data set, such as the first batch, the second batch, the third batch, and so on. Alternatively, two or more decompression stages are determined to be the same batch. Wherein each associated compressed data area has/stores therein at least one associated data set (compressed data set).

A second decompression unit 908, responsive to completion of decompression within the current compressed data segment, for decompressing within the at least one associated compressed data segment at a decompression level: the sub-region marked as the second decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed first, and then the sub-region marked as the third decompression stage within the at least one associated compressed data region within each associated compressed data segment is decompressed. A compressed data segment having at least one associated data group is selected as an associated compressed data segment, and a compressed data area having at least one associated data group within the associated compressed data segment is determined as an associated compressed data area. Storing data resulting from decompressing sub-regions within at least one associated compressed data region within each associated compressed data segment in a second data region of the first memory. Before decompression in the at least one associated compressed data segment according to the decompression level, marking an unassociated compressed data area without an associated data group in each associated compressed data segment as an unreadable area, and when decompression is performed in the at least one associated compressed data segment according to the decompression level, not performing any processing on the unassociated compressed data area marked as an unreadable area. Before decompression in the current compressed data segment according to the decompression level, marking the non-associated compressed data area without the target data group or the associated data group in the current compressed data segment as an unreadable area, and when decompression is performed in the current compressed data segment according to the decompression level, not performing any processing on the non-associated compressed data area marked as the unreadable area.

Claims

1. A method of hierarchical processing of data in a mobile terminal, the method comprising:

2. The method according to claim 1, upon detecting that an operating system within the mobile terminal is loaded into the first memory and that the operating system boot is complete, determining a plurality of applications of the mobile terminal to be loaded according to a preset loading profile, copying a package of files associated with each of the plurality of applications to be loaded from a second memory into the first memory.

3. The method of claim 2, creating a plurality of compressed data segments in the first memory for storing compressed data after the operating system startup is completed and before the plurality of applications to be loaded of the mobile terminal are determined according to a preset loading profile, wherein each compressed data segment comprises a plurality of compressed data areas and each compressed data area comprises a plurality of sub-areas.

4. The method of claim 3, the acquisition request comprising an identifier of a target data set to be acquired;

5. The method according to claim 4, after determining a plurality of applications to be loaded of the mobile terminal according to a preset loading profile, copying an association statistics file from the second memory to the first memory, the association statistics file comprising a plurality of association statistics, wherein each association statistics is used to indicate a plurality of association data groups of each data group.

6. A system for hierarchical processing of data in a mobile terminal, the system comprising:

7. The system according to claim 6, further comprising a loading unit, upon detecting that the operating system in the mobile terminal is loaded into the first memory and the start of the operating system is completed, determining a plurality of applications to be loaded of the mobile terminal according to a preset loading configuration file, and copying a file package associated with each of the plurality of applications to be loaded from a second memory into the first memory.

8. The system according to claim 7, further comprising an initialization unit that creates a plurality of compressed data segments for storing compressed data in the first memory after the operating system boot is completed and before the plurality of applications to be loaded of the mobile terminal are determined according to a preset loading profile, wherein each compressed data segment comprises a plurality of compressed data areas and each compressed data area comprises a plurality of sub-areas.

9. The system of claim 8, the acquisition request including an identifier of a target data set to be acquired;

the first retrieval unit includes:

10. The system according to claim 9, after determining a plurality of applications to be loaded of the mobile terminal according to a preset loading profile, copying an association statistics file from the second memory to the first memory, the association statistics file comprising a plurality of association statistics, wherein each association statistics is used to indicate a plurality of association data groups of each data group.