CN110414813B

CN110414813B - Index curve construction method, device and equipment

Info

Publication number: CN110414813B
Application number: CN201910650663.0A
Authority: CN
Inventors: 琚克俭
Original assignee: Advanced New Technologies Co Ltd
Current assignee: Advanced Nova Technology Singapore Holdings Ltd
Priority date: 2019-07-18
Filing date: 2019-07-18
Publication date: 2023-08-22
Anticipated expiration: 2039-07-18
Also published as: CN110414813A

Abstract

The embodiment of the specification provides a method, a device and equipment for constructing an index curve. The build request includes at least an indicator of the current desired build curve and a build time period. The index values of the index at the respective time points in the construction period are read from the storage unit. The index value of the index at each time point is obtained by executing index value statistics logic of the index after the management platform receives the scheduling request sent by the scheduling platform at regular time. The index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain the index value of the time point. The statistical record is determined based on field values of dependent fields in the index's dependent data table. And constructing an index curve of the index based on the index values of each time point in the construction time period.

Description

Index curve construction method, device and equipment

Technical Field

One or more embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a method, an apparatus, and a device for constructing an index curve.

Background

The index curve generally corresponds to a time period, which may be constructed based on index values at various points in time within the corresponding time period. The user can intuitively check the change trend of the index value in a period of time through the index curve.

In the conventional technology, when an index curve of a certain index is constructed, independent development and application are generally required, and the development period is relatively long. In addition, lengthy data preparation procedures, such as the preparation of application data for each of the layers from the operations data store (Operational Data Store, ODS) to the enterprise data warehouse (Enterprise Data Warehouse, EDW) to the aggregate data (Aggregated Data Market, ADM), are required.

Therefore, it is desirable to provide a solution that can quickly construct an index profile.

Disclosure of Invention

One or more embodiments of the present disclosure describe a method, an apparatus, and a device for constructing an index curve, which can quickly construct the index curve.

In a first aspect, a method for constructing an index curve is provided, including:

receiving a construction request of an index curve;

the construction request at least comprises an index of a current required construction curve and a construction time period;

reading index values of the index at various time points in the construction time period from a storage unit; the index value of the index at each time point is obtained by executing index value statistical logic of the index after the management platform receives a scheduling request sent by a scheduling platform at regular time; the index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain an index value of the time point; the statistical record is determined based on field values of dependent fields in a dependent data table of the index;

and constructing an index curve of the index based on the index values of each time point in the construction time period.

In a second aspect, there is provided an apparatus for constructing an index curve, including:

the receiving unit is used for receiving the construction request of the index curve;

a reading unit, configured to read, from a storage unit, index values of the index at respective time points in the construction period; the index value of the index at each time point is obtained by executing index value statistical logic of the index after the device receives a scheduling request sent by a scheduling platform at regular time; the index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain an index value of the time point; the statistical record is determined based on field values of dependent fields in a dependent data table of the index;

and the construction unit is used for constructing an index curve of the index based on the index values of all time points in the construction time period read by the reading unit.

In a third aspect, there is provided an apparatus for constructing an index curve, including:

a memory;

one or more processors; and

one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, which when executed by the processors implement the steps of:

receiving a construction request of an index curve;

According to the method, the device and the equipment for constructing the index curve, which are provided by one or more embodiments of the present disclosure, a request for constructing the index curve is received. The build request includes at least an indicator of the current desired build curve and a build time period. The index values of the index at the respective time points in the construction period are read from the storage unit. The index value of the index at each time point is obtained by executing index value statistics logic of the index after the management platform receives the scheduling request sent by the scheduling platform at regular time. The index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain the index value of the time point. The statistical record is determined based on field values of dependent fields in the index's dependent data table. And constructing an index curve of the index based on the index values of each time point in the construction time period. In other words, in the scheme provided by the specification, the index value of each time point is obtained by running the index value statistics logic, so that the automatic statistics process of the index value is realized, and the statistics efficiency of the index value is greatly improved. In addition, the index values of all time points required by the construction of the index curve are generated by the scheduling platform timing scheduling management platform without real-time generation, so that the construction speed of the index curve can be increased.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present description, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of an index system provided in the present specification;

FIG. 2 is a flowchart of a method for constructing an index curve according to an embodiment of the present disclosure;

FIG. 3 is a flow chart of an analysis method of the index provided in the present specification;

FIG. 4 is a schematic diagram of an analysis report provided in the present specification;

FIG. 5 is a schematic diagram of an apparatus for constructing an index curve according to an embodiment of the present disclosure;

FIG. 6 is a schematic diagram of an apparatus for constructing an index curve according to an embodiment of the present disclosure.

Detailed Description

The following describes the scheme provided in the present specification with reference to the drawings.

The metrics described herein may include, but are not limited to, business metrics, which may be used for business intelligence analysis. For example, the business index may be a number of monthly active users (month active users, mau), and so on. An index system for constructing an index curve and generating index dependent data is described below.

Fig. 1 is a schematic diagram of an index system provided in the present specification. As shown in fig. 1, the index system may include at least: management platform 102, scheduling component 104, storage unit 106, and report presentation interface 108.

The management platform 102 is used to manage predefined metadata of the metrics, where the predefined metadata is used at least to describe dependency data tables (also called physical tables) and dependency fields of the metrics. Furthermore, it can be used to describe the mapping relation of the dependent fields, the aggregation field, the aggregation type, etc. The management platform 102 is further configured to generate an index value statistics logic of the index, and execute the index value statistics logic to obtain an index value of the index. The index value statistics logic may be obtained by the management platform 102 after updating the predefined SQL template based on the predefined metadata (the updating process is described later). The SQL template at least comprises variables corresponding to the dependency data table and the dependency fields, and also comprises variables corresponding to the aggregation type and the aggregation fields.

The management platform 102 may also be configured to construct an index curve of the index based on the index values at each time point in the specified time period; and generating logic for executing the index dependent data to generate index dependent data (also referred to as cube data). The index dependent data may include aggregated results for the index under different dimensional combinations.

The scheduling component 104 is configured to schedule the management platform 102 to generate index values and/or index dependent data for the index at various points in time. In addition, the creation interface is also used for timing scheduling of the kylin component.

The storage unit 106 may include, but is not limited to, hbase or hive components, which may be used to store index values of the index at various points in time, cube data of the index, and the like.

A report presentation interface 108 for presenting and analyzing a report based on the cube data stored in the storage unit 106. The analysis report described in the present specification may be in a tree structure, where a top node of the tree structure is an index value of an index, and other nodes of the tree structure are summary results under other dimension combinations.

The above is a description of the index system, and the update procedure of the SQL template mentioned above is explained below.

In one implementation, the update procedure may specifically be: the variables in the predefined SQL template are replaced based on the dependency data table, dependency fields, mapping relationships, aggregation fields, aggregation types, etc. Of course, in practical application, the above updating process can also be completed by writing corresponding SQL sentences. Specifically, an SQL statement for updating an SQL template is generated based on the dependency data table, the dependency field, the mapping relationship, the aggregation field, the aggregation type, and the like. The function of the SQL statement is to replace variables in the predefined SQL template. Executing the generated SQL sentence to obtain index value statistics logic of the index.

For example, the index mau may be the following code corresponding to the index value statistics logic:

wherein count may be the aggregate type of the index. The uid in brackets may be an aggregate field of the index. uid, region, age, channel, and paytime may be dependency fields of the index. And a dependency data table taking a user, an oder and a pay as indexes.

The above is a description of the update process of the SQL template. It will be appreciated that after the update process is performed, index value statistics for the index may be obtained. By executing the statistical logic, index values for the respective time points for constructing the index curve can be obtained. Since the index value acquisition methods at different time points are similar, the index value acquisition process at an arbitrary first time point will be described as an example.

In one implementation, the acquisition process may be: and receiving a scheduling request sent by a scheduling platform. The scheduling request may include at least a first point in time. Based on the first time point, updating the statistical time point in index value statistical logic of the index. For example, the variables in the code are updated: $ { dt }. And executing the updated index value statistics logic to obtain the index value of the index at the first time point.

As can be seen from the code corresponding to the index value statistics logic, the execution process of the index value statistics logic can be divided into two parts: a first part: a logical table is built that may include a number of data records, where each data record is determined based on field values of dependent fields in the index's dependent data table. A second part: and aggregating and summarizing the statistical records of the indexes according to the first time point to obtain the index values of the first time point.

The two parts are described below in connection with examples.

Taking the index mau as an example, assume that it depends on the data table: the fields in the user, the oder and the pay and the corresponding field values are as follows:

user table

uid	gender	age	date	region
					1	Man's body	20	2018-08-01	(Hangzhou)
2	Female	30	2018-08-01	Shenzhen (Shenzhen)
					…	…	…	…	…

oder table

pay table

uid	oderid	paytime
			1	10000	2018-08-01
1	10001	2018-08-03
			…	…	…

Then the logical table built may be as follows:

logic table

uid	region	Age group	channel	paytime	…
						1	(Hangzhou)	young	Web	2018-08-01	…
…	…	…	…	…	…

It should be noted that, regarding the field value of the age group in the logical table, it may be obtained based on the following mapping relationship:

10<age<30＝＝>young

30<age<40＝＝>middle

age>50＝＝>old

it should be noted that each field in the above logic table is only an exemplary illustration, and in practical applications, other fields, such as use case, etc., may also be included in the above logic table. Alternatively, fields other than the age group may be mapped, for example, paytime may be converted into is_active (whether or not it is an active user in the present month), and the present specification is not limited thereto.

It can be understood that, after the statistics records in the logic table are aggregated according to the time points, the index value of the first time point can be obtained. For example, according to the time points: after aggregate summarization of 2018-08-01, the mau value for the day of 2018-08-01 is obtained.

Referring to the method of acquiring the index value at the first time point, the index value of the index at each time point may be acquired. Thereafter, the index values of the index at each time point may be stored in the above-mentioned storage unit 106, so as to facilitate the construction of a subsequent index curve.

The following describes the construction process of the index curve.

Fig. 2 is a flowchart of a method for constructing an index curve according to an embodiment of the present disclosure. The subject of execution of the method may be a device with processing capabilities: the server or system or platform, for example, may be the management platform 102 of fig. 1, etc. As shown in fig. 2, the method specifically may include:

step 202, a request for constructing an indicator curve is received.

In one example, the build request may be received through the report presentation interface 108. Specifically, when a user clicks on a control associated with building an index curve on the report presentation interface 108, the management platform 102 may receive a request to build the index curve. The build request may include at least an indicator of the current desired build curve, a build time period, and the like. Taking mau as an example, the build time period here may be one month.

Step 204, reading index values of the index at various time points in the construction period from the storage unit.

It is understood that the storage unit described in the present specification may record a plurality of indexes and index values of the respective indexes at a plurality of time points. The statistical process of the index value of each index at each time point is the same as that described above, and will not be repeated here.

For example mau, the mau value per day for one month may be read.

And 206, constructing an index curve of the index based on the index values of each time point in the construction time period.

Also taking mau as an example, based on mau values per day, an index curve of mau can be constructed within one month.

After an index curve of a certain index is constructed, a user may determine whether the index value at a certain time point or a certain time points is abnormal by looking up a trend of the index curve. Of course, in practical application, whether the index value at a certain time point is abnormal may be determined based on a preset rule. The preset rules here may be, for example: whether the index value is greater than a threshold value or less than a threshold value, etc.

In addition, in this specification, for an index value in which an abnormality exists, it can be analyzed based on the result of aggregation of the index in different dimensions. Taking mau as an example, assuming that there is an anomaly in mau value on a certain day, the anomaly can be analyzed from the summarized results in different dimensions such as region, age group, channel, and paytime, and the summarized results in different dimensions can also be referred to as index dependent data (or cube data). The generation process of the index-dependent data will be described below.

In the present specification, the index-dependent data can be generated in the following two ways.

First, cube data is generated by timing execution index dependent data generation logic. In particular, the scheduling component 104 can schedule the management platform 102 at a timing such that the management platform 102 executes the index dependent data generation logic. The function of the index-dependent data generation logic is to aggregate and summarize the statistics records of the index according to different dimensional combinations so as to obtain cube data of the index. The cube data includes summary results of the metrics under different dimensional combinations that are determined based on field values of the dependent fields. The cube data may include an index value of the index.

The determination of the combinations of dimensions is illustrated below.

Taking the index mau as an example, assume that its dependent fields are: region and age, and the field values of region include: hangzhou and Beijing, the field values for the age group include: young, middle, and old, then the dimension combinations corresponding to mau may be: { Hangzhou }, { Beijing }, { young }, { middle }, { old }, { Hangzhou }, young }, { Hangzhou, middle }, { Hangzhou, old }, { Beijing, young }, beijing, middle }, { Beijing, old }, old }. Where { Hangzhou } is equivalent to { Hangzhou, all }, all herein may refer to people of all ages. Similarly, { Beijing } is equivalent to { Beijing, all }, and so on. It should be appreciated that the above combinations of dimensions may also include: { all, all }, it is understood that the summary result corresponding to the dimension combination is mau value of a certain day.

Regarding the above-described index-dependent data generation logic, in one example, the code corresponding thereto may be:

select aggregate type (aggregate field) as count, dimension combination as key

from(udtf(uid,age,region)as logictable

) group by dimension combination

Wherein, udtf is used for the statistics of the extension index. count may be understood as a summary result.

As can be seen from the above codes, the summary results are determined based on the aggregation type and/or the aggregation field. The summary result will be described below with reference to examples.

Assume the index is mau and the statistical record of mau is shown below.

Statistical table

uid	region	Age group
			1	(Hangzhou)	young
1	Beijing	young
			2	(Hangzhou)	old
3	(Hangzhou)	old
			…	…	…

Then, when the aggregation type is: count, aggregate field is: uid is an example, for a dimension combination: { Hangzhou }, the corresponding summary result may be: 3. for dimensional combinations: { Hangzhou, old }, the corresponding summary result may be: 2.

second, the creation interface of the kylin component is scheduled at regular time by the scheduling component 104 to generate cube data. In particular, a data generation request may be sent to the kylin component, the data generation request comprising predefined metadata. The data generation request here is used to instruct the kylin component to construct cube data for the index based on the predefined metadata.

It is understood that after the cube data of the index is acquired, the cube data of the index may be stored in the storage unit 108. Specifically, the index can be stored in hbase for use in the process of subsequent index analysis.

The process of index analysis described herein may be based on the report presentation interface 108 described above. The user may set the index to be analyzed and the corresponding point in time through the report presentation interface 108.

In one example, the method of index analysis may be specifically as shown in fig. 3. In fig. 3, the method may include:

step 302, an index analysis request is received.

And step 304, responding to the index analysis request, obtaining an index value to be analyzed, and displaying the index value as a top node of the tree structure.

Here, the index value to be analyzed may be acquired from the storage unit 106. In addition, the exposed index value may correspond to a plurality of button controls, where each button control is configured to expose one analysis dimension of the index value.

For the index mau, the dependency fields are: region and age, and the field values of region include: hangzhou and Beijing, the field values for the age group include: examples of young, middle, and old, where the analysis dimension presented by the button control may be: region and age group.

Step 306, a drill-down analysis request for an index value is received.

The drill-down analysis request may be triggered by the user clicking on any button control corresponding to the indicator value.

Step 308, based on the drill-down analysis request, a combination of dimensions for the current drill-down is determined.

As in the previous example, when the user clicks on a button control for showing "region," the determined combination of dimensions may be: { Beijing, all } { Hangzhou, all }. The determining process of the dimension combinations herein is not focused on the discussion of the embodiments of the present specification, and therefore will not be described in detail.

And 310, reading a summary result under the current dimension combination drilled down from the cube data of the index, and displaying the summary result as a lower node of the tree structure.

In the foregoing example, since two dimensional combinations are determined, two lower level nodes may be extended downward, so that a two-level tree structure may be obtained.

It can be understood that, for the two extended lower nodes, the two lower nodes can be further processed by drill-down analysis, and the specific analysis process is the same as that described above, and is not repeated here.

After all drill-down analysis is completed for a certain index value, an analysis report of the index value can be obtained. In one example, the resulting analytical report may be as shown in FIG. 4. In fig. 4, the top node is mau of a certain day, and the two nodes of the second layer are respectively a summary result corresponding to { beijing, all }, and a summary result corresponding to { hangzhou, all }. The two nodes of the third layer are a result of aggregation corresponding to { Beijing, young }, a result of aggregation corresponding to { Beijing, middle }, and a result of aggregation corresponding to { Beijing, old }, respectively.

In the present specification, the access frequency can be counted for the analysis report shown in fig. 4. If the access frequency is greater than the threshold value, the analysis report may be saved to the LR cache for the next reading.

Finally, since the cube data generated by the index dependent data generation logic includes the index value of the index, in practical application, the index value statistics logic and the dependent data generation logic may be unified into one logic, for example, unified into the index dependent data generation logic, that is, the index value statistics logic is replaced by the index dependent data generation logic, which is not limited in this specification.

In summary, according to the method for creating the index curve provided by the embodiment of the specification, the index value of each time point is obtained by running the index value statistics logic, so that the automatic statistics process of the index value is realized, and the statistics efficiency of the index value is greatly improved. In addition, the index values of all time points required by the construction of the index curve are generated by the scheduling platform timing scheduling management platform without real-time generation, so that the construction speed of the index curve can be increased. Finally, the scheme can also generate index dependent data (or cube data) at regular time, so that multidimensional analysis or transaction analysis and the like on the index value can be facilitated.

Corresponding to the above method for constructing an index curve, an embodiment of the present disclosure further provides an apparatus for constructing an index curve, as shown in fig. 5, where the apparatus may include:

a receiving unit 502, configured to receive a request for constructing an index curve.

The build request includes at least an indicator of the current desired build curve and a build time period.

A reading unit 504, configured to read, from the storage unit, index values of the index at respective time points in the construction period. The index value of the index at each time point is obtained by executing index value statistics logic of the index after the device receives the scheduling request sent by the scheduling platform at regular time. The index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain the index value of the time point. The statistical record is determined based on field values of dependent fields in the index's dependent data table.

A construction unit 506, configured to construct an index curve of the index based on the index values of the respective time points in the construction period read by the reading unit 504.

Optionally, the apparatus further comprises:

an obtaining unit 508 is configured to obtain predefined metadata of the index, where the predefined metadata is at least used to describe a dependency data table and a dependency field of the index.

The obtaining unit 508 is further configured to obtain a predefined SQL template, where the predefined SQL template includes at least variables corresponding to the dependency data table and the dependency field.

And the replacing unit 510 is configured to replace respective corresponding variables in the predefined SQL template based at least on the dependency data table and the dependency field, so as to obtain index value statistics of the index.

The replacing unit 510 may specifically be configured to:

based at least on the dependency data table and the dependency fields, an SQL statement is generated for updating the SQL template. The function of the SQL statement is to replace variables in the predefined SQL template.

And executing the SQL sentence to obtain index value statistics logic of the index.

Optionally, the index value statistics logic of the index includes at least statistics time points, each time point including a first time point. The device further comprises: update unit 512 and execution unit 514.

The receiving unit 502 is further configured to receive a scheduling request sent by the scheduling platform, where the scheduling request includes at least a first time point.

An updating unit 512, configured to update the statistical time point in the index value statistics logic of the index based on the first time point received by the receiving unit 502.

An execution unit 514, configured to execute the index value statistics logic updated by the update unit 512 to obtain the index value of the index at the first time point.

Optionally, the apparatus may further include:

a first sending unit 516 is configured to send a data generation request to the kylin component, where the data generation request includes predefined metadata. The data generation request is used for instructing the kylin component to construct cube data of the index based on the predefined metadata.

The cube data comprises summary results of the index under different dimension combinations, the dimension combinations are determined based on field values of the dependent fields, and the summary results comprise index values.

Optionally, the apparatus may further include:

a second transmitting unit 518 for acquiring and executing the predefined index dependent data generation logic; the index dependent data generation logic is used for aggregating and summarizing the statistical records of the index according to different dimension combinations to obtain cube data of the index.

The cube data includes summary results of the index under different dimensional combinations, the dimensional combinations are determined based on field values of the dependent fields, and the summary results include index values.

Optionally, the apparatus may further include: a display unit 520 and a determination unit 522.

The receiving unit 502 is further configured to receive an index analysis request.

The display unit 520 is configured to obtain an index value in response to the index analysis request received by the receiving unit 502, and display the index value as a top node of the tree structure, where the displayed index value may be drilled down based on different dimensional combinations.

The receiving unit 502 is further configured to receive a request for drill-down analysis for the index value.

A determining unit 522, configured to determine a dimension combination of the current drill-down based on the drill-down analysis request received by the receiving unit 502.

The reading unit 504 is further configured to read, from cube data of the index, a summary result under the current dimension combination drilled down, and display the summary result as a next-layer node of the tree structure.

Optionally, the apparatus may further include:

a statistics unit 524, configured to count the access frequency of each analysis path of the index value, where the analysis paths are obtained by combining nodes in different layers.

A saving unit 526, configured to save the analysis path with the access frequency greater than the threshold value counted by the counting unit 524 in the LR cache, so as to directly load the analysis path in a process of subsequent analysis of the index value.

The functions of the functional modules of the apparatus in the foregoing embodiments of the present disclosure may be implemented by the steps of the foregoing method embodiments, so that the specific working process of the apparatus provided in one embodiment of the present disclosure is not repeated herein.

In the device for constructing an index curve according to one embodiment of the present disclosure, the receiving unit 502 receives a request for constructing an index curve. The build request includes at least an indicator of the current desired build curve and a build time period. The reading unit 504 reads the index values of the index at the respective time points within the construction period from the storage unit. The index value of the index at each time point is obtained by executing index value statistics logic of the index after the device receives the scheduling request sent by the scheduling platform at regular time. The index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain the index value of the time point. The statistical record is determined based on field values of dependent fields in the index's dependent data table. The construction unit 506 constructs an index curve of the index based on the index values at the respective time points in the construction period. Thus, the index curve can be constructed quickly.

The apparatus for constructing an index profile according to one embodiment of the present disclosure may be a module or unit in the management platform 102 in fig. 1.

Correspondingly to the above method for constructing an index curve, the embodiment of the present disclosure further provides an apparatus for constructing an index curve, as shown in fig. 6, where the apparatus may include: memory 602, one or more processors 604, and one or more programs. Wherein the one or more programs are stored in the memory 602 and configured to be executed by the one or more processors 604, the programs when executed by the processor 604 performing the steps of:

and receiving a construction request of the index curve.

The index values of the index at the respective time points in the construction period are read from the storage unit. The index value of the index at each time point is obtained by executing index value statistics logic of the index after the management platform receives the scheduling request sent by the scheduling platform at regular time. The index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain the index value of the time point. The statistical record is determined based on field values of the dependency fields in the dependency data table of the indicator.

The index curve construction device provided by one embodiment of the present specification can quickly construct an index curve.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the apparatus embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.

The steps of a method or algorithm described in connection with the disclosure herein may be embodied in hardware, or may be embodied in software instructions executed by a processor. The software instructions may be comprised of corresponding software modules that may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. In addition, the ASIC may reside in a server. The processor and the storage medium may reside as discrete components in a server.

Those skilled in the art will appreciate that in one or more of the examples described above, the functions described in the present invention may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, these functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The foregoing detailed description of the embodiments has further described the objects, technical solutions and advantages of the present specification, and it should be understood that the foregoing description is only a detailed description of the embodiments of the present specification, and is not intended to limit the scope of the present specification, but any modifications, equivalents, improvements, etc. made on the basis of the technical solutions of the present specification should be included in the scope of the present specification.

Claims

1. A method of constructing an index curve, performed by a management platform, the method comprising:

receiving a construction request of an index curve;

constructing an index curve of the index based on index values of all time points in the construction time period, and identifying the index value with abnormality;

based on the cube data of the index, performing drill-down analysis on the index value with the abnormality; the cube data comprises summarized results of the index under different dimensional combinations, and the dimensional combinations are determined based on field values of the dependent fields;

the drill-down analysis comprises the steps that the index value with the abnormality is displayed as a top node of a tree structure, the top node corresponds to a plurality of button controls, and each button control corresponds to one analysis dimension; receiving a drill-down analysis request sent by a user by triggering any button control, and determining a dimension combination of current drill-down based on the drill-down analysis request; and reading a summary result under the dimension combination currently drilled from the cube data of the index, displaying the summary result as a lower node of the tree structure, and the like until the drill analysis is finished.

2. The method of claim 1, further comprising the step of obtaining an index value statistics logic for the index, comprising:

acquiring predefined metadata of the index; the predefined metadata is at least used for describing a dependency data table and a dependency field of the index;

acquiring a predefined SQL template; the predefined SQL template at least comprises variables corresponding to the dependency data table and the dependency fields respectively;

and replacing respective corresponding variables in the predefined SQL template at least based on the dependency data table and the dependency field to obtain index value statistics logic of the index.

3. The method of claim 2, the replacing respective corresponding variables in the predefined SQL template based at least on the dependency data table and the dependency field, comprising:

generating an SQL statement for updating an SQL template based at least on the dependency data table and the dependency field; the SQL statement is used for replacing variables in the predefined SQL template;

executing the SQL sentence to obtain index value statistics logic of the index.

4. The method of claim 1, wherein the index value statistics logic of the index comprises at least a statistics time point; the respective time points include a first time point; the method further comprises the steps of:

receiving a scheduling request sent by the scheduling platform, wherein the scheduling request at least comprises the first time point;

updating the statistical time point in the index value statistical logic of the index based on the first time point;

and executing the updated index value statistics logic to obtain the index value of the index at the first time point.

5. The method of claim 2, cube data of the index is obtained by:

sending a data generation request to a kylin component, the data generation request comprising the predefined metadata; the data generation request is used for indicating the kylin component to construct cube data of the index based on the predefined metadata.

6. The method of claim 1, cube data of the index is obtained by:

acquiring and executing predefined index dependent data generation logic; the index dependent data generation logic is used for aggregating and summarizing the statistical records of the index according to different dimensional combinations to obtain cube data of the index.

7. The method of claim 1, further comprising:

counting the access frequency of each analysis path of the index value; the analysis path is obtained by combining nodes of different layers;

and storing the analysis paths with the access frequency larger than the threshold value into an LR cache so as to be convenient for directly loading the analysis paths in the process of subsequent analysis of the index value.

8. An apparatus for constructing an index curve, the apparatus comprising:

a construction unit, configured to construct an index curve of the index based on the index values of the respective time points in the construction time period read by the reading unit, to identify an index value having an abnormality;

9. The apparatus of claim 8, further comprising:

an acquisition unit configured to acquire predefined metadata of the index; the predefined metadata is at least used for describing a dependency data table and a dependency field of the index;

the acquisition unit is also used for acquiring a predefined SQL template; the predefined SQL template at least comprises variables corresponding to the dependency data table and the dependency fields respectively;

and the replacing unit is used for replacing respective corresponding variables in the predefined SQL template at least based on the dependency data table and the dependency field so as to obtain index value statistical logic of the index.

10. The device according to claim 9, the substitution unit being in particular for:

executing the SQL sentence to obtain index value statistics logic of the index.

11. The apparatus of claim 8, the indicator value statistics logic of the indicator comprising at least a statistics time point; the respective time points include a first time point; the apparatus further comprises: an updating unit and an executing unit;

the receiving unit is further configured to receive a scheduling request sent by the scheduling platform, where the scheduling request at least includes the first time point;

the updating unit is used for updating the statistical time point in the index value statistical logic of the index based on the first time point received by the receiving unit;

the execution unit is used for executing the index value statistical logic updated by the updating unit so as to obtain the index value of the index at the first time point.

12. The apparatus of claim 9, further comprising:

a first sending unit, configured to send a data generation request to a kylin component, where the data generation request includes the predefined metadata; the data generation request is used for indicating the kylin component to construct cube data of the index based on the predefined metadata.

13. The apparatus of claim 8, further comprising:

a second transmitting unit for acquiring and executing a predefined index dependent data generation logic; the index dependent data generation logic is used for aggregating and summarizing the statistical records of the index according to different dimensional combinations to obtain cube data of the index.

14. The apparatus of claim 8, further comprising:

a statistics unit, configured to count access frequencies of each analysis path of the index value; the analysis path is obtained by combining nodes of different layers;

and the storage unit is used for storing the analysis paths with the access frequency larger than the threshold value, which are counted by the counting unit, into an LR cache so as to be convenient for directly loading the analysis paths in the subsequent analysis process of the index value.

15. An index curve construction apparatus comprising:

a memory;

one or more processors; and

receiving a construction request of an index curve;

reading index values of the index at various time points in the construction time period from a storage unit; the index value of the index at each time point is obtained by executing index value statistical logic of the index after the management platform receives a scheduling request sent by the scheduling platform at regular time; the index value statistics logic is used for aggregating and summarizing the statistics records of the index according to the time point to obtain an index value of the time point; the statistical record is determined based on field values of dependent fields in a dependent data table of the index;