CN113590659B - Stock selection control method, device and system based on data classification processing - Google Patents
Stock selection control method, device and system based on data classification processing Download PDFInfo
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Abstract
The application discloses a stock selection control method, device and system based on data classification processing, wherein the method comprises the following steps: acquiring a stock selection request; extracting various strategy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the strategy requirements of the strategy factors; acquiring a static data stock result set based on the static data stock selection request, and acquiring a calculation data stock result set based on the calculation data stock selection request; and combining the static data stock result set and the calculation data stock result set to form an output stock result set, and returning to the request terminal for sending the stock selection request. According to the application, the stock selection data is divided into the static data stock result set and the calculation data stock result set for classified storage and scheduling, and the calculation data stock result set is divided into the primary storage and the secondary storage, so that the processing speed and the processing precision of the stock selection request are effectively improved, and more objective and high-accuracy stocks can be recommended for users.
Description
Technical Field
The application relates to the field of finance, in particular to the technical field of stock data analysis, and specifically relates to a stock selection control method, device and system based on data classification processing.
Background
Along with the high-speed development of market economy in China, more and more investors focus on stocks, and the stock investment becomes an important mode in personal financial management. Stocks can be transferred in market circulation, and the stocks have the characteristics of high risk and high return, so that tens of millions of investors are caught from the day of production, and the investors pay attention to fluctuation and development trend of stock prices at all times, which is a hot problem in the research of the economic field.
The aim pursued by securities investors is that the income is large and the risk is small. Two general types of investment analysis methods, basic analysis and technical analysis, are commonly employed to achieve this goal. The basic analysis method is used for determining the real value of the stock by analyzing basic factors influencing the supply and demand relationship of the stock market, judging the market trend of the stock and providing the basis for investors to select the stock. The technical analysis is a method for analyzing the market change completely according to the market price, and by analyzing the historical data, the future change trend of the price of the whole stock market or individual stock is judged, the possible turning of the investment behavior in the stock market is discussed, and a stock buying and selling signal is provided for investors.
In the actual stock investment process, the user usually decides which stock to purchase according to subjective judgment or according to the recent stock consultation, or recommends which stock to purchase subjectively to the user through an investment manager according to some related information of the benchmark stock, however, the stock selection uncertainty based on artificial experience is large. Therefore, how to recommend stocks to users more quickly and accurately is a technical problem to be solved.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, an object of the present application is to provide a stock selection control method, apparatus and system based on data classification processing, for recommending stocks for users more quickly and accurately.
In order to achieve the above object and other related objects, the present application provides a stock selection control method based on data classification processing, including: acquiring a stock selection request; extracting various policy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the policy requirements of the policy factors; acquiring a static data stock result set from a static data storage area based on the static data stock selection request, and acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request; and combining the static data stock result set and the calculation data stock result set to form an output stock result set, and returning the output stock result set to a request terminal for sending the stock selection request.
In an embodiment of the present application, the computing data storage area includes a first level data buffer for buffering the current day computing data stock result set and a second level data buffer for buffering the multiple days computing data stock result set.
In an embodiment of the present application, the stock selection request is a user stock selection request; and acquiring the calculation data stock result set from the first-level data cache area in the calculation data stock result set acquired from the calculation data storage area based on the calculation data stock selection request.
In an embodiment of the present application, when the calculated data stock result set does not exist in the primary data cache region, the calculated data stock result set is obtained from the secondary data cache region.
In one embodiment of the present application, the set of calculated data stock results is obtained from a data calculation server that generates the set of calculated data stock results when the set of calculated data stock results does not exist in the secondary data cache.
In an embodiment of the present application, the stock selection request is a back-measurement stock selection request; when the stock selection request is a return measurement stock selection request, splitting the return measurement stock selection request into a plurality of single-day stock selection requests according to the day.
In an embodiment of the present application, when the stock selection request is a back measurement stock selection request, a calculation data stock result set is obtained from a calculation data storage area based on the calculation data stock selection request, and a calculation data stock result set is obtained from a second data cache area for caching the calculation data stock result set on the same day.
In one embodiment of the present application, the set of calculated data stock results is obtained from a data calculation server that generates the set of calculated data stock results when the set of calculated data stock results does not exist in the secondary data cache.
In an embodiment of the present application, the static data storage area is distributed among a plurality of static data servers that extend longitudinally; the computing data store is distributed across a plurality of data processing servers that are laterally expanded and a plurality of data computing servers that are laterally expanded.
In order to achieve the above object and other related objects, the present application also provides a stock selection control device based on data classification processing, including: the request acquisition module is used for acquiring a stock selection request; the request splitting processing module is used for extracting various strategy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the strategy requirement of each strategy factor; the static data acquisition module is used for acquiring a static data stock result set from the static data storage area based on the static data stock selection request; the calculation data acquisition module is used for acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request; and the data set processing output module is used for carrying out combination processing on the static data stock result set and the calculation data stock result set to form an output stock result set, and returning the output stock result set to the request terminal for sending the stock selection request.
In an embodiment of the present application, the computing data storage area includes a first level data buffer for buffering the current day computing data stock result set and a second level data buffer for buffering the multiple days computing data stock result set.
In an embodiment of the present application, the stock selection request is a user stock selection request; acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, and acquiring the calculation data stock result set from the primary data cache area; or the stock selection request is a back measurement stock selection request, when the stock selection request is a back measurement stock selection request, the back measurement stock selection request is split into a plurality of single-day stock selection requests according to the day, when the stock selection request is a back measurement stock selection request, the calculation data stock result set is obtained from the calculation data storage area based on the calculation data stock result set, and the calculation data stock result set is obtained from the secondary data cache area for caching the current day calculation data stock result set.
In an embodiment of the present application, when there is no calculation data stock result set in the primary data buffer, the calculation data stock result set is obtained from the secondary data buffer; and when the calculated data stock result set does not exist in the secondary data cache area, acquiring the calculated data stock result set from a data calculation server generating the calculated data stock result set.
In order to achieve the above and other related objects, the present application also provides a stock selection control system based on data classification processing, which comprises at least one data processing server, at least one static data server and at least one data calculation server; a static data storage area for storing a static data stock result set is distributed to the at least one static data server, and a calculation data storage area for storing a calculation data stock result set is distributed to the at least one data processing server and the at least one data calculation server; the data computing server generates the computing data stock result set; the data processing server runs the stock selection control method based on the data classification processing as described above.
As described above, the stock selection control method, device and system based on data classification processing has the following beneficial effects:
according to the application, the stock selection data is divided into the static data stock result set and the calculation data stock result set for classified storage and scheduling, and the calculation data stock result set is divided into the primary storage and the secondary storage, so that the processing speed and the processing precision of the stock selection request are effectively improved, and more objective and high-accuracy stocks can be recommended for users.
Drawings
Fig. 1 is a schematic overall flow chart of a stock selection control method based on data classification processing in an embodiment of the application.
Fig. 2 is a schematic diagram of acquiring data based on a user stock selection request in a stock selection control method based on data classification processing according to an embodiment of the present application.
Fig. 3 is a schematic diagram of acquiring data based on a return measurement strand selection request in a strand selection control method based on data classification processing according to an embodiment of the present application.
Fig. 4 is a schematic flow chart of outputting a stock result set based on a user stock selection request in a stock selection control method based on data classification processing according to an embodiment of the application.
Fig. 5 is a schematic flow chart of outputting a stock result set based on a return measurement stock selection request in a stock selection control method based on data classification processing according to an embodiment of the application.
Fig. 6 is a schematic block diagram of a stock selection control device based on data classification processing in an embodiment of the application.
Fig. 7 is a schematic diagram of a stock selection control system based on data classification processing according to an embodiment of the application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present application with reference to specific examples. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present application by way of illustration, and only the components related to the present application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
The embodiment aims to provide a stock selection control method, device and system based on data classification processing, which are used for recommending more objective and highly accurate stocks for users.
The principle and implementation of the data classification processing-based stock selection control method, device and system of the present embodiment will be described in detail below, so that those skilled in the art can understand the data classification processing-based stock selection control method, device and system of the present embodiment without creative labor.
Example 1
Fig. 1 is a schematic overall flow chart of a stock selection control method based on data classification processing in the present embodiment. As shown in fig. 1, the present embodiment provides a stock selection control method based on data classification processing, where the stock selection control method based on data classification processing includes the following steps:
step S100, obtaining a stock selection request;
step S200, extracting various strategy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the strategy requirement of each strategy factor;
step S300, acquiring a static data stock result set from a static data storage area based on the static data stock selection request, and acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request;
and step S400, combining the static data stock result set and the calculation data stock result set to form an output stock result set, and returning the output stock result set to the request terminal for sending the stock selection request.
Steps S100 to S400 in the stock selection control method based on the data classification processing in the present embodiment are described in detail below.
Step S100, obtaining a stock selection request.
In this embodiment, the stock selection request may be a user stock selection request from a user terminal, or a return stock selection request from a return platform.
In this embodiment, before the user generates the user stock selection request through the user terminal, providing user stock selection parameter configuration, where in the user stock selection parameter configuration, data of the day is preferably selected, and a plurality of optional stock selection configuration parameters are preset, and limiting the user stock selection parameter configuration while performing parameter configuration guidance on the user, so that the user can acquire stock data meeting the selection rule as soon as possible.
In this embodiment, at least one return model is set in the return platform, and the return model performs historical return on stock data according to at least one configurable return strategy to obtain a return result. The return platform can randomly adjust various stock selection configuration parameters when generating stock selection requests, and a batch (for example, hundreds) stock selection requests are generated by one return request.
In this embodiment, when the stock selection request is a user stock selection request from a user terminal, the step S200 is directly executed continuously, and when the stock selection request is a return measurement stock selection request from a return measurement platform, the return measurement stock selection request is split into a plurality of single-day stock selection requests by day, and the step S200 is executed continuously for each single-day stock selection request.
Step 200, extracting various policy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the policy requirements of the policy factors.
The method for extracting various strategy factors from the stock selection request comprises the following steps:
and extracting a strand selection range, a strand selection condition and a strand selection type from the strand selection request to form corresponding policy factors, and then determining whether static data or dynamic data is needed for the corresponding policy factors based on fields corresponding to the strand selection types.
Step S300, a static data stock result set is obtained from a static data storage area based on the static data stock selection request, and a calculation data stock result set is obtained from a calculation data storage area based on the calculation data stock selection request.
In this embodiment, the static data storage area is distributed among a plurality of static data servers (datasvr) that extend longitudinally; the computing data storage area is distributed over a plurality of data processing servers (centrersvr) that are laterally expanded and a plurality of data computing servers (calcsvr) that are laterally expanded.
In this embodiment, the data processing server (centrsvr) sends the stock selection request to different servers (static data server and calcsvr) according to different policy factor requirements of one stock selection request,
the data processing server (centrersvr) has no state, the data cache is a first-level cache, reading in advance is not needed, and after the user accesses, all result sets of the same day are reserved in the service memory, because stock selection data for the user are all the same day, and the access performance of stock selection of the user is improved.
The data processing server (centrersvr) can be extended in parallel, so that concurrency is improved, and service availability is increased.
In this embodiment, a static data server (datasvr) caches static data, which facilitates fast polling. When the total data amount is increased to a single static data server (datasvr) memory and is difficult to load, longitudinal segmentation is adopted, the data is segmented into different services according to different types of the data, and then the static data server (datasvr) is derivatized into financial services, financial report services and the like. When the user volume is increased to be intolerable to a static data server (datasvr) single machine, lateral expansion is performed, and service concurrency and usability are improved.
In this embodiment, the static data server (datasvr) preferably adopts a vertical expansion and then a horizontal expansion. Because there is a class of demand when selecting factors, such as requesting 5-20% of the market value stocks, it becomes very difficult to calculate the request if the market value factors are cut across multiple different static data servers (datasvr), the basic guideline for the design is to keep a single static factor from being distributed among the different static data servers (datasvr) as much as possible.
In this embodiment, the data computing server (calcsvr) calculates corresponding derivative data according to different algorithm indexes through the basic K-line data, that is, generates a computing data stock result set according to the stored computing data,
the data computation server (calcsvr) has no state, but needs to cache the underlying K-line data at startup for computing other derived data. For example, data above the K level on day 2 is relatively small in volume, fast in reading speed, large in K data per minute when the service is started, and relatively small in usage, and is loaded when requested by the user and then cached in the memory so as not to affect the service restart time.
The data computing server (calcsvr) can be extended in parallel, concurrency is improved, and service availability is improved.
In this embodiment, the stock data is divided into static data and calculation data.
The static data is numerical data which can be directly obtained in general and does not cause great change of results due to different external input parameters. Such as whether a stock is a documented or profound stock, whether it is a st stock, capital structure and revenue, etc., which are generally fixed for the stock and in most cases, the results can be easily described by a simple int or float type, so that their data usage can be estimated more easily.
In this embodiment, the static data includes, but is not limited to, stock base information, financial information, and financial report information. Wherein the stock base information includes, but is not limited to, exchanges to which the stock belongs (e.g., up, down), stock blocks (e.g., concepts, territories, industries), stock status (e.g., stop, new stock, days of trade, days of market), etc.; such financial information includes, but is not limited to, valuations, performance scores, capital structure, indicators per strand, capacity for compensation, and the like; the financial information includes, but is not limited to, business income, business expenditure, profit, assets, liabilities, financial issue days, etc.
The calculation data refers to data of different calculation data result sets obtained according to different external input parameters by a specific algorithm. The feature of the calculated data is that the amount of basic data forming the result is usually not too large, but the result set calculated from different external input parameters is very large and is not suitable for unified static storage. For example, calculating data ma (30) refers to taking an average of the data from the previous 30 days, and taking a return measurement typically requires ma (30) from the previous year, thus requiring an average of each day of the previous year to be calculated. If only one ma (30) is simply stored, the actual result set is not large, but various parameters such as ma (1-200) and the like may be transmitted when the device is used, so that if the result set corresponding to all the ma needs to be stored, the data volume becomes very large and uncontrollable.
In this embodiment, the calculation data includes, but is not limited to, market base, technical index, K-line shape, etc. Wherein, the market base comprises but is not limited to stock price, accumulated hand change rate, stock price amplitude, amount of exchange, fluctuation range and the like; such specifications include, but are not limited to ma, ema, macd, etc.
In this embodiment, a static data stock result set is formed based on static data, a calculation data stock result set is formed based on calculation data, the static data stock result set is obtained from the static data storage area based on the static data stock selection request, and the calculation data stock result set is obtained from the calculation data storage area based on the calculation data stock selection request.
Specifically, in this embodiment, the static data storage area stores a static data stock result set, and the calculation data storage area includes a first-level data buffer area for buffering the current day calculation data stock result set and a second-level data buffer area for buffering the multiple days calculation data stock result set.
In this embodiment, the primary data buffer is a memory, and the secondary data buffer is a Redis database.
That is, in this embodiment, the calculation data is hierarchically stored: and storing the current day calculation data stock result set in a memory, and storing the multiple day calculation data stock result set in a Redis database so as to be scheduled by different stock selection subjects, thereby improving the scheduling speed.
Fig. 2 is a schematic diagram showing the data acquisition based on the user stock selection request in the stock selection control method based on the data classification processing in the present embodiment. In this embodiment, as shown in fig. 2, when the stock selection request is a user stock selection request, in acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, the calculation data stock result set is acquired from the primary data cache area (memory), when there is no calculation data stock result set in the primary data cache area (memory), the calculation data stock result set is acquired from the secondary data cache area (dis database), and when there is no calculation data stock result set in the secondary data cache area, the calculation data stock result set is acquired from a data calculation server that generates a calculation data stock result set. That is, when the stock selection request is a user stock selection request, only the data of the current day is accessed, and the access speed thereof is further improved using the first-level cache.
Fig. 3 is a schematic diagram showing the acquisition of data based on the back measurement stock selection request in the stock selection control method based on the data classification processing in the present embodiment. As shown in fig. 3, in this embodiment, when the stock selection request is a return stock selection request, the return stock selection request is first split into a plurality of stock selection requests of a single day by day. And then for each single-day stock selection request, acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, acquiring the calculation data stock result set from a secondary data cache area (Redis database) for caching the calculation data stock result set of the current day, and acquiring the calculation data stock result set from a data calculation server for generating the calculation data stock result set when the calculation data stock result set does not exist in the secondary data cache area (Redis database). That is, when the stock selection request is a return stock selection request, the number of users in the primary data buffer (memory) is not accessed, but the data in the secondary data buffer (Redis database) is directly accessed so as not to affect the access speed of the user stock selection request.
And step S400, combining the static data stock result set and the calculation data stock result set to form an output stock result set, and returning the output stock result set to the request terminal for sending the stock selection request.
In this embodiment, static data stock result sets are obtained from the static data storage area, a calculation data stock result set is obtained from the calculation data storage area, then the static data stock result set and the calculation data stock result set are combined to form an output stock result set, the output stock result set is returned to a request terminal for sending the stock selection request, and the request terminal is a user terminal or a return testing platform.
Fig. 4 is a schematic flow chart of outputting a stock result set based on a user stock selection request in the stock selection control method based on data classification processing in the present embodiment.
As shown in fig. 4, a user initiates a stock selection request, and the load balancer searches for an available data processing server, where the load balancer may search for an available data processing server in a random selection manner or a polling selection manner, and split the stock selection request by the data processing server, i.e., split the stock selection request into a static data stock selection request and a calculation data stock selection request. And acquiring a static data stock result set from a static data storage area based on the static data stock selection request, and acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, wherein the calculation data stock result set is acquired from the primary data cache area (memory) when the calculation data stock result set is not present in the primary data cache area (memory), the calculation data stock result set is acquired from the secondary data cache area (dis database), and the calculation data stock result set is acquired from a data calculation server that generates the calculation data stock result set when the calculation data stock result set is not present in the secondary data cache area. That is, when the stock selection request is a user stock selection request, only the data of the current day is accessed, and the access speed thereof is further improved using the first-level cache. And then combining the static data stock result set and the calculated data stock result set to form an output stock result set, and returning the output stock result set to the user terminal for sending the stock selection request.
Fig. 5 is a schematic flow chart of outputting a stock result set based on a back-measured stock selection request in the stock selection control method based on data classification processing in the present embodiment.
As shown in fig. 5, the return platform initiates a stock selection request, the load balancer searches for an available data processing server, where the load balancer may search for an available data processing server in a random selection manner or a round robin selection manner, and when the stock selection request is a return stock selection request from the return platform, the data processing server splits the return stock selection request into a plurality of single-day stock selection requests by day, then obtains a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request for each single-day, obtains a calculation data stock result set from a secondary data cache area (rediss database) that caches the calculation data stock result set by day, and obtains the calculation data stock result set from a data calculation server that generates the calculation data stock result set when the calculation data stock result set does not exist in the secondary data cache area (rediss database). That is, when the stock selection request is a return stock selection request, the number of users in the primary data buffer (memory) is not accessed, but the data in the secondary data buffer (Redis database) is directly accessed so as not to affect the access speed of the user stock selection request. And then combining the static data stock result set and the calculated data stock result set to form an output stock result set, and returning the output stock result set to a return testing platform for sending the stock selection request.
Example 2
As shown in fig. 6, the present embodiment provides a stock selection control device 100 based on data classification processing, the stock selection control device 100 based on data classification processing includes: a request acquisition module 110, a request splitting processing module 120, a static data acquisition module 130, a calculation data acquisition module 140, and a data set processing output module 150.
In this embodiment, the request acquisition module 110 is configured to acquire a stock selection request.
In this embodiment, the request splitting processing module 120 is configured to extract a plurality of policy factors from the stock selection request, and split the stock selection request into a static data stock selection request and a calculated data stock selection request based on a policy requirement of each policy factor.
In this embodiment, the static data obtaining module 130 is configured to obtain a static data stock result set from a static data storage area based on the static data stock selection request.
In this embodiment, the computing data obtaining module 140 is configured to obtain a computing data stock result set from a computing data storage area based on the computing data stock selection request.
In this embodiment, the data set processing output module 150 is configured to combine the static data stock result set and the calculated data stock result set to form an output stock result set, and return the output stock result set to the request terminal that sends the stock selection request.
In this embodiment, the calculation data storage area includes a first-level data buffer area for buffering the current day calculation data stock result set and a second-level data buffer area for buffering the multiple days calculation data stock result set.
In this embodiment, the stock selection request is a user stock selection request; acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, and acquiring the calculation data stock result set from the primary data cache area; or the stock selection request is a back measurement stock selection request, when the stock selection request is a back measurement stock selection request, the back measurement stock selection request is split into a plurality of single-day stock selection requests according to the day, when the stock selection request is a back measurement stock selection request, the calculation data stock result set is obtained from the calculation data storage area based on the calculation data stock result set, and the calculation data stock result set is obtained from the secondary data cache area for caching the current day calculation data stock result set.
In this embodiment, when there is no calculated data stock result set in the primary data buffer, the calculated data stock result set is obtained from the secondary data buffer; and when the calculated data stock result set does not exist in the secondary data cache area, acquiring the calculated data stock result set from a data calculation server generating the calculated data stock result set.
The technical features of the specific implementation of the stock selection control device 100 based on the data classification processing in this embodiment are substantially the same as those of the specific implementation of the stock selection control method based on the data classification processing in the foregoing embodiment, and general technical content between embodiments may not be repeated.
Example 3
As shown in fig. 7, the present embodiment provides a stock selection control system based on data classification processing, which includes at least one data processing server 3, at least one static data server 4, and at least one data calculation server 5; a static data storage area storing a static data stock result set is distributed to the at least one static data server 4, and a calculation data storage area storing a calculation data stock result set is distributed to the at least one data processing server 3 and the at least one data calculation server 5; the data calculation server 5 generates the set of calculation data stock results.
The static data storage area stores a static data stock result set, and the calculation data storage area comprises a first-level data buffer area for buffering the current day calculation data stock result set and a second-level data buffer area for buffering the multiple days calculation data stock result set.
In this embodiment, the primary data buffer is a memory, and the secondary data buffer is a dis cluster 6.
In this embodiment, the static data storage area is distributed among a plurality of static data servers 4 (datasvr) that extend longitudinally; the calculated data storage areas are distributed over a plurality of data processing servers 3 (centrersvr) extending laterally and a plurality of data calculation servers 5 (calcsvr) extending laterally.
In this embodiment, the data processing server 3 (centrersvr) sends a stock selection request to different servers (the static data server 4 and the calcsvr) according to different policy factor requirements of a stock selection request, where the stock selection request may be a user stock selection request from the user terminal 1 or a return stock selection request from the return platform 2.
The data processing server 3 (centrersvr) has no state, the data cache is a first-level cache, reading in advance is not needed, and after the user accesses, all result sets of the same day are reserved in the service memory, because stock selection data for the user are all the same day, and the access performance of stock selection of the user is improved.
The data processing server 3 (centrersvr) can be extended in parallel, so that concurrency is improved, and service availability is increased.
In this embodiment, the static data server 4 (datasvr) caches static data, which is convenient for fast polling. When the total data amount is increased to the single static data server 4 (datasvr) and the memory is hard to load, longitudinal segmentation is adopted, and the data is segmented into different services according to different types of the data, and then the static data server 4 (datasvr) is derivatized into financial services, financial report services and the like. When the user volume is increased to be intolerable to a single machine of the static data server 4 (datasvr), lateral expansion is performed, and service concurrency and usability are improved.
In this embodiment, the static data server 4 (datasvr) preferably adopts a vertical expansion and then a horizontal expansion. Because there is a class of demand when selecting factors, such as requesting 5-20% of the market value stocks, it becomes very difficult to calculate the request if the market value factors are cut across multiple different static data servers 4 (datasvr), the basic guideline of the design is to keep a single static factor from being distributed among the different static data servers 4 (datasvr) as much as possible.
In this embodiment, the data computing server 5 (calcsvr) calculates corresponding derivative data according to different algorithm indexes through the basic K-line data, that is, generates a computing data stock result set according to the stored computing data,
the data computation server 5 (calcsvr) has no state, but needs to cache the underlying K-line data at start-up to operate on other derived data. For example, data above the K level on day 2 is relatively small in volume, fast in reading speed, large in K data per minute when the service is started, and relatively small in usage, and is loaded when requested by the user and then cached in the memory so as not to affect the service restart time.
The data computing server 5 (calcsvr) can be extended in parallel, so that concurrency is improved, and service availability is increased.
The data processing server 3 runs the stock selection control method based on the data sorting process as described in embodiment 1.
The stock selection control method based on the data classification process is described in detail in embodiment 1, and is not described herein.
In summary, the stock selection data is divided into the static data stock result set and the calculation data stock result set for classified storage and scheduling, and the calculation data stock result set is divided into the primary storage and the secondary storage, so that the processing speed and the processing precision of the stock selection request are effectively improved, and objective and high-accuracy stocks can be recommended for users. Therefore, the stock selection control method, the stock selection control device and the stock selection control system based on the data classification processing have higher innovation compared with the prior art.
The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. Accordingly, it is intended that all equivalent modifications and variations of the application be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (5)
1. A stock selection control method based on data classification processing is characterized in that: comprising the following steps:
acquiring a stock selection request;
extracting various policy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the policy requirements of the policy factors;
acquiring a static data stock result set from a static data storage area based on the static data stock selection request, and acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request; the static data comprises stock basic information, financial information and financial report information; the calculation data is data of different calculation data result sets according to different external input parameters by a specific algorithm; the computing data storage area comprises a first-level data cache area for caching the current day computing data stock result set and a second-level data cache area for caching the multiple days computing data stock result set;
when the stock selection request is a user stock selection request, acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, and acquiring the calculation data stock result set from the first-level data cache area; when the calculated data stock result set does not exist in the primary data cache region, acquiring the calculated data stock result set from the secondary data cache region;
when the stock selection request is a back measurement stock selection request, acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, and acquiring a calculation data stock result set from a secondary data cache area for caching the calculation data stock result set for a plurality of days; when the calculated data stock result set does not exist in the secondary data cache area, acquiring the calculated data stock result set from a data calculation server generating the calculated data stock result set;
and combining the static data stock result set and the calculation data stock result set to form an output stock result set, and returning the output stock result set to a request terminal for sending the stock selection request.
2. The stock selection control method based on data classification processing according to claim 1, characterized in that: the strand selection request is a return measurement strand selection request; when the stock selection request is a return measurement stock selection request, splitting the return measurement stock selection request into a plurality of single-day stock selection requests according to the day.
3. The stock selection control method based on data classification processing according to claim 1, characterized in that: the static data storage areas are distributed on a plurality of static data servers which are longitudinally expanded; the computing data store is distributed across a plurality of data processing servers that are laterally expanded and a plurality of data computing servers that are laterally expanded.
4. A strand selection control device based on data classification processing is characterized in that: comprising the following steps:
the request acquisition module is used for acquiring a stock selection request;
the request splitting processing module is used for extracting various strategy factors from the stock selection request, and splitting the stock selection request into a static data stock selection request and a calculation data stock selection request based on the strategy requirement of each strategy factor;
the static data acquisition module is used for acquiring a static data stock result set from the static data storage area based on the static data stock selection request;
the calculation data acquisition module is used for acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request;
the static data comprises stock basic information, financial information and financial report information; the calculation data is data of different calculation data result sets according to different external input parameters by a specific algorithm; the computing data storage area comprises a first-level data cache area for caching the current day computing data stock result set and a second-level data cache area for caching the multiple days computing data stock result set;
when the stock selection request is a user stock selection request, acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, and acquiring the calculation data stock result set from the first-level data cache area; when the calculated data stock result set does not exist in the primary data cache region, acquiring the calculated data stock result set from the secondary data cache region;
when the stock selection request is a back measurement stock selection request, acquiring a calculation data stock result set from a calculation data storage area based on the calculation data stock selection request, and acquiring a calculation data stock result set from a secondary data cache area for caching the calculation data stock result set for a plurality of days; when the calculated data stock result set does not exist in the secondary data cache area, acquiring the calculated data stock result set from a data calculation server generating the calculated data stock result set;
and the data set processing output module is used for carrying out combination processing on the static data stock result set and the calculation data stock result set to form an output stock result set, and returning the output stock result set to the request terminal for sending the stock selection request.
5. A strand selection control system based on data classification processing is characterized in that: comprises at least one data processing server, at least one static data server and at least one data computing server;
a static data storage area for storing a static data stock result set is distributed to the at least one static data server, and a calculation data storage area for storing a calculation data stock result set is distributed to the at least one data processing server and the at least one data calculation server; the data computing server generates the computing data stock result set;
the data processing server runs the stock selection control method based on the data sorting process as claimed in any one of claims 1 to 3.
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| CN110704738A (en) * | 2019-09-29 | 2020-01-17 | 平安直通咨询有限公司上海分公司 | Service information pushing method and device based on judge portrait, terminal and storage medium |
| CN110782345A (en) * | 2019-09-27 | 2020-02-11 | 合肥黎曼信息科技有限公司 | Intelligent stock selection method based on market transaction big data |
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| CN110782345A (en) * | 2019-09-27 | 2020-02-11 | 合肥黎曼信息科技有限公司 | Intelligent stock selection method based on market transaction big data |
| CN110704738A (en) * | 2019-09-29 | 2020-01-17 | 平安直通咨询有限公司上海分公司 | Service information pushing method and device based on judge portrait, terminal and storage medium |
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