CN112286957A - API application method and system of BI system based on structured query language - Google Patents
API application method and system of BI system based on structured query language Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2433—Query languages
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
Abstract
The invention provides an API application method of a BI system based on a structured query language, which comprises the following steps: constructing a structured query language for customized data requirements, and constructing HTTP request parameters according to a standard structure; performing authority verification according to the HTTP request parameters; acquiring the content of a structured query language and converting the content into a plurality of executable SQL sentences; sending a plurality of executable SQL statements to a query engine to execute tasks; uniformly combining a plurality of tasks to form a result list; and carrying out data preprocessing on the result list to form a standard output result and returning the standard output result. API system of BI system based on structured query language. The invention can realize the rules of zero development, flexible algorithm adjustment and object-oriented based on structured query and customized requirements.
Description
Technical Field
The invention relates to the technical field of BI systems, in particular to an API application method and system of a BI system based on a structured query language.
Background
A BI (Business Intelligence) system, also called Business Intelligence or Business Intelligence, is a system integration that integrates data collection, data cleaning, data conversion, real-time calculation, data storage, data mining, and data visualization, and is an important component of big data and artificial Intelligence, so that massive data can generate Business value to help professionals make decisions and improve data analysis efficiency and quality. BI visualization (front end): generally, the method is realized by adopting a single technology, is independent of back-end application, is completely decoupled from a server, and currently, popular front-end technologies include vue. An API (Application Program Interface) is an Interface for data interaction between a client (including a PC and a mobile terminal) and a server, is deployed at the server, generally performs two-terminal communication based on an HTTP protocol, and supports a POST/GET request mode. BI System visualization integration: and calling the API through the HTTP request by using the visual page developed by the front-end technology, and finally displaying the result returned by the API on the webpage.
The existing BI systems have the following problems:
1) the development workload is large, the reuse rate is low: the entire BI system may require the development of hundreds or thousands of APIs, requiring a significant amount of labor and time to develop, and the APIs used between different pages may not be reusable.
2) The maintenance cost is high: maintenance needs to be performed for each API, the implementation logic of each API is different, and service understanding needs to be performed for a single API. If the function is adjusted, the specific service implementation needs to be modified, and there is a huge risk in the modification process, and the more the adjustment, the higher the cost.
3) Do not support customized reporting or support not friendly enough: each analyst has different requirements for data presentation, and the BI system is required to customize the analysis template, because the API has predefined functions, the customization requirements are difficult to meet.
4) Data inconsistency problem: different pages may have the same data, and the same data comes from different APIs, and the same data may appear, which may cause different data due to problems of logic processing, different understanding of different developers, development deviation, and the like, thereby affecting data analysis and decision making.
5) The data definition cannot be dynamically modified: each item of data on the page has standard definition description, if the definition is to be modified, the corresponding page is required to be modified, if a plurality of copies exist, the plurality of copies are required to be modified synchronously, and the dynamic modification of the data definition description is difficult to realize on the premise of not releasing a new version.
6) Version iteration cost is high: with more and more services and more APIs, only newly added APIs can be continuously added when new data analysis functions are developed, so that the whole project is too bloated, and the later version iteration progress and efficiency are greatly reduced.
7) The API-oriented objects are services: APIs are developed based on specific services and are highly coupled to the services.
By combining the above problems, it can be known that the main problem of the API in the existing BI system is to enter a parameter list. An exit is also a fixed return field; the coupling degree is high, the business logic is solidified in the code, and the logic cannot be dynamically adjusted; the service is single, one service corresponds to one interface, and the code reuse rate is low.
Disclosure of Invention
In order to overcome the problems in the prior art, the present invention provides an API application method and system for a BI system based on a structured query language.
The technical scheme of the invention is as follows:
the API application method of the BI system based on the structured query language comprises the following steps:
constructing a structured query language for customized data requirements, and constructing HTTP request parameters according to a standard structure;
performing authority verification according to the HTTP request parameters;
acquiring the content of a structured query language and converting the content into a plurality of executable SQL sentences;
sending a plurality of executable SQL statements to a query engine to execute tasks;
uniformly combining a plurality of tasks to form a result list;
and carrying out data preprocessing on the result list to form a standard output result and returning the standard output result.
Further, the authority verification is carried out according to the HTTP request parameters; the method specifically comprises the following steps: performing authority verification according to the header and body contents of the HTTP; the authority verification comprises login verification, project authority, channel authority and data authority.
Further, the content of the structured query language is obtained and converted into a plurality of executable SQL statements; the method specifically comprises the following steps: the method comprises the steps of obtaining the content of a structured query language, analyzing the content into various sub-elements, disassembling the sub-elements corresponding to metadata information, obtaining metadata configuration information from a metadata table, and finally converting the metadata configuration information into a plurality of executable SQL statements through an SQL engine.
Further, the plurality of executable SQL statements are sent to a query engine to execute the task; and allocating a thread for each executable SQL statement task, and executing a plurality of threads simultaneously under the same management of the thread pool.
Further, carrying out data preprocessing on the result list to form a standard output result and returning the standard output result; the method specifically comprises the following steps: and carrying out data definition description dynamic playback and formula calculation on the data in the result list.
An API application system for a BI system based on a structured query language, comprising:
the demand construction service unit is used for constructing a structured query language for customized data demands and constructing HTTP request parameters according to a standard structure;
the authority service unit is used for carrying out authority verification according to the HTTP request parameters;
the translation service unit is used for acquiring the content of the structured query language and converting the content into a plurality of executable SQL sentences;
the engine service unit sends a plurality of executable SQL sentences to the query engine to execute tasks;
the parallel processing unit is used for uniformly combining a plurality of tasks to form a result list;
and the preprocessing unit is used for preprocessing the data of the result list to form a standard output result and returning the standard output result.
Further, the translation service unit includes:
the query engine is used for complex query of mass data;
the data memory is used for distributed storage, column type storage, data compression, single data reading and writing and modification;
and real-time warehousing is used for real-time batch processing and interactive query.
Further, the parallel processing unit includes:
the resource manager is used for managing resource distribution and scheduling of the real-time warehousing task;
and the real-time data collector collects the application server logs to a specified target source in real time.
Further, the parallel processing unit further comprises a log subscription service system, which is used for temporarily storing the logs collected from the real-time data collector and the distributed publishing subscription messages.
Further, the preprocessing unit comprises a client of the SQL statement, and is used for intuitively querying and displaying data.
The invention has the beneficial effects that:
the method is developed based on a structured query language (JSON), the JSON is analyzed, the optimal metadata is matched, executable SQL sentences are generated, multithreading is executed in parallel, results are combined, and expected results are returned finally. The method can realize rules based on structured query, customized requirements, zero development, flexible adjustment of algorithm and object-oriented.
Drawings
FIG. 1 is a flow chart of an API application method of a BI system based on a structured query language proposed by the present invention;
FIG. 2 is a flow chart of an embodiment of the present invention;
FIG. 3 is a diagram of an embodiment for converting structured query language to SQL:
FIG. 4 is a diagram of one embodiment of the structured query language + metadata resulting in an SQL statement;
FIG. 5 is a diagram of an API application system of the BI system based on a structured query language according to the present invention.
Detailed Description
The conception, the specific structure, and the technical effects produced by the present invention will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the features, and the effects of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and those skilled in the art can obtain other embodiments without inventive effort based on the embodiments of the present invention, and all embodiments are within the protection scope of the present invention.
Referring to fig. 1, it is a flowchart of an API application method of a BI system based on a structured query language proposed in the present invention;
as shown in FIG. 1, the API application method of the BI system based on the structured query language comprises the following steps:
102, performing authority verification according to the HTTP request parameters;
103, acquiring the content of the structured query language and converting the content into a plurality of executable SQL statements;
104, sending a plurality of executable SQL statements to a query engine to execute tasks;
and step 106, carrying out data preprocessing on the result list to form a standard output result and returning the standard output result.
In step 102, performing authority verification according to the HTTP request parameters; the method specifically comprises the following steps: performing authority verification according to the header and body contents of the HTTP; the authority verification comprises login verification, project authority, channel authority and data authority.
In step 103, obtaining the content of the structured query language and converting the content into a plurality of executable SQL statements; the method specifically comprises the following steps: the method comprises the steps of obtaining the content of a structured query language, analyzing the content into various sub-elements, disassembling the sub-elements corresponding to metadata information, obtaining metadata configuration information from a metadata table, and finally converting the metadata configuration information into a plurality of executable SQL statements through an SQL engine.
In step 104, sending the plurality of executable SQL statements to a query engine to execute the task; and allocating a thread for each executable SQL statement task, and executing a plurality of threads simultaneously under the same management of the thread pool.
In step 106, data preprocessing is carried out on the result list to form a standard output result and the standard output result is returned; the method specifically comprises the following steps: and carrying out data definition description dynamic playback and formula calculation on the data in the result list.
In the embodiment of the present invention, referring to fig. 2, the specific process is as follows: according to the requirement of customized data, a structured query language is constructed, and HTTP request parameters are constructed according to a standard structure; performing authority verification according to the header and body contents of the HTTP; acquiring the content of a structured query language, analyzing the content into various sub-elements, disassembling the sub-elements into information corresponding to metadata, acquiring metadata configuration information from a metadata table, and finally converting the metadata configuration information into a plurality of executable SQL statements through an SQL engine; the generated multiple executable SQL are given to a query engine to be executed, each task is allocated with a thread, the thread pool is used for managing uniformly, multiple threads can be executed simultaneously, and query efficiency is improved; the results obtained by each task (thread) are uniformly combined to form a result list, so that the visualization front-end display is facilitated; some data preprocessing is performed on the result list, including: and (4) dynamically displaying back the data definition description, calculating a formula and the like, and finally returning a ready-made standard output result.
FIG. 3 is an example of structured query language translation to SQL: each field in the JSON corresponds to a clause of the SQL statement one by one; fields corresponds to a select statement; conditions correspond to where statements; aggregations corresponds to a group by statement.
FIG. 4 is an example of the structured query language + metadata resulting in an SQL statement: each field of json can find a corresponding relationship in the metadata; the configuration inside the metadata corresponds to the elements of the SQL clause.
Referring to fig. 5, a structural diagram of an API application system of a BI system based on a structured query language is provided in the present invention;
as shown in FIG. 5, the API application of the BI system based on the structured query language includes:
the requirement construction service unit 201 is used for constructing a structured query language for customized data requirements and constructing HTTP request parameters according to a standard structure;
the authority service unit 202 performs authority verification according to the HTTP request parameter;
the translation service unit 203 is used for acquiring the content of the structured query language and converting the content into a plurality of executable SQL sentences;
the engine service unit 204 is used for sending a plurality of executable SQL statements to the query engine to execute tasks;
the parallel processing unit 205 is used for uniformly combining a plurality of tasks to form a result list;
and the preprocessing unit 206 is used for preprocessing the data of the result list to form a standard output result and returning the standard output result.
The translation service unit 203 includes:
the query engine is used for complex query of mass data;
the data memory is used for distributed storage, column type storage, data compression, single data reading and writing and modification;
and real-time warehousing is used for real-time batch processing and interactive query.
In the embodiment of the invention, the query engine adopts an Impala memory-based query engine, is similar to SQL and HiveSQL, supports JDBC/ODBC, and is suitable for complex query of mass data. By adopting a kudu data warehouse, a distributed column type storage database can be realized, is similar to Hbase and is used for large-scale reading, writing and modifying of distributed type, column type storage, data compression, single data and the like; and (3) performing real-time Streaming (batch) warehousing by using Spark, performing large-scale data processing including Spark Core, Spark SQL and Spark Streaming, performing real-time dimensional batch processing and performing large-scale interactive query.
The parallel processing unit 205 includes:
the resource manager is used for managing resource distribution and scheduling of the real-time warehousing task;
and the real-time data collector collects the application server logs to a specified target source in real time.
In the embodiment of the present invention, the resource manager yarn manages the resource allocation and scheduling of tasks (such as memory, CPU, etc.), including resource monitoring, allocation, management, etc., of spark, etc., and implements resource management and scheduling of multiple components (cluster service); and the real-time data collector collects application server logs to a specified target source in real time by adopting fluent and Logstash.
The parallel processing unit 205 further includes a log subscription service system, configured to temporarily store logs collected from the real-time data collector and distributed publishing subscription messages; the log subscription service system adopts kafka, can realize high throughput, low delay, persistence and reliability, and is suitable for log unified collection and log containers.
The preprocessing unit 206 includes a client of the SQL statement, and in the embodiment of the present invention, the client of the SQL statement operates the client by using the Hue's visual web database, so as to facilitate intuitive query of data, and achieve database access visualization operation similar to navicat and SQL log.
The invention also supports dual time zones; support for the eighty-east zone + the master time zone; the same data multi-algorithm is supported: the matched algorithm self-defined conditions can be intelligently screened out according to different dimensions for query: the condition can be packaged into a json substring and brought into the SQL engine; the output data defines: and simultaneously returning the data, the data definition can be returned to support synchronous updating.
The API use standard is constructed by standardizing input parameters and output results, the problem of data consistency is solved through the standard, API implementation logic is unified, development workload is reduced, API service-oriented service is changed into technology-oriented implementation, API exists without service, maintenance cost is greatly reduced, and requirements for service understanding of developers are lowered. The API also becomes an open product, can be used for customized development of clients, only needs to follow development standards and specifications, and does not need to be docked by API developers.
The invention reduces the development workload and the maintenance cost: because the structured query language-based API only has one API, the development workload and the maintenance cost are greatly reduced, only the API needs to be continuously optimized, and zero development can be realized after the API is stabilized. The problem of data consistency is solved: and a uniform and unique API is provided for the client, so that data deviation between different APIs with the same data is avoided. Version iteration efficiency is high: the whole BI visualization page only needs to perform version iteration on the only API, so that the iteration workload is greatly reduced, and the risk is also greatly reduced. Support individualized and customized report forms: the API can realize personalized display effect, meet different analysis requirements, and can customize dozens or hundreds of (theory has no upper limit) customized template requirements. And (3) standardization: the standardized parameter input is constructed based on the structured language, the output result is also a standardized structure, and the data definition description is dynamically displayed back to the result, so that the problem of dynamic modification of the data definition is solved.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention has been described in detail, but the present invention is not limited to the above embodiments, and various changes can be made without departing from the gist of the present invention within the knowledge of those skilled in the art. Many other changes and modifications can be made without departing from the spirit and scope of the invention. It is to be understood that the invention is not to be limited to the specific embodiments, but only by the scope of the appended claims.
Claims (10)
1. The API application method of the BI system based on the structured query language is characterized by comprising the following steps:
constructing a structured query language for customized data requirements, and constructing HTTP request parameters according to a standard structure;
performing authority verification according to the HTTP request parameters;
acquiring the content of a structured query language and converting the content into a plurality of executable SQL sentences;
sending a plurality of executable SQL statements to a query engine to execute tasks;
uniformly combining a plurality of tasks to form a result list;
and carrying out data preprocessing on the result list to form a standard output result and returning the standard output result.
2. The method of claim 1, wherein the authorization verification is performed according to HTTP request parameters; the method specifically comprises the following steps: performing authority verification according to the header and body contents of the HTTP; the authority verification comprises login verification, project authority, channel authority and data authority.
3. The method of claim 1, wherein the structured query language content is obtained and converted into a plurality of executable SQL statements; the method specifically comprises the following steps: the method comprises the steps of obtaining the content of a structured query language, analyzing the content into various sub-elements, disassembling the sub-elements corresponding to metadata information, obtaining metadata configuration information from a metadata table, and finally converting the metadata configuration information into a plurality of executable SQL statements through an SQL engine.
4. The method of claim 1, wherein sending the plurality of executable SQL statements to a query engine performs the task; and allocating a thread for each executable SQL statement task, and executing a plurality of threads simultaneously under the same management of the thread pool.
5. The method according to claim 1, characterized in that the result list is subjected to data preprocessing to form a standard output result and returned; the method specifically comprises the following steps: and carrying out data definition description dynamic playback and formula calculation on the data in the result list.
6. The method of claims 1-5, presenting an API system of a BI system based on a structured query language, comprising:
the demand construction service unit is used for constructing a structured query language for customized data demands and constructing HTTP request parameters according to a standard structure;
the authority service unit is used for carrying out authority verification according to the HTTP request parameters;
the translation service unit is used for acquiring the content of the structured query language and converting the content into a plurality of executable SQL sentences;
the engine service unit sends a plurality of executable SQL sentences to the query engine to execute tasks;
the parallel processing unit is used for uniformly combining a plurality of tasks to form a result list;
and the preprocessing unit is used for preprocessing the data of the result list to form a standard output result and returning the standard output result.
7. The system of claim 6, wherein the translation service comprises:
the query engine is used for complex query of mass data;
the data memory is used for distributed storage, column type storage, data compression, single data reading and writing and modification;
and real-time warehousing is used for real-time batch processing and interactive query.
8. The system of claim 6, wherein the parallel processing unit comprises:
the resource manager is used for managing resource distribution and scheduling of the real-time warehousing task;
and the real-time data collector collects the application server logs to a specified target source in real time.
9. The system of claim 8, wherein the parallel processing unit further comprises a log subscription service system for temporarily storing the log collected from the real-time data collector and the distributed publish-subscribe message.
10. The system of claim 6, wherein the preprocessing unit comprises a client of SQL statements for visually querying display data.
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