CN112256516A - Data analysis processing method for hotel direct connection system - Google Patents
Data analysis processing method for hotel direct connection system Download PDFInfo
- Publication number
- CN112256516A CN112256516A CN201910659172.2A CN201910659172A CN112256516A CN 112256516 A CN112256516 A CN 112256516A CN 201910659172 A CN201910659172 A CN 201910659172A CN 112256516 A CN112256516 A CN 112256516A
- Authority
- CN
- China
- Prior art keywords
- data
- abnormal
- early warning
- hotel
- monitoring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
Abstract
The invention discloses a data analysis processing method for a hotel direct connection system, which belongs to the technical field of data analysis processing and comprises the following steps: s1: the system processing the data monitors for supplier system interface anomalies; s2: distributing the abnormal information to message queues with different abnormal levels for temporary storage; s3: reading temporary abnormal data in the message queue and a set early warning strategy, and judging whether the conditions of the early warning strategy are met; s4: processing the meeting conditions correspondingly; s5: processing the condition which does not meet the monitoring and early warning strategy; s6: and scanning the data monitoring table. The invention aims to establish a set of standard internal interface error model to be compatible and matched with different data types of external system interfaces, and analyze and monitor interface data through a self-defined early warning rule, thereby improving the system stability and improving the risk control capability.
Description
Technical Field
The invention relates to the technical field of data analysis and processing, in particular to a data analysis and processing method for a hotel direct connection system.
Background
With the rapid development of the travel industry, the hotel industry is rapidly expanded, each hotel group carries respective system management, under the promotion of the internet, more and more franchised chain hotels and third party sales integration channels appear, so that the timeliness and the correctness of hotel data are ensured, the hotel data are frequently encountered by all chain hotel systems and third party sales systems, and if the interface returns abnormal data or cannot normally leave an order due to the abnormal connected hotel systems, the fact that the hotel direct connection system can normally synchronize and process the interface data of each hotel resource source end becomes a factor for measuring the stability of the whole system, and therefore, the strict monitoring and processing of each different direct connection hotel system interface is an indispensable barrier for ensuring the hotel system.
However, the existing interface data analysis and processing method for the hotel system is difficult to classify and record a large amount of data of the interface and perform rapid processing and analysis, and can not integrate the error types corresponding to each hotel system into a uniform error model, thereby rapidly monitoring and processing the error models.
Therefore, a data analysis processing method for the hotel direct connection system is provided.
Disclosure of Invention
1. Technical problem to be solved
Aiming at the problems in the prior art, the invention aims to establish a set of standard internal interface error model to be compatible and matched with the data types of different external system interfaces, and analyze and monitor the interface data through a self-defined early warning rule, thereby improving the system stability and improving the risk control capability.
2. Technical scheme
In order to solve the above problems, the present invention adopts the following technical solutions.
A data analysis processing method for a hotel direct connection system comprises the following steps:
s1: the processing data system monitors the supplier system interface abnormality;
s2: according to the error model of the data processing system, distributing the abnormal information of the supplier system to message queues with different abnormal levels for temporary storage;
s3: then, reading temporary abnormal data in the message queue at regular time through the JOB, reading a set early warning strategy, and comparing whether the abnormal data meets the condition of the early warning strategy or not;
s4: if the abnormal data meets the condition of the early warning strategy, the data is distributed to a new message queue, and then the data is read through the JOB timing task to immediately perform early warning;
s5: if the abnormal data does not meet the condition of the monitoring and early warning strategy, storing the data into a data monitoring table in a database, continuing to monitor, then regularly reading the data from the data monitoring table by JOB, comparing the monitoring strategy setting, if the data is abnormal, distributing the data into a message queue temporarily storing the abnormal data, reading the stored interface error, and recording the data in the message queue, if the data meets the early warning strategy, distributing the abnormal data into a message queue service to be early warned, and storing the abnormal data into the database and marking the abnormal data as processed; if the monitored data is normal, deleting the monitored data from the monitoring table, not monitoring any more, circulating the process, and if the abnormal data meets the monitoring early warning strategy condition, redistributing the data to a stored message queue recorded by interface errors;
s6: and scanning the data monitoring table, if the data reaches the abnormal condition set by the monitoring strategy, distributing the data to the message queue for temporary storage, namely returning to S2, and then circulating according to the steps.
Further, the supplier system in S1 is configured to provide data to the process data system.
Further, the message queue in S2 is used for temporarily storing the data.
Further, the warning policy in S3 is the number of times of abnormality per unit time.
Further, the number of times of abnormality setting differs for different levels.
Further, in S3, the JOB timing is to read the data in the message queue to the database by the timing task.
Further, the database in S5 is used for storing data.
Further, the method of scanning the data monitoring table in S6 adopts a JOB timing scan by monitoring.
3. Advantageous effects
Compared with the prior art, the invention has the advantages that:
the method establishes a set of standard internal interface error models to be compatible and matched with different data types of external system interfaces, monitors the interfaces through the configured error models, quickly positions and early warns the interfaces with abnormal interfaces, and analyzes and monitors the interface data through self-defined early warning rules, thereby improving the system stability and improving the risk control capability.
Drawings
FIG. 1 is a block diagram of the overall structure of the present invention;
FIG. 2 is a flow chart of the system monitoring arrangement of the present invention;
FIG. 3 is a flow chart of abnormal data monitoring according to the present invention;
FIG. 4 is a flow chart of the anomaly data analysis of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments 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 all other embodiments obtained by those skilled in the art without any inventive work are within the scope of the present invention.
Example 1:
referring to fig. 1 to 4, as shown in fig. 1, a data analysis processing method for a hotel direct connection system includes the following steps:
s1: firstly, a processing data system (EB system) monitors abnormity of a provider system (PMS) interface which provides data for the processing data system;
s2: then according to an error model of the processing data system (EB system), distributing exception information of a provider system (PMS) providing data for the processing data system to Message Queues (MQ) with different exception levels for temporary storage, wherein the error type refers to that a plurality of providers use different error codes to represent the same error and the same error code on the processing data system (EB system) is mapped uniformly;
s3: reading temporary abnormal data in a Message Queue (MQ) at regular time through the JOB, reading a set early warning strategy, wherein the early warning strategy is the abnormal times in unit time, the abnormal times of different grades are set differently, and judging whether the conditions of the early warning strategy are met or not by comparing the abnormal data;
s4: if the abnormal data meets the condition of the early warning strategy, the data is distributed to a new Message Queue (MQ), and then the data is read through the JOB to immediately perform early warning;
s5: as shown in fig. 2, fig. 3 and fig. 4, if the abnormal data does not satisfy the condition of monitoring the early warning policy, the data is stored in a data monitoring table in a Database (DB) for storing the data, monitoring is continued, then JOB reads the data from the data monitoring table at regular time, the monitoring policy setting is compared, if the data is abnormal, the data is distributed to a message queue for temporarily storing the abnormal data, the stored interface error is read, and the data in the message queue is recorded, if the data satisfies the early warning policy, the abnormal data is distributed to the message queue service to be early warned, and the abnormal data is stored in the database and marked as processed; if the monitored data is normal, deleting the monitored data from the monitoring table, not monitoring any more, circulating the process, and if the abnormal data meets the monitoring early warning strategy condition, redistributing the data to a stored message queue recorded by interface errors;
s6: and scanning the data monitoring table at regular time through the monitored JOB, if the data reaches the abnormal condition set by the monitoring strategy, distributing the data to a Message Queue (MQ) for temporary storage, namely returning to S2, and then circulating according to the steps.
The technical scheme provides a set of application program programming data analysis method for automatically processing the interface abnormity of an external docking system, the method establishes a set of standard internal interface error models to be compatible and matched with the data types of different external system interfaces, monitors the interfaces through the configured error models, quickly positions and pre-warns the abnormal interfaces, and analyzes and monitors the interface data through the self-defined pre-warning rules, thereby improving the system stability and improving the risk control capability.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A data analysis processing method for a hotel direct connection system is characterized by comprising the following steps:
s1: the processing data system monitors the supplier system interface abnormality;
s2: according to the error model of the data processing system, distributing the abnormal information of the supplier system to message queues with different abnormal levels for temporary storage;
s3: then, reading temporary abnormal data in the message queue at regular time through the JOB, reading a set early warning strategy, and comparing whether the abnormal data meets the condition of the early warning strategy or not;
s4: if the abnormal data meets the condition of the early warning strategy, the data is distributed to a new message queue, and then the data is read through the JOB timing task and early warning is carried out immediately;
s5: if the abnormal data does not meet the condition of the monitoring and early warning strategy, storing the data into a data monitoring table in a database, continuing to monitor, then regularly reading the data from the data monitoring table by JOB, comparing the monitoring strategy setting, if the data is abnormal, distributing the data into a message queue temporarily storing the abnormal data, reading the stored interface error, and recording the data in the message queue, if the data meets the early warning strategy, distributing the abnormal data into a message queue service to be early warned, and storing the abnormal data into the database and marking the abnormal data as processed; if the monitored data is normal, deleting the monitored data from the monitoring table, not monitoring any more, circulating the process, and if the abnormal data meets the monitoring early warning strategy condition, redistributing the data to a stored message queue recorded by interface errors;
s6: and scanning the data monitoring table, if the data reaches the abnormal condition set by the monitoring strategy, distributing the data to the message queue for temporary storage, namely returning to S2, and then circulating according to the steps.
2. The data analysis and processing method for the hotel direct connection system according to claim 1, wherein: the supplier system in S1 is configured to provide data to the process data system.
3. The data analysis and processing method for the hotel direct connection system according to claim 1, wherein: the message queue in S2 is used for temporarily storing data.
4. The data analysis and processing method for the hotel direct connection system according to claim 1, wherein: the early warning strategy in the step S3 is the number of abnormal times per unit time.
5. The data analysis and processing method for the hotel direct connection system according to claim 4, wherein: the number of times of exception setting differs for different levels.
6. The data analysis and processing method for the hotel direct connection system according to claim 1, wherein: in the step S3, the JOB timing is to read the data in the message queue to the database by the timing task.
7. The data analysis and processing method for the hotel direct connection system according to claim 1, wherein: the database in S5 is used for storing data.
8. The data analysis and processing method for the hotel direct connection system according to claim 1, wherein: the method of scanning the data monitoring table in S6 employs a timed scan by a monitoring JOB.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910659172.2A CN112256516A (en) | 2019-07-22 | 2019-07-22 | Data analysis processing method for hotel direct connection system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910659172.2A CN112256516A (en) | 2019-07-22 | 2019-07-22 | Data analysis processing method for hotel direct connection system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112256516A true CN112256516A (en) | 2021-01-22 |
Family
ID=74224695
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910659172.2A Pending CN112256516A (en) | 2019-07-22 | 2019-07-22 | Data analysis processing method for hotel direct connection system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112256516A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103618643A (en) * | 2013-11-26 | 2014-03-05 | 北京京东尚科信息技术有限公司 | Method and device for dynamic alarm type monitoring of message queue |
| CN104572401A (en) * | 2015-02-09 | 2015-04-29 | 浪潮软件股份有限公司 | Alarming method and alarming system |
| CN105825401A (en) * | 2016-03-16 | 2016-08-03 | 广州酷旅旅行社有限公司 | Distributed multichannel group-buying coupon checking system |
| US20170048120A1 (en) * | 2015-08-11 | 2017-02-16 | Txmq, Inc. | Systems and Methods for WebSphere MQ Performance Metrics Analysis |
| CN107992398A (en) * | 2017-12-22 | 2018-05-04 | 宜人恒业科技发展（北京）有限公司 | The monitoring method and monitoring system of a kind of operation system |
| US20180278497A1 (en) * | 2017-03-22 | 2018-09-27 | Quanta Computer Inc. | Systems for monitoring application servers |
-
2019
- 2019-07-22 CN CN201910659172.2A patent/CN112256516A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103618643A (en) * | 2013-11-26 | 2014-03-05 | 北京京东尚科信息技术有限公司 | Method and device for dynamic alarm type monitoring of message queue |
| CN104572401A (en) * | 2015-02-09 | 2015-04-29 | 浪潮软件股份有限公司 | Alarming method and alarming system |
| US20170048120A1 (en) * | 2015-08-11 | 2017-02-16 | Txmq, Inc. | Systems and Methods for WebSphere MQ Performance Metrics Analysis |
| CN105825401A (en) * | 2016-03-16 | 2016-08-03 | 广州酷旅旅行社有限公司 | Distributed multichannel group-buying coupon checking system |
| US20180278497A1 (en) * | 2017-03-22 | 2018-09-27 | Quanta Computer Inc. | Systems for monitoring application servers |
| CN107992398A (en) * | 2017-12-22 | 2018-05-04 | 宜人恒业科技发展（北京）有限公司 | The monitoring method and monitoring system of a kind of operation system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11657309B2 (en) | Behavior analysis and visualization for a computer infrastructure | |
| JP2017076385A (en) | Distributed industrial performance monitoring and analytics platform | |
| JP2017076387A (en) | Source-independent queries in distributed type industrial system | |
| JP2017076386A (en) | Distributed type industrial performance monitoring and analysis | |
| JP2017076384A (en) | Data analytic service for distributed industrial performance monitoring | |
| JP2017079057A (en) | Distributed industrial performance monitoring and analytics | |
| CN112232717A (en) | Quality inspection system using plug-in | |
| CN109960635B (en) | Monitoring and alarming method, system, equipment and storage medium of real-time computing platform | |
| CN103699693A (en) | Metadata-based data quality management method and system | |
| US11556445B2 (en) | Mechanism for monitoring and alerts of computer systems applications | |
| US9621679B2 (en) | Operation task managing apparatus and method | |
| CN114429256A (en) | Data monitoring method and device, electronic equipment and storage medium | |
| WO2024067358A1 (en) | Efficiency analysis method and system for warehouse management system, and computer device | |
| CN110471912B (en) | Employee attribute information verification method and device and terminal equipment | |
| US20180108095A1 (en) | System and method for production well test automation | |
| CN112256516A (en) | Data analysis processing method for hotel direct connection system | |
| CN110910061A (en) | Material management method, material management system, storage medium and electronic equipment | |
| CN109165212A (en) | Big data real-time monitoring and auditing method | |
| CN111061609A (en) | Log monitoring method and system | |
| CN114124743A (en) | Method and system for executing data application full link check rule | |
| CN112286792A (en) | Interface testing method, device, equipment and storage medium | |
| CN113806196B (en) | Root cause analysis method and system | |
| CN111752786A (en) | Data storage method, data summarization method, equipment and medium in pressure test process | |
| CN109656776B (en) | Completeness inspection method and equipment for abnormal monitoring of computer system | |
| CN117474518A (en) | Digitization method and system for preventive maintenance outline |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210122 |