CN113868099A - Data monitoring system - Google Patents

Data monitoring system Download PDF

Info

Publication number
CN113868099A
CN113868099A CN202111220820.8A CN202111220820A CN113868099A CN 113868099 A CN113868099 A CN 113868099A CN 202111220820 A CN202111220820 A CN 202111220820A CN 113868099 A CN113868099 A CN 113868099A
Authority
CN
China
Prior art keywords
module
data
monitoring
monitoring module
warehouse
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
Application number
CN202111220820.8A
Other languages
Chinese (zh)
Inventor
徐育帅
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Suzhou Zhongke Advanced Technology Research Institute Co Ltd
Original Assignee
Suzhou Zhongke Advanced Technology Research Institute Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Suzhou Zhongke Advanced Technology Research Institute Co Ltd filed Critical Suzhou Zhongke Advanced Technology Research Institute Co Ltd
Priority to CN202111220820.8A priority Critical patent/CN113868099A/en
Publication of CN113868099A publication Critical patent/CN113868099A/en
Pending legal-status Critical Current

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
    • G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3055—Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
    • G06F11/324—Display of status information
    • 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
    • G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
    • 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
    • G06F16/26—Visual data mining; Browsing structured data

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Quality & Reliability (AREA)
  • Computing Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Mathematical Physics (AREA)
  • Debugging And Monitoring (AREA)

Abstract

The invention relates to the field of electronic data management, in particular to a data monitoring system, which comprises: the system comprises a Hadoop cluster monitoring module, a warehouse monitoring module, an ETL operation monitoring module and a data visualization module; the Hadoop cluster monitoring module comprises basic information, running conditions, cluster exceptions and node details for monitoring the running of the system; the warehouse monitoring module is used for monitoring the running state or the stock condition of a warehouse; the ETL operation monitoring module is used for monitoring ETL operation information and displaying the ETL operation information through a chart, wherein the ETL operation information is mainly obtained from an interface provided by an ETL tool; the data visualization module is used for displaying the monitoring data of the Hadoop cluster monitoring module, the warehouse monitoring module and the ETL operation monitoring module. According to the method and the system, the user is helped to accurately master various indexes of the data center in real time through monitoring data or information, and timely early warning and processing are carried out on abnormal information.

Description

Data monitoring system
Technical Field
The invention relates to the field of electronic data management, in particular to a data monitoring system.
Background
Big data (big data), or huge data, means that the size of the data is huge enough to achieve the purpose of capturing, managing, processing and organizing more actively helping enterprise business decision within reasonable time through the current mainstream software tools; with the development of science and technology, modern equipment provides great convenience for people's daily life, but higher technical products need support of a large amount of data, so that data collection, processing and management are particularly important, data abnormality may occur in the data management process, a system capable of monitoring a large amount of data is needed, and data abnormality is likely to occur in the monitoring process of the large amount of data.
Therefore, it is necessary to develop a data monitoring system for monitoring data abnormality, and efficient data abnormality monitoring can process abnormal data in time, which greatly reduces the burden of actual work.
Disclosure of Invention
The embodiment of the invention provides a data monitoring system which can timely master various data indexes of the system and timely early warn and process abnormal information.
According to an embodiment of the present invention, there is provided a data monitoring system including: the system comprises a Hadoop cluster monitoring module, a warehouse monitoring module, an ETL operation monitoring module and a data visualization module;
the Hadoop cluster monitoring module comprises basic information, running conditions, cluster exceptions and node details for monitoring the running of the system;
the warehouse monitoring module is used for monitoring the running state or the stock condition of the warehouse;
the ETL operation monitoring module is used for monitoring ETL operation information and displaying the ETL operation information through a chart, wherein the ETL operation information is mainly obtained from an interface provided by an ETL tool;
the data visualization module is used for displaying the monitoring data of the Hadoop cluster monitoring module, the warehouse monitoring module and the ETL operation monitoring module.
Further, the system also comprises an ODS cluster monitoring module, wherein the ODS cluster monitoring module is used for monitoring basic information, abnormal information and database states of the ODS cluster.
Further, the system further comprises:
and the homepage browsing module is used for browsing the Hadoop cluster monitoring module, the warehouse monitoring module, the ETL operation monitoring module and the data visualization module.
Further, the system further comprises:
and the system management module is used for determining the authority management and the user management of the login user.
Further, the system further comprises:
and the first judgment module is used for judging whether the data of the Hadoop cluster monitoring module, the warehouse monitoring module, the ETL operation monitoring module and the data visualization module are abnormal or not.
Further, the system further comprises:
the abnormity notification module is used for sending out a notification based on the judgment result of the first judgment module;
and the exception processing module is used for processing the exception data according to the notification sent by the exception notification module.
Further, the system further comprises:
and the log management module is used for recording historical data of the Hadoop cluster monitoring module, the warehouse monitoring module and the ETL operation monitoring module and generating a historical data log so as to be convenient to check.
Further, the system comprises:
and the second judging module is used for judging whether the data is abnormal according to the historical data.
Further, the system further comprises:
and the abnormality detection module is used for detecting the causes of the abnormality of the historical data.
Further, the system further comprises:
and the data export module is used for exporting the history log generated by the history data.
The data monitoring system in the embodiment of the invention comprises: the system comprises a Hadoop cluster monitoring module, a warehouse monitoring module, an ETL operation monitoring module and a data visualization module; the Hadoop cluster monitoring module comprises basic information, running conditions, cluster exceptions and node details for monitoring the running of the system; the warehouse monitoring module is used for monitoring the running state or the stock condition of the warehouse; the ETL operation monitoring module is used for monitoring ETL operation information and displaying the ETL operation information through a chart, wherein the ETL operation information is mainly obtained from an interface provided by an ETL tool; the data visualization module is used for displaying the monitoring data of the Hadoop cluster monitoring module, the warehouse monitoring module and the ETL operation monitoring module. The data or information monitoring of the modules helps a user to accurately master various indexes of the data center in real time, and abnormal information is early warned and processed in time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic diagram of a data monitoring system of the present invention;
FIG. 2 is another schematic diagram of the data monitoring system of the present invention;
fig. 3 is a detailed schematic diagram of the data monitoring system of the present invention.
Reference numerals: the system comprises a 100-Hadoop cluster monitoring module, a 200-warehouse monitoring module, a 300-ETL operation monitoring module, a 400 data visualization module, a 500-ODS cluster monitoring module, a 600-homepage browsing module, a 700-system management module and a 800-log management module.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present invention, there is provided a data monitoring system, referring to fig. 1, including: the system comprises a Hadoop cluster monitoring module 100, a warehouse monitoring module 200, an ETL operation monitoring module 300 and a data visualization module 400;
the Hadoop cluster monitoring module 100 comprises basic information, running conditions, cluster exceptions and node details for monitoring the running of the system;
the warehouse monitoring module 200 monitors the operation state or the stock condition of the warehouse;
the ETL operation monitoring module 300 is configured to monitor ETL operation information, and show the ETL operation information through a chart, where the ETL operation information is mainly obtained from an interface provided by an ETL tool;
the data visualization module 400 is configured to display monitoring data of the Hadoop cluster monitoring module 100, the warehouse monitoring module, and the ETL operation monitoring module 300.
The data monitoring system comprises a system management function, a Hadoop cluster monitoring function, a warehouse monitoring function, an ODS cluster monitoring function, an ETL operation monitoring function, a data visualization function, a log management function and a Huacheng cloud platform cluster monitoring function. Through the monitoring of the enumeration information of the modules, the system helps a user to accurately master various indexes of the data center in real time, and timely early warning and processing are carried out on abnormal information.
Referring to fig. 2 and 3, the Hadoop cluster monitoring includes basic information, operating conditions, cluster exceptions, and node details. The data warehouse monitoring comprises monitoring the operation state of the data warehouse and the storage condition of the data warehouse. ODS cluster monitoring includes monitoring ODS cluster basic information, exception information, and database state. The ETL operation monitoring includes ETL operation start, end time, operation status, etc. The data visualization includes a menu association layout and SmartBI publications.
Specifically, the Hadoop cluster monitoring module 100 monitors the system with the following dimensions: basic information, operating conditions, cluster exceptions, and node details. The data are mainly obtained by calling a cluster interface, analyzed, sorted and displayed through a chart.
The basic information includes: cluster general, CPU use information, memory use information, network information and hard disk storage information;
the operation conditions comprise: the running state of each component (obtaining data by calling interfaces of each component, such as HDFS, Hive, ZK and the like), the running state of nodes, the percentage of the utilization rate of DataNodes, the number of running nodes, the number of dead nodes, the number of retired nodes and the like;
the node details include: the detailed information of the active node, the retired node, the lost node and the unhealthy node, such as: node labels, a rack, node states, node addresses, node HTTP addresses, latest update time, health reports, containers, used memory, total memory, used CPU cores and the number of residual CPU cores;
the cluster exceptions include: abnormal alarm information such as memory, CPU, hard disk, network IO and the like; and (4) abnormal early warning information of components such as HDFS, Hive, ZK and the like of each component of the big data. And displaying the abnormal information through the list, and supporting to inquire the abnormal alarm information according to the abnormal grade.
Specifically, the data warehouse monitoring module 200 monitors the operation status and the warehouse storage status of the warehouse. The bin interface will be invoked and the diagram shows the bin run.
The operation state of the plurality of bins comprises: active session conditions, e.g., username, IP address, number of operations, run time (seconds), idle time. A running query statement case, e.g., username, statement content, execution engine, state, start time, time that has run, last state. The last twenty-five sentences which have been run are also included;
the inventory storage conditions include: basic information of all databases in Hive, such as database ID, database description, database HDFS path, database name, database owner user name, and owner role. Basic information of Hive table, such as database name, table name, owner, table type, capacity, line number, creation time, last access time. The table stores authorization information of the table, for example, database name, table name, authority, authorized user type, authorized user, authorizer type, authorized execution user, authorization time. The table stores field information corresponding to the table, such as database name, table name, field type, and field order.
Specifically, the ETL operation monitoring module 300 mainly monitors ETL operation information. The ETL operation information is mainly obtained from an interface provided by an ETL tool, and a chart shows relevant information.
The ETL operation information mainly comprises the following indexes: ETL operation start time, end time, ETL operation status, number of input data pieces per step, number of output data pieces per step, update number, speed, etc.
In this embodiment, the system further includes an ODS cluster monitoring module 500, where the ODS cluster monitoring module 500 is configured to monitor basic information, exception information, and a database state of the ODS cluster.
Specifically, the ODS cluster monitoring module 500 monitors the packet data including: and monitoring basic information, abnormal information and database state. Calling and using an MPP cluster interface, and displaying relevant information by a chart.
Basic information: cluster general, CPU use information, memory use information, network information and hard disk storage information;
abnormal information: abnormal alarm information of a memory, a CPU, a hard disk, a network IO and the like, storage capacity, storage quantity, a storage data resource directory, abnormal information of a data warehouse and the like. And displaying the abnormal information in a list, and supporting to inquire the abnormal alarm information according to the abnormal grade.
Monitoring the state of the database: segment current state, whether in change tracking state, whether re-synchronizing, whether they are their original role, whether to see if a distributed statement is running on all nodes, whether master is backing up, whether master is started and working.
In this embodiment, the system further includes:
the homepage browsing module 600 is used for browsing the Hadoop cluster monitoring module 100, the warehouse monitoring module 200, the ETL operation monitoring module 300 and the data visualization module 400. Through the homepage browsing module 600, the user can choose to browse the modules of the system to realize the corresponding functions.
In this embodiment, the system further includes:
the system management module 700 is used for determining the authority management and the user management of the login user.
The system management module 700 may perform operations including add rights, edit rights, and delete rights; or operations of adding, editing and deleting users can be performed. The authority management also comprises authority distribution, specifically comprising role adding, role modifying and role deleting; and adding the user after the authority is distributed.
In this embodiment, the system further includes:
the first judging module is configured to judge whether data of the Hadoop cluster monitoring module 100, the warehouse monitoring module 200, the ETL operation monitoring module 300, and the data visualization module 400 are abnormal.
The system respectively shows the monitoring data of the Hadoop cluster monitoring module 100, the warehouse monitoring module 200, the ETL operation monitoring module 300, the data visualization module 400 and the ODS cluster monitoring module 500, judges whether an abnormality exists in the monitored data, and if the abnormality exists in the monitored data, sends a notification to a user through the abnormality notification module based on the judgment result of the first judgment module; the notification may be an audible alert or a flashing indicator light; then, processing abnormal data according to the notification sent by the abnormal notification module through the abnormal processing module; if the abnormal data is not processed, the reason why the abnormal data is not processed is clarified. For example, although data is abnormal, the problem is not so great and processing is not required for the moment.
As shown in fig. 3, the user logs in, then the system judges whether there is a corresponding right, and the user can enter modules for homepage browsing, system management, data monitoring, log management and the like according to different rights;
wherein, data monitoring includes: the Hadoop cluster monitoring module 100, the warehouse monitoring module 200, the ODS cluster monitoring module 500, the ETL operation monitoring module 300, the data visualization module 400, and the like, which correspondingly implement the functions of Hadoop cluster monitoring, data warehouse monitoring, ODS cluster monitoring, ETL operation monitoring, data visualization, and the like. And the data monitoring module and other modules can respectively display the monitoring data and the checking of the specific monitoring data, then judge whether the monitoring data is abnormal or not, inform a user if the monitoring data is abnormal, further judge whether the monitoring data is processed or not, and if the monitoring data is not processed, write the reason of not processing.
The log management module 800: the system is used for recording historical data of the Hadoop cluster monitoring module 100, the warehouse monitoring module 200 and the ETL operation monitoring module 300 and generating a historical data log for viewing.
Specifically, the log management comprises logs of six units, namely a Hadoop log, a Hive log, an ETL log, an MPP log, a cluster system log, SmartBI and the like. In the process of log management, the second judging module judges whether log data (historical data) are abnormal or not at any time, if so, the abnormal data are sent to the abnormal detection module, and the abnormal reason is detected by the abnormal detection module.
In addition, if the historical data needs to be exported, the historical logs generated by the historical data are exported through the data export module so as to be convenient to view.
And (3) system management: the operation including adding authority, editing authority and deleting authority can be carried out through the authority management unit; or the user management unit can perform operations of adding users, editing users and deleting users. The authority management also comprises authority distribution, specifically comprising role adding, role modifying and role deleting; and adding the user after the authority is distributed.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A data monitoring system, comprising: the system comprises a Hadoop cluster monitoring module, a warehouse monitoring module, an ETL operation monitoring module and a data visualization module;
the Hadoop cluster monitoring module comprises basic information, running conditions, cluster exceptions and node details for monitoring the running of the system;
the warehouse monitoring module is used for monitoring the running state or the stock condition of a warehouse;
the ETL operation monitoring module is used for monitoring ETL operation information and displaying the ETL operation information through a chart, wherein the ETL operation information is mainly obtained from an interface provided by an ETL tool;
the data visualization module is used for displaying the monitoring data of the Hadoop cluster monitoring module, the warehouse monitoring module and the ETL operation monitoring module.
2. The data monitoring system of claim 1, further comprising an ODS cluster monitoring module for monitoring ODS cluster basic information, exception information, and database state.
3. The data monitoring system of claim 1, further comprising:
and the homepage browsing module is used for browsing the Hadoop cluster monitoring module, the warehouse monitoring module, the ETL operation monitoring module and the data visualization module.
4. The data monitoring system of claim 1, further comprising:
and the system management module is used for determining the authority management and the user management of the login user.
5. The data monitoring system of claim 1, further comprising:
and the first judgment module is used for judging whether the data of the Hadoop cluster monitoring module, the warehouse monitoring module, the ETL operation monitoring module and the data visualization module are abnormal or not.
6. The data monitoring system of claim 5, further comprising:
an abnormality notification module for issuing a notification based on the judgment result of the first judgment module;
and the exception processing module is used for processing the exception data according to the notification sent by the exception notification module.
7. The data monitoring system of claim 1, further comprising:
and the log management module is used for recording historical data of the Hadoop cluster monitoring module, the warehouse monitoring module and the ETL operation monitoring module and generating a historical data log so as to be convenient to check.
8. The data monitoring system of claim 7, wherein the system comprises:
and the second judging module is used for judging whether the data is abnormal or not according to the historical data.
9. The data monitoring system of claim 8, further comprising:
and the abnormality detection module is used for detecting the abnormality reason of the historical data.
10. The data monitoring system of claim 9, further comprising:
and the data export module is used for exporting the history log generated by the history data.
CN202111220820.8A 2021-10-20 2021-10-20 Data monitoring system Pending CN113868099A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111220820.8A CN113868099A (en) 2021-10-20 2021-10-20 Data monitoring system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111220820.8A CN113868099A (en) 2021-10-20 2021-10-20 Data monitoring system

Publications (1)

Publication Number Publication Date
CN113868099A true CN113868099A (en) 2021-12-31

Family

ID=78996701

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111220820.8A Pending CN113868099A (en) 2021-10-20 2021-10-20 Data monitoring system

Country Status (1)

Country Link
CN (1) CN113868099A (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105095056A (en) * 2015-08-14 2015-11-25 焦点科技股份有限公司 Method for monitoring data in data warehouse
CN105718351A (en) * 2016-01-08 2016-06-29 北京汇商融通信息技术有限公司 Hadoop cluster-oriented distributed monitoring and management system

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105095056A (en) * 2015-08-14 2015-11-25 焦点科技股份有限公司 Method for monitoring data in data warehouse
CN105718351A (en) * 2016-01-08 2016-06-29 北京汇商融通信息技术有限公司 Hadoop cluster-oriented distributed monitoring and management system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
松伯: "大数据理论体系总结--数据仓库管理与全链路数据体系", pages 1 - 5, Retrieved from the Internet <URL:https://www.cnblogs.com/yangsy0915/p/9084180.html> *

Similar Documents

Publication Publication Date Title
US8407669B2 (en) Device based software authorizations for software asset management
CN113556254B (en) Abnormal alarm method and device, electronic equipment and readable storage medium
CN110581773A (en) automatic service monitoring and alarm management system
CN111339175B (en) Data processing method, device, electronic equipment and readable storage medium
CN110460476B (en) Network operation and maintenance management method
CN111752808A (en) Method for implementing data sharing exchange service operation monitoring system
CN116755992B (en) Log analysis method and system based on OpenStack cloud computing
CN114780335A (en) Correlation method and device of monitoring data, computer equipment and storage medium
US12062234B1 (en) Codeless anchor detection for detectable features in an environment
CN114048090A (en) K8S-based container cloud platform monitoring method and device and storage medium
CN112231180A (en) SQL monitoring method and device based on cloud environment
US20030023721A1 (en) Method and apparatus for generating context-descriptive messages
US11836869B1 (en) Generating three-dimensional data visualizations in an extended reality environment
CN114915634A (en) Industrial data acquisition and storage system and method based on data lake
CN110677271A (en) Big data alarm method, device, equipment and storage medium based on ELK
CN107423035B (en) Product data management system in software development process
CN113762910A (en) Document monitoring method and device
CN113868099A (en) Data monitoring system
CN101515864A (en) Alarm information allocation system and allocation method thereof
CN113986656B (en) Power grid data safety monitoring system based on data center platform
CN114020893A (en) Log retrieval method and device based on distributed storage and storage medium
CN113886378A (en) Big data management system
CN111930590A (en) Real-time monitoring system for computer software and hardware resources
CN108415808B (en) Real-time visual monitoring method, system, equipment and medium for access distribution unit
AU2002240575A1 (en) Method and apparatus for generating context-descriptive messages

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