IMPLEMENTING INTELLIGENT STANDARD DEVIATION INSERTS INTO A RELATIONAL DATABASE MANAGEMENT SYSTEM
20190392041 ยท 2019-12-26
Inventors
Cpc classification
G06F16/215
PHYSICS
G06F17/18
PHYSICS
International classification
Abstract
A method, system and computer program product are provided for implementing intelligent standard deviation inserts into a relational database management system (RDBMS). A trigger program type logic is provided within a database for processing outlier data based upon deviation constraints. The processed outlier data is used for automatically taking appropriate action including preventing insertion of outliers into the Relational Database Management System (RDBMS).
Claims
1. A system for implementing intelligent standard deviation inserts into a relational database management system (RDBMS) comprising: a trigger program control logic, said trigger program control logic tangibly embodied in a non-transitory machine readable medium used to implement intelligent standard deviation insertion; said trigger program control logic, processing outlier data based upon deviation constraints; and said trigger program control logic, using the processed outlier data for automatically taking an appropriate action including preventing insertion of outliers into a Relational Database Management System (RDBMS).
2. The system as recited in claim 1 wherein said trigger program control logic, processing outlier data based upon deviation constraints includes defining insertion values used by said trigger program control logic.
3. The system as recited in claim 1 wherein said trigger program control logic, processing outlier data based upon deviation constraints includes ensuring outlier data records being inserted have reasonable values within a sliding time window.
4. The system as recited in claim 3 includes rejecting an insert.
5. The system as recited in claim 3 includes providing error codes and warning messages on an insert.
6. The system as recited in claim 3 includes storing an insert in a holding data structure.
7. The system as recited in claim 1 wherein said trigger program control logic, processing outlier data based upon deviation constraints includes identifying specified deviation values within a given time frame.
8. The system as recited in claim 1 includes control code stored on a non-transitory computer readable medium, and wherein said control code is used for implementing intelligent standard deviation inserts.
9. A method for implementing intelligent standard deviation inserts into a relational database management system (RDBMS) comprising: providing a trigger program control logic, said trigger program control logic tangibly embodied in a non-transitory machine readable medium used to implement intelligent standard deviation insertion; said trigger program control logic: processing outlier data based upon deviation constraints; and using the processed outlier data for automatically taking an appropriate action including preventing insertion of outliers into a Relational Database Management System (RDBMS).
10. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes applying insertion threshold analysis.
11. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes identifying deviant data values within a specified time period.
12. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes checking whether data values of one or more given database columns are within specified amount of deviation.
13. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes using configurable deviation checks.
14. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes identifying a data value being inserted having a higher value than a specified threshold deviation constraint.
15. The method as recited in claim 14 includes storing a data insert in a holding data structure.
16. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes identifying deviation values within a specified window of time.
17. The method as recited in claim 9 wherein processing outlier data based upon deviation constraints includes identifying deviation values outside a threshold value, and applying a stored rejection policy.
18. The method as recited in claim 17 includes one of rejecting an insert and providing error codes and warning messages on an insert.
19. The method as recited in claim 17 includes automatically taking an appropriate action including holding outlier values in a separate data structure.
20. The method as recited in claim 17 ensuring data to be inserted is reasonable, effectively addressing outlying information to provide enhanced and improved database operation.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] The present invention together with the above and other objects and advantages may best be understood from the following detailed description of the preferred embodiments of the invention illustrated in the drawings, wherein:
[0016]
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[0018]
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0019] In the following detailed description of embodiments of the invention, reference is made to the accompanying drawings, which illustrate example embodiments by which the invention may be practiced. It is to be understood that other embodiments may be utilized and structural changes may be made without departing from the scope of the invention.
[0020] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms a, an and the are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms comprises and/or comprising, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
[0021] In accordance with features of the invention, a method and system are provided for implementing intelligent standard deviation inserts into a relational database management system (RDBMS).
[0022] Having reference now to the drawings, in
[0023] Computer system 102 includes a system memory 106 including an operating system 108 and relational database management systems (RDBMS) 110. System memory 106 is a random-access semiconductor memory for storing data, including programs. System memory 106 is comprised of, for example, a dynamic random access memory (DRAM), a synchronous direct random access memory (SDRAM), a current double data rate (DDRx) SDRAM, non-volatile memory, optical storage, and other storage devices.
[0024] Computer system 102 includes a storage 112 including a database 114 and a network interface 116. Computer system 102 includes an I/0 interface 118 for transferring data to and from computer system components including CPU 104, memory 106 including the operating system 108 and RDBMS 110, storage 112 including database 114, and network interface 116 and a network 120 and a client system and application 122.
[0025] In accordance with features of the invention, the new computer system 102 of the preferred embodiment implements special processing of outlying data to ensure data to be inserted into the database 114 is reasonable, effectively addressing outlying information to provide enhanced and improved database operation.
[0026] In accordance with features of the invention, when the value being inserted has a higher value from a deviation perspective then an appropriate action is taken including a selected one of: reject the insert, provide warning messages on the insert and take some other form of corrective action. For example, the database can hold the outlier values in a separate data structure, possibly holding table, and not return the outlier values to normal queries. The outlier values in a separate data structure optionally are returned to normal queries when a specified number of deviant values occur within a specified time frame. For example, once an hour is probably a glitch, but two a minute is a problem, the outlier values optionally are included in the data or a corrective action is taken. How to handle held results is configured, for example by the application programmer and the database administrator.
[0027] In accordance with features of the invention, partitioning data into a held structure has uses that go beyond just holding data for deviant values. When inserting blocks of records it can be ensured that all records are within a specified deviation value. This means that a group of records can be inserted within a single statement or an insert could be done via sub-select query. This gives a natural grouping of records to act upon. The deviation can be made to be computed by looking at records inserted within a given time frame such as a last 5 minutes, last 30 minutes, the last day, and the like. Also a specified X amount of previously inserted records can make up a window of records that are used to decide what the deviation values to be computed with. Furthermore the deviation can be broken into where the data is being inserted from and or who is doing the inserting.
[0028] In accordance with features of the invention, for example a drone may report its position as part of its information packet. Its position, while changing, cannot change more than a certain amount during a given time frame. Thus an information packet that contains a position value that deviates dramatically from the previous window of positions is suspect and should either be ignored or analyzed more carefully. An interesting aspect of this example, is that the deviation can also be dependent on a time aspect of the data, for example, where either the arrival time of the information packet, such as row insertion time or a timestamp provided in the information packet, data within the row.
[0029] Referring to
[0030] Referring to
[0031] Referring now to
[0032] Referring now to
[0033] Computer readable program instructions 404, 406, 408, and 410 described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The computer program product 400 may include cloud based software residing as a cloud application, commonly referred to by the acronym (SaaS) Software as a Service. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions 404, 406, 408, and 410 from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
[0034] A sequence of program instructions or a logical assembly of one or more interrelated modules defined by the recorded program means 404, 406, 408, and 410, direct the system 100 for implementing intelligent standard deviation inserts into a relational database management system (RDBMS) of the preferred embodiment.
[0035] While the present invention has been described with reference to the details of the embodiments of the invention shown in the drawing, these details are not intended to limit the scope of the invention as claimed in the appended claims.