Utilizing machine learning to determine data storage pruning parameters

Patent metadata

Field	Value
Publication number	US-10353863-B1
Application number	US-201815950482-A
Country	US
Kind code	B1
Filing date	Apr 11, 2018
Priority date	Apr 11, 2018
Publication date	Jul 16, 2019
Grant date	Jul 16, 2019

Abstract

A device receives, from a user device, a request to prune a primary database, and receives primary database information associated with the primary database and secondary database information associated with a secondary database that is different than the primary database. The device processes the primary database information and the secondary database information, with a machine learning model, to generate suggested pruning parameters, and provides the suggested pruning parameters to the user device. The device receives selected pruning parameters from the user device, where the selected pruning parameters are selected from the suggested pruning parameters or are input via the user device. The device removes pruned information from the primary database based on the selected pruning parameters, and provides the pruned information to the secondary database based on the selected pruning parameters.

First claim

What is claimed is:

1. A device, comprising:
one or more memories; and
one or more processors, communicatively coupled to the one or more memories, to:
receive, from a user device, a request to prune a primary database;
receive primary database information associated with the primary database,
the primary database information specifying metadata associated with the primary database;

receive secondary database information associated with a secondary database that is different than the primary database,
the secondary database information specifying metadata associated with the secondary database;

process the primary database information and the secondary database information, with a machine learning model, to generate suggested pruning parameters,
the suggested pruning parameters including one or more of:
a pruning frequency parameter,
a primary database name parameter,
a column to query parameter, or
a date parameter;

provide the suggested pruning parameters to the user device;
receive selected pruning parameters from the user device,
the selected pruning parameters being selected from the suggested pruning parameters or being input via the user device;

remove first information from the primary database based on the selected pruning parameters,
the first information including a plurality of database records;

provide the first information to the secondary database based on the selected pruning parameters;
determine, based on a pattern identified from historical access to the first information, a predicted time associated with the first information,
the historical access to the first information including at least one of:
historical access to the first information when the first information was stored in the primary database, or
historical access to the first information when the first information was stored in the secondary database;

remove the first information from the secondary database prior to the predicted time; and
provide the first information to the primary database prior to the predicted time.

2. The device of claim 1 , wherein the one or more processors are further to:
provide, to the user device, information indicating a result of providing the first information to the secondary database.

3. The device of claim 1 , wherein the one or more processors are further to:
determine a problem with the primary database or the secondary database; and
provide, to the user device, an alert associated with the problem.

4. The device of claim 3 , wherein the one or more processors are further to:
receive, from the user device, reconfigured pruning parameters based on providing the alert to the user device;
remove the first information from the primary database based on the reconfigured pruning parameters; and
provide the first information to the secondary database based on the reconfigured pruning parameters.

5. The device of claim 1 , wherein the machine learning model includes one or more of:
an exploratory factor analysis model,
a confirmatory factor analysis model,
a principal component analysis model,
a k-means clustering model, or
a least absolute shrinkage and selection operator (Lasso) regression analysis model.

6. The device of claim 1 , wherein the one or more processors are further to:
perform an analysis of a plurality of secondary databases; and
select the secondary database from the plurality of secondary databases based on the analysis of the plurality of secondary databases.

7. The device of claim 1 , wherein the one or more processors are further to:
perform an analysis of the primary database information and the secondary database information;
determine a backup strategy for the primary database based on the analysis of the primary database information and the secondary database information; and
implement the backup strategy via the selected pruning parameters.

8. A non-transitory computer-readable medium storing instructions, the instructions comprising:
one or more instructions that, when executed by one or more processors, cause the one or more processors to:
receive, from a user device, a request to prune a primary database;
receive primary database information associated with the primary database,
the primary database information specifying metadata associated with the primary database;

perform an analysis of a plurality of secondary databases;
select a secondary database from the plurality of secondary databases based on the analysis of the plurality of secondary databases;
receive secondary database information associated with the secondary database,
the secondary database information specifying metadata associated with the secondary database;

process the primary database information and the secondary database information, with a model, to generate pruning parameters,
the pruning parameters including one or more of:
a pruning frequency parameter,
a primary database name parameter,
a column to query parameter, or
a date parameter;

automatically implement the pruning parameters;
remove first information from the primary database based on automatically implementing the pruning parameters,
the first information including a plurality of database records;

provide the first information to the secondary database based on automatically implementing the pruning parameters;
determine, based on a pattern identified from historical access to the first information, a predicted time associated with the first information;
the historical access to the first information including at least one of:
historical access to the first information when the first information was stored in the primary database, or
historical access to the first information when the first information was stored in the secondary database;

remove the first information from the secondary database prior to the predicted time; and
provide the first information to the primary database prior to the predicted time.

9. The non-transitory computer-readable medium of claim 8 , wherein the primary database information includes information indicating one or more of:
a cost associated with operation of the primary database,
a capacity of the primary database,
a quantity of data in the primary database, or
a type of data in the primary database.

10. The non-transitory computer-readable medium of claim 8 , wherein the secondary database information includes information indicating one or more of:
a cost associated with operation of the secondary database,
a capacity of the secondary database,
a quantity of data in the secondary database, or
a type of data in the secondary database.

11. The non-transitory computer-readable medium of claim 8 , wherein the instructions further comprise:
one or more instructions that, when executed by the one or more processors, cause the one or more processors to:
provide, to the user device, information indicating a result of providing the first information to the secondary database.

12. The non-transitory computer-readable medium of claim 8 , wherein the instructions further comprise:
one or more instructions that, when executed by the one or more processors, cause the one or more processors to:
determine a problem with the primary database or the secondary database;
provide, to the user device, an alert associated with the problem;
receive, from the user device, reconfigured pruning parameters based on providing the alert to the user device;
remove the first information from the primary database based on the reconfigured pruning parameters; and
provide the first information to the secondary database based on the reconfigured pruning

Assignees

• Capital One Services Llc

Inventors

• Deshpande Amit
• Subramanian Ponnazhakan
• Chikkaveerappa Satish
• Pandya Asutosh
• Venuraju Mithra Kosur
• Mohammed Sahul

Classifications

• G06F16/125 Primary

  characterised by the use of retention policies (retention policies for HSM systems G06F16/185) · CPC title

• G06F16/284

  Relational databases · CPC title

• G06F16/113 Primary

  Details of archiving (lifecycle management in storage systems G06F3/0649; point-in-time backing up or restoration of persistent data G06F11/1446) · CPC title

• G06F16/2365

  Ensuring data consistency and integrity · CPC title