IP Library › Granted Patent US 12,645,651
Granted Patent B2
US 12,645,651 · App. 18/631,608 · Granted Jun 2, 2026

Usage driven data archive

Inventor: Seethalakshmi Viswanathan (Cerritos, CA)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06F16/215G06F16/285
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Quick Facts
Patent No.
US 12,645,651
App. No.
18/631,608
Granted
Jun 2, 2026
Kind
B2
Abstract

Systems and techniques that facilitate creation and archiving of controlled structures are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory that can execute the computer executable components stored in memory. The computer executable components can comprise a categorizer component that categorizes a set of data into categories based on respective attributes of subsets of the set of data; a reorganizer component that reorganizes the set of data into a controlled structure based on one or more categories; and a combiner component that combines and delimits entries within one or more segments of the controlled structure.

Claims (56)

1 . A system comprising:

a memory that stores computer executable components;

a processor that executes the computer executable components stored in the memory,

wherein the computer executable components comprise:

a database component that determines usage metrics for a set of data;

a categorizer component that categorizes the set of data into categories based on one or more respective attributes of subsets of the set of data, wherein the one or more attributes comprise a modification rate and a frequently queried attribute, and wherein the categorizer component further assigns the one or more respective attributes of the subsets of the set of data based on the usage metrics;

a reorganizer component that reorganizes the set of data into a controlled structure based on one or more categories, wherein entries of set of data are organized from highest frequently queried attribute to lowest frequently queried attribute; and

a combiner component that combines two or more entries of the set of data within one or more segments of the controlled structure, wherein the combiner component combines the two or more entries of the set of data within one or more segments of the controlled structure by:

determining memory usage of a first entry within the segments of the controlled structure and memory usage of a second entry within the segments of the controlled structure;

determining that a combination of the memory usage of the first entry and memory usage of the second entry is less than storage space of a single memory block;

appending a delimiter token to an end of the first entry;

concatenating the first entry, the delimiter token, and the second entry into a combined entry;

and stores the combined entry within the single memory block.

2 . The system of claim 1 , wherein the combiner component further archives the one or more segments with corresponding data pointers.

3 . The system of claim 2 , wherein the combiner component further purges entries that do not have an active data pointer.

4 . The system of claim 1 , wherein the one or more attributes further comprise at least one of a frequently accessed attribute, a never accessed attribute, and an infrequently changing attribute.

5 . The system of claim 4 , wherein the frequently queried data attribute is based on where clause statistics.

6 . The system of claim 4 , wherein the frequently accessed attribute is based on selected query fields.

7 . The system of claim 1 , wherein data within the controlled structure is organized from most likely to be accessed to least likely to be accessed.

8 . A computer-implemented method comprising:

determining, by a system operatively coupled to a processor, usage metrics for a set of data;

assigning, by the system, one or more respective attributes of subsets of the set of data based on the usage metrics;

categorizing, by the system, the set of data into categories based on the one or more respective attributes of the subsets of the set of data, wherein the one or more attributes comprise a modification rate of the set of data and a frequently queried attribute;

reorganizing, by the system, the set of data into a controlled structure based on one or more categories, wherein entries of set of data are organized from highest frequently queried attribute to lowest frequently queried attribute;

combining, by the system, two or more entries within one or more segments of the controlled structure, wherein the combining comprises:

measuring, by the system, memory usage of a first entry within the segments of the controlled structure and memory usage of a second entry within the segments of the controlled structure;

determining, by the system, that a combination of the memory usage of the first entry and memory usage of the second entry is less than storage space of a single memory block;

appending, by the system, a delimiter token to an end of the first entry; and

concatenating, by the system, the first entry, the delimiter token, and the second entry into a combined entry;

and

storing, by the system, the combined entry within a single memory block.

9 . The computer-implemented method of claim 8 , further comprising archiving, by the system, the one or more segments with corresponding data pointers.

10 . The computer-implemented method of claim 9 , further comprising purging, by the system, entries that do not have an active data pointer.

11 . The computer-implemented method of claim 8 , wherein the one or more attributes further comprise at least one of a frequently accessed attribute, a never accessed attribute, and an infrequently changing attribute.

12 . The computer-implemented method of claim 11 , wherein the frequently queried data attribute is based on where clause statistics.

13 . The computer-implemented method of claim 11 , wherein the frequently accessed attribute is based on selected query fields.

14 . The computer-implemented method of claim 8 , wherein data within the controlled structure is organized from most likely to be accessed to least likely to be accessed.

15 . A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

determine, by the processor, usage metrics for a set of data;

assign, by the processor, one or more respective attributes of subsets of the set of data based on the usage metrics;

categorize, by the processor, the set of data into categories based on the one or more respective attributes of the subsets of the set of data, wherein the one or more attributes comprise a modification rate of the set of data and a frequently queried attribute;

reorganize, by the processor, the set of data into a controlled structure based on one or more categories, wherein entries of set of data are organized from highest frequently queried attribute to lowest frequently queried attribute;

combine by the processor, two or more entries within one or more segments of the controlled structure wherein the combining causes the processor to:

measure, by the processor, memory usage of a first entry within the segments of the controlled structure and memory usage of a second entry within the segments of the controlled structure;

determine, by the processor, that a combination of the memory usage of the first entry and memory usage of the second entry is less than storage space of a single memory block;

append, by the processor, a delimiter token to an end of the first entry; and

concatenate, by the processor, the first entry, the delimiter token, and the second entry into a combined entry;

and

store, by the processor, the combined entries within a single memory block.

16 . The computer program product of claim 15 , wherein the program instructions are further executable to cause the processor to:

archive, by the processor, the one or more segments with corresponding data pointers.

17 . The computer program product of claim 16 , wherein the program instructions are further executable to cause the processor to:

purge, by the processor, entries that do not have an active data pointer.

18 . The computer program product of claim 15 , wherein the one or more attributes further comprise at least one of a frequently accessed attribute, a never accessed attribute, and an infrequently changing attribute.

19 . The computer program product of claim 18 , wherein the frequently queried data attribute is based on where clause statistics.

20 . The computer program product of claim 15 , wherein data within the controlled structure is organized from most likely to be accessed to least likely to be accessed.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 10, 2024
From: VISWANATHAN, SEETHALAKSHMI
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 067063/0966 →
Continuity (1)
Related Publication 20250321940A1 · Oct 16, 2025
References Cited (22)
US 6481008B1 · Chaiken · 2002 [cited by examiner]
US 6499083B1 · Hamlin · 2002 [cited by examiner]
US 6931027B1 · Vogel · 2005 [cited by examiner]
US 7552108B2 · Gwizdaloski · 2009 [cited by examiner]
US 9646075B2 · Riggs · 2017 [cited by examiner]
US 11151078B2 · Oberoi et al. · 2021 [cited by applicant]
US 11269888B1 · Farooq et al. · 2022 [cited by applicant]
US 20020087824A1 · Hum · 2002 [cited by examiner]
US 20080050026A1 · Bashyam · 2008 [cited by examiner]
US 20090106518A1 · Dow · 2009 [cited by examiner]
US 20190370170A1 · Oltean · 2019 [cited by examiner]
US 20190392053A1 · Chalakov · 2019 [cited by examiner]
US 20200042634A1 · Stewart · 2020 [cited by examiner]
US 20200242078A1 · Dain · 2020 [cited by examiner]
US 20200285391A1 · Sun · 2020 [cited by examiner]
US 20210073222A1 · Kadiyala et al. · 2021 [cited by applicant]
US 20220214994A1 · Narayanan et al. · 2022 [cited by applicant]
US 20220327095A1 · Kim et al. · 2022 [cited by applicant]
US 20220374163A1 · Colella · 2022 [cited by examiner]
DE 102021002079B3 · 2022 [cited by applicant]
EP 2975539B1 · 2019 [cited by applicant]
cloud.ibm.com, “File Storage,” Retreived from the Internet: Feb. 20, 2024, https://www.ibm.com/cloud/file-storage/pricing. [cited by applicant]