DATA LOGS MANAGEMENT IN A MULTI-CLIENT ARCHITECTURE

• US 20150254285A1
• Filed: 09/17/2013
• Published: 09/10/2015
• Est. Priority Date: 10/04/2012
• Status: Active Grant

• Current Assignee: Alcatel-Lucent SA (Nokia Corporation)
• Original Assignee: Alcatel-Lucent SA (Nokia Corporation)
• Inventors: Achar, Anitha, Unnikrishnan, Brijesh
• Granted Patent: US 10,007,685 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/278 Data partitioning, e.g. horizontal or vertical partitioning

Abstract

Systems and methods for data logs management in a multi-client architecture are described. According to the present subject matter, the system(s) implement the described method(s) for efficient data logs management. The method includes identifying purging parameters associated with each entity of the plurality of entities, where the purging parameters signify a mechanism of purging data logs stored in partition corresponding the entity, and where the purging parameters comprises at least criticality point associated with data logs to relinquish storage space. Further, the method includes purging of data logs stored in the partition of the entity based on the purging parameters, wherein the purging relinquishes the storage space.

Claims

1. A method for data logs management comprising:

identifying purging parameters associated with an entity from amongst a plurality of entities, wherein the purging parameters comprises at least criticality point associated with data logs, and wherein the purging parameters signify criteria of purging data logs stored by the entity in a database; and

purging the data logs based on the purging parameters.

2. The method as claimed in claim 1 further comprising partitioning the database into a plurality of partitions to store data logs, wherein the plurality of partitions are allocated among the plurality of entities, and wherein each entity from amongst the plurality of entities is allocated at least one partition from amongst the plurality of partitions.

3. The method as claimed in claim 2, wherein the partitioning is based on partitioning parameters associated with each of the plurality of entities, and wherein the partitioning parameters define the size of partition allocated to each of the plurality of the entities.

4. The method as claimed in claim 1, wherein the method further comprises:

identifying fragmentation parameters associated with the each entity from amongst the plurality of entities, wherein the fragmentation parameters define a fragmentation criteria of data logs into different sizes; and

fragmenting the data logs generated by each of the entity from amongst the plurality of entities to different sizes based on the identified fragmentation parameters.

5. The method as claimed in claim 4, wherein the different sizes of the data logs fragmented for the entity is based on storage size of the database allocated to the entity and number of the data logs generated by the entity.

6. The method as claimed in claim 1, wherein the purging parameters further comprise frequency of purging and time instances based on which, the stored data logs are purged.

7. The method as claimed in claim 2, wherein the purging of the data logs is further based on a pre-defined time duration and a threshold number of data logs stored in the partition, wherein the pre-defined time duration and the threshold of data logs are indicative of the data logs that are stored with an impulse.

8. The method as claimed in claim 2, wherein the method further comprises:

identifying overwriting factors associated with each entity from amongst the plurality of entities, wherein the overwriting factors define overwriting criteria of data logs from one partition to another; and

overwriting the data logs of the entity onto an unused partition of another entity based on the overwriting factors.

9. The method as claimed in claim 8, wherein the overwriting factors associated with each entity comprise at least one of storage space available, criticality of the data logs, and sharing capability of entities'"'"' partition.

10. The method as claimed in claim 1, wherein the method further comprises partitioning dynamically, the storage space among the plurality of entities based on changing requirement of storage space of the plurality of entities.

11. A system for data logs management comprising:

a processor;

a purging module coupled to the processor, configured to;

identify purging parameters associated with an entity from amongst a plurality of entities, wherein the purging parameters comprises at least criticality point associated with data logs, and wherein the purging parameters signify criteria of purging data logs stored by the entity in a database; and

purging the data logs based on the purging parameters.

12. The system as claimed in claim 11 further comprising a partitioning module configured to partition the database into a plurality of partitions to store data logs, wherein the plurality of partitions are allocated among the plurality of entities, and wherein each entity from amongst the plurality of entities is allocated at least one partition from amongst the plurality of partitions.

13. The system as claimed in claim 11, wherein the system further comprises a fragmentation module configured to:

identify fragmentation parameters associated with each entity from amongst the plurality of entities, wherein the fragmentation parameters define a fragmentation criteria of data logs into different sizes; and

fragment the data logs generated by each of the entity from amongst the plurality of entities to different sizes based on the identified fragmentation parameters.

14. The system as claimed in claim 12, wherein the system further comprises a overwriting module configured to:

identify overwriting factors associated with each entity from amongst the plurality of entities, wherein the overwriting factors define overwriting criteria of data logs from one partition to another; and

overwrite the data logs of the entity onto partition of another entity based on the overwriting factors, wherein the partition of another entity is unused.

15. The system as claimed in claim 12, wherein the partitioning module is further configured to dynamically partition, the storage space among the plurality of entities based on changing requirement of storage space of the plurality of entities.

16. A non-transitory computer-readable medium having embodied thereon a computer readable program code for executing a method comprising:

identifying purging parameters associated with an entity from amongst a plurality of entities, wherein the purging parameters comprises at least criticality point associated with data logs, and wherein the purging parameters signify criteria of purging data logs stored by the entity in a database; and

purging the data logs based on the purging parameters.

17. The method as claimed in claim 16, wherein the method further comprises:

identifying fragmentation parameters associated with each entity from amongst the plurality of entities, wherein the fragmentation parameters define a fragmentation criteria of data logs into different sizes; and

fragmenting the data logs generated by each of the entity from amongst the plurality of entities to different sizes based on the identified fragmentation parameters.