Container Metadata Hierarchy for Unique Data Replication
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Solution Overview
Problem
Current database management systems face inefficiencies in data replication and backup processes due to the complexity of software applications and the need for flexible data management across multiple client environments, where database tables are often duplicated across containers with similar but distinct data, leading to resource-intensive data transfers and potential duplication.
Innovation Solution
The system generates a hierarchy of metadata tables to identify unique data sets across containers by calculating checksums and using unique identifiers, allowing for efficient data replication and backup by distinguishing between identical and distinct data within tables with the same name across different containers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If database tables are duplicated across multiple containers to support different client environments, then flexibility and adaptability are improved, but data replication complexity and resource consumption increase
Solution Approach 1:
The patent creates copies of database tables as container instances, where each container can be independently configured for different client environments. These table copies maintain the same schema but can have different data, allowing flexible adaptation without increasing replication complexity through standardized copying mechanisms.
Solution Approach 2:
The patent segments data into separate container instances, each representing a specific client environment or scenario. This segmentation allows independent management and replication of data for different clients while maintaining a unified table structure, resolving the complexity issue through modular organization.
2Reliability
If all table content is replicated across containers, then data completeness is ensured, but data transfer resources and time are consumed
Solution Approach 1:
The patent performs preliminary identification of unique table instances before replication occurs. By pre-evaluating which tables need to be replicated based on container configurations and data uniqueness, the system avoids unnecessary data transfer while ensuring complete replication only when needed, thus reducing transfer time.
Solution Approach 2:
The patent extracts only the necessary table instances for replication by evaluating uniqueness across containers. Instead of replicating all tables, the system identifies and extracts only those unique table instances that need to be transferred, reducing data transfer resources while maintaining data completeness for the target container.
3Quantity of substance
If table instances with identical data are replicated, then data redundancy is created, but ensuring data uniqueness requires complex evaluation
Solution Approach 1:
The patent uses checksums as copies of data fingerprints to quickly identify duplicate table instances. By calculating and comparing checksums, the system can efficiently detect redundant data without complex evaluation, maintaining data uniqueness information while avoiding redundant replication.
Solution Approach 2:
The patent replaces complex mechanical data comparison systems with checksum-based identification. Instead of comparing entire table contents to determine uniqueness, the system uses simplified checksum calculations, significantly reducing evaluation complexity while maintaining accurate data redundancy detection.
Data Source
AI summary
The present disclosure relates to computer-implemented methods, software, and systems for generating a hierarchy of metadata tables for a database comprising containers including tables. The tables are identified by table names and assigned to containers. A first table is assigned to two containers and may define two table instances of the first table. The hierarchy of metadata tables includes a first metadata table defining mappings between container identifiers, table names, table sections, and unique identifiers for corresponding data within table sections of table instances defined with the table names mapped to the container identifiers. In response to receiving a request to generate a replication of table content, a second metadata table is generated to identify a unique set of table instances from the set of the containers based on evaluating the first metadata table. The unique set of table instances comprises data from the database storage without repetition.