Distributed Content Indexing System Architecture
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Solution Overview
Problem
Conventional content indexing systems face scalability issues due to their single-device architecture, require reconfiguration when backup data formats change, and necessitate synchronization between metadata and content index databases, leading to increased computing costs and potential errors.
Innovation Solution
A distributed content indexing system that combines backup and content index databases into a single entity, allowing parallel processing and load balancing across multiple servers and media agents, enabling content indexing regardless of backup data format and reducing synchronization needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single computing device or server is used for content indexing, then the system is simple to manage, but scalability issues occur as data volume increases
Solution Approach 1:
The system divides the content indexing functionality into multiple independent servers, each capable of processing indexing tasks autonomously. This segmentation allows the system to scale horizontally by adding more servers as data volume increases, resolving the contradiction between architectural simplicity and scalability.
Solution Approach 2:
The patent transitions from a single-dimensional (single server) architecture to a multi-dimensional distributed architecture where multiple servers operate in parallel. This dimensional change enables the system to handle larger data volumes while maintaining manageable complexity through standardized server configurations.
2Device complexity
If conventional content indexing systems use separate backup metadata database and content index database, then data organization is structured, but synchronization requirements increase computing costs and potential errors
Solution Approach 1:
The patent combines the backup metadata database and content index database into a unified database structure. This merging eliminates the need for synchronization between separate databases, reducing computing resource consumption and potential synchronization errors while maintaining organized data storage through a single integrated system.
3Ease of manufacture
If conventional systems are configured to content index files in a specific backup data format, then initial configuration is straightforward, but reconfiguration is needed when format changes occur
Solution Approach 1:
The distributed server architecture implements universal content indexing capabilities that can handle multiple backup data formats through standardized processing interfaces. Each server is configured to recognize and process various file formats, eliminating the need for reconfiguration when format changes occur while maintaining straightforward initial setup procedures.
4Reliability
If synchronization between backup metadata database and content index database is implemented, then data consistency is maintained, but additional computing resources are allocated and errors can occur
Solution Approach 1:
By merging the backup metadata database and content index database into a single unified database, the system maintains data consistency inherently without requiring complex synchronization mechanisms. This eliminates synchronization-related computing overhead and potential errors while preserving data reliability through a single source of truth.
Data Source
AI summary
An improved content indexing system is disclosed herein that content indexing system combines the functionality of the backup metadata database and the content index database into a single backup and content index database to avoid the need to perform synchronization operations. By using a single backup and content index database, the content indexing system also reduces the computing performance costs that would be associated with the synchronization operations as the amount of indexed content increases, thereby solving scalability issues.