Multi-Queue Architecture for Content Mining Crawler Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In content mining systems, the inefficiencies arise from converters processing data at different rates than crawlers, leading to queue backlogs and unnecessary downtime due to the need for throttling or suspending the crawler, especially in tape storage systems where physical movement inefficiencies occur.
Innovation Solution
Implementing a plurality of queues associated with different converters, each customized in size based on the processing speed of the corresponding converter type, allowing for incremental processing and avoiding overaccumulation of similar file types in a single queue, thereby preventing downtime and maintaining continuous data crawling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single queue is used to process all files, then device complexity is reduced, but queue backlogs occur and processing efficiency deteriorates when converters process data at different rates
Solution Approach 1:
The patent divides the single queue into multiple queues, with each queue dedicated to a specific converter type. This segmentation allows each converter to process its specific file type independently without causing backlogs in other queues, thereby improving overall processing efficiency while maintaining manageable system complexity through structured organization.
2Productivity
If the crawler is throttled or suspended to match converter processing speeds, then queue backlogs are prevented, but loss of time increases and continuous crawling is interrupted
Solution Approach 1:
By segmenting the processing pipeline into separate queues for each converter type, the system allows the crawler to continue operating at full speed while each converter processes files at its own optimized rate. This eliminates the need to throttle or suspend the crawler, preventing downtime and maintaining continuous processing.
Solution Approach 2:
The multiple queue structure enables continuous crawling without interruption. While one converter is processing a batch of files, other converters can simultaneously process different file types from their respective queues, ensuring that the crawler never has to wait or suspend, thus maintaining continuous useful action.
3Adaptability or versatility
If converters process data at different rates, then processing flexibility is improved, but queue backlogs form and processing efficiency deteriorates
Solution Approach 1:
The patent implements separate queues for each converter type, allowing each converter to process its specific file type at its own rate without affecting other converters. This segmentation maintains processing flexibility for different file types while preventing queue backlogs, thereby preserving processing efficiency.
Solution Approach 2:
The queues act as intermediaries between the crawler and the converters, buffering the differences in processing rates. Each queue manages its own flow of files to its corresponding converter, allowing flexible processing rates for different file types while preventing backlogs from propagating to other parts of the system.
Data Source
AI summary
Described is a content mining system comprising a crawler configured to retrieve a plurality of files from a data storage system. The content mining system further comprises a plurality of converters configured to extract data from the plurality of files retrieved by the crawler from the data storage system, where each of the plurality of converters is configured to process a respective type of data. The content mining system further comprises a plurality of queues interposed between the crawler and the plurality of converters, where each queue is associated with a single converter.