Search Core Reindexing Based on Workload Characteristics
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Solution Overview
Problem
Existing search engine indexing technologies face challenges in efficiently and accurately reindexing data due to version incompatibilities, schema changes, data integrity issues, and performance optimization requirements, which can lead to inconsistent search results and degraded performance.
Innovation Solution
A system and method for efficient core reindexing that analyzes workload characteristics and metadata to determine the need for reindexing, selecting an appropriate configuration, and executing the reindexing operation while managing resources to minimize disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reindexing is performed frequently to maintain data accuracy and compatibility with system upgrades, then data integrity and system compatibility are improved, but system performance and resource consumption deteriorate due to the intensive computational requirements of reindexing operations
Solution Approach 1:
The patent implements dynamic reindexing by continuously monitoring workload characteristics and system conditions to determine when reindexing should be performed. The system adjusts reindexing frequency and timing based on real-time conditions, performing reindexing operations when system resources are available and workload is low, thereby maintaining data integrity while minimizing performance impact.
Solution Approach 2:
The patent performs reindexing operations in advance during periods of low system activity or scheduled maintenance windows, preparing updated indexes before they are needed. This preliminary action ensures data accuracy and compatibility are maintained while avoiding performance degradation during peak usage periods.
2Adaptability or versatility
If reindexing operations are performed to ensure compatibility with system upgrades and schema changes, then system adaptability and version compatibility are improved, but reindexing time and operational disruption increase
Solution Approach 1:
The system dynamically assesses workload characteristics and system conditions to determine the optimal timing for reindexing operations. By monitoring real-time conditions, the system schedules reindexing during appropriate windows when the impact on operational time is minimized, while still ensuring compatibility with system upgrades and schema changes.
Solution Approach 2:
The patent implements periodic reindexing based on monitored system conditions and workload patterns. Instead of continuous or fixed-schedule reindexing, the system performs reindexing operations periodically when conditions indicate it is appropriate, reducing overall reindexing time while maintaining version compatibility.
3Measurement precision
If comprehensive reindexing is performed on all cores to maintain search accuracy, then search result accuracy is improved, but computational resources and processing time increase significantly
Solution Approach 1:
The patent applies local quality by performing reindexing operations selectively on specific cores or data subsets rather than uniformly across all cores. The system identifies which cores require reindexing based on monitored conditions and performs targeted reindexing only where necessary, maintaining search accuracy for affected areas while conserving computational resources.
Solution Approach 2:
The system performs partial reindexing by updating only the portions of indexes that require refreshment based on monitored conditions, rather than performing complete reindexing of all cores. This partial action maintains search accuracy for updated data while significantly reducing computational resource consumption compared to comprehensive reindexing.
Data Source
AI summary
Techniques are disclosed for performing reindexing operations for indexes associated with search engine cores. A system determines that a core is associated with a core index that is a candidate for reindexing. The core is configured to execute an instance of a core index that includes a mapping of terms to metadata. Responsive to determining that the core index is a candidate for reindexing, the system performs a reindexing operation at least by (a) detecting workload characteristics associated with the core index, (b) based at least in part on the workload characteristics, selecting a configuration for the reindexing operation, and (c) initiating the reindexing operation using the selected configuration.