Index Handler Multiplexing Data Buckets for Resource Optimization
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Solution Overview
Problem
Conventional indexing systems create multiple indices per user, leading to degradation in indexer performance and increased system resource demands due to the need to load and maintain all indexes in memory for search operations.
Innovation Solution
The system employs an index handler to multiplex data by generating slots and data buckets, allowing for dynamic attachment and detachment of data buckets to slots, optimizing resource usage and enabling efficient search operations across multiple indices without the need for excessive index resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional indexing systems create an index per user to maintain separation of customer data, then data security and user isolation are improved, but indexer performance degrades and system resource demands increase
Solution Approach 1:
Multiple user indices are merged into a single shared index structure where data from different users is stored together in the same index. This consolidation allows the system to maintain data separation through logical access controls while physically sharing the index infrastructure, thereby improving indexer performance and reducing resource overhead.
Solution Approach 2:
A single index structure is designed to serve multiple users simultaneously, making it universal in its functionality. The index can handle search and data retrieval operations for different users without requiring separate index instances, thus maintaining data security through user-specific access permissions while eliminating the performance degradation associated with multiple separate indices.
2Reliability
If conventional indexing systems create an index per user, then user data isolation is maintained, but the number of indices increases leading to higher memory requirements
Solution Approach 1:
User data is merged into a single shared index structure rather than maintaining separate index files for each user. This consolidation dramatically reduces the total memory footprint by eliminating redundant index structures, while user data isolation is maintained through logical access controls and user-specific metadata tracking within the shared index.
Solution Approach 2:
Instead of creating separate physical copies of index structures for each user, the system uses a single shared index that can be accessed by multiple users. User-specific data is identified through metadata or indexing keys rather than through separate index files, thereby reducing memory consumption while maintaining data isolation.
3Adaptability or versatility
If multiple indices are maintained in memory for search operations, then search coverage is improved, but system resource demands increase
Solution Approach 1:
Multiple user-specific search capabilities are merged into a single shared index structure. The index is designed to accommodate data from multiple users and supports search operations across all user data through unified search interfaces and query processing, thereby maintaining comprehensive search coverage while reducing the system resources required compared to maintaining multiple separate indices in memory.
Data Source
AI summary
Disclosed herein are systems and method for multiplexing data of an underlying index. In an exemplary aspect, an index handler may: search for a data file in a plurality of data buckets associated with an index, wherein at least one respective data bucket of a plurality of data buckets is attached to a respective slot of a plurality of slots; identify, based on the searching, a first data bucket of the plurality of data buckets that comprises the data file; in response to determining that the first data bucket is not attached to any of the plurality of slots, attach the first data bucket to a first slot of the plurality of slots; and enable access to the data file via the first data bucket attached to the first slot.