Data Repartitioning via Redundant Partitions
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Solution Overview
Problem
Current data storage systems face inefficiencies and downtime during repartitioning processes, particularly as transaction data volume increases, leading to delays and increased costs due to the unavailability of logical partitions and the need for frequent data redistribution.
Innovation Solution
Implementing a system that automatically repartitions data among multiple logical partitions, allowing for efficient data redistribution and maintaining redundancy to ensure continuous service by identifying available memory partitions, deleting data portions, and assigning redundant partitions to maintain data integrity and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data storage systems add logical partitions by adding additional computing machines to increase data storage capacity, then the data storage capacity is improved, but the repartitioning process causes logical partitions to be unavailable for memory access, resulting in processing and transaction delays
Solution Approach 1:
The system performs preliminary actions by creating redundant partitions before the repartitioning process begins. These redundant partitions are pre-configured and populated with data in advance, so that when repartitioning occurs, the system can immediately switch to using the pre-prepared redundant partitions, avoiding service interruptions and delays during the actual data redistribution process
Solution Approach 2:
The system creates copies of data in redundant partitions that mirror or supplement the primary partitions. These copied data sets are maintained in advance and can be quickly activated during repartitioning operations, allowing the system to maintain service availability while data is being redistributed across the expanded storage capacity
2Stability of the object's composition
If the system performs complete data redistribution during repartitioning to balance data across all partitions, then data balance is improved, but the unavailability of partitions during the process increases, causing service interruptions
Solution Approach 1:
The system performs preliminary population of redundant partitions with data before the repartitioning process. This advance preparation ensures that when repartitioning begins, balanced data distributions are already in place in the redundant partitions, allowing the system to maintain service availability while achieving data balance without complete redistribution interruptions
Solution Approach 2:
The redundant partitions act as intermediaries during the repartitioning process. They serve as temporary data repositories that allow the system to redistribute data across partitions while maintaining continuous service availability, as the intermediaries hold data that can be quickly accessed or migrated without interrupting operations
3Reliability
If the system maintains redundant partitions with complete data copies to ensure service continuity, then service availability is improved, but the storage space required and the time needed to populate redundant partitions increase
Solution Approach 1:
The system applies local quality by making redundant partitions available at specific locations in the partition hierarchy where they are most needed for continuity. Rather than uniformly duplicating all data across all redundant partitions, the system selectively populates redundant partitions with data based on local requirements, reducing overall storage space while maintaining service availability where critical
Solution Approach 2:
The system uses partial action by populating redundant partitions with only the necessary portions of data required for service continuity, rather than complete copies of all data. This selective population reduces the storage space requirement while still providing sufficient redundancy to maintain service availability during repartitioning operations
Data Source
AI summary
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