Tiered Index Architecture for Database Insert Bottlenecks
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Solution Overview
Problem
Database systems face inefficiencies in inserting new data into sorted indices as the index grows, requiring longer read and move times, and struggle to balance dense packing with incremental inserts, leading to increased disk I/O reads during querying.
Innovation Solution
A tiered index architecture is introduced, dividing the index into multiple sorted tiers where data across tiers can remain unsorted, allowing for efficient insertion into smaller tiers, and dynamic tier sizing to maintain dense packing and reduce insertion time, with data flowing periodically to lower tiers and merging operations proportional to insert loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the index is densely packed to minimize disk I/O reads during querying, then storage efficiency is improved, but the time required for incremental insert operations increases due to more splitting operations
Solution Approach 1:
The patent divides the index into multiple segments or tiers, where each segment can be independently managed. This segmentation allows the system to maintain dense packing in each segment while enabling efficient insert operations by adding new data to appropriate segments without requiring extensive splitting operations across the entire index structure.
2Loss of time
If empty spaces are allocated in the index to facilitate faster incremental inserts, then insert operation time is reduced, but disk I/O reads increase during querying due to sparser storage
Solution Approach 1:
The patent applies local quality by allowing different regions or segments of the index to have different density characteristics. Some segments can be densely packed for efficient querying while others can have more space allocated for efficient inserts, optimizing both operations locally rather than requiring uniform characteristics across the entire index.
3Productivity
If a segmented index approach is used to maintain separate indices over different data ranges, then insert efficiency is improved, but accurate data model forecasting becomes critical and segment size variation can create bottlenecks
Solution Approach 1:
The patent implements dynamic segment management where segment boundaries and sizes can adapt based on actual data distribution and access patterns rather than relying on static forecasts. This allows the system to automatically balance segment sizes and maintain efficiency without requiring accurate predictive modeling of future data characteristics.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for storing data in a database using a tiered index architecture, An embodiment operates by creating a first tier and assigning a first threshold size to the first tier. When the first tier exceed the first threshold size, the system pushes data from the first tier into a second tier.