Reference Map Normalization for In-Memory Data Grids
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In-memory data grids face inefficiencies due to recurring instances of reference data across multiple object instances, leading to significant memory usage and performance impacts from distributed data access across interconnected Java Virtual Machines (JVMs).
Innovation Solution
Applying normalization techniques to identify and create a reference map for reference data, replicating this map across all partitions of the in-memory data grid, and updating object fields to reference the map, allowing for efficient access and storage of reference data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If reference data is stored in each object instance across multiple partitions, then data access is simplified and fast, but memory usage increases significantly due to redundant storage
Solution Approach 1:
The patent extracts reference data from individual object instances and centralizes it in a separate reference map structure. This allows objects to reference the centralized data rather than containing copies, reducing memory usage while maintaining fast access through the reference map.
Solution Approach 2:
The patent merges all reference data into a single centralized reference map that is shared across all partitions. This consolidation eliminates redundant storage of identical reference data across multiple object instances while maintaining accessibility through the unified reference map.
2Reliability
If reference data is replicated across all partitions, then data availability and access speed improve, but memory consumption increases due to redundant copies
Solution Approach 1:
The patent introduces a reference map as an intermediary layer between object instances and reference data. This reference map serves as a centralized mediator that all partitions can access, ensuring data availability without requiring each partition to maintain redundant copies of the reference data.
3Productivity
If normalization techniques are applied to create a reference map, then memory efficiency and scalability improve, but system complexity increases due to additional data structures
Solution Approach 1:
The patent creates a universal reference map structure that serves multiple functions: storing reference data, providing centralized access across partitions, and enabling efficient memory utilization. This multi-functional approach consolidates what would otherwise require multiple separate mechanisms into a single unified structure.
Data Source
AI summary
Embodiments relate to providing normalization techniques for reference data in an in-memory data grid. An aspect includes monitoring object creation and access in an in-memory data grid and identifying reference data in an object field of a plurality of object instances. A reference map for the object field is created and the reference map is replicated across all partitions of the in-memory data grid. The reference data of an embodiment is stored in the reference map and the object field is updated to identify the reference map. Accordingly, the reference data may be accessed using the created reference map.