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Quasi-light Storage for Optical Data Packets

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A Distributed Storage Model for Healthcare Big Data Designed on HBase.

Lu Zhang, Qi Li, Ye Li

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 17, 2018

Summary

A new snowflake model using HBase efficiently manages large healthcare datasets, outperforming traditional models. Index tables significantly boost query speed for real-time health record analysis.

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Area of Science:

Health Informatics
Database Management Systems
Big Data Analytics

Background:

Traditional relational database management systems (RDBMS) face limitations with the exponential growth of healthcare data, including scalability, unstructured data storage, concurrency, and cost.
Efficient management of large-scale health records is crucial for modern healthcare applications.

Purpose of the Study:

To propose and evaluate a novel snowflake data model based on HBase for efficient management of large-scale healthcare data.
To introduce a guideline for designing index tables tailored for healthcare data processing applications.

Main Methods:

Developed a snowflake model utilizing HBase with a multi-table structure and three types of index tables.
Proposed a guideline for index table design to meet diverse healthcare data processing needs.
Conducted benchmark tests on a 750 million record dataset, comparing the snowflake model against a traditional tall-table HBase model using six query types.

Main Results:

The snowflake model demonstrated superior efficiency compared to the traditional tall-table model on HBase.
The implementation of index tables significantly enhanced query speeds for both models, enabling real-time queries.
The proposed model proved effective in managing large volumes of health records.

Conclusions:

The snowflake model offers an advantageous alternative for managing large-scale healthcare data.
Index tables are critical for improving query performance and enabling real-time analytics in healthcare databases.
The developed guideline supports the design of effective index tables for healthcare data applications.