Swift MySQL RESAR Part 8

The final installment of this eight-part series about the Swift MySQL RESAR saga. In Part 7, we presented the performance results for Swift RESAR and the Stream Star Schema. In this post we will complete this series by summarizing the project and attempt to draw some conclusions.

Powerful Extension to Swift Cloud Storage

In this project, we have described and demonstrated a powerful extension to Swift cloud storage: Swift RESAR. This facility greatly empowers Swift Administrators in managing large numbers of cloud devices. It also fully enables said administrators to employ mathematical models so that device reliability can be optimized.

Previously, Swift ignored device management. Swift RESAR extends this project in a painless manner that is highly scalable. This project was implemented in the popular and powerful programming language – Python, thus enabling further development in this area. We thus welcome outside input to the Swift RESAR project. Swift is, after all, OpenSource. This project has also presented a new approach to processing data streams: the stream star schema.

High Data Stream Rates

This new type of star schema is proposed to accommodate high data stream rates: giga bits per second, by reducing insertion time to a constant. An experimental implementation of both star schema types on the RESAR data stream showed that stream star schema insertion performance is constant and superior to star schema insertion performance by a factor of over 1,000, which is 3 orders of magnitude. Our experiments also show that stream star schema query time was 60 – 562 times faster than the star schema database, which is significant. So not only does the stream star schema have significant insert performance over the star schema, it also has significant query performance. We have thus greatly enabled device management for Swift in both function and performance.

As to the future. We should explore the mathematical modeling that is enabled by the Swift RESAR project. Subjects like Graph Coloring.