Book Image

Time Series Indexing

By : Mihalis Tsoukalos
Book Image

Time Series Indexing

By: Mihalis Tsoukalos

Overview of this book

Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX. The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript. By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data.
Table of Contents (11 chapters)

Visualizing an iSAX index

In this section, we are going to begin visualizing iSAX indexes.

As in most areas of computing, your visualizations are going to improve over time. The first visualizations are usually less beautiful and/or informative than later ones. So, we are going to experiment and try things before we end up with a good-looking iSAX visualization.

As visualizations include personal taste, your visualization of choice might differ from the ones used in this chapter. However, we need to start doing and improve in the process!

Let us begin with the visualization of the next subsection.

A personal story

At the time of writing this book, I am doing research related to iSAX. In one of my experiments, I ran a utility that creates two iSAX indexes and joins them in a more sophisticated way than the one presented in Chapter 5. The utility processed 2 time series with 500,000 elements each and ran for more than 18 days! Additionally, it took the same utility about...