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)

How iSAX is constructed

This section is going to describe the way an iSAX index is constructed. All the presented information is based on the research paper that describes iSAX. The logical steps are as follows:

  • We begin with a node that is the root of the iSAX index. The root contains no actual data (subsequences) but it contains pointers to all nodes with the specified segments value and a cardinality value of 2, which is a single bit that can only have two values, 0 and 1.
  • After that, we construct the children of the root node, which at this initial point are all terminal nodes without any subsequences in them.
  • We now begin adding subsequences to the children of the root based on their SAX representation.
  • When the threshold value of a terminal node is reached, we perform the splits, based on the specified promotion strategy, and we distribute the subsequences to the two newly created terminal nodes.
  • The process goes on until all subsequences have been inserted...