Book Image

Machine Learning with the Elastic Stack - Second Edition

By : Rich Collier, Camilla Montonen, Bahaaldine Azarmi
5 (1)
Book Image

Machine Learning with the Elastic Stack - Second Edition

5 (1)
By: Rich Collier, Camilla Montonen, Bahaaldine Azarmi

Overview of this book

Elastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively. With the addition of machine learning, a key commercial feature, the Elastic Stack makes this process even more efficient. This updated second edition of Machine Learning with the Elastic Stack provides a comprehensive overview of Elastic Stack's machine learning features for both time series data analysis as well as for classification, regression, and outlier detection. The book starts by explaining machine learning concepts in an intuitive way. You'll then perform time series analysis on different types of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you'll deploy machine learning within Elastic Stack for logging, security, and metrics. Finally, you'll discover how data frame analysis opens up a whole new set of use cases that machine learning can help you with. By the end of this Elastic Stack book, you'll have hands-on machine learning and Elastic Stack experience, along with the knowledge you need to incorporate machine learning in your distributed search and data analysis platform.
Table of Contents (19 chapters)
1
Section 1 – Getting Started with Machine Learning with Elastic Stack
4
Section 2 – Time Series Analysis – Anomaly Detection and Forecasting
11
Section 3 – Data Frame Analysis

Using Painless for advanced transform configurations

As we have seen in many of the previous sections, the built-in pivot and aggregation options allow us to analyze and interrogate our data in various ways. However, for more custom or advanced use cases, the built-in functions may not be flexible enough. For these use cases, we will need to write custom pivot and aggregation configurations. The flexible scripting language that is built into Elasticsearch, Painless, allows us to do this.

In this section, we will introduce Painless, illustrate some tools that are useful when working with Painless, and then show how Painless can be applied to create custom Transform configurations.

Introducing Painless

Painless is a scripting language that is built into Elasticsearch. We will take a look at Painless in terms of variables, control flow constructs, operations, and functions. These are the basic building blocks that will help you develop your own custom scripts to use with transforms...