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  • Book Overview & Buying Learning ELK Stack
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Learning ELK Stack

Learning ELK Stack

By : Saurabh Chhajed
3.2 (5)
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Learning ELK Stack

Learning ELK Stack

3.2 (5)
By: Saurabh Chhajed

Overview of this book

The ELK stack—Elasticsearch, Logstash, and Kibana, is a powerful combination of open source tools. Elasticsearch is for deep search and data analytics. Logstash is for centralized logging, log enrichment, and parsing. Kibana is for powerful and beautiful data visualizations. In short, the Elasticsearch ELK stack makes searching and analyzing data easier than ever before. This book will introduce you to the ELK (Elasticsearch, Logstash, and Kibana) stack, starting by showing you how to set up the stack by installing the tools, and basic configuration. You’ll move on to building a basic data pipeline using the ELK stack. Next, you’ll explore the key features of Logstash and its role in the ELK stack, including creating Logstash plugins, which will enable you to use your own customized plugins. The importance of Elasticsearch and Kibana in the ELK stack is also covered, along with various types of advanced data analysis, and a variety of charts, tables ,and maps. Finally, by the end of the book you will be able to develop full-fledged data pipeline using the ELK stack and have a solid understanding of the role of each of the components.
Table of Contents (12 chapters)
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11
Index

Input dataset

For our example, the dataset that we are going to use here is the daily Google (GOOG) Quotes price dataset over a 6 month period from July 1, 2014 to December 31, 2014. This is a good dataset to understand how we can quickly analyze simple datasets, such as these, with ELK.

Note

This dataset can be easily downloaded from the following source:

http://finance.yahoo.com/q/hp?s=GOOG

Data format for input dataset

The most significant fields of this dataset are Date, Open Price, Close Price, High Price, Volume, and Adjusted Price.

The following table shows some of the sample data from the dataset. The actual dataset is in the CSV format.

Date

Open

High

Low

Close

Volume

Adj Close

Dec 31, 2014

531.25

532.60

525.80

526.40

1,368,200

526.40

Dec 30, 2014

528.09

531.15

527.13

530.42

876,300

530.42

Dec 29, 2014

532.19

535.48

530.01

530.33

2,278,500

530.33

Dec 26, 2014

528.77

534.25

527.31

534.03

1,036,000

534.03

Dec 24, 2014

530.51

531.76

527.02

528.77...

CONTINUE READING
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Learning ELK Stack
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