Book Image

Mastering Kibana 6.x

Book Image

Mastering Kibana 6.x

Overview of this book

Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana’s Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities.
Table of Contents (21 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Avoiding large document indexing


We should avoid indexing large documents since Elasticsearch has a default maximum content size, and if we try to index a document that crosses this limit, Elasticsearch will refuse to index the document. Elasticsearch's default maximum length for any document is 100 MB, and it is defined using the following configuration:

http.max_content_length

Although we can increase the default max_content_length in Elasticsearch, it is not recommended to increase the limit. Large document sizes increase network load, and we will lose the benefit of Elasticsearch because the main advantage of Elasticsearch lies in the search capabilities and speed that it provides. If we index a large document, it puts stress on memory usage, disks, and also on the network.

Note

We have the Lucene maximum content limit, which is about 2 GB.

 

It is required to understand the data that we are going to index before indexing it into Elasticsearch, such as categorizing it in order to conclude...