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Mastering Elastic Stack

You're reading from   Mastering Elastic Stack Dive into data analysis with a pursuit of mastering ELK Stack on real-world scenarios.

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786460011
Length 526 pages
Edition 1st Edition
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Authors (2):
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Ravi Kumar Gupta Ravi Kumar Gupta
Author Profile Icon Ravi Kumar Gupta
Ravi Kumar Gupta
Yuvraj Gupta Yuvraj Gupta
Author Profile Icon Yuvraj Gupta
Yuvraj Gupta
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Toc

Table of Contents (13) Chapters Close

Preface 1. Elastic Stack Overview FREE CHAPTER 2. Stepping into Elasticsearch 3. Exploring Logstash and Its Plugins 4. Kibana Interface 5. Using Beats 6. Elastic Stack in Action 7. Customizing Elastic Stack 8. Elasticsearch APIs 9. X-Pack: Security and Monitoring 10. X-Pack: Alerting, Graph, and Reporting 11. Best Practices 12. Case Study-Meetup

Ingest nodes

As we learnt in the previous section, ingest nodes help to preprocess things before a document is indexed. Before a bulk request or index operations, the ingest node intercepts the request and does required processing on the document. An example of such a processor can be the date processor, which is used to parse the dates in fields. Another example is a convert processor, which converts a field value to a target type, for example, string to integer. A number of processors are available at: https://www.elastic.co/guide/en/elasticsearch/reference/5.1/ingest-processors.html.

These kinds of nodes are helpful when a huge processing happens and we do not want a data node or master node to engage in processing. Dedicated ingest nodes can help to reduce the load significantly. It is best to set node.ingest as false for data and master nodes.

To understand how ingest nodes work with pipelines, let's follow these steps. Let's take the example of our library index and type...

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