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The Definitive Guide to OpenSearch

The Definitive Guide to OpenSearch

By : Jon Handler, Soujanya Konka, Prashant Agrawal
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The Definitive Guide to OpenSearch

The Definitive Guide to OpenSearch

By: Jon Handler, Soujanya Konka, Prashant Agrawal

Overview of this book

From seasoned data professionals managing billions of records to aspiring analysts exploring diverse datasets, this guide is for users at all levels who want to make the most of OpenSearch's capabilities and functionalities. Written by distinguished AWS Solutions Architects Jon Handler, Ph.D., a former search engine developer, Prashant Agrawal, a search specialist, and Soujanya Konka, an expert in large-scale data migrations, this guide brings together deep technical expertise with practical, hands-on knowledge of implementing OpenSearch in real-world scenarios. Starting with an introduction to OpenSearch, you’ll get to grips with the key features before delving into essential topics such as installing OpenSearch, ingesting data, crafting queries, visualizing results, ensuring security, and optimizing performance. Each concept is accompanied by practical examples and tutorials, allowing you to grasp the material through hands-on experience. Keeping up with OpenSearch’s new releases and updates, this book equips you to fully leverage its potential through real-world scenarios and examples that demonstrate how OpenSearch works. Whether enhancing your search experience or extracting insightful analytics from data, The Definitive Guide to OpenSearch provides developers, engineers, data scientists, and system administrators with the tools needed to thrive.
Table of Contents (21 chapters)
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1
Part 1: Getting Started with OpenSearch: Fundamentals and Deployment
5
Part 2: Data Management and Discovery: Indexing, Querying, and Visualization
10
Part 3: Extending OpenSearch: Plugins, AI Integration, and Application Development
15
Part 4: Securing and Optimizing OpenSearch: Administration Best Practices
20
Index

Query processing

When you send a query to OpenSearch, the query passes through a number of processing steps before OpenSearch sends back the result.

Figure 5.1: Query processing chain

As shown in Figure 5.1, first, your search request lands on a coordinating node. Depending on how you set up your cluster and how you send your requests to the cluster, the coordinating node might be a dedicated coordinator node, a data node, an ML node, or a cluster manager node. Dedicated coordinator nodes are a good idea for high-scale workloads, but usually, you’ll use data nodes as request coordinators (see Chapters 13 and 14 for more on scaling, including dedicated coordinators).

Request queues and thread pools

In order to manage the work that each node performs, OpenSearch creates thread pools with associated queues to hold tasks for the threads. You can use the _cat/thread_pool API call to see all of the queues. (Note: the response shows a snapshot...

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