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  • Book Overview & Buying Mastering Elasticsearch
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Mastering Elasticsearch

Mastering Elasticsearch - Second Edition

By : Marek Rogozinski
4.3 (9)
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Mastering Elasticsearch

Mastering Elasticsearch

4.3 (9)
By: Marek Rogozinski
Buy this Book

Overview of this book

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.
Table of Contents (11 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction to Elasticsearch
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1. Introduction to Elasticsearch
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Introducing Apache Lucene
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Introducing Elasticsearch
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The story
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Summary
2
2. Power User Query DSL
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2. Power User Query DSL
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Default Apache Lucene scoring explained
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Query rewrite explained
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Query templates
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Handling filters and why it matters
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Choosing the right query for the job
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Summary
3
3. Not Only Full Text Search
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3. Not Only Full Text Search
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Query rescoring
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Controlling multimatching
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Significant terms aggregation
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Documents grouping
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Relations between documents
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Scripting changes between Elasticsearch versions
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Summary
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4. Improving the User Search Experience
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4. Improving the User Search Experience
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Correcting user spelling mistakes
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Improving the query relevance
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Summary
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5. The Index Distribution Architecture
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5. The Index Distribution Architecture
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Choosing the right amount of shards and replicas
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Routing explained
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Altering the default shard allocation behavior
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Query execution preference
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Summary
6
6. Low-level Index Control
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6. Low-level Index Control
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Altering Apache Lucene scoring
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Choosing the right directory implementation – the store module
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NRT, flush, refresh, and transaction log
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Segment merging under control
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When it is too much for I/O – throttling explained
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Understanding Elasticsearch caching
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Summary
7
7. Elasticsearch Administration
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7. Elasticsearch Administration
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Discovery and recovery modules
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The human-friendly status API – using the Cat API
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Backing up
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Federated search
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Summary
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8. Improving Performance
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8. Improving Performance
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Using doc values to optimize your queries
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Knowing about garbage collector
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Benchmarking queries
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Very hot threads
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Scaling Elasticsearch
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Summary
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9. Developing Elasticsearch Plugins
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9. Developing Elasticsearch Plugins
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Creating the Apache Maven project structure
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Understanding the basics
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Creating custom REST action
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Creating the custom analysis plugin
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Summary
10
Index
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Index

Using doc values to optimize your queries

In the Understanding Elasticsearch caching section of Chapter 6, Low-level Index Control we described caching: one of many ways that allow us to improve Elasticsearch's outstanding performance. Unfortunately, caching is not a silver bullet and, sometimes, it is better to avoid it. If your data is changing rapidly and your queries are very unique and not repeatable, then caching won't really help and can even make your performance worse sometimes.

The problem with field data cache

Every cache is based on a simple principle. The main assumption is that to improve performance, it is worth storing some part of the data in the memory instead of fetching from slow sources such as spinning disks, or to save the system a need to recalculate some processed data. However, caching is not free and it has its price—in terms of Elasticsearch, the cost of caching is mostly memory. Depending on the cache type, you may only need to store recently used data, but again...

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Mastering Elasticsearch
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