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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
4
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
5
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
8
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
9
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

Default Apache Lucene scoring explained

A very important part of the querying process in Apache Lucene is scoring. Scoring is the process of calculating the score property of a document in a scope of a given query. What is a score? A score is a factor that describes how well the document matched the query. In this section, we'll look at the default Apache Lucene scoring mechanism: the TF/IDF (term frequency/inverse document frequency) algorithm and how it affects the returned document. Knowing how this works is valuable when designing complicated queries and choosing which queries parts should be more relevant than the others. Knowing the basics of how scoring works in Lucene allows us to tune queries more easily and the results retuned by them to match our use case.

When a document is matched

When a document is returned by Lucene, it means that it matched the query we've sent. In such a case, the document is given a score. Sometimes, the score is the same for all the documents...

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Mastering Elasticsearch
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