Elasticsearch in Action

498 Pages·2015·15.01 MB·English

Radu Gheorghe
Matthew Lee Hinman
Roy Russo
M A N N I N G
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Elasticsearch in Action
Licensed to Thomwaws wS.nite-eabdo <[email protected]>
Licensed to Thomwaws wS.nite-eabdo <[email protected]>
Elasticsearch
in Action
RADU GHEORGHE
MATTHEW LEE HINMAN
ROY RUSSO
MANNING
SHELTER ISLAND
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brief contents
PART 1 .......................................................................................1
1 ■ Introducing Elasticsearch 3
2 ■ Diving into the functionality 20
3 ■ Indexing, updating, and deleting data 53
4 ■ Searching your data 83
5 ■ Analyzing your data 118
6 ■ Searching with relevancy 148
7 ■ Exploring your data with aggregations 179
8 ■ Relations among documents 215
PART 2 ...................................................................................259
9 ■ Scaling out 261
10 ■ Improving performance 293
11 ■ Administering your cluster 340
v
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contents
preface xv
acknowledgments xvii
about this book xix
about the cover illustration xxiii
PART 1 ........................................................................ 1
1 Introducing Elasticsearch 3
1.1 Solving search problems with Elasticsearch 4
Providing quick searches 5 ■ Ensuring relevant results 6
Searching beyond exact matches 7
1.2 Exploring typical Elasticsearch use cases 8
Using Elasticsearch as the primary back end 9
Adding Elasticsearch to an existing system 9
Using Elasticsearch with existing tools 11
Main Elasticsearch features 12 ■ Extending Lucene
functionality 13 ■ Structuring your data in Elasticsearch 15
Installing Java 15 ■ Downloading and starting
Elasticsearch 16 ■ Verifying that it works 16
1.3 Summary 18
vii
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viii CONTENTS
2 Diving into the functionality 20
2.1 Understanding the logical layout: documents, types,
and indices 22
Documents 23 ■ Types 24 ■ Indices 25
2.2 Understanding the physical layout: nodes and shards 25
Creating a cluster of one or more nodes 26 ■ Understanding
primary and replica shards 27 ■ Distributing shards in
a cluster 30 ■ Distributed indexing and searching 31
2.3 Indexing new data 32
Indexing a document with cURL 32 ■ Creating an index
and mapping type 35 ■ Indexing documents from the
code samples 36
2.4 Searching for and retrieving data 37
Where to search 38 ■ Contents of the reply 39
How to search 42 ■ Getting documents by ID 45
2.5 Configuring Elasticsearch 46
Specifying a cluster name in elasticsearch.yml 46
Specifying verbose logging via logging.yml 47
Adjusting JVM settings 47
2.6 Adding nodes to the cluster 48
Starting a second node 50 ■ Adding additional nodes 51
2.7 Summary 52
3 Indexing, updating, and deleting data 53
3.1 Using mappings to define kinds of documents 54
Retrieving and defining mappings 56 ■ Extending an
existing mapping 57
3.2 Core types for defining your own fields in documents 58
String 59 ■ Numeric 61 ■ Date 62 ■ Boolean 63
3.3 Arrays and multi-fields 63
Arrays 64 ■ Multi-fields 64
3.4 Using predefined fields 65
Controlling how to store and search your documents 66
Identifying your documents 68
3.5 Updating existing documents 70
Using the update API 72 ■ Implementing concurrency control
through versioning 74
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CONTENTS ix
3.6 Deleting data 78
Deleting documents 78 ■ Deleting indices 80
Closing indices 81 ■ Re-indexing sample documents 81
3.7 Summary 82
4 Searching your data 83
4.1 Structure of a search request 84
Specifying a search scope 85 ■ Basic components of
a search request 86 ■ Request body–based search request 88
Understanding the structure of a response 91
4.2 Introducing the query and filter DSL 92
Match query and term filter 92 ■ Most used basic queries
and filters 95 ■ Match query and term filter 102
Phrase_prefix query 103
4.3 Combining queries or compound queries 105
bool query 105 ■ bool filter 107
4.4 Beyond match and filter queries 109
Range query and filter 109 ■ Prefix query and filter 111
Wildcard query 112
4.5 Querying for field existence with filters 113
Exists filter 114 ■ Missing filter 114 ■ Transforming any
query into a filter 115
4.6 Choosing the best query for the job 116
4.7 Summary 117
5 Analyzing your data 118
5.1 What is analysis? 119
Character filtering 120 ■ Breaking into tokens 120
Token filtering 120 ■ Token indexing 120
5.2 Using analyzers for your documents 121
Adding analyzers when an index is created 122
Adding analyzers to the Elasticsearch configuration 123
Specifying the analyzer for a field in the mapping 124
5.3 Analyzing text with the analyze API 126
Selecting an analyzer 127 ■ Combining parts to create
an impromptu analyzer 127 ■ Analyzing based on a field’s
mapping 128 ■ Learning about indexed terms using the
terms vectors API 128
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