5. Search, Queries, and Filters | ElasticSearch Cookbook

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Table Of Contents

ElasticSearch Cookbook - Second Edition

By : Alberto Paro

4.1 (7)

ElasticSearch Cookbook

4.1 (7)

By: Alberto Paro

Overview of this book

If you are a developer who implements ElasticSearch in your web applications and want to sharpen your understanding of the core elements and applications, this is the book for you. It is assumed that you’ve got working knowledge of JSON and, if you want to extend ElasticSearch, of Java and related technologies.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Sections

Conventions

Reader feedback

Customer support

Free Chapter

1. Getting Started

1. Getting Started

Introduction

Understanding nodes and clusters

Understanding node services

Managing your data

Understanding clusters, replication, and sharding

Communicating with ElasticSearch

Using the HTTP protocol

Using the native protocol

Using the Thrift protocol

2. Downloading and Setting Up

2. Downloading and Setting Up

Introduction

Downloading and installing ElasticSearch

Setting up networking

Setting up a node

Setting up for Linux systems

Setting up different node types

Installing plugins in ElasticSearch

Installing a plugin manually

Removing a plugin

Changing logging settings

3. Managing Mapping

3. Managing Mapping

Introduction

Using explicit mapping creation

Mapping base types

Mapping arrays

Mapping an object

Mapping a document

Using dynamic templates in document mapping

Managing nested objects

Managing a child document

Adding a field with multiple mappings

Mapping a geo point field

Mapping a geo shape field

Mapping an IP field

Mapping an attachment field

Adding metadata to a mapping

Specifying a different analyzer

Mapping a completion suggester

4. Basic Operations

4. Basic Operations

Introduction

Creating an index

Deleting an index

Opening/closing an index

Putting a mapping in an index

Getting a mapping

Deleting a mapping

Refreshing an index

Flushing an index

Optimizing an index

Checking if an index or type exists

Managing index settings

Using index aliases

Indexing a document

Getting a document

Deleting a document

Updating a document

Speeding up atomic operations (bulk operations)

Speeding up GET operations (multi GET)

5. Search, Queries, and Filters

5. Search, Queries, and Filters

Introduction

Executing a search

Sorting results

Highlighting results

Executing a scan query

Suggesting a correct query

Counting matched results

Deleting by query

Matching all the documents

Querying/filtering for a single term

Querying/filtering for multiple terms

Using a prefix query/filter

Using a Boolean query/filter

Using a range query/filter

Using span queries

Using a match query

Using an ID query/filter

Using a has_child query/filter

Using a top_children query

Using a has_parent query/filter

Using a regexp query/filter

Using a function score query

Using exists and missing filters

Using and/or/not filters

Using a geo bounding box filter

Using a geo polygon filter

Using geo distance filter

Using a QueryString query

Using a template query

6. Aggregations

6. Aggregations

Introduction

Executing an aggregation

Executing the stats aggregation

Executing the terms aggregation

Executing the range aggregation

Executing the histogram aggregation

Executing the date histogram aggregation

Executing the filter aggregation

Executing the global aggregation

Executing the geo distance aggregation

Executing nested aggregation

Executing the top hit aggregation

7. Scripting

7. Scripting

Introduction

Installing additional script plugins

Managing scripts

Sorting data using script

Computing return fields with scripting

Filtering a search via scripting

Updating a document using scripts

8. Rivers

8. Rivers

Introduction

Managing a river

Using the CouchDB river

Using the MongoDB river

Using the RabbitMQ river

Using the JDBC river

Using the Twitter river

9. Cluster and Node Monitoring

9. Cluster and Node Monitoring

Introduction

Controlling cluster health via the API

Controlling cluster state via the API

Getting cluster node information via the API

Getting node statistics via the API

Managing repositories

Executing a snapshot

Restoring a snapshot

Installing and using BigDesk

Installing and using ElasticSearch Head

Installing and using SemaText SPM

Installing and using Marvel

10. Java Integration

10. Java Integration

Introduction

Creating an HTTP client

Creating a native client

Managing indices with the native client

Managing mappings

Managing documents

Managing bulk actions

Building a query

Executing a standard search

Executing a search with aggregations

Executing a scroll/scan search

11. Python Integration

11. Python Integration

Introduction

Creating a client

Managing indices

Managing mappings

Managing documents

Executing a standard search

Executing a search with aggregations

12. Plugin Development

12. Plugin Development

Introduction

Creating a site plugin

Creating a native plugin

Creating a REST plugin

Creating a cluster action

Creating an analyzer plugin

Creating a river plugin

Index

Index

Using a top_children query

In the previous recipe, the has_child query consumes a huge amount of memory because it requires you to fetch all child IDs. To bypass this limitation in huge data contexts, the top_children query allows you to fetch only the top child results. This scenario is very common: think of a blog with the latest 10 comments.

Getting ready

You need a working ElasticSearch cluster and an index populated with the script chapter_05/populate_query.sh, available in the code bundle for this book.

How to do it...

In order to execute the top_children query, perform the following steps:

Search the test-type parent of which the test-type2 top child has a term in the field value as value1. We can create a query, as follows:

curl -XPOST 'http://127.0.0.1:9200/test-index/test-type/_search?pretty=true' -d '{
  "query": {
    "top_children" : {
      "type" : "test-type2",
      "query" : {
        "term" : {
          "value" : "value1"
        }
      },
      "score" : "max",
      "factor...

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