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  • Book Overview & Buying ElasticSearch Cookbook
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ElasticSearch Cookbook

ElasticSearch Cookbook - Second Edition

By : Alberto Paro
4.1 (7)
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ElasticSearch Cookbook

ElasticSearch Cookbook

4.1 (7)
By: Alberto Paro
Buy this Book

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.
Table of Contents (14 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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Sections
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Conventions
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Reader feedback
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Customer support
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1
1. Getting Started
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1. Getting Started
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Introduction
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Understanding nodes and clusters
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Understanding node services
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Managing your data
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Understanding clusters, replication, and sharding
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Communicating with ElasticSearch
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Using the HTTP protocol
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Using the native protocol
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Using the Thrift protocol
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2. Downloading and Setting Up
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2. Downloading and Setting Up
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Introduction
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Downloading and installing ElasticSearch
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Setting up networking
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Setting up a node
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Setting up for Linux systems
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Setting up different node types
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Installing plugins in ElasticSearch
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Installing a plugin manually
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Removing a plugin
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Changing logging settings
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3. Managing Mapping
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3. Managing Mapping
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Introduction
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Using explicit mapping creation
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Mapping base types
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Mapping arrays
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Mapping an object
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Mapping a document
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Using dynamic templates in document mapping
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Managing nested objects
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Managing a child document
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Adding a field with multiple mappings
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Mapping a geo point field
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Mapping a geo shape field
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Mapping an IP field
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Mapping an attachment field
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Adding metadata to a mapping
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Specifying a different analyzer
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Mapping a completion suggester
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4. Basic Operations
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4. Basic Operations
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Introduction
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Creating an index
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Deleting an index
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Opening/closing an index
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Putting a mapping in an index
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Getting a mapping
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Deleting a mapping
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Refreshing an index
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Flushing an index
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Optimizing an index
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Checking if an index or type exists
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Managing index settings
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Using index aliases
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Indexing a document
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Getting a document
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Deleting a document
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Updating a document
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Speeding up atomic operations (bulk operations)
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Speeding up GET operations (multi GET)
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5. Search, Queries, and Filters
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5. Search, Queries, and Filters
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Introduction
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Executing a search
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Sorting results
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Highlighting results
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Executing a scan query
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Suggesting a correct query
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Counting matched results
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Deleting by query
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Matching all the documents
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Querying/filtering for a single term
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Querying/filtering for multiple terms
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Using a prefix query/filter
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Using a Boolean query/filter
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Using a range query/filter
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Using span queries
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Using a match query
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Using an ID query/filter
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Using a has_child query/filter
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Using a top_children query
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Using a has_parent query/filter
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Using a regexp query/filter
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Using a function score query
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Using exists and missing filters
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Using and/or/not filters
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Using a geo bounding box filter
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Using a geo polygon filter
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Using geo distance filter
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Using a QueryString query
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Using a template query
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6. Aggregations
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6. Aggregations
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Introduction
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Executing an aggregation
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Executing the stats aggregation
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Executing the terms aggregation
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Executing the range aggregation
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Executing the histogram aggregation
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Executing the date histogram aggregation
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Executing the filter aggregation
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Executing the global aggregation
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Executing the geo distance aggregation
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Executing nested aggregation
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Executing the top hit aggregation
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7. Scripting
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7. Scripting
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Introduction
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Installing additional script plugins
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Managing scripts
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Sorting data using script
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Computing return fields with scripting
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Filtering a search via scripting
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Updating a document using scripts
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8. Rivers
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8. Rivers
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Introduction
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Managing a river
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Using the CouchDB river
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Using the MongoDB river
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Using the RabbitMQ river
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Using the JDBC river
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Using the Twitter river
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9. Cluster and Node Monitoring
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9. Cluster and Node Monitoring
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Introduction
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Controlling cluster health via the API
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Controlling cluster state via the API
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Getting cluster node information via the API
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Getting node statistics via the API
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Managing repositories
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Executing a snapshot
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Restoring a snapshot
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Installing and using BigDesk
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Installing and using ElasticSearch Head
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Installing and using SemaText SPM
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Installing and using Marvel
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10. Java Integration
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10. Java Integration
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Introduction
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Creating an HTTP client
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Creating a native client
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Managing indices with the native client
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Managing mappings
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Managing documents
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Managing bulk actions
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Building a query
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Executing a standard search
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Executing a search with aggregations
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Executing a scroll/scan search
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11. Python Integration
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11. Python Integration
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Introduction
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Creating a client
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Managing indices
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Managing mappings
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Managing documents
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Executing a standard search
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Executing a search with aggregations
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12. Plugin Development
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12. Plugin Development
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Introduction
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Creating a site plugin
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Creating a native plugin
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Creating a REST plugin
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Creating a cluster action
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Creating an analyzer plugin
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Creating a river plugin
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Index
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Index

Using the Thrift protocol

Thrift is an interface definition language, initially developed by Facebook, used to define and create services. This protocol is now maintained by Apache Software Foundation.

Its usage is similar to HTTP, but it bypasses the limit of HTTP protocol (latency, handshake and so on) and it's faster.

Getting ready

You need a working instance of ElasticSearch cluster with the thrift plugin installed (https://github.com/elasticsearch/elasticsearch-transport-thrift/); the standard port for the Thrift protocol is 9500.

How to do it...

To use the Thrift protocol in a Java environment, perform the following steps:

  1. We must be sure that Maven loads the thrift library adding to the pom.xml file; the code lines are:
    <dependency>
  <groupId>org.apache.thrift</groupId>
  <artifactId>libthrift</artifactId>
  <version>0.9.1</version>
</dependency>
  2. In Java, creating a client is quite easy using ElasticSearch generated classes:
    import org.apache.thrift.protocol.TBinaryProtocol;
import org.apache.thrift.protocol.TProtocol;
import org.apache.thrift.transport.TSocket;
import org.apache.thrift.transport.TTransport;
import org.apache.thrift.transport.TTransportException;
import org.elasticsearch.thrift.*;
TTransport transport = new TSocket("127.0.0.1", 9500);
TProtocol protocol = new TBinaryProtocol(transport);
Rest.Client client = new Rest.Client(protocol);
transport.open();
  3. To initialize a connection, first we need to open a socket transport. This is done with the TSocket(host, port) setting, using the ElasticSearch thrift standard port 9500.
  4. Then the socket transport protocol must be encapsulated in a binary protocol, this is done with the TBinaryProtocol(transport) parameter.
  5. Now, a client can be initialized by passing the protocol. The Rest.Client utility class and other utility classes are generated by elasticsearch.thrift. It resides in the org.elasticsearch.thrift namespace.
  6. To have a fully working client, we must open the socket (transport.open()).
  7. At the end of program, we should close the client connection (transport.close()).

There's more...

Some drivers, to connect to ElasticSearch, provide an easy-to-use API to interact with Thrift without the boulder that this protocol needs.

For advanced usage, I suggest the use of the Thrift protocol to bypass some problems related to HTTP limits, such as:

  • The number of simultaneous connections required in HTTP; Thrift transport efficiently uses resources
  • The network traffic is light weight because it is binary and is very compact

A big advantage of this protocol is that on the server side it wraps the REST entry points so that it can also be used with calls provided by external REST plugins.

See also

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