NAME
ElasticSearchX::Model - Extensible and flexible model for ElasticSearch based on Moose
VERSION
version 0.1.7
SYNOPSIS
package MyModel::Tweet;
use Moose;
use ElasticSearchX::Model::Document;
has message => ( is => 'ro', isa => 'Str' );
has date => (
is => 'ro',
required => 1,
isa => 'DateTime',
default => sub { DateTime->now }
);
package MyModel;
use Moose;
use ElasticSearchX::Model;
__PACKAGE__->meta->make_immutable;
my $model = MyModel->new;
$model->deploy;
my $tweet = $model->index('default')->type('tweet')->put({
message => 'Hello there!'
});
print $tweet->_id;
$tweet->delete;
DESCRIPTION
This is an ElasticSearch to Moose mapper which hides the REST api behind object-oriented api calls. ElasticSearch types and indices are defined using Moose classes and a flexible DSL.
Deployment statements for ElasticSearch can be build dynamically using these classes. Results from ElasticSearch inflate automatically to the corresponding Moose classes. Furthermore, it provides sensible defaults.
The search API makes the tedious task of building ElasticSearch queries a lot easier.
The ElasticSearchX::Model::Tutorial is probably the best place to get started!
WARNING: This module is being used in production already but I don't consider it being stable in terms of the API and implementation details.
DSL
index
index twitter => ( namespace => 'MyNamespace', traits => ['MyTrait'] );
index facebook => ( types => [qw(FB::User FB::Friends)] );
Adds an index to the model. By default there is a default
index, which will be removed once you add custom indices.
See "ATTRIBUTES" in ElasticSearchX::Model::Index for available options.
analyzer
tokenizer
filter
analyzer lowercase => ( tokenizer => 'keyword', filter => 'lowercase' );
tokenizer camelcase => (
type => 'pattern',
pattern => "([^\\p{L}\\d]+)|(?<=\\D)(?=\\d)|(?<=\\d)(?=\\D)|(?<=[\\p{L}&&[^\\p{Lu}]])(?=\\p{Lu})|(?<=\\p{Lu})(?=\\p{Lu}[\\p{L}&&[^\\p{Lu}]])"
);
analyzer camelcase => (
type => 'custom',
tokenizer => 'camelcase',
filter => ['lowercase', 'unique']
);
Adds analyzers, tokenizers or filters to all indices. They can then be used in attributes of ElasticSearchX::Model::Document classes.
ATTRIBUTES
es
Builds and holds the ElasticSearch object. Valid values are:
- :9200
-
Connect to a server on
127.0.0.1
, port9200
with thehttptiny
transport class and a timeout of 30 seconds. - [qw(:9200 12.12.12.12:9200)]
-
Connect to
127.0.0.1:9200
and12.12.12.12:9200
with the same defaults as above. - { %args }
-
Passes
%args
directly to the ElasticSearch constructor.
bulk
my $bulk = $model->bulk( size => 100 );
$bulk->put($tweet);
$bulk->commit; # optional
Returns an instance of ElasticSearchX::Model::Bulk.
METHODS
index
my $index = $model->index('twitter');
Returns an ElasticSearchX::Model::Index object.
deploy
deploy
pushes the mapping to the ElasticSearch server. It will automatically try to upgrade your mapping if the types already exists. However, this might not be possible in case you changes a field from one data type to another and ElasticSearch cannot figure out how to translate it. In this case deploy
will throw an error message.
To create the indices from scratch, pass delete => 1
. This will delete all the data in your indices.
$model->deploy( delete => 1 );
es_version
if($model->es_version > 0.02) { ... }
Returns the version number of the ElasticSearch server you are currently connected to. ElasticSearch uses Semantic Versioning. However, release candidates have a special syntax. For example, the version 0.20.0.RC1 would be parsed as 0.020_000_001.
PERFORMANCE CONSIDERATIONS
Creating objects is a quite expensive operation. If you are crawling through large amounts of data, you will gain a huge speed improvement by not inflating the results to their document classes (see "raw" in ElasticSearchX::Model::Document::Set).
AUTHOR
Moritz Onken
COPYRIGHT AND LICENSE
This software is Copyright (c) 2013 by Moritz Onken.
This is free software, licensed under:
The (three-clause) BSD License