.. _ref-installing-search-engines:

=========================
Installing Search Engines
=========================

Solr
====

Official Download Location: http://www.apache.org/dyn/closer.cgi/lucene/solr/

Solr is Java but comes in a pre-packaged form that requires very little other
than the JRE and Jetty. It's very performant and has an advanced featureset.
Haystack suggests using Solr 3.5+, though it's possible to get it working on
Solr 1.4 with a little effort. Installation is relatively simple::

    curl -LO https://archive.apache.org/dist/lucene/solr/4.10.2/solr-4.10.2.tgz
    tar xvzf solr-4.10.2.tgz
    cd solr-4.10.2
    cd example
    java -jar start.jar

You'll need to revise your schema. You can generate this from your application
(once Haystack is installed and setup) by running
``./manage.py build_solr_schema``. Take the output from that command and place
it in ``solr-4.10.2/example/solr/collection1/conf/schema.xml``. Then restart Solr.

.. note::
    ``build_solr_schema`` uses a template to generate ``schema.xml``. Haystack
    provides a default template using some sensible defaults. If you would like
    to provide your own template, you will need to place it in
    ``search_configuration/solr.xml``, inside a directory specified by your app's
    ``TEMPLATE_DIRS`` setting. Examples::

        /myproj/myapp/templates/search_configuration/solr.xml
        # ...or...
        /myproj/templates/search_configuration/solr.xml

You'll also need a Solr binding, ``pysolr``. The official ``pysolr`` package,
distributed via PyPI, is the best version to use (2.1.0+). Place ``pysolr.py``
somewhere on your ``PYTHONPATH``.

.. note::

    ``pysolr`` has its own dependencies that aren't covered by Haystack. See
    https://pypi.python.org/pypi/pysolr for the latest documentation.

More Like This
--------------

To enable the "More Like This" functionality in Haystack, you'll need
to enable the ``MoreLikeThisHandler``. Add the following line to your
``solrconfig.xml`` file within the ``config`` tag::

    <requestHandler name="/mlt" class="solr.MoreLikeThisHandler" />

Spelling Suggestions
--------------------

To enable the spelling suggestion functionality in Haystack, you'll need to
enable the ``SpellCheckComponent``.

The first thing to do is create a special field on your ``SearchIndex`` class
that mirrors the ``text`` field, but uses ``FacetCharField``. This disables
the post-processing that Solr does, which can mess up your suggestions.
Something like the following is suggested::

    class MySearchIndex(indexes.SearchIndex, indexes.Indexable):
        text = indexes.CharField(document=True, use_template=True)
        # ... normal fields then...
        suggestions = indexes.FacetCharField()

        def prepare(self, obj):
            prepared_data = super(MySearchIndex, self).prepare(obj)
            prepared_data['suggestions'] = prepared_data['text']
            return prepared_data

Then, you enable it in Solr by adding the following line to your
``solrconfig.xml`` file within the ``config`` tag::

    <searchComponent name="spellcheck" class="solr.SpellCheckComponent">

        <str name="queryAnalyzerFieldType">textSpell</str>

        <lst name="spellchecker">
          <str name="name">default</str>
          <str name="field">suggestions</str>
          <str name="spellcheckIndexDir">./spellchecker1</str>
          <str name="buildOnCommit">true</str>
        </lst>
    </searchComponent>

Then change your default handler from::

    <requestHandler name="standard" class="solr.StandardRequestHandler" default="true" />

... to ...::

    <requestHandler name="standard" class="solr.StandardRequestHandler" default="true">
        <arr name="last-components">
            <str>spellcheck</str>
        </arr>
    </requestHandler>

Be warned that the ``<str name="field">suggestions</str>`` portion will be specific to
your ``SearchIndex`` classes (in this case, assuming the main field is called
``text``).


Elasticsearch
=============

Official Download Location: http://www.elasticsearch.org/download/

Elasticsearch is Java but comes in a pre-packaged form that requires very
little other than the JRE. It's also very performant, scales easily and has
an advanced featureset. Haystack requires at least version 0.90.0+.
Installation is best done using a package manager::

    # On Mac OS X...
    brew install elasticsearch

    # On Ubuntu...
    apt-get install elasticsearch

    # Then start via:
    elasticsearch -f -D es.config=<path to YAML config>

    # Example:
    elasticsearch -f -D es.config=/usr/local/Cellar/elasticsearch/0.90.0/config/elasticsearch.yml

You may have to alter the configuration to run on ``localhost`` when developing
locally. Modifications should be done in a YAML file, the stock one being
``config/elasticsearch.yml``::

    # Unicast Discovery (disable multicast)
    discovery.zen.ping.multicast.enabled: false
    discovery.zen.ping.unicast.hosts: ["127.0.0.1"]

    # Name your cluster here to whatever.
    # My machine is called "Venus", so...
    cluster:
      name: venus

    network:
      host: 127.0.0.1

    path:
      logs: /usr/local/var/log
      data: /usr/local/var/data

You'll also need an Elasticsearch binding: elasticsearch_ (**NOT**
``pyes``). Place ``elasticsearch`` somewhere on your ``PYTHONPATH``
(usually ``python setup.py install`` or ``pip install elasticsearch``).

.. _elasticsearch: http://pypi.python.org/pypi/elasticsearch/

.. note::

  Elasticsearch 1.0 is slightly backwards incompatible so you need to make sure
  you have the proper version of `elasticsearch` installed - releases with
  major version 1 (1.X.Y) are to be used with Elasticsearch 1.0 and later, 0.4
  releases are meant to work with Elasticsearch 0.90.X.

.. note::

    ``elasticsearch`` has its own dependencies that aren't covered by
    Haystack. You'll also need ``urllib3``.


Whoosh
======

Official Download Location: http://bitbucket.org/mchaput/whoosh/

Whoosh is pure Python, so it's a great option for getting started quickly and
for development, though it does work for small scale live deployments. The
current recommended version is 1.3.1+. You can install via PyPI_ using
``sudo easy_install whoosh`` or ``sudo pip install whoosh``.

Note that, while capable otherwise, the Whoosh backend does not currently
support "More Like This" or faceting. Support for these features has recently
been added to Whoosh itself & may be present in a future release.

.. _PyPI: http://pypi.python.org/pypi/Whoosh/


Xapian
======

Official Download Location: http://xapian.org/download

Xapian is written in C++ so it requires compilation (unless your OS has a
package for it). Installation looks like::

    curl -O http://oligarchy.co.uk/xapian/1.2.18/xapian-core-1.2.18.tar.xz
    curl -O http://oligarchy.co.uk/xapian/1.2.18/xapian-bindings-1.2.18.tar.xz

    unxz xapian-core-1.2.18.tar.xz
    unxz xapian-bindings-1.2.18.tar.xz

    tar xvf xapian-core-1.2.18.tar
    tar xvf xapian-bindings-1.2.18.tar

    cd xapian-core-1.2.18
    ./configure
    make
    sudo make install

    cd ..
    cd xapian-bindings-1.2.18
    ./configure
    make
    sudo make install

Xapian is a third-party supported backend. It is not included in Haystack
proper due to licensing. To use it, you need both Haystack itself as well as
``xapian-haystack``. You can download the source from
http://github.com/notanumber/xapian-haystack/tree/master. Installation
instructions can be found on that page as well. The backend, written
by David Sauve (notanumber), fully implements the `SearchQuerySet` API and is
an excellent alternative to Solr.
