Phrase queries

[[stopwords-phrases]] === Stopwords and Phrase Queries

About 5% of all queries are ((("stopwords", "phrase queries and")))((("phrase matching", "stopwords and")))phrase queries (see <>), but they often account for the majority of slow queries. Phrase queries can perform poorly, especially if the phrase includes very common words; a phrase like ``To be, or not to be'' could be considered pathological. The reason for this has to do with the amount of data that is necessary to support proximity matching.

In <>, we said that removing stopwords saves only a small amount of space in the inverted index.((("indices", "typical, data contained in"))) That was only partially true. A typical index may contain, among other data, some or all of the following:

Terms dictionary::

A sorted list of all terms that appear in the documents in the index,
and a count of the number of documents that contain each term.

Postings list::

A list of which documents contain each term.

Term frequency::

How often each term appears in each document.

Positions::

The position of each term within each document, for phrase and proximity
queries.

Offsets::

The start and end character offsets of each term in each document, for
snippet highlighting. Disabled by default.

Norms::

A factor used to normalize fields of different lengths, to give shorter
fields more weight.

Removing stopwords from the index may save a small amount of space in the terms dictionary and the postings list, but positions and offsets are another matter. Positions and offsets data can easily double, triple, or quadruple index size.

==== Positions Data

Positions are enabled on analyzed string fields by default,((("stopwords", "phrase queries and", "positions data")))((("phrase matching", "stopwords and", "positions data"))) so that phrase queries will work out of the box. The more often that a term appears, the more space is needed to store its position data. Very common words, by definition, appear very commonly, and their positions data can run to megabytes or gigabytes on large collections.

Running a phrase query on a high-frequency word like the might result in gigabytes of data being read from disk. That data will be stored in the kernel filesystem cache to speed up later access, which seems like a good thing, but it might cause other data to be evicted from the cache, which will slow subsequent queries.

This is clearly a problem that needs solving.

[[index-options]] ==== Index Options

The first question you should ((("stopwords", "phrase queries and", "index options")))((("phrase matching", "stopwords and", "index options")))ask yourself is: Do you need phrase or proximity queries?

Often, the answer is no. For many use cases, such as logging, you need to know whether a term appears in a document -- information that is provided by the postings list--but not where it appears. Or perhaps you need to use phrase queries on one or two fields, but you can disable positions data on all of the other analyzed string fields.

The index_options parameter ((("index_options parameter")))allows you to control what information is stored in the index for each field.((("fields", "index options"))) Valid values are as follows:

docs::

Only store which documents contain which terms. This is the default for
`not_analyzed` string fields.

freqs::

Store `docs` information, plus how often each term appears in each
document. Term frequencies are needed for complete <>
relevance calculations, but they are not required if you just need to know
whether a document contains a particular term.

positions::

Store `docs` and `freqs`, plus the position of each term in each document.
This is the default for `analyzed` string fields, but can be disabled if
phrase/proximity matching is not needed.

offsets::

Store `docs`, `freqs`, `positions`, and the start and end character offsets
of each term in the original string.  This information is used by the
http://bit.ly/1u9PJ16[`postings` highlighter]
but is disabled by default.

You can set index_options on fields added at index creation time, or when adding new fields by using((("put-mapping API"))) the put-mapping API. This setting can't be changed on existing fields:

[source,json]

PUT /my_index { "mappings": { "my_type": { "properties": { "title": { <1> "type": "string" }, "content": { <2> "type": "string", "index_options": "freqs" } } }

}

<1> The title field uses the default setting of positions, so it is suitable for phrase/proximity queries.

<2> The content field has positions disabled and so cannot be used for phrase/proximity queries.

==== Stopwords

Removing stopwords is one way of reducing the size of the positions data quite dramatically.((("stopwords", "phrase queries and", "removing stopwords"))) An index with stopwords removed can still be used for phrase queries because the original positions of the remaining terms are maintained, as we saw in <>. But of course, excluding terms from the index reduces searchability. We wouldn't be able to differentiate between the two phrases Man in the moon and Man on the moon.

Fortunately, there is a way to have our cake and eat it: the <>.