[[stopwords-phrases]]
=== Stopwords and Phrase Queries
About 5% of all queries are ((("stopwords", "phrase queries and")))((("phrase matching", "stopwords and")))phrase queries (see <<phrase-matching>>), 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 <<pros-cons-stopwords>>, 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-intro,TF/IDF>>
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 <<maintaining-positions>>. 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
<<common-grams,`common_grams` token filter>>.
- Introduction
- 入门
- 是什么
- 安装
- API
- 文档
- 索引
- 搜索
- 聚合
- 小结
- 分布式
- 结语
- 分布式集群
- 空集群
- 集群健康
- 添加索引
- 故障转移
- 横向扩展
- 更多扩展
- 应对故障
- 数据
- 文档
- 索引
- 获取
- 存在
- 更新
- 创建
- 删除
- 版本控制
- 局部更新
- Mget
- 批量
- 结语
- 分布式增删改查
- 路由
- 分片交互
- 新建、索引和删除
- 检索
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- 搜索
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- 映射和分析
- 数据类型差异
- 确切值对决全文
- 倒排索引
- 分析
- 映射
- 复合类型
- 结构化查询
- 请求体查询
- 结构化查询
- 查询与过滤
- 重要的查询子句
- 过滤查询
- 验证查询
- 结语
- 排序
- 排序
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- 相关性
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- 分布式搜索
- 查询阶段
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- 搜索选项
- 扫描和滚屏
- 索引管理
- 创建删除
- 设置
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- 映射
- 根对象
- 元数据中的source字段
- 元数据中的all字段
- 元数据中的ID字段
- 动态映射
- 自定义动态映射
- 默认映射
- 重建索引
- 别名
- 深入分片
- 使文本可以被搜索
- 动态索引
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- 持久化变更
- 合并段
- 结构化搜索
- 查询准确值
- 组合过滤
- 查询多个准确值
- 包含,而不是相等
- 范围
- 处理 Null 值
- 缓存
- 过滤顺序
- 全文搜索
- 匹配查询
- 多词查询
- 组合查询
- 布尔匹配
- 增加子句
- 控制分析
- 关联失效
- 多字段搜索
- 多重查询字符串
- 单一查询字符串
- 最佳字段
- 最佳字段查询调优
- 多重匹配查询
- 最多字段查询
- 跨字段对象查询
- 以字段为中心查询
- 全字段查询
- 跨字段查询
- 精确查询
- 模糊匹配
- Phrase matching
- Slop
- Multi value fields
- Scoring
- Relevance
- Performance
- Shingles
- Partial_Matching
- Postcodes
- Prefix query
- Wildcard Regexp
- Match phrase prefix
- Index time
- Ngram intro
- Search as you type
- Compound words
- Relevance
- Scoring theory
- Practical scoring
- Query time boosting
- Query scoring
- Not quite not
- Ignoring TFIDF
- Function score query
- Popularity
- Boosting filtered subsets
- Random scoring
- Decay functions
- Pluggable similarities
- Conclusion
- Language intro
- Intro
- Using
- Configuring
- Language pitfalls
- One language per doc
- One language per field
- Mixed language fields
- Conclusion
- Identifying words
- Intro
- Standard analyzer
- Standard tokenizer
- ICU plugin
- ICU tokenizer
- Tidying text
- Token normalization
- Intro
- Lowercasing
- Removing diacritics
- Unicode world
- Case folding
- Character folding
- Sorting and collations
- Stemming
- Intro
- Algorithmic stemmers
- Dictionary stemmers
- Hunspell stemmer
- Choosing a stemmer
- Controlling stemming
- Stemming in situ
- Stopwords
- Intro
- Using stopwords
- Stopwords and performance
- Divide and conquer
- Phrase queries
- Common grams
- Relevance
- Synonyms
- Intro
- Using synonyms
- Synonym formats
- Expand contract
- Analysis chain
- Multi word synonyms
- Symbol synonyms
- Fuzzy matching
- Intro
- Fuzziness
- Fuzzy query
- Fuzzy match query
- Scoring fuzziness
- Phonetic matching
- Aggregations
- overview
- circuit breaker fd settings
- filtering
- facets
- docvalues
- eager
- breadth vs depth
- Conclusion
- concepts buckets
- basic example
- add metric
- nested bucket
- extra metrics
- bucket metric list
- histogram
- date histogram
- scope
- filtering
- sorting ordering
- approx intro
- cardinality
- percentiles
- sigterms intro
- sigterms
- fielddata
- analyzed vs not
- 地理坐标点
- 地理坐标点
- 通过地理坐标点过滤
- 地理坐标盒模型过滤器
- 地理距离过滤器
- 缓存地理位置过滤器
- 减少内存占用
- 按距离排序
- Geohashe
- Geohashe
- Geohashe映射
- Geohash单元过滤器
- 地理位置聚合
- 地理位置聚合
- 按距离聚合
- Geohash单元聚合器
- 范围(边界)聚合器
- 地理形状
- 地理形状
- 映射地理形状
- 索引地理形状
- 查询地理形状
- 在查询中使用已索引的形状
- 地理形状的过滤与缓存
- 关系
- 关系
- 应用级别的Join操作
- 扁平化你的数据
- Top hits
- Concurrency
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- 嵌套
- 嵌套对象
- 嵌套映射
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- 嵌套排序
- 嵌套集合
- Parent Child
- Parent child
- Indexing parent child
- Has child
- Has parent
- Children agg
- Grandparents
- Practical considerations
- Scaling
- Shard
- Overallocation
- Kagillion shards
- Capacity planning
- Replica shards
- Multiple indices
- Index per timeframe
- Index templates
- Retiring data
- Index per user
- Shared index
- Faking it
- One big user
- Scale is not infinite
- Cluster Admin
- Marvel
- Health
- Node stats
- Other stats
- Deployment
- hardware
- other
- config
- dont touch
- heap
- file descriptors
- conclusion
- cluster settings
- Post Deployment
- dynamic settings
- logging
- indexing perf
- rolling restart
- backup
- restore
- conclusion