# Nested
# 嵌套数据类型
`nested `类型是一种对象类型的特殊版本,它允许索引对象数组,独立地索引每个对象。
## 如何使对象数组变扁平
内部类对象数组并不以你预料的方式工作。Lucene没有内部对象的概念,所以Elasticsearch将对象层次扁平化,转化成字段名字和值构成的简单列表。比如,以下的文档:
|
`curl -XPUT ``'localhost:9200/my_index/my_type/1?pretty'` `-d'`
`{`
`"group"` `: ``"fans"``,`
`"user"` `: [ ``// 1`
`{`
`"first"` `: ``"John"``,`
`"last"` `: ``"Smith"`
`},`
`{`
`"first"` `: ``"Alice"``,`
`"last"` `: ``"White"`
`}`
`]`
`}'`
|
`user `字段作为对象动态添加
在内部被转化成如下格式的文档:
|
`{`
`"group"` `: ``"fans"``,`
`"user.first"` `: [ ``"alice"``, ``"john"` `],`
`"user.last"` `: [ ``"smith"``, ``"white"` `]`
`}`
|
`user.first `和 `user.last `扁平化为多值字段,`alice `和 `white `的关联关系丢失了。导致这个文档错误地匹配对 `alice `和 `smith `的查询:
|
`curl -XGET ``'localhost:9200/my_index/_search?pretty'` `-d'`
`{`
`"query"``: {`
`"bool"``: {`
`"must"``: [`
`{ ``"match"``: { ``"user.first"``: ``"Alice"` `}},`
`{ ``"match"``: { ``"user.last"``: ``"Smith"` `}}`
`]`
`}`
`}`
`}'`
|
## 使用`nested`字段对应`object`数组
如果你需要索引对象数组,并且保持数组中每个对象的独立性,你应该使用`nested`对象类型而不是`object`类型。`nested`对象将数组中每个对象作为独立隐藏文档来索引,这意味着每个嵌套对象都可以独立被搜索:
|
`curl -XPUT ``'localhost:9200/my_index?pretty'` `-d'`
`{`
`"mappings"``: {`
`"my_type"``: {`
`"properties"``: {`
`"user"``: {`
`"type"``: ``"nested"` `// 1`
`}`
`}`
`}`
`}`
`}'`
`curl -XPUT ``'localhost:9200/my_index/my_type/1?pretty'` `-d'`
`{`
`"group"` `: ``"fans"``,`
`"user"` `: [`
`{`
`"first"` `: ``"John"``,`
`"last"` `: ``"Smith"`
`},`
`{`
`"first"` `: ``"Alice"``,`
`"last"` `: ``"White"`
`}`
`]`
`}'`
`curl -XGET ``'localhost:9200/my_index/_search?pretty'` `-d'`
`{`
`"query"``: {`
`"nested"``: {`
`"path"``: ``"user"``,`
`"query"``: {`
`"bool"``: {`
`"must"``: [`
`{ ``"match"``: { ``"user.first"``: ``"Alice"` `}},`
`{ ``"match"``: { ``"user.last"``: ``"Smith"` `}} ``// 2`
`]`
`}`
`}`
`}`
`}`
`}'`
`curl -XGET ``'localhost:9200/my_index/_search?pretty'` `-d'`
`{`
`"query"``: {`
`"nested"``: {`
`"path"``: ``"user"``,`
`"query"``: {`
`"bool"``: {`
`"must"``: [`
`{ ``"match"``: { ``"user.first"``: ``"Alice"` `}},`
`{ ``"match"``: { ``"user.last"``: ``"White"` `}} ``// 3`
`]`
`}`
`},`
`"inner_hits"``: { ``// 4`
`"highlight"``: {`
`"fields"``: {`
`"user.first"``: {}`
`}`
`}`
`}`
`}`
`}`
`}'`
|
| 1 | `user `字段映射为 `nested `类型而不是 `objec t`类型 |
| 2 | 该查询没有匹配,因为 `Alice `和 `Smith `不在同一个嵌套类中 |
| 3 | 该查询有匹配,因为 `Alice `和 `White `在同一个嵌套类中 |
| 4 | `inner_hits `可以高亮匹配的嵌套文档 |
嵌套文档可以:
| 1 |
`使用 `[nested](https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-nested-query.html "Nested Query") ``<span style="color: rgb(36, 41, 46);">查询来搜索</span>
|
| 2 | 使用 `[nested](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-nested-aggregation.html "Nested Aggregation") `<span style="color: rgb(36, 41, 46);">和 [`reverse_nested`](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-reverse-nested-aggregation.html "Reverse nested Aggregation")</span><span style="color: rgb(36, 41, 46);">聚合来分析</span> |
| 3 | 使用 [nested sorting](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-sort.html#nested-sorting "Sorting within nested objects.")<span style="color: rgb(36, 41, 46);">来排序</span> |
| 4 | 使用 [nested inner hits](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-inner-hits.html#nested-inner-hits "Nested inner hits") <span style="color: rgb(36, 41, 46);">来检索和高亮</span> |
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## `nested `字段参数
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| <span style="color: rgb(36, 41, 46);">参数</span> | <span style="color: rgb(36, 41, 46);">说明</span> |
| <span style="color: rgb(36, 41, 46);">dynamic</span> | <span style="color: rgb(36, 41, 46);">新属性是否应动态添加到现有对象。接受 true (默认), false 和 strict。</span> |
| <span style="color: rgb(36, 41, 46);">include_in_all</span> | <span style="color: rgb(36, 41, 46);">为对象中的所有属性设置默认的 </span>`include_in_all `<span style="color: rgb(36, 41, 46);">值,对象本身没有添加到 _all 字段。</span> |
| <span style="color: rgb(36, 41, 46);">properties</span> | <span style="color: rgb(36, 41, 46);">对象内的字段,可以是任何数据类型,包括对象。可以将新属性添加到现有对象。</span> |
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注意
<span class="aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon" style="border: none; display: block; height: 16px; margin: 0px; padding: 0px; text-indent: -999em; vertical-align: text-bottom; width: 16px; line-height: 20px; position: absolute; left: 10px; top: 12px; color: rgb(74, 103, 133); background-position: 0px 0px; background-repeat: no-repeat;"></span>
<div class="confluence-information-macro-body" style="margin: 0px; padding: 0px;">
<span style="color: rgb(106, 115, 125);">因为嵌套文档是作为单独的文档被索引的,所以嵌套文档只能被 </span>`nested `<span style="color: rgb(106, 115, 125);">查询、</span>`nested / reverse_nested`<span style="color: rgb(106, 115, 125);">或者 </span>`nested inner hits `<span style="color: rgb(106, 115, 125);">访问。 比如,一个</span>`string `<span style="color: rgb(106, 115, 125);">字段包含嵌套文档,嵌套文档中 </span>`index_options `<span style="color: rgb(106, 115, 125);">设置为 </span>`offsets `<span style="color: rgb(106, 115, 125);">以使用 postings highlighter,这些偏移量在主要的高亮阶段是不可用的。必须通过 </span>`nested inner hits `<span style="color: rgb(106, 115, 125);">来进行高亮操作。</span>
</div>
</div>
</div>
</div>
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## 限制`nested`字段的数量
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<div class="readme blob instapaper_body" style="margin: 0px; padding: 0px;">
索引一个包含 100 个 `nested `字段的文档实际上就是索引 101 个文档,每个嵌套文档都作为一个独立文档来索引。为了防止过度定义嵌套字段的数量,每个索引可以定义的嵌套字段被限制在 50 个。
- 入门
- 基本概念
- 安装
- 探索你的集群
- 集群健康
- 列出所有索引库
- 创建一个索引库
- 索引文档创建与查询
- 删除一个索引库
- 修改你的数据
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- 批量处理
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- 搜索API
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- 执行搜索
- 执行过滤
- 执行聚合
- 总结
- Elasticsearch设置
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- .zip或.tar.gz文件的安装方式
- Install Elasticsearch with .zip on Windows
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- Install Elasticsearch with Windows MSI Installer
- Docker安装方式
- 配置Elasticsearch
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- Set up X-Pack
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- 邻接矩阵聚合
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- Filter Aggregation(过滤器聚合)
- Filters Aggregation
- Geo Distance Aggregation(地理距离聚合) 转至元数据结尾
- GeoHash grid Aggregation(GeoHash网格聚合)
- Global Aggregation(全局聚合) 转至元数据结尾
- Histogram Aggregation
- IP Range Aggregation(IP范围聚合)
- Missing Aggregation
- Nested Aggregation(嵌套聚合)
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- Reverse nested Aggregation
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- Percentiles Bucket Aggregation(百分数桶聚合)
- Moving Average Aggregation
- Cumulative Sum Aggregation(累积汇总聚合)
- Bucket Script Aggregation(桶脚本聚合)
- Bucket Selector Aggregation(桶选择器聚合)
- Serial Differencing Aggregation(串行差异聚合)
- Matrix Aggregations
- Matrix Stats
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- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Indices APIs
- Create Index /创建索引
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- Put Mapping /提交映射
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- Types Exists
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- Cluster APIs
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- Match All Query
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- 多字段查询
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- Term level queries
- Term Query
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- Bool 查询
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- Has Child Query
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- Nested Query(嵌套查询)
- Parent Id Query
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- Geo Distance Query(地理距离查询)
- Geo Polygon Query(地理多边形查询)
- Specialized queries
- More Like This Query
- Script Query
- Percolate Query
- Span queries
- Span Term 查询
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- Span First 查询
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- Minimum Should Match
- Multi Term Query Rewrite
- Mapping
- Removal of mapping types
- Field datatypes
- Array
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- Boolean
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- Geo-point datatype
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- Nested datatype
- Numeric datatypes
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- Text
- Token数
- 渗滤型
- join datatype
- Meta-Fields
- _all field
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- _id field
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- _meta field
- _routing field
- _source field
- _type field
- _uid field
- Mapping parameters
- analyzer(分析器)
- normalizer(归一化)
- boost(提升)
- Coerce(强制类型转换)
- copy_to(合并参数)
- doc_values(文档值)
- dynamic(动态设置)
- enabled(开启字段)
- eager_global_ordinals
- fielddata(字段数据)
- format (日期格式)
- ignore_above(忽略超越限制的字段)
- ignore_malformed(忽略格式不对的数据)
- index (索引)
- index_options(索引设置)
- fields(字段)
- Norms (标准信息)
- null_value(空值)
- position_increment_gap(短语位置间隙)
- properties (属性)
- search_analyzer (搜索分析器)
- similarity (匹配方法)
- store(存储)
- Term_vectors(词根信息)
- Dynamic Mapping
- Dynamic field mapping(动态字段映射)
- Dynamic templates(动态模板)
- default mapping(mapping中的_default_)
- Analysis
- Anatomy of an analyzer(分析器的分析)
- Testing analyzers(测试分析器)
- Analyzers(分析器)
- Configuring built-in analyzers(配置内置分析器)
- Standard Analyzer(标准分析器)
- Simple Analyzer(简单分析器)
- 空白分析器
- Stop Analyzer
- Keyword Analyzer
- 模式分析器
- 语言分析器
- 指纹分析器
- 自定义分析器
- Normalizers
- Tokenizers(分词器)
- Standard Tokenizer(标准分词器)
- Letter Tokenizer
- Lowercase Tokenizer (小写分词器)
- Whitespace Analyzer
- UAX URL Email Tokenizer
- Classic Tokenizer
- Thai Tokenizer(泰语分词器)
- NGram Tokenizer
- Edge NGram Tokenizer
- Keyword Analyzer
- Pattern Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Path Hierarchy Tokenizer(路径层次分词器)
- Token Filters(词元过滤器)
- Standard Token Filter
- ASCII Folding Token Filter
- Flatten Graph Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Synonym Graph Token Filter
- Compound Word Token Filters
- Reverse Token Filter
- Elision Token Filter
- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters(字符过滤器)
- HTML Strip Character Filter
- Mapping Character Filter
- Pattern Replace Character Filter
- 模块
- Cluster
- 集群级路由和碎片分配
- 基于磁盘的分片分配
- 分片分配awareness
- 分片分配过滤
- Miscellaneous cluster settings
- Scripting
- Painless Scripting Language
- Lucene Expressions Language
- Advanced scripts using script engines
- Snapshot And Restore
- Thread Pool
- Index Modules(索引模块)
- 预处理节点
- Pipeline Definition
- Ingest APIs
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- Delete Pipeline API
- Simulate Pipeline API
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Monitoring Elasticsearch
- X-Pack APIs
- X-Pack Commands
- How To
- Testing(测试)
- Glossary of terms
- Release Notes
- X-Pack Release Notes