# Glossary of terms (词汇表)
##### analysis(分析)
**Analysis**(分析)是将 [full text](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/glossary.html#glossary-text)(全文)转化为 [terms](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/glossary.html#glossary-term)(词条)的过程。使用不同的 **analyzer**(分词器),`**FOO BAR**,``**Foo-Bar**<span style="font-family: Arial, sans-serif;">,</span>``**foo**,**bar** ``这些短语可能都会生成 `**foo **和 `**`b``ar `**`两个词条,实际的 **index**(索引)里面存储的就是这些 **terms**(词条)`*`。`*`针对`` **FoO:bAR**的 **full text query**(全文检索),会先将其分析成为 **foo,**`**bar** 这样的词条,然后匹配存储在 **index**(索引)中的 **term**(词条)。正是这个 **analysis**(分析)的过程(发生在索引和搜索时)使得 **elasticsearch **能够执行 **full text queries**(全文检索)。<span style="color: rgb(68, 68, 68);">也可以参阅 </span>[text](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/glossary.html#glossary-text)(文本)<span style="color: rgb(68, 68, 68);">和 </span>[term](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/glossary.html#glossary-term)(词条)了解更多细节信息。```
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">cluster (集群)</span>
**cluster**(集群)是由拥有同一个集群名的一个或者多个节点组成。每个集群拥有一个主节点,它由集群自行选举出来,在当前主节点挂了,能被其他节点取代。
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">document (文档)</span>
**document(文档)**是存储在**elasticsearch**中的**json**文档。类似于关系型数据库中的一行记录。每个文档存储在一个**index**(索引)中,它具有一个**type**(类型)和一个**id**。文档是包含零到多个**fields**(属性)或者键值对的**json**对象(类似于其他语言中的hash/hashmap/associative array)。当一个文档被**indexed**(索引)的时候,它的原始**json**文档会被存储成**_source**属性,对该文档进行**get**或者**search**操作时,默认返回的就是改属性。
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">id </span>
文档的**ID**标识一个文档。文档的index/type/id必须唯一。如果没有提供**ID**,**elasticsearch**会自动生成一个**ID**。(查询**routing**(路由)获取更多信息)
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">field(属性) </span>
一个文档包涵一系列的属性或者键值对。它的值可以是简单标量值(如字符串,整型数,日期),或者是像数组和对象一样的嵌套结构。属性类似于关系型数据库中的列。每个属性的**mapping**(映射)都有其类型(不同于**document**(文档)的**type**(类型)),表明该属性能存储成改类型的数据,例如 `integer`, `string`, `object。**mapping**(映射)也允许你定义属性的值是否需要**analyzed**(分词)。`
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">index (索引)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">**index**(索引)类似于关系型数据库中的表。它有一个**mapping**(映射)来定义索引中的**fields**(属性),这些属性被分组成多种**type**(类型)。索引是一个逻辑命名空间,它对应一到多个**primary** **shards**(主分片)和零到多个**replica shards**(副本分片)。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">mapping (映射)</span>
<span style="color: rgb(0, 0, 0);">**mapping**(映射)类似于关系型数据库中的元数据定义。每一个**index**(索引)对应一个**mapping**(映射),它定义了**index**(索引)中的每一个**type**(类型),另外还有一些索引级别的设置。**mapping**(映射)可以显式定义,或者当一个文档进行索引时自动生成。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">node (节点)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">**node**(节点)是从属于一个**elasticsearch**集群的正在运行的节点。当以测试为目的时,可以在一台主机上启动多个节点,但是通常一台主机最好运行一个节点。在启动时,节点会使用广播的方式,自动感知(网络中)具有相同集群名的集群,并尝试加入它。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">primary shard (主分片)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">每个文档存储在单**primary shard** (主分片)中。当索引一个文档时,它会首先被索引到主分片上,然后索引到主分片的所有副本上。默认情况下,一个**index**(索引)有5个**primary shard** (主分片)。根据**index**(索引)的处理能力,你可以指定更少或者更多的**primary shard** (主分片)来扩展文档数量。当**index**(索引)创建之后,**primary shard** (主分片)的数量不可更改。查询**routing**(路由)获取更多信息。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">replica shard (副本分片)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">每一个**primary shard** (主分片)拥有零到多个副本。副本是**primary shard** (主分片)的拷贝,它的存在有两个目的:</span>
1. <span class="glossterm" style="color: rgb(0, 0, 0);">增加容错:当主分片失败时,一个**replica shard**(副本分片)可以提升为**primary shard** (主分片)</span>
2. <span class="glossterm" style="color: rgb(0, 0, 0);">提升性能:**primary shard** (主分片)和**replica shard**(副本分片)都能处理**get**和**shearch**请求。默认情况下,每个**primary shard** (主分片)有一个副本,副本的个数可以动态的修改。**replica shard**(副本分片)不会和**primary shard** (主分片)分配在同一个节点上。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">routing (路由)</span>
<span style="color: rgb(43, 69, 144);"> 当你索引一个文档时,它会被存储在一个单独的主分片上。通过对routing值进行哈希计算来决定具体是哪一个主分片。默认情况下,routing值是来自于文档ID,如果文档指定了一个父文档,则通过其父文档ID(保证父子文档存储在同一个分片上)。如果你不想使用默认的文档ID来作为routing值,你可以在索引时直接指定一个routing值,或者在mapping中指定一个字段的值来作为routing值。</span>
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##### <span style="color: rgb(43, 69, 144);">shard (分片)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">**shard**(分片)是一个**Lucene**实例。它是由**elasticsearch**管理的低层次的工作单元。**index**(索引)是指向 主分片和副本分片的逻辑命名空间。除了定义**index**(索引)应该具有的**primary** **shard**(主分片)和**replica shard**(副本分片)的数量之外,你不需要对**shard**(分片)作其它的工作。相反,你的代码应该只处理**index**(索引)。**elasticsearch**将**shards**(分片)分配到整个集群的所有节点上,当节点失败时可以自动将分片迁移到其他节点或者新增的节点上。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">source field (源属性)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">在默认情况下,你索引的**json** **document**(文档)会存储在_source **field**(属性)中,**get**和**search**请求会返回该**field**(属性)。这样可以直接在搜索结果中获取原始文档对象,不需要通过**ID**再检索一次文档对象。</span>
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##### <span class="glossterm" style="color: rgb(43, 69, 144);">term (词条)</span>
<span class="glossterm" style="color: rgb(0, 0, 0);">**term**(词条)是**elasticsearch**中被索引的确切值。`foo`, `Foo`, `FOO 这些**term**(词条)不相等。**term**(词条)可以通过词条搜索来检索。查询**text**(文本)和**anaylsis**(分词)获取更多信息。`
##### text (文本)
**text**(文本)(或者说全文)是普通的非结构化文本,如一个段落。默认情况下,**text**(文本)会被**analyzed**(分词)成**term**(词条),term(词条)是实际存储在索引中的内容。文本的**field**(属性)必须在索引时完成**analyzed**(分词)来支持全文检索的功能,全文检索使用的关键词也必须在搜索时**analyzed**(分词)成索引时产生的相同**term**(词条)。查询**term**(词条)和**analysis**(分词)获取更多信息。
##### type (类型)
**type**(类型)代表文档的类型,如一封邮件,一个用户,一条推文。搜索API可以通过文档类型来过滤。**index**(索引)可以包涵多个类型,每一个**type**(类型)有一系列的**fields**(属性)。同一个**index**(索引)中不同**type**(类型)的同名**fields**(属性)必须使用相同的**mapping**(映射)(定义文档的属性如何索引以及是文档能被搜索)。
- 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
- 更新文档
- 删除文档
- 批量处理
- 探索你的数据
- 搜索API
- 查询语言介绍
- 执行搜索
- 执行过滤
- 执行聚合
- 总结
- Elasticsearch设置
- 安装Elasticsearch
- .zip或.tar.gz文件的安装方式
- Install Elasticsearch with .zip on Windows
- Debian软件包安装方式
- RPM安装方式
- Install Elasticsearch with Windows MSI Installer
- Docker安装方式
- 配置Elasticsearch
- 安全配置
- 日志配置
- 重要的Elasticsearch配置
- 重要的系统配置
- 系统设置
- 在jvm.options中设置JVM堆大小
- 禁用swapping
- 文件描述符
- 虚拟内存
- 线程数
- DNS cache settings
- 启动前检查
- 堆大小检查
- 文件描述符检查
- 内存锁定检查
- 最大线程数检查
- 最大虚拟内存检查
- Max file size check
- 最大map数检查
- JVM Client模式检查
- 串行收集使用检查
- 系统调用过滤检查
- OnError与OnOutOfMemoryError检查
- Early-access check
- G1GC检查
- Elasticsearch停机
- Elasticsearch升级
- 滚动升级
- 全集群重启升级
- 索引重建升级
- Set up X-Pack
- Installing X-Pack
- X-Pack Settings
- Watcher Settings
- Configuring Security
- Breaking changes in 6.0
- X-Pack Breaking Changes
- 重大变化
- 6.0的重大变化
- 聚合变化
- Cat API变化
- 客户端变化
- 集群变化
- 文档API变化
- 索引变化
- 预处理变化
- 映射变化
- Packaging变化
- Percolator变化
- 插件变化
- 索引重建变化
- 信息统计变化
- DSL查询变化
- 设置变化
- 脚本变化
- API约定
- 多索引语法
- 索引库名称的日期运算
- 常用选项
- URL-based访问控制
- 文档APIs
- 读写文档
- 索引接口
- Get接口
- Delete API
- Delete By Query API
- Update API
- Update By Query API
- Multi Get API
- Bulk API
- Reindex API
- Term Vectors
- Multi termvectors API
- ?refresh
- 搜索APIs
- Search
- URI Search
- Request Body Search
- Query
- From / Size
- Sort
- Source filtering
- Fields
- Script Fields
- Doc value Fields
- Post filter
- Highlighting
- Rescoring
- Search Type
- Scroll
- Preference
- Explain
- Version
- Index Boost
- min_score
- Named Queries
- Inner hits
- Field Collapsing
- Search After
- Search Template
- Multi Search Template
- Search Shards API
- Suggesters
- Term suggester
- Phrase Suggester
- Completion Suggester
- Context Suggester
- Returning the type of the suggester
- Multi Search API
- Count API
- Validate API
- Explain API
- Profile API
- Profiling Queries
- Profiling Aggregations
- Profiling Considerations
- Field Capabilities API
- Aggregations
- Metrics Aggregations
- 平均值聚合
- 值计数聚合(Value Count Aggregation)
- Cardinality Aggregation
- Extended Stats Aggregation
- 地理边界聚合
- 地理重心聚合
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top hits Aggregation
- Value Count Aggregation
- Bucket Aggregations
- 邻接矩阵聚合
- Children Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Significant Terms Aggregation
- 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)
- Range Aggregation(范围聚合)
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation(导数聚合)
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation(扩展信息桶聚合)
- 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
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Indices APIs
- Create Index /创建索引
- Delete Index /删除索引
- Get Index /获取索引
- Indices Exists /索引存在
- Open / Close Index API /启动关闭索引
- Shrink Index /缩小索引
- Rollover Index/滚动索引
- Put Mapping /提交映射
- Get Mapping /获取映射
- Get Field Mapping /获取字段映射
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Explain Analyze
- Index Templates
- 索引统计信息
- 索引段
- 索引恢复
- 索引分片存储
- 清理缓存
- 刷新
- 同步刷新
- 重新加载
- 强制合并
- Cat APIs
- cat aliases
- cat allocation
- cat count
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat thread pool
- cat snapshots
- cat templates
- Cluster APIs
- 集群健康
- 集群状态
- 集群统计
- 挂起的集群任务
- 集群重新路由
- Cluster Update Settings
- Nodes Stats
- Nodes Info
- Nodes Feature Usage
- Remote Cluster Info
- Task Management API
- Nodes hot_threads
- Cluster Allocation Explain API
- Query DSL
- 查询context与过滤context
- Match All Query
- 全文搜索
- 匹配查询
- 短语匹配查询
- 短语前缀匹配查询
- 多字段查询
- 常用术语查询
- 查询语句查询
- 简单查询语句
- Term level queries
- Term Query
- Terms Query
- Range Query
- Exists Query
- Prefix Query
- Wildcard Query
- Regexp Query
- Fuzzy Query
- Type Query
- Ids Query
- 复合查询
- Constant Score 查询
- Bool 查询
- Dis Max 查询
- Function Score 查询
- Boosting 查询
- Joining queries
- Has Child Query
- Has Parent Query
- Nested Query(嵌套查询)
- Parent Id Query
- Geo queries
- GeoShape Query(地理形状查询)
- Geo Bounding Box Query(地理边框查询)
- 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
- Span Multi Term 查询
- Span First 查询
- Span Near 查询
- Span Or 查询
- Span Not 查询
- Span Containing 查询
- Span Within 查询
- Span Field Masking 查询 转至元数据结尾
- Minimum Should Match
- Multi Term Query Rewrite
- Mapping
- Removal of mapping types
- Field datatypes
- Array
- Binary
- Range
- Boolean
- Date
- Geo-point datatype
- Geo-Shape datatype
- IP datatype
- Keyword datatype
- Nested datatype
- Numeric datatypes
- Object datatype
- Text
- Token数
- 渗滤型
- join datatype
- Meta-Fields
- _all field
- _field_names field
- _id field
- _index field
- _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
- Put Pipeline API
- Get Pipeline API
- 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