// I'd limit this list to the metrics and rely on the obvious. You don't need to explain what min/max/avg etc are. Then say that we'll discusss these more interesting metrics in later chapters: cardinality, percentiles, significant terms. The buckets I'd mention under the relevant section, eg Histo & Range, etc
== Available Buckets and Metrics
There are a number of different buckets and metrics. The reference documentation
does a great job describing the various parameters and how they affect
the component. Instead of re-describing them here, we are simply going to
link to the reference docs and provide a brief description. Skim the list
so that you know what is available, and check the reference docs when you need
exact parameters.
[float]
=== Buckets
- {ref}search-aggregations-bucket-global-aggregation.html[Global]: includes all documents in your index
- {ref}search-aggregations-bucket-filter-aggregation.html[Filter]: only includes documents that match
the filter
- {ref}search-aggregations-bucket-missing-aggregation.html[Missing]: all documents which _do not_ have
a particular field
- {ref}search-aggregations-bucket-terms-aggregation.html[Terms]: generates a new bucket for each unique term
- {ref}search-aggregations-bucket-range-aggregation.html[Range]: creates arbitrary ranges which documents
fall into
- {ref}search-aggregations-bucket-daterange-aggregation.html[Date Range]: similar to Range, but calendar
aware
- {ref}search-aggregations-bucket-iprange-aggregation.html[IPV4 Range]: similar to Range, but can handle "IP logic" like CIDR masks, etc
- {ref}search-aggregations-bucket-geodistance-aggregation.html[Geo Distance]: similar to Range, but operates on
geo points
- {ref}search-aggregations-bucket-histogram-aggregation.html[Histogram]: equal-width, dynamic ranges
- {ref}search-aggregations-bucket-datehistogram-aggregation.html[Date Histogram]: similar to Histogram, but
calendar aware
- {ref}search-aggregations-bucket-nested-aggregation.html[Nested]: a special bucket for working with
nested documents (see <<nested-aggregation>>)
- {ref}search-aggregations-bucket-geohashgrid-aggregation.html[Geohash Grid]: partitions documents according to
what geohash grid they fall into (see <<geohash-grid-agg>>)
- {ref}search-aggregations-metrics-top-hits-aggregation.html[TopHits]: Return the top search results grouped by the value of a field (see <<top-hits>>)
[float]
=== Metrics
- Individual statistics: {ref}search-aggregations-metrics-min-aggregation.html[Min], {ref}search-aggregations-metrics-max-aggregation.html[Max], {ref}search-aggregations-metrics-avg-aggregation.html[Avg], {ref}search-aggregations-metrics-sum-aggregation.html[Sum]
- {ref}search-aggregations-metrics-stats-aggregation.html[Stats]: calculates min/mean/max/sum/count of documents in bucket
- {ref}search-aggregations-metrics-extendedstats-aggregation.html[Extended Stats]: Same as stats, except it also includes variance, std deviation, sum of squares
- {ref}search-aggregations-metrics-valuecount-aggregation.html[Value Count]: calculates the number of values, which may
be different from the number of documents (e.g. multi-valued fields)
- {ref}search-aggregations-metrics-cardinality-aggregation.html[Cardinality]: calculates number of distinct/unique values (see <<cardinality>>)
- {ref}search-aggregations-metrics-percentile-aggregation.html[Percentiles]: calculates percentiles/quantiles for
numeric values in a bucket (see <<percentiles>>)
- {ref}search-aggregations-bucket-significantterms-aggregation.html[Significant Terms]: finds "uncommonly common" terms
(see <<significant-terms>>)
- 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
- 局部更新
- 批量请求
- 批量格式
- 搜索
- 空搜索
- 多索引和多类型
- 分页
- 查询字符串
- 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
- 字符串排序
- 相关性
- 字段数据
- 分布式搜索
- 查询阶段
- 取回阶段
- 搜索选项
- 扫描和滚屏
- 索引管理
- 创建删除
- 设置
- 配置分析器
- 自定义分析器
- 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
- 近实时搜索
- 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
- Concurrency solutions
- 嵌套
- 嵌套对象
- 嵌套映射
- 嵌套查询
- 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