// 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
- 入門
- 是什么
- 安裝
- API
- 文檔
- 索引
- 搜索
- 聚合
- 小結
- 分布式
- 結語
- 分布式集群
- 空集群
- 集群健康
- 添加索引
- 故障轉移
- 橫向擴展
- 更多擴展
- 應對故障
- 數據
- 文檔
- 索引
- 獲取
- 存在
- 更新
- 創建
- 刪除
- 版本控制
- 局部更新
- Mget
- 批量
- 結語
- 分布式增刪改查
- 路由
- 分片交互
- 新建、索引和刪除
- 檢索
- 局部更新
- 批量請求
- 批量格式
- 搜索
- 空搜索
- 多索引和多類型
- 分頁
- 查詢字符串
- 映射和分析
- 數據類型差異
- 確切值對決全文
- 倒排索引
- 分析
- 映射
- 復合類型
- 結構化查詢
- 請求體查詢
- 結構化查詢
- 查詢與過濾
- 重要的查詢子句
- 過濾查詢
- 驗證查詢
- 結語
- 排序
- 排序
- 字符串排序
- 相關性
- 字段數據
- 分布式搜索
- 查詢階段
- 取回階段
- 搜索選項
- 掃描和滾屏
- 索引管理
- 創建刪除
- 設置
- 配置分析器
- 自定義分析器
- 映射
- 根對象
- 元數據中的source字段
- 元數據中的all字段
- 元數據中的ID字段
- 動態映射
- 自定義動態映射
- 默認映射
- 重建索引
- 別名
- 深入分片
- 使文本可以被搜索
- 動態索引
- 近實時搜索
- 持久化變更
- 合并段
- 結構化搜索
- 查詢準確值
- 組合過濾
- 查詢多個準確值
- 包含,而不是相等
- 范圍
- 處理 Null 值
- 緩存
- 過濾順序
- 全文搜索
- 匹配查詢
- 多詞查詢
- 組合查詢
- 布爾匹配
- 增加子句
- 控制分析
- 關聯失效
- 多字段搜索
- 多重查詢字符串
- 單一查詢字符串
- 最佳字段
- 最佳字段查詢調優
- 多重匹配查詢
- 最多字段查詢
- 跨字段對象查詢
- 以字段為中心查詢
- 全字段查詢
- 跨字段查詢
- 精確查詢
- 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
- 地理坐標點
- 地理坐標點
- 通過地理坐標點過濾
- 地理坐標盒模型過濾器
- 地理距離過濾器
- 緩存地理位置過濾器
- 減少內存占用
- 按距離排序
- Geohashe
- Geohashe
- Geohashe映射
- Geohash單元過濾器
- 地理位置聚合
- 地理位置聚合
- 按距離聚合
- Geohash單元聚合器
- 范圍(邊界)聚合器
- 地理形狀
- 地理形狀
- 映射地理形狀
- 索引地理形狀
- 查詢地理形狀
- 在查詢中使用已索引的形狀
- 地理形狀的過濾與緩存
- 關系
- 關系
- 應用級別的Join操作
- 扁平化你的數據
- Top hits
- Concurrency
- Concurrency solutions
- 嵌套
- 嵌套對象
- 嵌套映射
- 嵌套查詢
- 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