## Date Range Aggregation (日期范围聚合)
用于日期值的范围聚合。此聚合和正常[range](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-range-aggregation.html)(范围)聚合的主要区别在于可以用[Date Math](https://www.elastic.co/guide/en/elasticsearch/reference/current/common-options.html#date-math)(日期数学)表达式来表示from和to的值,并且还可以指定返回 from 和 to 响应字段的日期格式。注意,此聚合包含 from 值,但是不包含 to 值。
例子:
|
`POST /sales/_search?size=0`
`{`
`"aggs": {`
`"range": {`
`"date_range": {`
`"field": "date",`
`"format": "MM-yyy",`
`"ranges": [`
`{ "to": "now-10M/M" }, #1`
`{ "from": "now-10M/M" } #2`
`]`
`}`
`}`
`}`
`}`
|
#1
#2 >=现在减去10个月,向下舍入到月初
上面的例子,我们创建了两个范围buckets(区间),第一个将“bucket”的所有文件在10个月前,而第二个将“bucket”所有的文件都是10个月前的
结果:
|
`{`
`...`
`"aggregations": {`
`"range": {`
`"buckets": [`
`{`
`"to": 1.4436576E12,`
`"to_as_string": "10-2015",`
`"doc_count": 7,`
`"key": "*-10-2015"`
`},`
`{`
`"from": 1.4436576E12,`
`"from_as_string": "10-2015",`
`"doc_count": 0,`
`"key": "10-2015-*"`
`}`
`]`
`}`
`}`
`}`
|
### Date Format/Pattern (日期格式)
这些信息是从[JodaDate](http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html)复制过来的
所有ASCII字母都保留为格式模式字母,定义如下:
| 符号 | 含义 | Presentation | 范例 |
| G | era | text | AD |
| C | century of era (>=0) | number | 20 |
| Y | year of era (>=0) | year | 1996 |
| x | weekyear | year | 1996 |
| w | week of weekyear | number | 27 |
| e | day of week | number | 2 |
| E | day of week | text | Tuesday; Tue |
| y | year | year | 1996 |
| D | day of year | number | 189 |
| M |
month of year
| month | July; Jul; 07 |
| d | day of month | number | 10 |
| a | halfday of day | text | PM |
| K | hour of halfday (0~11) | number | 0 |
| h | clockhour of halfday (1~12) | number | 12 |
| H | hour of day (0~23) | number | 0 |
| k | clockhour of day (1~24) | number | 24 |
| m | minute of hour | number | 30 |
| s | second of minute | number | 55 |
| S | fraction of second | number | 978 |
| z | time zone | text | Pacific Standard Time; PST |
| Z | time zone offset/id | zone | -0800; -08:00; America/Los_Angeles |
| ' | escape for text | delimiter | '' |
模式字母的数量决定了格式
Text
如果模式字母的数量是4或更多,则使用完整的形式,否则,如果有的话,使用简短或缩写形式。
Number
最小位数 ,如果不足用0填充
Year
特别处理年,年的数字表示。 例如,如果y的计数为2,则该年份将显示为本世纪的零年,这是两位数。
Month
3或以上,使用文字,否则使用数字
Zone
Z输出无冒号的偏移量,ZZ以冒号输出偏移量,ZZZ或更大输出区域ID。
Zone names
时区名称(z)无法解析。
任何不在[a..z]和[A..Z]范围内的字符都将被视为引用的文本。 例如,像:,。,','#和? 即使它们不包含在单引号内,也会出现在生成的时间文本中。
### Time zone in date range aggregations(日期范围聚合中的时区)
可以通过指定time_zone参数将日期从另一个时区转换为UTC。
时区可以被指定为ISO 8601 UTC偏移量(例如+01:00或-08:00),也可以指定为TZ数据库的时区ID之一。
time_zone参数也适用于日期数学表达式中的舍入。 例如,要在CET时区开始一天的开始,您可以执行以下操作:
|
`POST /sales/_search?size=0`
`{`
`"aggs": {`
`"range": {`
`"date_range": {`
`"field": "date",`
`"time_zone": "CET",`
`"ranges": [`
`{ "to": "2016/02/01" }, #1`
`{ "from": "2016/02/01", "to" : "now/d" #2},`
`{ "from": "now/d" }`
`]`
`}`
`}`
`}`
`}`
|
#1 这个日期将改为2016-02-15t00:00 + 01:00
#2 now/d 将在CET时区四舍五入到一天的开始
### Keyed Response
将 keyed 标志设置为 true ,会将唯一的key与每个bucket关联起来,并将范围作为散列而不是数组返回
|
`POST /sales/_search?size=0`
`{`
`"aggs": {`
`"range": {`
`"date_range": {`
`"field": "date",`
`"format": "MM-yyy",`
`"ranges": [`
`{ "to": "now-10M/M" },`
`{ "from": "now-10M/M" }`
`],`
`"keyed": true`
`}`
`}`
`}`
`}`
|
结果:
|
`{`
`...`
`"aggregations": {`
`"range": {`
`"buckets": {`
`"*-10-2015": {`
`"to": 1.4436576E12,`
`"to_as_string": "10-2015",`
`"doc_count": 7`
`},`
`"10-2015-*": {`
`"from": 1.4436576E12,`
`"from_as_string": "10-2015",`
`"doc_count": 0`
`}`
`}`
`}`
`}`
`}`
|
也可以为每个区间自定义key
|
`POST /sales/_search?size=0`
`{`
`"aggs": {`
`"range": {`
`"date_range": {`
`"field": "date",`
`"format": "MM-yyy",`
`"ranges": [`
`{ "from": "01-2015", "to": "03-2015", "key": "quarter_01" },`
`{ "from": "03-2015", "to": "06-2015", "key": "quarter_02" }`
`],`
`"keyed": true`
`}`
`}`
`}`
`}`
|
响应结果:
|
`{`
`...`
`"aggregations": {`
`"range": {`
`"buckets": {`
`"quarter_01": {`
`"from": 1.4200704E12,`
`"from_as_string": "01-2015",`
`"to": 1.425168E12,`
`"to_as_string": "03-2015",`
`"doc_count": 5`
`},`
`"quarter_02": {`
`"from": 1.425168E12,`
`"from_as_string": "03-2015",`
`"to": 1.4331168E12,`
`"to_as_string": "06-2015",`
`"doc_count": 2`
`}`
`}`
`}`
`}`
`}`
|
- 入门
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- Analysis
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- 模块
- Cluster
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