DELETE cars
PUT cars
{
"mappings": {
"transactions": {
"properties": {
"price": {
"type":"long"
},
"color": {
"type":"keyword"
},
"make": {
"type":"keyword"
},
"sold": {
"type":"date"
}
}
}
}
}
POST /cars/transactions/_bulk
{ "index": {}}
{ "price" : 10000, "color" : "red", "make" : "honda", "sold" : "2014-10-28" }
{ "index": {}}
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "index": {}}
{ "price" : 30000, "color" : "green", "make" : "ford", "sold" : "2014-05-18" }
{ "index": {}}
{ "price" : 15000, "color" : "blue", "make" : "toyota", "sold" : "2014-07-02" }
{ "index": {}}
{ "price" : 12000, "color" : "green", "make" : "toyota", "sold" : "2014-08-19" }
{ "index": {}}
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "index": {}}
{ "price" : 80000, "color" : "red", "make" : "bmw", "sold" : "2014-01-01" }
{ "index": {}}
{ "price" : 25000, "color" : "blue", "make" : "ford", "sold" : "2014-02-12" }
----------Filter Aggregation-------
红色车的数量
POST /cars/transactions/_search?size=0
{
"aggs" : {
"red_cars" : {
"filter" : { "term": { "color": "red" } }
}
}
}
----------Filters Aggregation-------
统计红色车、蓝色车各多少个
POST /cars/transactions/_search
{
"size": 0,
"aggs" : {
"cars" : {
"filters" : {
"filters" : {
"red_cars" : { "match" : { "color" : "red" }},
"blue_cars" : { "match" : { "color" : "blue" }}
}
}
}
}
}
统计红色车、蓝色车各多少个,并计算两种颜色车的平均价格
POST /cars/transactions/_search
{
"size": 0,
"aggs" : {
"cars" : {
"filters" : {
"filters" : {
"red_cars" : { "match" : { "color" : "red" }},
"blue_cars" : { "match" : { "color" : "blue" }}
}
},
"aggs" : {
"avg_price" : { "avg" : { "field" : "price" } }
}
}
}
}
----------Date Histogram Aggregation-------
每月销售多少台汽车
interval参数: year, quarter, month, week, day, hour, minute, second
interval参数:还可以写具体的时间,比如24h,90m
GET /cars/transactions/_search
{
"size" : 0,
"aggs": {
"sales_over_time": {
"date_histogram": {
"field": "sold",
"interval": "month",
"format": "yyyy-MM-dd"
}
}
}
}
指定周期90分钟
GET /cars/transactions/_search
{
"size" : 0,
"aggs": {
"sales_over_time": {
"date_histogram": {
"field": "sold",
"interval": "90m",
"format": "yyyy-MM-dd HH:mm:ss"
}
}
}
}
加入keyed参数,使返回的buckets不作为一个数组返回
GET /cars/transactions/_search
{
"size" : 0,
"aggs": {
"sales_over_time": {
"date_histogram": {
"field": "sold",
"interval": "month",
"format": "yyyy-MM-dd",
"keyed":true
}
}
}
}
----------Date Range Aggregation-------
按照售卖日期范围统计车辆数量
GET /cars/transactions/_search
{
"size": 0,
"aggs": {
"range": {
"date_range": {
"field": "sold",
"format": "yyyy-MM-dd",
"ranges": [
{"from": "now-36M/M"},
{"to": "now-24M/M"},
{"from": "now-36M/M","to": "now-12M/M"}
]
}
}
}
}
加入keyed参数,使返回的buckets不作为一个数组返回,并指定key值
GET /cars/transactions/_search
{
"size": 0,
"aggs": {
"range": {
"date_range": {
"field": "sold",
"format": "yyyy-MM-dd",
"ranges": [
{"from": "now-36M/M","key":"36months"},
{"to": "now-24M/M","key":"2years_ago"},
{"from": "now-36M/M","to": "now-12M/M"}
],
"keyed":true
}
}
}
}
按照售卖日期范围统计车辆数量,并计算该周期内的平均售卖价格
GET /cars/transactions/_search
{
"size": 0,
"aggs": {
"range": {
"date_range": {
"field": "sold",
"format": "yyyy-MM-dd",
"ranges": [
{"from": "now-36M/M","key":"36months"},
{"to": "now-24M/M","key":"2years_ago"},
{"from": "now-36M/M","to": "now-12M/M"}
],
"keyed":true
},
"aggs" : {
"avg_price" : { "avg" : { "field" : "price" } }
}
}
}
}
----------Histogram Aggregation-------
直方图,按照20000为区间进行分桶
GET /cars/transactions/_search
{
"size" : 0,
"aggs" : {
"colors" : {
"histogram" : {
"field" : "price",
"interval": 20000
}
}
}
}
min_doc_count参数,限制桶内至少有几个才显示
GET /cars/transactions/_search
{
"size" : 0,
"aggs" : {
"colors" : {
"histogram" : {
"field" : "price",
"interval": 20000,
"min_doc_count": 1
}
}
}
}
extended_bounds参数,扩展显示范围
GET /cars/transactions/_search
{
"size" : 0,
"aggs" : {
"colors" : {
"histogram" : {
"field" : "price",
"interval": 20000,
"extended_bounds": {
"min" : 0,
"max" : 200000
}
}
}
}
}
增加排序,按照桶名降序
GET /cars/transactions/_search
{
"size" : 0,
"aggs" : {
"colors" : {
"histogram" : {
"field" : "price",
"interval": 20000,
"order" : { "_key" : "desc" }
}
}
}
}
增加排序,按照统计数量排序
GET /cars/transactions/_search
{
"size" : 0,
"aggs" : {
"colors" : {
"histogram" : {
"field" : "price",
"interval": 20000,
"order" : { "_count" : "desc" }
}
}
}
}
直方图,按照20000为区间进行分桶,并进行汇总
GET /cars/transactions/_search
{
"size" : 0,
"aggs":{
"price":{
"histogram":{
"field": "price",
"interval": 20000
},
"aggs":{
"price_sum": {
"sum": {
"field" : "price"
}
}
}
}
}
}
直方图,按照20000为区间进行分桶,并进行汇总
按照子聚合的指标进行排序
GET /cars/transactions/_search
{
"size" : 0,
"aggs":{
"price":{
"histogram":{
"field": "price",
"interval": 20000,
"order":{ "price_sum.value" : "desc" }
},
"aggs":{
"price_sum": {
"sum": {
"field" : "price"
}
}
}
}
}
}
增加keyed参数
GET /cars/transactions/_search
{
"size" : 0,
"aggs":{
"price":{
"histogram":{
"field": "price",
"interval": 20000,
"order":{ "price_sum.value" : "desc" }
,"keyed":true
},
"aggs":{
"price_sum": {
"sum": {
"field" : "price"
}
}
}
}
}
}
----------Terms Aggregation-------
按照某个字段的词条进行分桶
在每个分片上先获取前几个数量最多的词条,然后再整体二次重排,所以可能会有误差
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"field" : "make"
}
}
}
}
按照词条的字母顺序排序
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"field" : "make",
"order" : { "_term" : "asc" }
}
}
}
}
min_doc_count:用于限制只提取出现次数大于多少次的词条
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"field" : "make",
"min_doc_count": 3
}
}
}
}
使用脚本,进行修改field内容
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"script" : {
"inline": "'make:'+doc['make'].value",
"lang": "painless"
}
}
}
}
}
同上
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"field" : "make",
"script" : {
"inline" : "'make: ' +_value",
"lang" : "painless"
}
}
}
}
}
使用正则表达式过滤词条
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"field" : "make",
"include" : ".*o.*",
"exclude" : "f.*"
}
}
}
}
使用精确指定的词条进行分桶
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"make_terms" : {
"terms" : {
"field" : "make",
"include" : ["mazda", "honda"]
}
}
}
}
----------Range Aggregation-------
按照指定的范围区间分桶,并计算数量
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"ranges" : [
{ "to" : 20000 },
{ "from" : 20000, "to" : 50000 },
{ "from" : 50000 }
]
}
}
}
}
用script脚本指定field
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"price_ranges" : {
"range" : {
"script" : {
"lang": "painless",
"inline": "doc['price'].value"
},
"ranges" : [
{ "to" : 20000 },
{ "from" : 20000, "to" : 50000 },
{ "from" : 50000 }
]
}
}
}
}
在分桶前,通过脚本更改值
GET /cars/transactions/_search
{
"size": 0,
"aggs" : {
"price_ranges" : {
"range" : {
"field" :"price",
"script" : {
"lang": "painless",
"inline": "_value * params.rate",
"params" : {
"rate" : 2.5
}
},
"ranges" : [
{ "to" : 20000 },
{ "from" : 20000, "to" : 50000 },
{ "from" : 50000 }
]
}
}
}
}
----------Global Aggregation-------
用global来计算所有的文档
GET /cars/transactions/_search?size=0
{
"query" : {
"match" : { "make" : "honda" }
},
"aggs" : {
"all_makes" : {
"global" : {},
"aggs" : {
"avg_price" : { "avg" : { "field" : "price" } }
}
},
"honda_make": { "avg" : { "field" : "price" } }
}
}
验证一下global计算是否正确
GET /cars/transactions/_search?size=0
{
"query" : {
"match_all" : { }
},
"aggs" : {
"all_make": { "avg" : { "field" : "price" } }
}
}
----------IP Range Aggregation-------
DELETE ips
PUT ips
{
"mappings": {
"transactions": {
"properties": {
"ip": {
"type":"ip"
}
}
}
}
}
POST /ips/doc/_bulk
{ "index": {}}
{ "ip" : "192.168.1.1"}
{ "index": {}}
{ "ip" : "192.168.1.10"}
{ "index": {}}
{ "ip" : "192.168.1.102"}
{ "index": {}}
{ "ip" : "192.168.1.150"}
{ "index": {}}
{ "ip" : "192.168.1.160"}
{ "index": {}}
{ "ip" : "192.168.1.250"}
按照指定的ip范围分桶,并统计数量
GET /ips/doc/_search
{
"size": 0,
"aggs" : {
"ip_ranges" : {
"ip_range" : {
"field" : "ip",
"ranges" : [
{"from" : "192.168.1.1" },
{"to" : "192.168.2.1" },
{"from" : "192.168.1.1","to" : "192.168.3.200" }
]
}
}
}
}
通过子网掩码范围分桶
192.168.1.0/24表示:192.168.1.1至192.168.1.254
192.168.2.0/25:192.168.2.1至192.168.2.126
GET /ips/doc/_search
{
"size": 0,
"aggs" : {
"ip_ranges" : {
"ip_range" : {
"field" : "ip",
"ranges" : [
{ "mask" : "192.168.1.0/24" },
{ "mask" : "192.168.2.0/25" }
]
}
}
}
}
加入keyed参数
GET /ips/doc/_search
{
"size": 0,
"aggs" : {
"ip_ranges" : {
"ip_range" : {
"field" : "ip",
"ranges" : [
{ "mask" : "192.168.1.0/24" },
{ "mask" : "192.168.2.0/25" }
],
"keyed": true
}
}
}
}
----------Geo Distance Aggregation-------
DELETE /museums
PUT /museums
{
"mappings": {
"doc": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
}
POST /museums/doc/_bulk?refresh
{"index":{"_id":1}}
{"location": "52.374081,4.912350", "name": "NEMO Science Museum"}
{"index":{"_id":2}}
{"location": "52.369219,4.901618", "name": "Museum Het Rembrandthuis"}
{"index":{"_id":3}}
{"location": "52.371667,4.914722", "name": "Nederlands Scheepvaartmuseum"}
{"index":{"_id":4}}
{"location": "51.222900,4.405200", "name": "Letterenhuis"}
{"index":{"_id":5}}
{"location": "48.861111,2.336389", "name": "Musée du Louvre"}
{"index":{"_id":6}}
{"location": "48.860000,2.327000", "name": "Musée d'Orsay"}
指定坐标点多少距离范围内的分桶文档,默认单位:m(米)
POST /museums/_search?size=0
{
"aggs" : {
"rings_around_amsterdam" : {
"geo_distance" : {
"field" : "location",
"origin" : "52.3760, 4.894",
"ranges" : [
{ "to" : 100000 },
{ "from" : 100000, "to" : 300000 },
{ "from" : 300000 }
]
}
}
}
}
指定单位为公里
可以使用:mi (miles英里), in (inches英寸), yd (yards码尺), km (kilometers), cm (centimeters), mm (millimeters).
POST /museums/_search?size=0
{
"aggs" : {
"rings_around_amsterdam" : {
"geo_distance" : {
"field" : "location",
"origin" : "52.3760, 4.894",
"unit" : "km",
"ranges" : [
{ "to" : 100000 },
{ "from" : 100000, "to" : 300000 },
{ "from" : 300000 }
]
}
}
}
}
指定距离模式
distance_type:arc弧度(默认,精度高,计算准确),plane(性能更好,速度更快,但精度稍差)
POST /museums/_search?size=0
{
"aggs" : {
"rings" : {
"geo_distance" : {
"field" : "location",
"origin" : "52.3760, 4.894",
"unit" : "km",
"distance_type" : "plane",
"ranges" : [
{ "to" : 100 },
{ "from" : 100, "to" : 300 },
{ "from" : 300 }
]
}
}
}
}
使用keyed
POST /museums/_search?size=0
{
"aggs" : {
"rings_around_amsterdam" : {
"geo_distance" : {
"field" : "location",
"origin" : "52.3760, 4.894",
"ranges" : [
{ "to" : 100000 },
{ "from" : 100000, "to" : 300000 },
{ "from" : 300000 }
],
"keyed": true
}
}
}
}