实战1
创建索引：
PUT student
{
"mappings" : {
"properties" : {
"name" : {
"type" : "keyword"
},
"age" : {
"type" : "integer"
},
"height": {
"type": "integer"
}
}
}
}
使用 _bulk 创建多个文档：
POST _bulk
{ "index" : { "_index" : "student", "_id" : "1" } }
{ "name" : "张三", "age": 12 }
{ "index" : { "_index" : "student", "_id" : "2" } }
{ "name" : "李四", "age": 10, "height": 112 }
{ "index" : { "_index" : "student", "_id" : "3" } }
{ "name" : "王五", "age": 11, "height": 108 }
{ "index" : { "_index" : "student", "_id" : "4" } }
{ "name" : "陈六", "age": 11, "height": 111 }
查询所有数据
GET student/_search
或者：
GET student/_search
{
"query": {
"match_all": {}
}
}
或者：
POST student/_search
{
"query": {
"match_all": {}
}
}
查询张三的信息：
POST student/_search
{
"query": {
"match": {
"name": "张三"
}
}
}
或者：
POST student/_search
{
"query": {
"term": {
"name": "张三"
}
}
}
或者：
POST student/_search
{
"query": {
"bool": {
"must": [
{ "term" : { "name": "张三" } }
]
}
}
}
查询 11 岁的张三的信息：
因为没有数据，所以下面的查询结果为空：
POST student/_search
{
"query": {
"bool": {
"must": [
{ "term" : { "name": "张三" } },
{ "term" : { "age": 11 } }
]
}
}
}
查询 11岁、12岁的所有学生信息
POST student/_search
{
"query": {
"bool": {
"must": [
{ "terms" : { "age": [11, 12] } }
]
}
}
}
注意，是terms，不是 term。
查询小于11岁的学生信息
POST student/_search
{
"query": {
"bool": {
"must": [
{
"range": {
"age": {
"lt": "11"
}
}
}
]
}
}
}
查询11岁到13岁的学生信息
POST student/_search
{
"query": {
"bool": {
"must": [
{
"range": {
"age": {
"gte": "11",
"lte": "13"
}
}
}
]
}
}
}
查询有身高 height 记录的学生
POST student/_search
{
"query": {
"exists": {
"field": "height"
}
}
}
查询没有身高 height 记录的学生
POST student/_search
{
"query": {
"bool": {
"must_not": [
{
"exists": { "field": "height"}
}
]
}
}
}
在 ES 2.2.0 之前有一个 missing 指令，效果相同。不过已经被废弃。
是否存在11岁的学生
POST student/_search
{
"query": {
"bool": {
"must": [
{
"term": {"age": 11}
}
]
}
},
"from": 0,
"size": 1
}
若结果中有记录，则认为存在。
11 岁的学生总人数
方法1：
# 请求
POST student/_count
{
"query": {
"bool": {
"must": [
{
"term": {"age": 11}
}
]
}
}
}
# 响应
{
"count" : 2,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
}
}
方法2：使用聚合查询
# 请求
POST student/_search
{
"aggs":{
"age_count": {
"terms": {"field": "age"}
}
},
"size": 0
}
# 响应
{
"took" : 71,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"age_count" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 11,
"doc_count" : 2
},
{
"key" : 10,
"doc_count" : 1
},
{
"key" : 12,
"doc_count" : 1
}
]
}
}
}
可以看到，11 岁的有2个，10岁的1个，12岁的1个。
方法3：查询后进行聚合：
# 请求
POST student/_search
{
"query": {
"bool": {
"must": [
{"term": {"age": 11} }
]
}
},
"aggs":{
"age_count": {
"terms": {"field": "age"}
}
},
"size": 0
}
# 响应
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"age_count" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 11,
"doc_count" : 2
}
]
}
}
}
方法4：
# 请求
POST student/_search
{
"size": 0,
"aggregations": {
"group_by_age": {
"aggregations": {
"count_age": {
"value_count": {
"field": "_index"
}
}
},
"terms": {
"field": "age"
}
}
}
}
# 响应
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_age" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 11,
"doc_count" : 2,
"count_age" : {
"value" : 2
}
},
{
"key" : 10,
"doc_count" : 1,
"count_age" : {
"value" : 1
}
},
{
"key" : 12,
"doc_count" : 1,
"count_age" : {
"value" : 1
}
}
]
}
}
}
学生的平均岁数
方式1：
# 请求
POST student/_search
{
"aggs":{
"age_stat": {
"stats": {"field": "age"}
}
},
"size": 0
}
# 响应
{
"took" : 45,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"age_stat" : {
"count" : 4,
"min" : 10.0,
"max" : 12.0,
"avg" : 11.0,
"sum" : 44.0
}
}
}
stats 指令，会计算出指定字段的 count、min、max、avg、sum。
方式2：
# 请求
POST student/_search
{
"aggs":{
"age_stat": {
"avg": {"field": "age"}
}
},
"size": 0
}
# 响应
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"age_stat" : {
"value" : 11.0
}
}
}
最高的学生是谁？
最高的学生可能有多个。
方式1：找到最高的身高值，然后根据身高搜索学生信息。
方式2：按照身高排序。找到第1个的身高，然后根据身高搜索所有学生信息：
POST student/_search
{
"query": {
"match_all": {}
},
"sort" : [
{"height": {"order": "desc"}}
],
"from": 0,
"size": 1
}
每个年龄的平均身高是多少？
# 请求
POST student/_search
{
"size": 0,
"aggregations": {
"group_by_age": {
"aggregations": {
"avg_height": {
"avg": {
"field": "height"
}
}
},
"terms": {
"field": "age"
}
}
}
}
# 响应
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_age" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 11,
"doc_count" : 2,
"avg_height" : {
"value" : 109.5
}
},
{
"key" : 10,
"doc_count" : 1,
"avg_height" : {
"value" : 112.0
}
},
{
"key" : 12,
"doc_count" : 1,
"avg_height" : {
"value" : null
}
}
]
}
}
}
获取每个年龄的平均身高，并按照年龄从小到大排序
方式1：
# 请求
POST student/_search
{
"size": 0,
"aggregations": {
"group_by_age": {
"aggregations": {
"avg_height": {
"avg": {
"field": "height"
}
}
},
"terms": {
"field": "age",
"order": {
"_term": "asc"
}
}
}
}
}
# 响应 （响应中指出 _term 已经废弃，应使用 _key）
#! Deprecation: Deprecated aggregation order key [_term] used, replaced by [_key]
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_age" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 10,
"doc_count" : 1,
"avg_height" : {
"value" : 112.0
}
},
{
"key" : 11,
"doc_count" : 2,
"avg_height" : {
"value" : 109.5
}
},
{
"key" : 12,
"doc_count" : 1,
"avg_height" : {
"value" : null
}
}
]
}
}
}
方式2：
POST student/_search
{
"size": 0,
"aggregations": {
"group_by_age": {
"aggregations": {
"avg_height": {
"avg": {
"field": "height"
}
},
"bucket_sort_by_avg_height": {
"bucket_sort": {
"sort": [
{"_key": {"order": "asc"}}
]
}
}
},
"terms": {
"field": "age"
}
}
}
}
获取每个年龄的平均身高，并按照平均身高从大到小排序
# 请求
POST student/_search
{
"size": 0,
"aggregations": {
"group_by_age": {
"aggregations": {
"avg_height": {
"avg": {
"field": "height"
}
},
"bucket_sort_by_avg_height": {
"bucket_sort": {
"sort": [
{"avg_height": {"order": "desc"}}
]
}
}
},
"terms": {
"field": "age"
}
}
}
}
# 响应
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_age" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 10,
"doc_count" : 1,
"avg_height" : {
"value" : 112.0
}
},
{
"key" : 11,
"doc_count" : 2,
"avg_height" : {
"value" : 109.5
}
}
]
}
}
}