一、 ES簡單的增刪改查
1、創建一篇文檔（有則修改，無則創建;注意：PUT/POST直接修改必須全字段)
PUT test/doc/2
{
"name":"wangfei",
"age":27,
"desc":"熱天還不讓后人不認同"
}
PUT test/doc/1
{
"name":"wangjifei",
"age":27,
"desc":"薩芬我反胃為范圍額"
}
PUT test/doc/3
{
"name":"wangyang",
"age":30,
"desc":"點在我心內的幾首歌"
}
// 指定修改name字段
POST test/doc/_update/3
{
"doc": {
"name":"kingtao"
}
}
2、查詢指定索引信息
GET test
3、 查詢指定文檔信息
GET test/doc/1
GET test/doc/2
4、查詢對應索引下所有數據
GET test/doc/_search
或
GET test/doc/_search
{
"query": {
"match_all": {}
}
}
5、刪除指定文檔
DELETE test/doc/3
POST test/_delete_by_query
{
"query":{
"term":{
"title":"666"
}
}
}
6、刪除索引
DELETE test
7、修改指定文檔方式
修改時，不指定的屬性會自動覆蓋，只保留指定的屬性(不正確的修改指定文檔方式)
PUT test/doc/1
{
"name":"王計飛"
}
使用POST命令，在id后面跟_update，要修改的內容放到doc文檔（屬性）中(正確的修改指定文檔方式)
POST test/doc/_update/1
{
"doc":{
"desc":"生活就像 茫茫海上"
}
}
二、ES查詢的兩種方式
1、查詢字符串搜索
GET test/doc/_search?q=name:wangfei
2、結構化查詢(單字段查詢,不能多字段組合查詢)
GET test/doc/_search
{
"query":{
"match":{
"name":"wang"
}
}
}
三、match系列之操作
1、match系列之match_all (查詢全部)
GET test/doc/_search
{
"query":{
"match_all": {
}
}
}
2、match系列之match_phrase（短語查詢）
準備數據
PUT test1/doc/1
{
"title": "中國是世界上人口最多的國家"
}
PUT test1/doc/2
{
"title": "美國是世界上軍事實力最強大的國家"
}
PUT test1/doc/3
{
"title": "北京是中國的首都"
}
查詢語句
GET test1/doc/_search
{
"query":{
"match":{
"title":"中國"
}
}
}
輸出結果
{
"took" : 241,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.68324494,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.68324494,
"_source" : {
"title" : "中國是世界上人口最多的國家"
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.5753642,
"_source" : {
"title" : "北京是中國的首都"
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : 0.39556286,
"_source" : {
"title" : "美國是世界上軍事實力最強大的國家"
}
}
]
}
}
通過觀察結果可以發現，雖然如期的返回了中國的文檔。但是卻把和美國的文檔也返回了，這并不是我們想要的。是怎么回事呢？因為這是elasticsearch在內部對文檔做分詞的時候，對于中文來說，就是一個字一個字分的，所以，我們搜中國，中和國都符合條件，返回，而美國的國也符合。而我們認為中國是個短語，是一個有具體含義的詞。所以elasticsearch在處理中文分詞方面比較弱勢。后面會講針對中文的插件。但目前我們還有辦法解決，那就是使用短語查詢 用match_phrase
GET test1/doc/_search
{
"query":{
"match_phrase": {
"title": "中國"
}
}
}
查詢結果
{
"took" : 10,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.5753642,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.5753642,
"_source" : {
"title" : "中國是世界上人口最多的國家"
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.5753642,
"_source" : {
"title" : "北京是中國的首都"
}
}
]
}
}
我們搜索中國和世界這兩個指定詞組時，但又不清楚兩個詞組之間有多少別的詞間隔。那么在搜的時候就要留有一些余地。這時就要用到了slop了。相當于正則中的中國.*?世界。這個間隔默認為0
GET test1/doc/_search
{
"query":{
"match_phrase": {
"title": {
"query": "中國世界",
"slop":2
}
}
}
}
查詢結果
{
"took" : 23,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.7445889,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.7445889,
"_source" : {
"title" : "中國是世界上人口最多的國家"
}
}
]
}
}
3、match系列之match_phrase_prefix（最左前綴查詢）智能搜索--以什么開頭
數據準備
PUT test2/doc/1
{
"title": "prefix1",
"desc": "beautiful girl you are beautiful so"
}
PUT test2/doc/2
{
"title": "beautiful",
"desc": "I like basking on the beach"
}
搜索特定英文開頭的數據
查詢語句
GET test2/doc/_search
{
"query": {
"match_phrase_prefix": {
"desc": "bea"
}
}
}
查詢結果（）
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.39556286,
"hits" : [
{
"_index" : "test2",
"_type" : "doc",
"_id" : "1",
"_score" : 0.39556286,
"_source" : {
"title" : "prefix1",
"desc" : "beautiful girl you are beautiful so"
}
},
{
"_index" : "test2",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"title" : "beautiful",
"desc" : "I like basking on the beach"
}
}
]
}
}
查詢短語
GET test2/doc/_search
{
"query": {
"match_phrase_prefix": {
"desc": "you are bea"
}
}
}
查詢結果
{
"took" : 28,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.8630463,
"hits" : [
{
"_index" : "test2",
"_type" : "doc",
"_id" : "1",
"_score" : 0.8630463,
"_source" : {
"title" : "prefix1",
"desc" : "beautiful girl you are beautiful so"
}
}
]
}
}
max_expansions 參數理解 前綴查詢會非常的影響性能，要對結果集進行限制，就加上這個參數。
GET test2/doc/_search
{
"query": {
"match_phrase_prefix": {
"desc": {
"query": "bea",
"max_expansions":1
}
}
}
}
4、match系列之multi_match（多字段查詢)
multi_match是要在多個字段中查詢同一個關鍵字 除此之外，mulit_match甚至可以當做match_phrase和match_phrase_prefix使用，只需要指定type類型即可
GET test2/doc/_search
{
"query": {
"multi_match": {
"query": "beautiful",
"fields": ["title","desc"]
}
}
}
查詢結果
{
"took" : 43,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.39556286,
"hits" : [
{
"_index" : "test2",
"_type" : "doc",
"_id" : "1",
"_score" : 0.39556286,
"_source" : {
"title" : "prefix1",
"desc" : "beautiful girl you are beautiful so"
}
},
{
"_index" : "test2",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"title" : "beautiful",
"desc" : "I like basking on the beach"
}
}
]
}
}
當設置屬性 type:phrase 時 等同于 短語查詢
GET test1/doc/_search
{
"query": {
"multi_match": {
"query": "中國",
"fields": ["title"],
"type": "phrase"
}
}
}
查詢結果
{
"took" : 47,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.5753642,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.5753642,
"_source" : {
"title" : "中國是世界上人口最多的國家"
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.5753642,
"_source" : {
"title" : "北京是中國的首都"
}
}
]
}
}
當設置屬性 type:phrase_prefix時 等同于 最左前綴查詢
GET test2/doc/_search
{
"query": {
"multi_match": {
"query": "bea",
"fields": ["desc"],
"type": "phrase_prefix"
}
}
}
查詢結果
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.5753642,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.5753642,
"_source" : {
"title" : "中國是世界上人口最多的國家"
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.5753642,
"_source" : {
"title" : "北京是中國的首都"
}
}
]
}
}
match 查詢相關總結
1、match：返回所有匹配的分詞。
2、match_all：查詢全部。
3、match_phrase：短語查詢，在match的基礎上進一步查詢詞組，可以指定slop分詞間隔。
4、match_phrase_prefix：前綴查詢，根據短語中最后一個詞組做前綴匹配，可以應用于搜索提示，但注意和max_expanions搭配。其實默認是50.......
5、multi_match：多字段查詢，使用相當的靈活，可以完成match_phrase和match_phrase_prefix的工作。
四、ES的排序查詢
es 6.8.4版本中，需要分詞的字段不可以直接排序，比如：text類型，如果想要對這類字段進行排序，需要特別設置：對字段索引兩次，一次索引分詞（用于搜索）一次索引不分詞（用于排序），es默認生成的text類型字段就是通過這樣的方法實現可排序的。
text類型字段排序問題
1.倒敘排序
GET test/doc/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "desc"
}
}
]
}
排序結果
{
"took" : 152,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : null,
"hits" : [
{
"_index" : "test",
"_type" : "doc",
"_id" : "3",
"_score" : null,
"_source" : {
"name" : "wangyang",
"age" : 30,
"desc" : "點在我心內的幾首歌"
},
"sort" : [
30
]
},
{
"_index" : "test",
"_type" : "doc",
"_id" : "2",
"_score" : null,
"_source" : {
"name" : "wangfei",
"age" : 27,
"desc" : "熱天還不讓后人不認同"
},
"sort" : [
27
]
},
{
"_index" : "test",
"_type" : "doc",
"_id" : "1",
"_score" : null,
"_source" : {
"name" : "wangjifei",
"age" : 27,
"desc" : "生活就像 茫茫海上"
},
"sort" : [
27
]
}
]
}
}
2.升序排序
GET test/doc/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "asc"
}
}
]
}
五、ES的分頁查詢
from：從哪開始查 size：返回幾條結果
GET test/doc/_search
{
"query": {
"match_phrase_prefix": {
"name": "wang"
}
},
"from": 0,
"size": 1
}
查詢結果
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"name" : "wangfei",
"age" : 27,
"desc" : "熱天還不讓后人不認同"
}
}
]
}
}
六、ES的bool查詢 (must、should)
must (must字段對應的是個列表，也就是說可以有多個并列的查詢條件，一個文檔滿足各個子條件后才最終返回)
1.must單條件查詢
GET test/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "wangfei"
}
}
]
}
}
}
查詢結果
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"name" : "wangfei",
"age" : 27,
"desc" : "熱天還不讓后人不認同"
}
}
]
}
}
2.must多條件組合查詢
GET test/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "wanggfei"
}
},{
"match": {
"age": 25
}
}
]
}
}
}
查詢結果
{
"took" : 21,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 0,
"max_score" : null,
"hits" : [ ]
}
}
3.should (只要符合其中一個條件就返回)
GET test/doc/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"name": "wangjifei"
}
},{
"match": {
"age": 27
}
}
]
}
}
}
查詢結果
{
"took" : 34,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 1.287682,
"hits" : [
{
"_index" : "test",
"_type" : "doc",
"_id" : "1",
"_score" : 1.287682,
"_source" : {
"name" : "wangjifei",
"age" : 27,
"desc" : "生活就像 茫茫海上"
}
},
{
"_index" : "test",
"_type" : "doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"name" : "wangfei",
"age" : 27,
"desc" : "熱天還不讓后人不認同"
}
}
]
}
}
4.must_not 顧名思義
GET test/doc/_search
{
"query": {
"bool": {
"must_not": [
{
"match": {
"name": "wangjifei"
}
},{
"match": {
"age": 27
}
}
]
}
}
}
查詢結果
{
"took" : 13,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test",
"_type" : "doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"name" : "wangyang",
"age" : 30,
"desc" : "點在我心內的幾首歌"
}
}
]
}
}
5.filter(條件過濾查詢，過濾條件的范圍用range表示gt表示大于、lt表示小于、gte表示大于等于、lte表示小于等于)
GET test/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "wangjifei"
}
}
],
"filter": {
"range": {
"age": {
"gte": 10,
"lt": 27
}
}
}
}
}
}
查詢結果
{
"took" : 33,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 0,
"max_score" : null,
"hits" : [ ]
}
}
bool查詢總結
must：與關系，相當于關系型數據庫中的 and。
should：或關系，相當于關系型數據庫中的 or。
must_not：非關系，相當于關系型數據庫中的 not。
filter：過濾條件。
range：條件篩選范圍。
gt：大于，相當于關系型數據庫中的 >。
gte：大于等于，相當于關系型數據庫中的 >=。
lt：小于，相當于關系型數據庫中的 <。
lte：小于等于，相當于關系型數據庫中的 <=。
七、ES之查詢結果過濾
準備數據
PUT test3/doc/1
{
"name":"顧老二",
"age":30,
"from": "gu",
"desc": "皮膚黑、武器長、性格直",
"tags": ["黑", "長", "直"]
}
現在，在所有的結果中，我只需要查看name和age兩個屬性,提高查詢效率
GET test3/doc/_search
{
"query": {
"match": {
"name": "顧"
}
},
"_source": ["name","age"]
}
查詢結果
{
"took" : 58,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test3",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顧老二",
"age" : 30
}
}
]
}
}
八、ES之查詢結果高亮顯示
ES的默認高亮顯示
GET test3/doc/_search
{
"query": {
"match": {
"name": "顧老二"
}
},
"highlight": {
"fields": {
"name": {}
}
}
}
查詢結果
{
"took" : 216,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.8630463,
"hits" : [
{
"_index" : "test3",
"_type" : "doc",
"_id" : "1",
"_score" : 0.8630463,
"_source" : {
"name" : "顧老二",
"age" : 30,
"from" : "gu",
"desc" : "皮膚黑、武器長、性格直",
"tags" : [
"黑",
"長",
"直"
]
},
"highlight" : {
"name" : [
"<em>顧</em><em>老</em><em>二</em>"
]
}
}
]
}
}
ES自定義高亮顯示（在highlight中，pre_tags用來實現我們的自定義標簽的前半部分，在這里，我們也可以為自定義的 標簽添加屬性和樣式。post_tags實現標簽的后半部分，組成一個完整的標簽。至于標簽中的內容，則還是交給fields來完成）
GET test3/doc/_search
{
"query": {
"match": {
"desc": "性格直"
}
},
"highlight": {
"pre_tags": "<b class='key' style='color:red'>",
"post_tags": "</b>",
"fields": {
"desc": {}
}
}
}
查詢結果
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.8630463,
"hits" : [
{
"_index" : "test3",
"_type" : "doc",
"_id" : "1",
"_score" : 0.8630463,
"_source" : {
"name" : "顧老二",
"age" : 30,
"from" : "gu",
"desc" : "皮膚黑、武器長、性格直",
"tags" : [
"黑",
"長",
"直"
]
},
"highlight" : {
"desc" : [
"皮膚黑、武器長、<b class='key' style='color:red'>性</b><b class='key' style='color:red'>格</b><b class='key' style='color:red'>直</b>"
]
}
}
]
}
}
九、ES之精確查詢與模糊查詢
term查詢查找包含文檔精確的倒排索引指定的詞條。也就是精確查找。
term和match的區別是：
match是經過analyer的，也就是說，文檔首先被分析器給處理了。根據不同的分析器，分析的結果也稍顯不同，然后再根據分詞結果進行匹配。
term則不經過分詞，它是直接去倒排索引中查找了精確的值了。
準備數據
PUT w1
{
"mappings": {
"doc": {
"properties":{
"t1":{
"type": "text"
},
"t2": {
"type": "keyword"
}
}
}
}
}
PUT w1/doc/1
{
"t1": "hi single dog",
"t2": "hi single dog"
}
對比兩者的不同 (結果就不展示出來了，只展示結果的文字敘述)
t1類型為text，會經過分詞，match查詢時條件也會經過分詞，所以下面兩種查詢都能查到結果
GET w1/doc/_search
{
"query": {
"match": {
"t1": "hi single dog"
}
}
}
GET w1/doc/_search
{
"query": {
"match": {
"t1": "hi"
}
}
}
t2類型為keyword類型，不會經過分詞，match查詢時條件會經過分詞，所以只能當值為"hi single dog"時能查詢到
GET w1/doc/_search
{
"query": {
"match": {
"t2": "hi"
}
}
}
GET w1/doc/_search
{
"query": {
"match": {
"t2": "hi single dog"
}
}
}
t1類型為text，會經過分詞，term查詢時條件不會經過分詞，所以只有當值為"hi"時能查詢到
GET w1/doc/_search
{
"query": {
"term": {
"t1": "hi single dog"
}
}
}
GET w1/doc/_search
{
"query": {
"term": {
"t1": "hi"
}
}
}
t2類型為keyword類型，不會經過分詞，term查詢時條件不會經過分詞，所以只能當值為"hi single dog"時能查詢到
GET w1/doc/_search
{
"query": {
"term": {
"t2": "hi single dog"
}
}
}
GET w1/doc/_search
{
"query": {
"term": {
"t2": "hi"
}
}
}
查找多個精確值（terms）
第一個查詢方式
GET test/doc/_search
{
"query": {
"bool": {
"should": [
{
"term": {
"age":27
}
},{
"term":{
"age":28
}
}
]
}
}
}
第二個查詢方式
GET test/doc/_search
{
"query": {
"terms": {
"age": [
"27",
"28"
]
}
}
}
兩種方式的查詢結果都是一下結果
{
"took" : 10,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test",
"_type" : "doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"name" : "wangfei",
"age" : 27,
"desc" : "熱天還不讓后人不認同"
}
},
{
"_index" : "test",
"_type" : "doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "wangjifei",
"age" : 27,
"desc" : "生活就像 茫茫海上"
}
}
]
}
}
第三個查詢方式-精確查數組-or
GET indexname/_search
{
"query": {
"terms": {
"images.keyword": [
"2457741_58feb159-c7a1-4527-8af5-64e87b29b2c8.jpg"，"xxxx" // a or b查詢
]
}
}
}
索引中有個字段
"images" : [
"2457741_58feb159-c7a1-4527-8af5-64e87b29b2c8.jpg"
],
字段的mapping設置
"images": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
十、ES的聚合查詢avg、max、min、sum
數據準備
PUT zhifou/doc/1
{
"name":"顧老二",
"age":30,
"from": "gu",
"desc": "皮膚黑、武器長、性格直",
"tags": ["黑", "長", "直"]
}
PUT zhifou/doc/2
{
"name":"大娘子",
"age":18,
"from":"sheng",
"desc":"膚白貌美，嬌憨可愛",
"tags":["白", "富","美"]
}
PUT zhifou/doc/3
{
"name":"龍套偏房",
"age":22,
"from":"gu",
"desc":"mmp，沒怎么看，不知道怎么形容",
"tags":["造數據", "真","難"]
}
PUT zhifou/doc/4
{
"name":"石頭",
"age":29,
"from":"gu",
"desc":"粗中有細，狐假虎威",
"tags":["粗", "大","猛"]
}
PUT zhifou/doc/5
{
"name":"魏行首",
"age":25,
"from":"廣云臺",
"desc":"仿佛兮若輕云之蔽月,飄飄兮若流風之回雪,mmp，最后竟然沒有嫁給顧老二！",
"tags":["閉月","羞花"]
}
GET zhifou/doc/_search
{
"query": {
"match_all": {}
}
}
1、查詢from是gu的人的平均年齡。
GET zhifou/doc/_search
{
"query": {
"match": {
"from": "gu"
}
},
"aggs": {
"my_avg": {
"avg": {
"field": "age"
}
}
},
"_source": ["name", "age"]
}
查詢結果
{
"took" : 83,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "zhifou",
"_type" : "doc",
"_id" : "4",
"_score" : 0.6931472,
"_source" : {
"name" : "石頭",
"age" : 29
}
},
{
"_index" : "zhifou",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顧老二",
"age" : 30
}
},
{
"_index" : "zhifou",
"_type" : "doc",
"_id" : "3",
"_score" : 0.2876821,
"_source" : {
"name" : "龍套偏房",
"age" : 22
}
}
]
},
"aggregations" : {
"my_avg" : {
"value" : 27.0
}
}
}
上例中，首先匹配查詢from是gu的數據。在此基礎上做查詢平均值的操作，這里就用到了聚合函數，其語法被封裝在aggs中，而my_avg則是為查詢結果起個別名，封裝了計算出的平均值。那么，要以什么屬性作為條件呢？是age年齡，查年齡的什么呢？是avg，查平均年齡。
如果只想看輸出的值，而不關心輸出的文檔的話可以通過size=0來控制
GET zhifou/doc/_search
{
"query": {
"match": {
"from": "gu"
}
},
"aggs":{
"my_avg":{
"avg": {
"field": "age"
}
}
},
"size":0,
"_source":["name","age"]
}
查詢結果
{
"took" : 35,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"my_avg" : {
"value" : 27.0
}
}
}
2、查詢年齡的最大值
GET zhifou/doc/_search
{
"query": {
"match_all": {}
},
"aggs": {
"my_max": {
"max": {
"field": "age"
}
}
},
"size": 0,
"_source": ["name","age","from"]
}
查詢結果
{
"took" : 10,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"my_max" : {
"value" : 30.0
}
}
}
3、查詢年齡的最小值
GET zhifou/doc/_search
{
"query": {
"match_all": {}
},
"aggs": {
"my_min": {
"min": {
"field": "age"
}
}
},
"size": 0,
"_source": ["name","age","from"]
}
查詢結果
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"my_min" : {
"value" : 18.0
}
}
}
4、查詢符合條件的年齡之和
GET zhifou/doc/_search
{
"query": {
"match": {
"from": "gu"
}
},
"aggs": {
"my_sum": {
"sum": {
"field": "age"
}
}
},
"size": 0,
"_source": ["name","age","from"]
}
查詢結果
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"my_sum" : {
"value" : 81.0
}
}
}
十一、ES的分組查詢
需求： 要查詢所有人的年齡段，并且按照1520，2025,25~30分組，并且算出每組的平均年齡。
GET zhifou/doc/_search
{
"size": 0,
"query": {
"match_all": {}
},
"aggs": {
"age_group": {
"range": {
"field": "age",
"ranges": [
{
"from": 15,
"to": 20
},
{
"from": 20,
"to": 25
},
{
"from": 25,
"to": 30
}
]
}
}
}
}
查詢結果
{
"took" : 9,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"age_group" : {
"buckets" : [
{
"key" : "15.0-20.0",
"from" : 15.0,
"to" : 20.0,
"doc_count" : 1
},
{
"key" : "20.0-25.0",
"from" : 20.0,
"to" : 25.0,
"doc_count" : 1
},
{
"key" : "25.0-30.0",
"from" : 25.0,
"to" : 30.0,
"doc_count" : 2
}
]
}
}
}
上例中，在aggs的自定義別名age_group中，使用range來做分組，field是以age為分組，分組使用ranges來做，from和to是范圍
接下來，我們就要對每個小組內的數據做平均年齡處理。
GET zhifou/doc/_search
{
"size": 0,
"query": {
"match_all": {}
},
"aggs": {
"age_group": {
"range": {
"field": "age",
"ranges": [
{
"from": 15,
"to": 20
},
{
"from": 20,
"to": 25
},
{
"from": 25,
"to": 30
}
]
},
"aggs": {
"my_avg": {
"avg": {
"field": "age"
}
}
}
}
}
}
查詢結果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"age_group" : {
"buckets" : [
{
"key" : "15.0-20.0",
"from" : 15.0,
"to" : 20.0,
"doc_count" : 1,
"my_avg" : {
"value" : 18.0
}
},
{
"key" : "20.0-25.0",
"from" : 20.0,
"to" : 25.0,
"doc_count" : 1,
"my_avg" : {
"value" : 22.0
}
},
{
"key" : "25.0-30.0",
"from" : 25.0,
"to" : 30.0,
"doc_count" : 2,
"my_avg" : {
"value" : 27.0
}
}
]
}
}
}
ES的聚合查詢的總結：聚合函數的使用，一定是先查出結果，然后對結果使用聚合函數做處理
avg：求平均
max：最大值
min：最小值
sum：求和
十二、ES之Mappings
GET test
查詢結果
{
"test" : {
"aliases" : { },
"mappings" : {
"doc" : {
"properties" : {
"age" : {
"type" : "long"
},
"desc" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
},
"settings" : {
"index" : {
"creation_date" : "1569133097594",
"number_of_shards" : "5",
"number_of_replicas" : "1",
"uuid" : "AztO9waYQiyHvzP6dlk4tA",
"version" : {
"created" : "6080299"
},
"provided_name" : "test"
}
}
}
}
由返回結果可以看到，分為兩大部分：
第一部分關于t1索引類型相關的，包括該索引是否有別名aliases，然后就是mappings信息，
包括索引類型doc，各字段的詳細映射關系都收集在properties中。
另一部分是關于索引t1的settings設置。包括該索引的創建時間，主副分片的信息，UUID等等。
- mappings 是什么？
- 映射就是在創建索引的時候，有更多定制的內容，更加的貼合業務場景。
- 用來定義一個文檔及其包含的字段如何存儲和索引的過程。
- 字段的數據類型
- 簡單類型如文本（text）、關鍵字（keyword）、日期（data）、整形（long）、雙精度
（double）、布爾（boolean）或ip。 - 可以是支持JSON的層次結構性質的類型，如對象或嵌套。或者一種特殊類型，如geo_point、geo_shape或completion。為了不同的目的，
以不同的方式索引相同的字段通常是有用的。例如，字符串字段可以作為全文搜索的文本字段進行索引，
也可以作為排序或聚合的關鍵字字段進行索引。或者，可以使用標準分析器、英語分析器和
法語分析器索引字符串字段。這就是多字段的目的。大多數數據類型通過fields參數支持多字段。
一個簡單的映射示例
PUT mapping_test { "mappings": { "test1":{ "properties":{ "name":{"type": "text"}, "age":{"type":"long"} } } } } - 簡單類型如文本（text）、關鍵字（keyword）、日期（data）、整形（long）、雙精度
我們在創建索引PUT mapping_test1的過程中，為該索引定制化類型（設計表結構），添加一個映射類型test1；指定字段或者屬性都在properties內完成。
GET mapping_test
查詢結果
{
"mapping_test" : {
"aliases" : { },
"mappings" : {
"test1" : {
"properties" : {
"age" : {
"type" : "long"
},
"name" : {
"type" : "text"
}
}
}
},
"settings" : {
"index" : {
"creation_date" : "1570794586526",
"number_of_shards" : "5",
"number_of_replicas" : "1",
"uuid" : "P4-trriPTxq-nJj89iYXZA",
"version" : {
"created" : "6080299"
},
"provided_name" : "mapping_test"
}
}
}
}
返回的結果中你肯定很熟悉！映射類型是test1，具體的屬性都被封裝在properties中。
3. ES mappings之dynamic的三種狀態
一般的，mapping則又可以分為動態映射（dynamic mapping）和靜態（顯示）映射（explicit mapping）和精確（嚴格）映射（strict mappings），具體由dynamic屬性控制。默認為動態映射
默認為動態映射
PUT test4
{
"mappings": {
"doc":{
"properties": {
"name": {
"type": "text"
},
"age": {
"type": "long"
}
}
}
}
}
GET test4/_mapping
查詢結果
{
"test4" : {
"mappings" : {
"doc" : {
"properties" : {
"age" : {
"type" : "long"
},
"name" : {
"type" : "text"
},
"sex" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
}
}
}
添加數據
PUT test4/doc/1
{
"name":"wangjifei",
"age":"18",
"sex":"不詳"
}
查看數據
GET test4/doc/_search
{
"query": {
"match_all": {}
}
}
查詢結果
{
"took" : 8,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test4",
"_type" : "doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "wangjifei",
"age" : "18",
"sex" : "不詳"
}
}
]
}
}
測試靜態映射：當elasticsearch察覺到有新增字段時，因為dynamic:false的關系，會忽略該字段，但是仍會存儲該字段。
創建靜態mapping
PUT test5
{
"mappings": {
"doc":{
"dynamic":false,
"properties": {
"name": {
"type": "text"
},
"age": {
"type": "long"
}
}
}
}
}
插入數據
PUT test5/doc/1
{
"name":"wangjifei",
"age":"18",
"sex":"不詳"
}
條件查詢
GET test5/doc/_search
{
"query": {
"match": {
"sex": "不詳"
}
}
}
查詢結果
{
"took" : 9,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 0,
"max_score" : null,
"hits" : [ ]
}
}
查看所有數據
GET /test5/doc/_search
{
"query": {
"match_all": {}
}
}
查詢結果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test5",
"_type" : "doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "wangjifei",
"age" : "18",
"sex" : "不詳"
}
}
]
}
}
測試嚴格映射：當elasticsearch察覺到有新增字段時，因為dynamic:strict 的關系，就會報錯，不能插入成功。
創建嚴格mapping
PUT test6
{
"mappings": {
"doc":{
"dynamic":"strict",
"properties": {
"name": {
"type": "text"
},
"age": {
"type": "long"
}
}
}
}
}
插入數據
PUT test6/doc/1
{
"name":"wangjifei",
"age":"18",
"sex":"不詳"
}
插入結果
{
"error": {
"root_cause": [
{
"type": "strict_dynamic_mapping_exception",
"reason": "mapping set to strict, dynamic introduction of [sex] within [doc] is not allowed"
}
],
"type": "strict_dynamic_mapping_exception",
"reason": "mapping set to strict, dynamic introduction of [sex] within [doc] is not allowed"
},
"status": 400
}
小結：
動態映射（dynamic：true）：動態添加新的字段（或缺省）。
靜態映射（dynamic：false）：忽略新的字段。在原有的映射基礎上，當有新的字段時，不會主動的添加新的映射關系，只作為查詢結果出現在查詢中。
嚴格模式（dynamic：strict）：如果遇到新的字段，就拋出異常。一般靜態映射用的較多。就像HTML的img標簽一樣，src為自帶的屬性，你可以在需要的時候添加id或者class屬性。當然，如果你非常非常了解你的數據，并且未來很長一段時間不會改變，strict不失為一個好選擇。
4. ES之mappings的 index 屬性
index屬性默認為true，如果該屬性設置為false，那么，elasticsearch不會為該屬性創建索引，也就是說無法當做主查詢條件。
PUT test7
{
"mappings": {
"doc": {
"properties": {
"name": {
"type": "text",
"index": true
},
"age": {
"type": "long",
"index": false
}
}
}
}
}
插入數據
PUT test7/doc/1
{
"name":"wangjifei",
"age":18
}
條件查詢數據
GET test7/doc/_search
{
"query": {
"match": {
"name": "wangjifei"
}
}
}
查詢結果
{
"took" : 18,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test7",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "wangjifei",
"age" : 18
}
}
]
}
}
條件查詢
GET test7/doc/_search
{
"query": {
"match": {
"age": 18
}
}
}
查詢結果
{
"error": {
"root_cause": [
{
"type": "query_shard_exception",
"reason": "failed to create query: {\n \"match\" : {\n \"age\" : {\n \"query\" : 18,\n \"operator\" : \"OR\",\n \"prefix_length\" : 0,\n \"max_expansions\" : 50,\n \"fuzzy_transpositions\" : true,\n \"lenient\" : false,\n \"zero_terms_query\" : \"NONE\",\n \"auto_generate_synonyms_phrase_query\" : true,\n \"boost\" : 1.0\n }\n }\n}",
"index_uuid": "fzN9frSZRy2OzinRjeMKGA",
"index": "test7"
}
],
"type": "search_phase_execution_exception",
"reason": "all shards failed",
"phase": "query",
"grouped": true,
"failed_shards": [
{
"shard": 0,
"index": "test7",
"node": "INueKtviRpO1dbNWngcjJA",
"reason": {
"type": "query_shard_exception",
"reason": "failed to create query: {\n \"match\" : {\n \"age\" : {\n \"query\" : 18,\n \"operator\" : \"OR\",\n \"prefix_length\" : 0,\n \"max_expansions\" : 50,\n \"fuzzy_transpositions\" : true,\n \"lenient\" : false,\n \"zero_terms_query\" : \"NONE\",\n \"auto_generate_synonyms_phrase_query\" : true,\n \"boost\" : 1.0\n }\n }\n}",
"index_uuid": "fzN9frSZRy2OzinRjeMKGA",
"index": "test7",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Cannot search on field [age] since it is not indexed."
}
}
}
]
},
"status": 400
}
5. ES 之 mappings 的copy_to屬性
PUT test8
{
"mappings": {
"doc": {
"dynamic":false,
"properties": {
"first_name":{
"type": "text",
"copy_to": "full_name"
},
"last_name": {
"type": "text",
"copy_to": "full_name"
},
"full_name": {
"type": "text"
}
}
}
}
}
插入數據
PUT test8/doc/1
{
"first_name":"tom",
"last_name":"ben"
}
PUT test8/doc/2
{
"first_name":"john",
"last_name":"smith"
}
查詢所有
GET test8/doc/_search
{
"query": {
"match_all": {}
}
}
查詢結果
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test8",
"_type" : "doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"first_name" : "john",
"last_name" : "smith"
}
},
{
"_index" : "test8",
"_type" : "doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"first_name" : "tom",
"last_name" : "ben"
}
}
]
}
}
條件查詢
GET test8/doc/_search
{
"query": {
"match": {
"first_name": "tom"
}
}
}
查詢結果
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test8",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"first_name" : "tom",
"last_name" : "ben"
}
}
]
}
}
條件查詢
GET test8/doc/_search
{
"query": {
"match": {
"full_name": "ben"
}
}
}
查詢結果
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test8",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"first_name" : "tom",
"last_name" : "ben"
}
}
]
}
}
上例中，我們將first_name和last_name都復制到full_name中。并且使用full_name查詢也返回了結果
既要查詢tom還要查詢smith該怎么辦？
GET test8/doc/_search
{
"query": {
"match": {
"full_name": {
"query": "tom smith",
"operator": "or"
}
}
}
}
查詢結果
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test8",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"first_name" : "john",
"last_name" : "smith"
}
},
{
"_index" : "test8",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"first_name" : "tom",
"last_name" : "ben"
}
}
]
}
}
operator參數為多個條件的查詢關系也可以是and
上面的查詢還可以簡寫成一下：
GET test8/doc/_search
{
"query": {
"match": {
"full_name": "tom smith"
}
}
}
copy_to還支持將相同的屬性值復制給不同的字段。
PUT test9
{
"mappings": {
"doc": {
"dynamic":false,
"properties": {
"first_name":{
"type": "text",
"copy_to": ["full_name1","full_name2"]
},
"last_name": {
"type": "text",
"copy_to": ["full_name1","full_name2"]
},
"full_name1": {
"type": "text"
},
"full_name2":{
"type":"text"
}
}
}
}
}
插入數據
PUT test9/doc/1
{
"first_name":"tom",
"last_name":"ben"
}
PUT test9/doc/2
{
"first_name":"john",
"last_name":"smith"
}
條件查詢
GET test9/doc/_search
{
"query": {
"match": {
"full_name1": "tom smith"
}
}
}
查詢結果
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test9",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"first_name" : "john",
"last_name" : "smith"
}
},
{
"_index" : "test9",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"first_name" : "tom",
"last_name" : "ben"
}
}
]
}
}
條件查詢
GET test9/doc/_search
{
"query": {
"match": {
"full_name2": "tom smith"
}
}
}
查詢結果
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test9",
"_type" : "doc",
"_id" : "2",
"_score" : 0.2876821,
"_source" : {
"first_name" : "john",
"last_name" : "smith"
}
},
{
"_index" : "test9",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"first_name" : "tom",
"last_name" : "ben"
}
}
]
}
}
full_name1 full_name2兩個字段都可以查出來
6. ES 之mappings的對象屬性
首先先看看ES自動創建的mappings
PUT test10/doc/1
{
"name":"wangjifei",
"age":18,
"info":{
"addr":"北京",
"tel":"18500327026"
}
}
GET test10
查詢結果
{
"test10" : {
"aliases" : { },
"mappings" : {
"doc" : {
"properties" : {
"age" : {
"type" : "long"
},
"info" : {
"properties" : {
"addr" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"tel" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
},
"settings" : {
"index" : {
"creation_date" : "1570975011394",
"number_of_shards" : "5",
"number_of_replicas" : "1",
"uuid" : "YvMGDHxkSri0Lgx6GGXiNw",
"version" : {
"created" : "6080299"
},
"provided_name" : "test10"
}
}
}
}
現在如果要以info中的tel為條件怎么寫查詢語句呢？
GET test10/doc/_search
{
"query": {
"match": {
"info.tel": "18500327026"
}
}
}
查詢結果
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test10",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "wangjifei",
"age" : 18,
"info" : {
"addr" : "北京",
"tel" : "18500327026"
}
}
}
]
}
}
info既是一個屬性，也是一個對象，我們稱為info這類字段為對象型字段。該對象內又包含addr和tel兩個字段，如上例這種以嵌套內的字段為查詢條件的話，查詢語句可以以字段點子字段的方式來寫即可
7. ES之mappings的settings 設置
在創建一個索引的時候，我們可以在settings中指定分片信息：
PUT test11
{
"mappings": {
"doc": {
"properties": {
"name": {
"type": "text"
}
}
}
},
"settings": {
"number_of_replicas": 1,
"number_of_shards": 5
}
}
number_of_shards是主分片數量（每個索引默認5個主分片），而number_of_replicas是復制分片，默認一個主分片搭配一個復制分片。
8. ES 之mappings的ignore_above參數
ignore_above參數僅針對于keyword類型有用
這樣設置是會報錯的
PUT test12
{
"mappings": {
"doc": {
"properties": {
"name": {
"type": "text",
"ignore_above":5
}
}
}
}
}
顯示結果
{
"error": {
"root_cause": [
{
"type": "mapper_parsing_exception",
"reason": "Mapping definition for [name] has unsupported parameters: [ignore_above : 5]"
}
],
"type": "mapper_parsing_exception",
"reason": "Failed to parse mapping [doc]: Mapping definition for [name] has unsupported parameters: [ignore_above : 5]",
"caused_by": {
"type": "mapper_parsing_exception",
"reason": "Mapping definition for [name] has unsupported parameters: [ignore_above : 5]"
}
},
"status": 400
}
正確的打開方式
PUT test12
{
"mappings": {
"doc": {
"properties": {
"name": {
"type": "keyword",
"ignore_above":5
}
}
}
}
}
PUT test12/doc/1
{
"name":"wangjifei"
}
這樣查詢能查出結果
GET test12/doc/_search
{
"query": {
"match_all": {}
}
}
查詢結果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test12",
"_type" : "doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "wangjifei"
}
}
]
}
}
這樣查詢不能查詢出結果
GET test12/doc/_search
{
"query": {
"match": {
"name": "wangjifei"
}
}
}
查詢結果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 0,
"max_score" : null,
"hits" : [ ]
}
}
上面的例子證明超過ignore_above設定的值后會被存儲但不會建立索引
那么如果字符串的類型是text時能用ignore_above嗎，答案是能，但要特殊設置：
PUT test13
{
"mappings": {
"doc":{
"properties":{
"name1":{
"type":"keyword",
"ignore_above":5
},
"name2":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above": 10
}
}
}
}
}
}
}
PUT test13/doc/1
{
"name1":"wangfei",
"name2":"wangjifei hello"
}
能查出來
GET test13/doc/_search
{
"query": {
"match_all": {}
}
}
查詢結果
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test13",
"_type" : "doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name1" : "wangfei",
"name2" : "wangjifei hello"
}
}
]
}
}
通過name1 字段查不出來，因為設置的是keyword類型 限制了5個字符的長度，
存儲的值超過了最大限制
GET test13/doc/_search
{
"query": {
"match": {
"name1": "wangfei"
}
}
}
查詢結果
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 0,
"max_score" : null,
"hits" : [ ]
}
}
通過name2 字段能查出來，雖然限制了5個字符的長度，存儲的值超過了最大限制，
但是，字段類型設置為text之后，ignore_above參數的限制就失效了。（了解就好，意義不大）
GET test13/doc/_search
{
"query": {
"match": {
"name2": "wangjifei"
}
}
}
查詢結果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test13",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name1" : "wangfei",
"name2" : "wangjifei hello"
}
}
]
}
}