ElasticSearch查詢文檔基本操作實例
更新時間：2023年02月02日 16:11:29 作者：程序員皮卡秋
這篇文章主要為大家介紹了ElasticSearch查詢文檔基本操作實例詳解，有需要的朋友可以借鑒參考下，希望能夠有所幫助，祝大家多多進步，早日升職加薪
查詢文檔 & 基本操作
為了方便學(xué)習(xí), 本節(jié)中所有示例沿用上節(jié)的索引
按照ID單個
GET class_1/_doc/1
查詢結(jié)果:
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "1",
"_version" : 4,
"_seq_no" : 4,
"_primary_term" : 3,
"found" : true,
"_source" : {
"name" : "l",
"num" : 6
}
}
按照ID批量
GET class_1/_mget
{
"ids":[1,2,3]
}
返回:
{
"docs" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "1",
"_version" : 4,
"_seq_no" : 4,
"_primary_term" : 3,
"found" : true,
"_source" : {
"name" : "l",
"num" : 6
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "2",
"found" : false
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "3",
"_version" : 3,
"_seq_no" : 10,
"_primary_term" : 4,
"found" : true,
"_source" : {
"num" : 9,
"name" : "e",
"age" : 9,
"desc" : [
"hhhh"
]
}
}
]
}
查詢文檔是否存在 & 通過id判斷
HEAD class_1/_doc/1
返回:
200 - OK
HEAD class_1/_doc/1000
返回:
404 - Not Found
查詢部分字段內(nèi)容
GET class_1/_doc/1?_source_includes=name
返回:
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "1",
"_version" : 4,
"_seq_no" : 4,
"_primary_term" : 3,
"found" : true,
"_source" : {
"name" : "l"
}
}
可以看到只返回了name字段, 以上是一個基本的操作，下面給大家講下條件查詢~
查詢文檔 & 條件查詢
查詢的復(fù)雜度取決于它附加的條件約束，跟我們寫sql一樣。下面就帶大家一步一步看一下ES中如何進行條件查詢~
不附加任何條件
GET class_1/_search
返回:
{
"took" : 15,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "h2Fg-4UBECmbBdQA6VLg",
"_score" : 1.0,
"_source" : {
"name" : "b",
"num" : 6
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "iGFt-4UBECmbBdQAnVJe",
"_score" : 1.0,
"_source" : {
"name" : "g",
"age" : 8
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "iWFt-4UBECmbBdQAnVJg",
"_score" : 1.0,
"_source" : {
"name" : "h",
"age" : 9
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "imFt-4UBECmbBdQAnVJg",
"_score" : 1.0,
"_source" : {
"name" : "i",
"age" : 10
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"num" : 9,
"name" : "e",
"age" : 9,
"desc" : [
"hhhh"
]
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "4",
"_score" : 1.0,
"_source" : {
"name" : "f",
"age" : 10,
"num" : 10
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "RWlfBIUBDuA8yW5cu9wu",
"_score" : 1.0,
"_source" : {
"name" : "一年級",
"num" : 20
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "l",
"num" : 6
}
}
]
}
}
可以看到索引class_1中的所有數(shù)據(jù)都是上節(jié)添加的。這里提一下，我們也可以添加多個索引一起查，然后返回,用,逗號隔開就可以了
GET class_1,class_2,class_3/_search
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 9,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "h2Fg-4UBECmbBdQA6VLg",
"_score" : 1.0,
"_source" : {
"name" : "b",
"num" : 6
}
},
{
"_index" : "class_2",
"_type" : "_doc",
"_id" : "RWlfBIUBDuA8yW5cu9wu",
"_score" : 1.0,
"_source" : {
"name" : "一年級",
"num" : 20
}
},
....
]
}
}
可以看到返回了索引class_2中的數(shù)據(jù)，并且合并到了一起。
相關(guān)字段解釋
有的小伙伴可能對返回的字段有點陌生，這里給大家統(tǒng)一解釋一下：
{
"took":"查詢操作耗時，單位毫秒",
"timed_out":"是否超時",
"_shards":{
"total":"分片總數(shù)",
"successful":"執(zhí)行成功分片數(shù)",
"skipped":"執(zhí)行忽略分片數(shù)",
"failed":"執(zhí)行失敗分片數(shù)"
},
"hits":{
"total":{
"value":"條件查詢命中數(shù)",
"relation":"計數(shù)規(guī)則(eq計數(shù)準(zhǔn)確/gte計數(shù)不準(zhǔn)確)"
},
"max_score":"最大匹配度分值",
"hits":[
{
"_index":"命中結(jié)果索引",
"_id":"命中結(jié)果ID",
"_score":"命中結(jié)果分?jǐn)?shù)",
"_source":"命中結(jié)果原文檔信息"
}
]
}
}
下面我們看下帶條件的查詢~
基礎(chǔ)分頁查詢
基本語法: es中通過參數(shù)size和from來進行基礎(chǔ)分頁的控制
from：指定跳過多少條數(shù)據(jù)size：指定返回多少條數(shù)據(jù)
下面看下示例：
url參數(shù)
GET class_1/_search?from=2&size=2
返回:
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "iWFt-4UBECmbBdQAnVJg",
"_score" : 1.0,
"_source" : {
"name" : "h",
"age" : 9
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "imFt-4UBECmbBdQAnVJg",
"_score" : 1.0,
"_source" : {
"name" : "i",
"age" : 10
}
}
]
}
}
body 參數(shù)
GET class_1/_search
{
"from" : 2,
"size" : 2
}
返回結(jié)果和上面是一樣的~
單字段全文索引查詢
這個大家應(yīng)該不陌生，前面幾節(jié)都見過。使用query.match進行查詢,match適用與對單個字段基于全文索引進行數(shù)據(jù)檢索。對于全文字段，match使用特定的分詞進行全文檢索。而對于那些精確值，match同樣可以進行精確匹配,match查詢短語時，會對短語進行分詞，再針對每個詞條進行全文檢索。
GET class_1/_search
{
"query": {
"match": {
"name":"i"
}
}
}
返回:
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.3862942,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "imFt-4UBECmbBdQAnVJg",
"_score" : 1.3862942,
"_source" : {
"name" : "i",
"age" : 10
}
}
]
}
}
單字段不分詞查詢
使用query.match_phrase進行查詢, 它與match的區(qū)別就是不進行分詞,干說，可能有點抽象，下面我們通過一個例子給大家分清楚:
先造點數(shù)據(jù)進去：
PUT class_1/_bulk
{ "create":{ } }
{"name":"I eat apple so haochi1~","num": 1}
{ "create":{ } }
{ "name":"I eat apple so zhen haochi2~","num": 1}
{ "create":{ } }
{"name":"I eat apple so haochi3~","num": 1}
假設(shè)有這么幾個句子，現(xiàn)在我有一個需求我要把I eat apple so zhen haochi2~這句話匹配出來
match分詞結(jié)果
GET class_1/_search
{
"query": {
"match": {
"name": "apple so zhen"
}
}
}
返回：
{
"took" : 15,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 2.2169428,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "cMfcCoYB090miyjed7YE",
"_score" : 2.2169428,
"_source" : {
"name" : "I eat apple so zhen haochi2~",
"num" : 1
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "b8fcCoYB090miyjed7YE",
"_score" : 1.505254,
"_source" : {
"name" : "I eat apple so haochi1~",
"num" : 1
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "ccfcCoYB090miyjed7YE",
"_score" : 1.505254,
"_source" : {
"name" : "I eat apple so haochi3~",
"num" : 1
}
}
]
}
}
從結(jié)果來看，剛剛的幾句話都被查出來了，但是結(jié)果并大符合預(yù)期。從score來看，"_score" : 2.2169428得分最高，排在了第一，語句是I eat apple so zhen haochi2~,說明匹配度最高，這個句子正是我們想要的結(jié)果~
match_phrase 不分詞查詢結(jié)果
GET class_1/_search
{
"query": {
"match_phrase": {
"name": "apple so zhen"
}
}
}
結(jié)果:
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 2.2169428,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "cMfcCoYB090miyjed7YE",
"_score" : 2.2169428,
"_source" : {
"name" : "I eat apple so zhen haochi2~",
"num" : 1
}
}
]
}
}
結(jié)果符合預(yù)期，只返回了我們想要的那句。那么match為什么都返回了，這就是前面講到的分詞,首先會對name: apple so zhen進行分詞,也就是說存在apple的都會被返回。
當(dāng)然，真正業(yè)務(wù)中的需求比這個復(fù)雜多了，這里只是為了給大家做區(qū)分~ 下面接著看~
多字段全文索引查詢
相當(dāng)于對多個字段執(zhí)行了match查詢, 這里需要注意的是query的類型要和字段類型一致，不然會報類型異常
GET class_1/_search
{
"query": {
"multi_match": {
"query": "apple",
"fields": ["name","desc"]
}
}
}
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 0.752627,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "b8fcCoYB090miyjed7YE",
"_score" : 0.752627,
"_source" : {
"name" : "I eat apple so haochi1~",
"num" : 1
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "ccfcCoYB090miyjed7YE",
"_score" : 0.752627,
"_source" : {
"name" : "I eat apple so haochi3~",
"num" : 1
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "cMfcCoYB090miyjed7YE",
"_score" : 0.7389809,
"_source" : {
"name" : "I eat apple so zhen haochi2~",
"num" : 1
}
}
]
}
}
范圍查詢
使用range來進行范圍查詢，適用于數(shù)組，時間等字段
GET class_1/_search
{
"query": {
"range": {
"num": {
"gt": 5,
"lt": 10
}
}
}
}
返回:
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "h2Fg-4UBECmbBdQA6VLg",
"_score" : 1.0,
"_source" : {
"name" : "b",
"num" : 6
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"num" : 9,
"name" : "e",
"age" : 9,
"desc" : [
"hhhh"
]
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "l",
"num" : 6
}
}
]
}
}
單字段精確查詢
使用term進行非分詞字段的精確查詢。需要注意的是，對于那些分詞的字段，即使查詢的value是一個完全匹配的短語，也無法完成查詢
GET class_1/_search
{
"query": {
"term": {
"num": {
"value": "9"
}
}
}
}
返回:
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"num" : 9,
"name" : "e",
"age" : 9,
"desc" : [
"hhhh"
]
}
}
]
}
}
字段精確查詢 & 多值
與term一樣, 區(qū)別在于可以匹配一個字段的多個值，滿足一個即檢索成功
GET class_1/_search
{
"query": {
"terms": {
"num": [
9,
1
]
}
}
}
返回:
{
"took" : 8,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"num" : 9,
"name" : "e",
"age" : 9,
"desc" : [
"hhhh"
]
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "b8fcCoYB090miyjed7YE",
"_score" : 1.0,
"_source" : {
"name" : "I eat apple so haochi1~",
"num" : 1
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "ccfcCoYB090miyjed7YE",
"_score" : 1.0,
"_source" : {
"name" : "I eat apple so haochi3~",
"num" : 1
}
},
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "cMfcCoYB090miyjed7YE",
"_score" : 1.0,
"_source" : {
"name" : "I eat apple so zhen haochi2~",
"num" : 1
}
}
]
}
}
文檔包含字段查詢
為了確定當(dāng)前索引有哪些文檔包含了對應(yīng)的字段，es中使用exists來實現(xiàn)
GET class_1/_search
{
"query": {
"exists": {
"field": "desc"
}
}
}
返回:
{
"took" : 8,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "class_1",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"num" : 9,
"name" : "e",
"age" : 9,
"desc" : [
"hhhh"
]
}
}
]
}
}
結(jié)束語
本節(jié)主要講了ES中的文檔查詢API操作，該部分內(nèi)容較多, 下節(jié)繼續(xù)給大家講，就先消化這么多~API大家都不要去背，多敲幾遍就記住了，關(guān)鍵是多用，多總結(jié) 。
以上就是ElasticSearch查詢文檔基本操作實例的詳細(xì)內(nèi)容，更多關(guān)于ElasticSearch查詢文檔的資料請關(guān)注腳本之家其它相關(guān)文章！
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這篇文章主要為大家介紹了詳解如何解析pom文件方法示例,有需要的朋友可以借鑒參考下,希望能夠有所幫助,祝大家多多進步,早日升職加薪2023-08-08
這篇文章主要介紹了SpringBoot Tomcat啟動實例代碼詳解,需要的朋友可以參考下2017-09-09
本文主要介紹了java實現(xiàn)窗口刷新的示例代碼,通過重寫paintComponent()方法和調(diào)用repaint()方法,可以實現(xiàn)窗口的即時刷新,具有一定的參考價值,感興趣的可以了解一下2024-02-02