- Elasticsearch 教程
- Elasticsearch - 主页
- Elasticsearch - 基本概念
- Elasticsearch - 安装
- Elasticsearch - 填充
- 版本之间的迁移
- Elasticsearch - API 约定
- Elasticsearch - 文档 API
- Elasticsearch - 搜索 API
- Elasticsearch - 聚合
- Elasticsearch - 索引 API
- Elasticsearch - CAT API
- Elasticsearch - 集群 API
- Elasticsearch - 查询 DSL
- Elasticsearch - 映射
- Elasticsearch - 分析
- Elasticsearch - 模块
- Elasticsearch - 索引模块
- Elasticsearch - 摄取节点
- Elasticsearch - 管理索引生命周期
- Elasticsearch - SQL 访问
- Elasticsearch - 监控
- Elasticsearch - 汇总数据
- Elasticsearch - 冻结索引
- Elasticsearch - 测试
- Elasticsearch - Kibana 仪表板
- Elasticsearch - 按字段过滤
- Elasticsearch - 数据表
- Elasticsearch - 区域地图
- Elasticsearch - 饼图
- Elasticsearch - 面积图和条形图
- Elasticsearch - 时间序列
- Elasticsearch - 标签云
- Elasticsearch - 热图
- Elasticsearch - 画布
- Elasticsearch - 日志 UI
- Elasticsearch 有用资源
- Elasticsearch - 快速指南
- Elasticsearch - 有用的资源
- Elasticsearch - 讨论
Elasticsearch - 查询 DSL
在Elasticsearch中，搜索是通过使用基于JSON的查询来进行的。查询由两个子句组成 -
叶查询子句- 这些子句是匹配、术语或范围，它们在特定字段中查找特定值。
复合查询子句- 这些查询是叶查询子句和其他复合查询的组合，以提取所需的信息。
Elasticsearch 支持大量查询。查询以查询关键字开始，然后以 JSON 对象的形式包含条件和过滤器。下面描述了不同类型的查询。
匹配所有查询
这是最基本的查询；它返回所有内容，每个对象的得分为 1.0。
POST /schools/_search
{
"query":{
"match_all":{}
}
}
运行上面的代码，我们得到以下结果 -
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "schools",
"_type" : "school",
"_id" : "5",
"_score" : 1.0,
"_source" : {
"name" : "Central School",
"description" : "CBSE Affiliation",
"street" : "Nagan",
"city" : "paprola",
"state" : "HP",
"zip" : "176115",
"location" : [
31.8955385,
76.8380405
],
"fees" : 2200,
"tags" : [
"Senior Secondary",
"beautiful campus"
],
"rating" : "3.3"
}
},
{
"_index" : "schools",
"_type" : "school",
"_id" : "4",
"_score" : 1.0,
"_source" : {
"name" : "City Best School",
"description" : "ICSE",
"street" : "West End",
"city" : "Meerut",
"state" : "UP",
"zip" : "250002",
"location" : [
28.9926174,
77.692485
],
"fees" : 3500,
"tags" : [
"fully computerized"
],
"rating" : "4.5"
}
}
]
}
}
全文查询
这些查询用于搜索全文，例如章节或新闻文章。该查询根据与该特定索引或文档关联的分析器进行工作。在本节中，我们将讨论不同类型的全文查询。
匹配查询
此查询将文本或短语与一个或多个字段的值进行匹配。
POST /schools*/_search
{
"query":{
"match" : {
"rating":"4.5"
}
}
}
运行上面的代码，我们得到如下所示的响应 -
{
"took" : 44,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 0.47000363,
"hits" : [
{
"_index" : "schools",
"_type" : "school",
"_id" : "4",
"_score" : 0.47000363,
"_source" : {
"name" : "City Best School",
"description" : "ICSE",
"street" : "West End",
"city" : "Meerut",
"state" : "UP",
"zip" : "250002",
"location" : [
28.9926174,
77.692485
],
"fees" : 3500,
"tags" : [
"fully computerized"
],
"rating" : "4.5"
}
}
]
}
}
多重匹配查询
此查询与具有多个字段的文本或短语匹配。
POST /schools*/_search
{
"query":{
"multi_match" : {
"query": "paprola",
"fields": [ "city", "state" ]
}
}
}
运行上面的代码，我们得到如下所示的响应 -
{
"took" : 12,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 0.9808292,
"hits" : [
{
"_index" : "schools",
"_type" : "school",
"_id" : "5",
"_score" : 0.9808292,
"_source" : {
"name" : "Central School",
"description" : "CBSE Affiliation",
"street" : "Nagan",
"city" : "paprola",
"state" : "HP",
"zip" : "176115",
"location" : [
31.8955385,
76.8380405
],
"fees" : 2200,
"tags" : [
"Senior Secondary",
"beautiful campus"
],
"rating" : "3.3"
}
}
]
}
}
查询字符串查询
此查询使用查询解析器和 query_string 关键字。
POST /schools*/_search
{
"query":{
"query_string":{
"query":"beautiful"
}
}
}
运行上面的代码，我们得到如下所示的响应 -
{
"took" : 60,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
………………………………….
术语级别查询
这些查询主要处理结构化数据，如数字、日期和枚举。
POST /schools*/_search
{
"query":{
"term":{"zip":"176115"}
}
}
运行上面的代码，我们得到如下所示的响应 -
……………………………..
hits" : [
{
"_index" : "schools",
"_type" : "school",
"_id" : "5",
"_score" : 0.9808292,
"_source" : {
"name" : "Central School",
"description" : "CBSE Affiliation",
"street" : "Nagan",
"city" : "paprola",
"state" : "HP",
"zip" : "176115",
"location" : [
31.8955385,
76.8380405
],
}
}
]
…………………………………………..
范围查询
此查询用于查找具有给定值范围之间的值的对象。为此，我们需要使用运算符，例如 -
- gte - 大于等于
- gt - 大于
- lte - 小于等于
- lt - 小于
例如，观察下面给出的代码 -
POST /schools*/_search
{
"query":{
"range":{
"rating":{
"gte":3.5
}
}
}
}
运行上面的代码，我们得到如下所示的响应 -
{
"took" : 24,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "schools",
"_type" : "school",
"_id" : "4",
"_score" : 1.0,
"_source" : {
"name" : "City Best School",
"description" : "ICSE",
"street" : "West End",
"city" : "Meerut",
"state" : "UP",
"zip" : "250002",
"location" : [
28.9926174,
77.692485
],
"fees" : 3500,
"tags" : [
"fully computerized"
],
"rating" : "4.5"
}
}
]
}
}
还存在其他类型的术语级别查询，例如 -
存在查询- 如果某个字段具有非空值。
缺少查询- 这与存在查询完全相反，该查询搜索没有特定字段或具有空值的字段的对象。
通配符或正则表达式查询- 此查询使用正则表达式来查找对象中的模式。
复合查询
这些查询是通过使用布尔运算符（如 and、or、not 或针对不同索引或具有函数调用等）相互合并的不同查询的集合。
POST /schools/_search
{
"query": {
"bool" : {
"must" : {
"term" : { "state" : "UP" }
},
"filter": {
"term" : { "fees" : "2200" }
},
"minimum_should_match" : 1,
"boost" : 1.0
}
}
}
运行上面的代码，我们得到如下所示的响应 -
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 0,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
}
}
地理查询
这些查询涉及地理位置和地理点。这些查询有助于查找任何位置附近的学校或任何其他地理对象。您需要使用地理点数据类型。
PUT /geo_example
{
"mappings": {
"properties": {
"location": {
"type": "geo_shape"
}
}
}
}
运行上面的代码，我们得到如下所示的响应 -
{ "acknowledged" : true,
"shards_acknowledged" : true,
"index" : "geo_example"
}
现在我们将数据发布到上面创建的索引中。
POST /geo_example/_doc?refresh
{
"name": "Chapter One, London, UK",
"location": {
"type": "point",
"coordinates": [11.660544, 57.800286]
}
}
运行上面的代码，我们得到如下所示的响应 -
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
"_index" : "geo_example",
"_type" : "_doc",
"_id" : "hASWZ2oBbkdGzVfiXHKD",
"_score" : 1.0,
"_source" : {
"name" : "Chapter One, London, UK",
"location" : {
"type" : "point",
"coordinates" : [
11.660544,
57.800286
]
}
}
}
}