Elasticsearch 简明教程
Elasticsearch - Query DSL
在 Elasticsearch 中，通过基于 JSON 的查询执行搜索。查询由两个子句组成 −
-
Leaf Query Clauses − 这些子句是 match、term 或 range，用于在特定字段中查找特定值。
-
Compound Query Clauses − 这些查询是叶查询子句和其他复合查询的组合，用于提取所需信息。
Elasticsearch 支持大量查询。查询以查询关键字开头，然后以 JSON 对象的形式在其中具有条件和过滤器。不同类型的查询已在下面进行描述。
Match All Query
这是最基本的查询；它返回所有内容，并且每个对象的得分均为 1.0。
POST /schools/_search
{
"query":{
"match_all":{}
}
}运行以上代码时，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"
}
}
]
}
}Full Text Queries
这些查询用于搜索全文文本，如章节或新闻文章。此查询根据与该特定索引或文档关联的分析器工作。在本章节中，我们将讨论不同类型的全文文本查询。
Match query
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"
}
}
}在运行以上代码时，我们得到响应，如下所示：-
{
"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"
}
}
]
}
}Multi Match Query
此查询将文本或短语与多个字段进行匹配。
POST /schools*/_search
{
"query":{
"multi_match" : {
"query": "paprola",
"fields": [ "city", "state" ]
}
}
}在运行以上代码时，我们得到响应，如下所示：-
{
"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"
}
}
]
}
}Query String Query
此查询使用查询解析器和 query_string 关键字。
POST /schools*/_search
{
"query":{
"query_string":{
"query":"beautiful"
}
}
}在运行以上代码时，我们得到响应，如下所示：-
{
"took" : 60,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
………………………………….Term Level Queries
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"}
}
}在运行以上代码时，我们得到响应，如下所示：-
……………………………..
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
],
}
}
]
…………………………………………..Range Query
此查询用于查找在给定值范围内具有值的那些对象。为此，我们需要使用操作符，如 −
-
gte − 大于等于
-
gt − greater-than
-
lte - 小于或等于
-
lt − less-than
例如，请观察下面给出的代码 -
POST /schools*/_search
{
"query":{
"range":{
"rating":{
"gte":3.5
}
}
}
}在运行以上代码时，我们得到响应，如下所示：-
{
"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"
}
}
]
}
}还存在其他类型的期限级别查询，例如 -
-
Exists query - 如果某个字段有非空值。
-
Missing query - 这与 exists 查询完全相反，此查询搜索没有特定字段或字段带有空值的对象。
-
Wildcard or regexp query - 此查询使用正则表达式查找对象中的模式。
Compound Queries
这些查询是通过使用布尔运算符（如与运算符、或运算符、非运算符或不同索引的运算符或有函数调用等的运算符）合并到一起的不同查询的集合。
POST /schools/_search
{
"query": {
"bool" : {
"must" : {
"term" : { "state" : "UP" }
},
"filter": {
"term" : { "fees" : "2200" }
},
"minimum_should_match" : 1,
"boost" : 1.0
}
}
}在运行以上代码时，我们得到响应，如下所示：-
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 0,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
}
}Geo Queries
这些查询涉及地理位置和地理点。这些查询有助于找到学校或任何其他靠近某个位置的地理对象。您需要使用地理点数据类型。
PUT /geo_example
{
"mappings": {
"properties": {
"location": {
"type": "geo_shape"
}
}
}
}在运行以上代码时，我们得到响应，如下所示：-
{ "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]
}
}在运行以上代码时，我们得到响应，如下所示：-
{
"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
]
}
}
}
}