ElasticSearch - SpringBoot整合ES:多个精确值查询 terms
01. ElasticSearch terms 查询支持的数据类型
在Elasticsearch中,terms查询支持多种数据类型,包括:
字符串类型:可以将多个字符串值作为数组传递给terms查询,以匹配包含任何一个指定字符串值的文档。
数值类型:可以将多个数值作为数组传递给terms查询,以匹配包含任何一个指定数值的文档。
日期类型:可以将多个日期值作为数组传递给terms查询,以匹配包含任何一个指定日期值的文档。
布尔类型:可以将多个布尔值作为数组传递给terms查询,以匹配包含任何一个指定布尔值的文档。
复杂数据类型如数组类型,对象类型也可以支持,具体可以参考term查询,term查询支持的数据类型,terms查询就会支持。区别在于 term查询用于匹配一个字段中包含指定值的文档,terms查询用于匹配一个字段中包含指定值之一的文档。
02. ElasticSearch term和 terms 查询的区别
在Elasticsearch中,term和terms查询都用于匹配一个字段中包含指定值的文档,但它们之间有一些区别。
term查询用于匹配包含完全相同值的文档,而无法匹配包含部分匹配值的文档。例如,以下查询将返回包含"red"颜色的文档:
{
"query": {
"term": {
"color": "red"
}
}
}
但是,如果要查询包含"red"或"blue"颜色的文档,应该使用terms查询,而不是term查询。例如,以下查询将返回包含"red"或"blue"颜色中任何一个的文档:
{
"query": {
"terms": {
"color": ["red", "blue"]
}
}
}
terms查询可以将多个值作为数组传递,以匹配包含任何一个指定值的文档,而term查询只能匹配包含单个指定值的文档。因此,如果要匹配包含多个值的文档,应该使用terms查询,而如果要匹配包含单个值的文档,应该使用term查询。
03. ElasticSearch terms 查询数值类型数据
一定要了解 term
和 terms
是包含操作,而非等值操作。 如何理解这句话呢?
在Elasticsearch中,term查询用于匹配一个字段中包含指定值的文档,terms查询用于匹配一个字段中包含指定值之一的文档。可以将多个值作为数组传递给terms查询,以匹配包含任何一个指定值的文档。
① 索引文档,构造数据:
PUT /my_index
{
"mappings": {
"properties": {
"price":{
"type": "integer"
}
}
}
}
PUT /my_index/_doc/1
{
"price":10
}
PUT /my_index/_doc/2
{
"price":20
}
PUT /my_index/_doc/3
{
"price":30
}
② 查询 price 包含 "10"或"20"的文档,可以使用以下查询:
GET /my_index/_search
{
"query": {
"terms": {
"price": [
"10",
"20"
]
}
}
}
{
"took" : 11,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"price" : 10
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"price" : 20
}
}
]
}
}
04. ElasticSearch terms 查询字符串型数据
terms查询用于匹配一个字段中包含指定值之一的文档。
① 索引文档,数据构造:
PUT /my_index
{
"mappings": {
"properties": {
"tag":{
"type": "keyword"
}
}
}
}
PUT /my_index/_doc/1
{
"tag":"tag1"
}
PUT /my_index/_doc/2
{
"tag":"tag2"
}
PUT /my_index/_doc/3
{
"tag":"tag3"
}
② 查询 tag 字段包含 tag1 和 tag2 的文档:
GET /my_index/_search
{
"query": {
"terms": {
"tag": [
"tag1",
"tag2"
]
}
}
}
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"tag" : "tag1"
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"tag" : "tag2"
}
}
]
}
}
不要使用term 和terms 查询文本类型的数据。因为会分词,查询可能会出现意想不到的结果。
05. ElasticSearch terms 查询日期性数据
① 索引文档,构造数据:
PUT /my_index
{
"mappings": {
"properties": {
"createTime":{
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss"
}
}
}
}
PUT /my_index/_doc/1
{
"createTime":"2023-03-29 10:30:11"
}
PUT /my_index/_doc/2
{
"createTime":"2023-03-29 10:35:11"
}
PUT /my_index/_doc/3
{
"createTime":"2023-03-29 10:38:11"
}
② 查询 createTime 字段包含 “2023-03-29 10:30:11” 或 “2023-03-29 10:38:11” 的文档:
{
"took" : 672,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"createTime" : "2023-03-29 10:30:11"
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"createTime" : "2023-03-29 10:38:11"
}
}
]
}
}
06. ElasticSearch terms 查询布尔型数据
① 索引文档,构造数据:
PUT /my_index
{
"mappings": {
"properties": {
"flag":{
"type": "boolean"
}
}
}
}
PUT /my_index/_doc/1
{
"flag":true
}
PUT /my_index/_doc/2
{
"flag":true
}
PUT /my_index/_doc/3
{
"flag":false
}
② 查询 flag 字段包含 true 或 false 的文档:
GET /my_index/_search
{
"query": {
"terms": {
"flag": [
"true",
"false"
]
}
}
}
{
"took" : 30,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"flag" : true
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"flag" : true
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"flag" : false
}
}
]
}
}
07. ElasticSearch terms 查询数组类型数据
terms查询可以用于匹配一个字段中包含指定值之一的文档。对于数组类型的字段,可以将多个值作为数组传递给terms查询,以匹配包含任何一个指定值的文档。
① 索引文档,构造数据:
PUT /my_index
{
"mappings": {
"properties": {
"tags":{
"type": "keyword"
}
}
}
}
PUT /my_index/_doc/1
{
"tags":["tag1"]
}
PUT /my_index/_doc/2
{
"tags":["tag2"]
}
PUT /my_index/_doc/3
{
"tags":["tag1","tag2"]
}
PUT /my_index/_doc/4
{
"tags":["tag1","tag2","tag3"]
}
② 要查询 tags 字段包含"tag1"或"tag2"的文档,可以使用以下查询:
GET /my_index/_search
{
"query": {
"terms": {
"tags": [
"tag1",
"tag2"
]
}
}
}
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"tags" : [
"tag1"
]
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"tags" : [
"tag2"
]
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"tags" : [
"tag1",
"tag2"
]
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "4",
"_score" : 1.0,
"_source" : {
"tags" : [
"tag1",
"tag2",
"tag3"
]
}
}
]
}
}
08. ElasticSearch terms 查询对象型数据
① 索引文档,构造数据:文章来源:https://www.toymoban.com/news/detail-576453.html
PUT /my_index
{
"mappings": {
"properties": {
"person": {
"type": "object",
"properties": {
"name": {
"type": "keyword"
},
"age": {
"type": "integer"
},
"address": {
"type": "keyword"
}
}
}
}
}
}
PUT /my_index/_doc/1
{
"person": {
"name": "John",
"age": 30,
"address": "123 Main St"
}
}
PUT /my_index/_doc/2
{
"person": {
"name": "Alex",
"age": 20,
"address": "123 Main St"
}
}
PUT /my_index/_doc/3
{
"person": {
"name": "Smith",
"age": 10,
"address": "123 Main St"
}
}
② 查询 person.name 字段包含 Alex 或者 Smith 的文档:文章来源地址https://www.toymoban.com/news/detail-576453.html
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"person" : {
"name" : "Alex",
"age" : 20,
"address" : "123 Main St"
}
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"person" : {
"name" : "Smith",
"age" : 10,
"address" : "123 Main St"
}
}
}
]
}
}
09. SpringBoot 整合ES实现terms查询
GET /my_index/_search
{
"query": {
"terms": {
"price": [
"10",
"20"
]
}
}
}
@Slf4j
@Service
public class ElasticSearchImpl {
@Autowired
private RestHighLevelClient restHighLevelClient;
public void searchUser() throws IOException {
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// terms查询
List<Integer> prices = Arrays.asList(10,20);
// 查询所有price字段包含10或者20的文档
TermsQueryBuilder termsQueryBuilder = new TermsQueryBuilder("price",prices);
searchSourceBuilder.query(termsQueryBuilder);
SearchRequest searchRequest = new SearchRequest(new String[]{"my_index"},searchSourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(searchResponse);
}
}
10. SpringBoot 整合ES实现terms查询
GET /my_index/_search
{
"query": {
"terms": {
"tags": ["tag1","tag2"]
}
}
}
@Slf4j
@Service
public class ElasticSearchImpl {
@Autowired
private RestHighLevelClient restHighLevelClient;
public void searchUser() throws IOException {
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// terms查询
List<String> tags = Arrays.asList("tag1","tag2");
// 查询所有tags字段包含tag1或者tag2的文档
TermsQueryBuilder termsQueryBuilder = new TermsQueryBuilder("tags",tags);
searchSourceBuilder.query(termsQueryBuilder);
SearchRequest searchRequest = new SearchRequest(new String[]{"my_index"},searchSourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(searchResponse);
}
}
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