A. Search API of basic grammar
1, search syntax
GET /search
{}
GET /index1,index2/type1,type2/search
{}
GET /_search
{
"from": 0,
"size": 10
}
2, http protocol get if you can bring request body
HTTP protocol, generally does not allow get requests to bring request body, but because get more suitable description of the operation query data, so it is so used
GET /_search?from=0&size=10
POST /_search
{
"from":0,
"size":10
}
As it happens, a lot of the browser, or server, also supports GET + request body mode
If you encounter does not support the scenario, you can also use POST / _search
Two .Query DSL Search
1. What is the Query DSL
GET /_search
{
"query": {
"match_all": {}
}
}
2, the basic syntax of the Query DSL
{
QUERY_NAME: {
ARGUMENT: VALUE,
ARGUMENT: VALUE,...
}
}
{
QUERY_NAME: {
FIELD_NAME: {
ARGUMENT: VALUE,
ARGUMENT: VALUE,...
}
}
}
Example:
GET /test_index/test_type/_search
{
"query": {
"match": {
"test_field": "test"
}
}
}
3, how to combine multiple search criteria
Search needs: title must include elasticsearch, content elasticsearch may contain or may not contain, author_id must not 111
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 1,
"hits": [
{
"_index": "website",
"_type": "article",
"_id": "2",
"_score": 1,
"_source": {
"title": "my hadoop article",
"content": "hadoop is very bad",
"author_id": 111
}
},
{
"_index": "website",
"_type": "article",
"_id": "1",
"_score": 1,
"_source": {
"title": "my elasticsearch article",
"content": "es is very bad",
"author_id": 110
}
},
{
"_index": "website",
"_type": "article",
"_id": "3",
"_score": 1,
"_source": {
"title": "my elasticsearch article",
"content": "es is very goods",
"author_id": 111
}
}
]
}
}
GET /website/article/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "elasticsearch"
}
}
],
"should": [
{
"match": {
"content": "elasticsearch"
}
}
],
"must_not": [
{
"match": {
"author_id": 111
}
}
]
}
}
}
GET /test_index/_search
{
"query": {
"bool": {
"must": { "match": { "name": "tom" }},
"should": [
{ "match": { "hired": true }},
{ "bool": {
"must": { "match": { "personality": "good" }},
"must_not": { "match": { "rude": true }}
}}
],
"minimum_should_match": 1
}
}
}
三.filter与query对比
1、filter与query示例
PUT /company/employee/2
{
"address": {
"country": "china",
"province": "jiangsu",
"city": "nanjing"
},
"name": "tom",
"age": 30,
"join_date": "2016-01-01"
}
PUT /company/employee/3
{
"address": {
"country": "china",
"province": "shanxi",
"city": "xian"
},
"name": "marry",
"age": 35,
"join_date": "2015-01-01"
}
搜索请求：年龄必须大于等于30，同时join_date必须是2016-01-01
GET /company/employee/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"join_date": "2016-01-01"
}
}
],
"filter": {
"range": {
"age": {
"gte": 30
}
}
}
}
}
}
2、filter与query对比大解密
filter，仅仅只是按照搜索条件过滤出需要的数据而已，不计算任何相关度分数，对相关度没有任何影响
query，会去计算每个document相对于搜索条件的相关度，并按照相关度进行排序
一般来说，如果你是在进行搜索，需要将最匹配搜索条件的数据先返回，那么用query；如果你只是要根据一些条件筛选出一部分数据，不关注其排序，那么用filter
除非是你的这些搜索条件，你希望越符合这些搜索条件的document越排在前面返回，那么这些搜索条件要放在query中；如果你不希望一些搜索条件来影响你的document排序，那么就放在filter中即可
3、filter与query性能
filter，不需要计算相关度分数，不需要按照相关度分数进行排序，同时还有内置的自动cache最常使用filter的数据
query，相反，要计算相关度分数，按照分数进行排序，而且无法cache结果
四.组合查询
1、match all
GET /_search
{
"query": {
"match_all": {}
}
}
2、match
GET /_search
{
"query": { "match": { "title": "my elasticsearch article" }}
}
3、multi match
GET /test_index/test_type/_search
{
"query": {
"multi_match": {
"query": "test",
"fields": ["test_field", "test_field1"]
}
}
}
4、range query
GET /company/employee/_search
{
"query": {
"range": {
"age": {
"gte": 30
}
}
}
}
5、term query
GET /test_index/test_type/_search
{
"query": {
"term": {
"test_field": "test hello"
}
}
}
6、terms query
GET /_search
{
"query": { "terms": { "tag": [ "search", "full_text", "nosql" ] }}
}
7、exist query（2.x中的查询，现在已经不提供了）
GET /website/article/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "elasticsearch"
}
}
],
"should": [
{
"match": {
"content": "elasticsearch"
}
}
],
"must_not": [
{
"match": {
"author_id": 111
}
}
]
}
}
}
{
"bool": {
"must": { "match": { "title": "how to make millions" }},
"must_not": { "match": { "tag": "spam" }},
"should": [
{ "match": { "tag": "starred" }}
],
"filter": {
"range": { "date": { "gte": "2014-01-01" }}
}
}
}
bool
must，must_not，should，filter
每个子查询都会计算一个document针对它的相关度分数，然后bool综合所有分数，合并为一个分数，当然filter是不会计算分数的
{
"bool": {
"must": { "match": { "title": "how to make millions" }},
"must_not": { "match": { "tag": "spam" }},
"should": [
{ "match": { "tag": "starred" }}
],
"filter": {
"bool": {
"must": [
{ "range": { "date": { "gte": "2014-01-01" }}},
{ "range": { "price": { "lte": 29.99 }}}
],
"must_not": [
{ "term": { "category": "ebooks" }}
]
}
}
}
}
GET /company/employee/_search
{
"query": {
"constant_score": {
"filter": {
"range": {
"age": {
"gte": 30
}
}
}
}
}
}
六.定位不合法的搜索
GET /test_index/test_type/_validate/query?explain
{
"query": {
"math": {
"test_field": "test"
}
}
}
{
"valid": false,
"error": "org.elasticsearch.common.ParsingException: no [query] registered for [math]"
}
GET /test_index/test_type/_validate/query?explain
{
"query": {
"match": {
"test_field": "test"
}
}
}
{
"valid": true,
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"explanations": [
{
"index": "test_index",
"valid": true,
"explanation": "+test_field:test #(#_type:test_type)"
}
]
}
一般用在那种特别复杂庞大的搜索下，比如你一下子写了上百行的搜索，这个时候可以先用validate api去验证一下，搜索是否合法