复杂类型数据及Object类型数据
1、multivalue field
建立索引时与string是一样的，数据类型不能混tag1 tag2 要么全是数字 要么全是字符串
{ "tags": [ "tag1", "tag2" ]}
2、empty field
null，[]，[null]
3、object field
PUT /company/employee/1
{
"address": {
"country": "china",
"province": "guangdong",
"city": "guangzhou"
},
"name": "jack",
"age": 27,
"join_date": "2017-01-01"
}
上面的address就是 object类型，address Object 数据底层的存储
{
"name": [jack],
"age": [27],
"join_date": [2017-01-01],
"address.country": [china],
"address.province": [guangdong],
"address.city": [guangzhou]
}
又比如
{
"authors": [
{ "age": 26, "name": "Jack White"},
{ "age": 55, "name": "Tom Jones"},
{ "age": 39, "name": "Kitty Smith"}
]
}
存储如下 ,底层是这样存储的
{
"authors.age": [26, 55, 39],
"authors.name": [jack, white, tom, jones, kitty, smith]
}
search api的基本语法
1、search api的基本语法
GET /search
{}
GET /index1,index2/type1,type2/search
{}
GET /_search
{
"from": 0,
"size": 10
}
HTTP协议，一般不允许get请求带上request body，但是因为get更加适合描述查询数据的操作，因此还是这么用了。
Query DSL
1、Query DSL的基本语法
{
QUERY_NAME: {
ARGUMENT: VALUE,
ARGUMENT: VALUE,...
}
}
2、如何组合多个搜索条件
搜索需求：title必须包含elasticsearch，content可以包含elasticsearch也可以不包含，author_id必须不为111
源数据如下
{
"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
}
}
]
}
}
搜索语句,当需要组合搜索的时候 就加一个bool
GET /website/article/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "elasticsearch"
}
}
],
"should": [
{
"match": {
"content": "elasticsearch"
}
}
],
"must_not": [
{
"match": {
"author_id": 111
}
}
]
}
}
}
must 是必须，should里面的条件是满足和非满足都无所谓，minimum_should_match最小数量必须为1
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
}
}
}
filter与query对比
1 加入数据
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
query搜索语法
1、match all 查询所有数据
GET /_search
{
"query": {
"match_all": {}
}
}
2、match 必须匹配该条件
GET /_search
{
"query": { "match": { "title": "my elasticsearch article" }}
}
3、multi match 多重匹配
GET /test_index/test_type/_search
{
"query": {
"multi_match": {
"query": "test",
"fields": ["test_field", "test_field1"]
}
}
}
4、range query 范围查找
GET /company/employee/_search
{
"query": {
"range": {
"age": {
"gte": 30
}
}
}
}
5、term query 注意：在term 里面搜索不会去分词查询，在match 里面搜索会去分词
GET /test_index/test_type/_search
{
"query": {
"term": {
"test_field": "test hello"
}
}
}
6、terms query
GET /_search
{
"query": { "terms": { "tag": [ "search", "full_text", "nosql" ] }}
}
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