1.filter查询语句
1）通过filter可以获取想要的数据
2）通过filter查询有缓存，大大提高查询效率，所以推荐使用filter查询
2.cache缓存
3.实例数据，准备数据：
POST /store/products/_bulk
{"index":{"_id":1}}
{"price":10,"productID":"SD1002136"}
{"index":{"_id":2}}
{"price":20,"productID":"SD2678421"}
{"index":{"_id":3}}
{"price":30,"productID":"SD8897573"}
{"index":{"_id":4}}
{"price":40,"productID":"SD4535233"}
4.查看测试数据
GET /store/products/_mget
{
"ids":[1,2,3,4]
}
5.filter查询
最简单的filter查询
先看看sql语句： select document from products where price = 20
filter的语句
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"term": {
"price": "20"
}
}
}
}
}
也可以指定多个值
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"terms": {
"price": [
"10",
"20"
]
}
}
}
}
}
再看另一个 select * from products where productId = "SD4535233"
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"term": {
"productID": "sd1002136"
}
}
}
}
}
注意：这里的大写查不到
对字段进行分析：
查看字段的分析结果，可以看到分析结果是小写的，所以上面的大写查找不到
GET /_analyze?text=SD4535233
结果如下：
{
"tokens": [
{
"token": "sd4535233",
"start_offset": 0,
"end_offset": 9,
"type": "<ALPHANUM>",
"position": 1
}
]
}
如果想要大写也可以搜索到，那么需要对该字段的mapping设置为not_analyzed，不进行分析器分析
DELETE /store
PUT /store
{
"mappings": {
"products":{
"properties": {
"productID":{
"type":"string",
"index":"not_analyzed"
}
}
}
}
}
6.bool过滤查询，可以做组合过滤查询
SELECT product FROM products where (price = 20 OR productID = 'SD1002136' ) AND (price != 30)
查询价格等于20的或者productID 为SD1002136的商品，排除价格30元的
类似的，elasticsearch也有and,or,not这样的组合条件查询方式
格式如下：
{
"bool":{
"must":[],
"should":[],
"must_not":[]
}
}must ： 条件必须满足，相当于and
should：条件可以满足也可以不满足，相当于or
must_not：条件不需要满足，相当于not
示例：
GET /store/products/_search
{
"query":{
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"should": [
{"term": {
"price": "20"
}},
{"term": {
"productID": "SD2678421"
}}
],
"must_not": [
{"term": {
"price": "30"
}}
]
}
}
}
}
}
7.嵌套查询
1)示例sql:select * from products where productID = "SD1002136" OR (productID = "SD4535233" AND price = 30)
示例查询：
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"should": [
{"term": {
"productID": "sd1002136"
}},
{"bool": {
"must": [
{
"term": {
"productID": "sd4535233"
}
},
{
"term": {
"price": "30"
}
}
]
}}
]
}
}
}
}
2) 另外一种：and , or , not查询
没有bool，直接使用and ,or ,not
示例，and的：
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"and":[
{
"term":{
"price" : 10
}
},
{
"term":{
"productID":"sd1002136"
}
}
]
}
}
}
}
示例，or的：
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"or":[
{
"term":{
"price" : 10
}
},
{
"term":{
"productID":"sd4535233"
}
}
]
}
}
}
}
not示例：
GET /store/products/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"not":{
"term":{
"price" : 10
}
}
}
}
}
}
8.range范围查询
示例sql: select * from products where price between 20 and 40
gt > 大于
lt < 小于
gte >= 大于等于
lte <= 小于等于
示例：
GET /store/products/_search
{
"query": {
"filtered": {
"query": {"match_all": {}},
"filter": {
"range": {
"price": {
"gte": 10,
"lte": 20
}
}
}
}
}
}
9.过滤空和非空
1）建立测试数据
POST /test_index/test/_bulk
{"index":{"_id":1}}
{"tags":["search"]}
{"index":{"_id":2}}
{"tags":["search","open_source"]}
{"index":{"_id":3}}
{"other_field":"some data"}
{"index":{"_id":4}}
{"tags":null}
{"index":{"_id":5}}
{"tags":["search",null]}
2)处理null空值的方法
select tags from test where tags is not null
select tags from test where tags is null
示例：
is not null
GET /test_index/test/_search
{
"query": {
"filtered": {
"query": {"match_all": {}},
"filter": {
"exists": {
"field": "tags"
}
}
}
}
}
is null
GET /test_index/test/_search
{
"query": {
"filtered": {
"query": {"match_all": {}},
"filter": {
"missing": {
"field": "tags"
}
}
}
}
}
10.cache缓存
elasticsearch在执行带有filter查询时，会打开索引的每个segment文件（lucene底层文件），然后去判断里面的文档是否符合filter要求。
注意：旧的segment文件不会变，新来的数据会产生新的segment。
匹配的结果会用一个大型的BigSet数组来存储，这个数组的值只有0和1
匹配：1
不匹配：0
BigSet值是存在内存里的，而不是硬盘里，所以速度快！
开启方式：在filter查询语句后面加"_cache":true
注意：
Script filters,Geo-filters,Date ranges这样的过滤方式开启cache毫无意义
exists,missing,range,term和terms查询时默认开启cache的
示例：
GET /store/products/_search
{
"query":{
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"should": [
{"term": {
"price": "20"
}},
{"term": {
"productID": "SD2678421"
}}
],"_cache":true,
"must_not": [
{"term": {
"price": "30"
}}
]
}
}
}
}
}
