1. What is DSL inquiry
Provide a rich and flexible query language, called by the ES DSL query (Query DSL), which allows you to build a more complex , powerful queries.
The DSL (domain-specific language the Domain Specific Language) in JSON form bodies request occurs.
DSL is a generic query query ES offers, the biggest feature of this approach is the development language of independence , that is, any client as long as the support HTTP requests, you can JSON format to perform complex search query data.
For simple query using a query string is better, but for complex queries , because conditions and more complicated nested logical, easy organization and expression of the query string, and error-prone, it is recommended complex queries by DSL request body content in JSON format instead.
DSL has two components: DSL query , DSL filter .
DSL DSL filter statements and queries are very similar, but their purpose is different:
DSL filter (pinpoint) query document is more like a way for my condition "yes" or "no", while DSL queries (fuzzy query) is like "How like."
DSL DSL filters and queries on the performance difference :
The results can be cached by filtration and applied to subsequent requests.
The documents that match the query, the correlation is calculated, it is more time-consuming, and does not cache.
Filter statement can effectively meet the query is completed document filtering.
In principle, the use of DSL queries do full-text searches or other need for relevance score of the scene, the other all-filtered with DSL.
2, DSL inquiry
Use DSL query, you must query parameters to be passed to the ES.
GET _search
{"query": YOUR_QUERY_HERE}
A common DSL relatively complete query:
GET itsource/employee/_search { "query": { "match": {"sex":"女"} }, "_source": ["id","name"], "from": 20, "size": 10, "sort": [{"join_date": "desc"},{"age": "asc"}] }
select id,name from t_user where name like “%heh%” order by id desc limit 0,10.
DSL on behalf of the above query: Discover employees gender woman staff, and in accordance Joined descending, ascending order of age, eventually returned Article 21-30 data (return only name, age and email fields)
3, DSL filter
Fuzzy query query with DSL and precise query filter statement with DSL.
2.0以上的用法
{ "query": { "bool": { "must": [ {"match": {"description": "search" }} ], "filter": { "term": {"age": "12"} } } }， "_source": ["id","name"], "from": 20, "size": 10, "sort": [{"join_date": "desc"},{"age": "asc"}] }
4, using DSL filter query
① full match (match_all)
Ordinary search (match all documents):
{ "query" : { "match_all" : {} } }
If you need to use filters (filter in all documents, not the red part of the default write):
{ "query" : { "bool" : { "must" : [{ "match_all":{} }], "filter":{....} } } }
② standard query (match and multi_match)
match the query is a standard query, whether you need full-text search or precise query basically have to use it.
If you use a full-text query match field, it will use the parser to parse the query character before the actual query:
{ "query": { "match": { "fullName": "Steven King" } } }
Steven King will search the above word and find documents that contain or Steven King, and then give ranking score.
If the next match with a precise value specified, in the face of numbers, date, boolean, or string not_analyzed, it will search for you the value given to you, such as:
{ "match": { "age": 20 }}
{ "match": { "date": "2016-05-01" }}
{ "match": { "public": true }}
{ "match": { "tag": "full_text" }}
multi_match query allows you to simultaneously search multiple fields basis do match the query on:
{ "query":{ "multi_match": { "query": "Steven King", "fields": [ "fullName","title" ] } } }
The above simultaneously search and matching fullName title field.
Tip: match generally only used to match query text field, generally not used for filtering.
③ word search and filter (Term and Terms )
{ "query": { "bool": { "must": { "match_all": {} }, "filter": { "term": { "age": "20" } } } } }
Terms search and filter
{ "query": { "terms": { "tags": ["jvm", "hadoop", "lucene"], "minimum_match": 2 } } }
minimum_match: at least the number of hits, default 1
④ combination condition search and filter (Bool )
Bool compositions may be combined with the search query to a plurality of query objects, including query criteria must, should and must_not.
For example: Query interested in eating rice, but also like a game or a sport, and people born in 1990-06-30 and beyond. Range: range
{ "query": { "bool": { "must": [{"term": {"hobby": "吃米饭"}}], "should": [{"term": {"hobby": "游戏"}}, {"term": {"hobby": "运动"}} ], "must_not": [ {"range" :{"birth_date":{"lt": "1990-06-30"}}} ], "filter": [...], "minimum_should_match": 1 } } }
Tip: If there is no clause must under bool inquiry, then at least there should be a clause should. But if there must clause, clause should not be queried.
⑤ range queries and filters (the Range )
range filter allows us to find a group of data in accordance with the specified range:
{ "query":{ "range": { "age": { "gte": 20, "lt": 30 } } } }
The example query older than or equal to 20 and less than 30.
gt:> gte:>= lt:< lte:<=
⑥ presence and absence of the filter (exists and Missing )
{ "query": { "bool": { "must": [{ "match_all": {} }], "filter": { "exists": { "field": "gps" } } } } }
Tip: exists and missing only be used to filter results.
⑦ before matching search and filter (prefix )
And similar term query, the search is not an exact match before the match, but similar in SQL like 'key%'
{ "query": { "prefix": { "fullName": "黄" } } }
That is the example for all queries surnamed Huang.
⑧ wildcard search (wildcard )
* For 0 ~ N, uses at? On behalf of one.
{ "query": { "wildcard": { "fullName": "文*华" } } }