ES Document API之多文档API

Posted 猪朵朵

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多文档API

#获取一个类型的多个文档,有多种API写法,如下:
#1
curl -XGET ‘localhost:9200/_mget?pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_index" : "test", "_type" : "type", "_id" : "1" }, { "_index" : "test", "_type" : "type", "_id" : "2" } ] }
#2
curl -XGET ‘localhost:9200/test/_mget?pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_type" : "type", "_id" : "1" }, { "_type" : "type", "_id" : "2" } ] } #3
curl -XGET ‘localhost:9200/test/type/_mget?pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_id" : "1" }, { "_id" : "2" } ] } #4
curl -XGET ‘localhost:9200/test/type/_mget?pretty‘ -H ‘Content-Type: application/json‘ -d{ "ids" : ["1", "2"] }
#_type字段可选,如果没有指定type,则默认第一个类型中满足条件的id文档作为返回结果,下面的例子中,返回两个相同的结果
curl -XGET ‘localhost:9200/test/_mget?pretty‘ -H ‘Content-Type: application/json‘ -d{ "ids" : ["1", "1"] }
#可以明确指定不同的类型
curl -XGET ‘localhost:9200/test/_mget/?pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_type":"typeA", "_id" : "1" }, { "_type":"typeB", "_id" : "1" } ] }
#过滤_source
curl -XGET ‘localhost:9200/_mget?pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_index" : "test", "_type" : "type", "_id" : "1", "_source" : false }, { "_index" : "test", "_type" : "type", "_id" : "2", "_source" : ["field3", "field4"] }, { "_index" : "test", "_type" : "type", "_id" : "3", "_source" : { "include": ["user"], "exclude": ["user.location"] } } ] }
#指定stored_field字段返回 1 返回 field1,field2,2返回field3,field4
curl -XGET ‘localhost:9200/test/type/_mget?stored_fields=field1,field2&pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_id" : "1" }, { "_id" : "2", "stored_fields" : ["field3", "field4"] } ] }
#指定routing
curl -XGET ‘localhost:9200/_mget?routing=key1&pretty‘ -H ‘Content-Type: application/json‘ -d{ "docs" : [ { "_index" : "test", "_type" : "type", "_id" : "1", "routing" : "key2" }, { "_index" : "test", "_type" : "type", "_id" : "2" } ] }

批量操作在写法上需要注意的事项:换行\n结尾; 回车\r ;开始 Content-Type头部应该被设置为application/x-ndjson;

支持的参数:version_type;routing;wait_for_active_shards;refresh;

update操作支持的动作参数:retry_on_conflict;doc;doc_as_upsert;script;lang;source.

 

#批量操作数据结构
action_and_meta_data \ n
optional_source \ n
action_and_meta_data \ n
optional_source \ n
....
action_and_meta_data \ n
optional_source \ n

curl -XPOST ‘localhost:9200/_bulk?pretty‘ -H ‘Content-Type: application/json‘ -d{ "index" : { "_index" : "test", "_type" : "type1", "_id" : "1" } } { "field1" : "value1" } { "delete" : { "_index" : "test", "_type" : "type1", "_id" : "2" } } { "create" : { "_index" : "test", "_type" : "type1", "_id" : "3" } } { "field1" : "value3" } { "update" : {"_id" : "1", "_type" : "type1", "_index" : "test"} } { "doc" : {"field2" : "value2"} }

 

curl -XPOST ‘localhost:9200/_bulk?pretty‘ -H ‘Content-Type: application/json‘ -d{ "update" : {"_id" : "1", "_type" : "type1", "_index" : "index1", "retry_on_conflict" : 3} }
{ "doc" : {"field" : "value"} }
{ "update" : { "_id" : "0", "_type" : "type1", "_index" : "index1", "retry_on_conflict" : 3} }
{ "script" : { "source": "ctx._source.counter += params.param1", "lang" : "painless", "params" : {"param1" : 1}}, "upsert" : {"counter" : 1}}
{ "update" : {"_id" : "2", "_type" : "type1", "_index" : "index1", "retry_on_conflict" : 3} }
{ "doc" : {"field" : "value"}, "doc_as_upsert" : true }
{ "update" : {"_id" : "3", "_type" : "type1", "_index" : "index1", "_source" : true} }
{ "doc" : {"field" : "value"} }
{ "update" : {"_id" : "4", "_type" : "type1", "_index" : "index1"} }
{ "doc" : {"field" : "value"}, "_source": true}
  • Term vectors 返回特定文档信息中的术语信息和统计信息
#示例
curl -XGET ‘localhost:9200/twitter/tweet/1/_termvectors?pretty‘

  #可以指定要检索的字段

  curl -XGET ‘localhost:9200/twitter/tweet/1/_termvectors?fields=message&pretty‘

返回字段包含:term infomation,term statistics,field statistics。默认返回:term infomation和field statistics。

term infomation:1.字段的term频率;2.term 位置;3.开始和结束偏移量;4.term 有效负载      即使没保存也可以计算。

term statistics :1.术语在总文档中出现的频次 2.包含当前术语的总文档数

field statistics : 1.包含该字段的文档数doc_count  2.该字段中所有term的文档总频次 sum_doc_freq 3.该term中每个term的总频次 sum_ttf

  • multi term vectors 一次性取回多个termvectors
curl -XPOST ‘localhost:9200/_mtermvectors?pretty‘ -H ‘Content-Type: application/json‘ -d{
   "docs": [
      {
         "_index": "twitter",
         "_type": "tweet",
         "_id": "2",
         "term_statistics": true
      },
      {
         "_index": "twitter",
         "_type": "tweet",
         "_id": "1",
         "fields": [
            "message"
         ]
      }
   ]
}

 

 

  • Search API

查询API通常是多文档 多类型的,除explain api

查询API可指定多个routing,用“,”隔开

自适应副本选择:代替循环查询副本的方式,将请求发送到被认为是最佳的分片上:

  • Response time of past requests between the coordinating node and the node containing the copy of the data
  • Time past search requests took to execute on the node containing the data
  • The queue size of the search threadpool on the node containing the data

 

统计信息组:search 与信息统计组关联,每个统计组包含其统计聚合

全局搜索超时:search.default_search_timeout  在集群更新中设置,设置为-1时,即不超时

搜索任务取消:task cancell中取消搜索任务

 

#指定routing
curl -XPOST ‘localhost:9200/twitter/tweet/_search?routing=kimchy&pretty‘ -H ‘Content-Type: application/json‘ -d{ "query": { "bool" : { "must" : { "query_string" : { "query" : "some query string here" } }, "filter" : { "term" : { "user" : "kimchy" } } } } }

 

#动态集群设置,自适应分片选择参数为true,默认为false
curl -XPUT ‘localhost:9200/_cluster/settings?pretty‘ -H ‘Content-Type: application/json‘ -d{ "transient": { "cluster.routing.use_adaptive_replica_selection": true } }
#与统计信息组做关联
curl -XPOST ‘localhost:9200/_search?pretty‘ -H ‘Content-Type: application/json‘ -d{ "query" : { "match_all" : {} }, "stats" : ["group1", "group2"] }

 

 

 

















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