Python 导数 Elasticsearch 元数据到CSV

##查询 nginxlog 状态码为200，最近5分钟内的数据（即："now-5M"，注意！！此处时间基准为@timetamp，数据入ES的时间，并非日志时间； ）
GET /nginxlog-2019.11.22/_search
{   
    "query":
      { "match" :
        { "statuscode" : "200" }
      },
     "aggs":{
      "@timestamp": {
         "filter": {
            "range": {
               "sold": {
                  "from": "now-5M"
               }
            }
         }
      }
    },
        "size": 2,
        "from": 0,
        "_source": [ "type", "verb", "upstream_response_time","statuscode" ]
}

解释说明：
①  "_source" 指定输出字段；以SQL语法解释来说，类似于 select "type", "verb", "upstream_response_time","statuscode"  from nginxlog 的意思；
②   "size"  限制输出；类似于mysql 的LIMIT 操作；（注：此处为了演示只输出2条记录）
③   "from"  开始输出位置；类似于mysql 的LIMIT 操作； Limit 0，2

 注：官方说明，from定义了目标数据的偏移值，size定义当前返回的事件数目；（为了更好的说明，上述抽象的表达了下概念）

##查询返回结果
{
  "took": 17,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 1448153,
    "max_score": 1,
    "hits": [
      {
        "_index": "nginxlog-2019.11.22",
        "_type": "log",
        "_id": "AW6QrSYLcN5cQJSYWJEL",
        "_score": 1,
        "_source": {
          "statuscode": 200,
          "verb": "POST",
          "upstream_response_time": 0.014,
          "type": "log"
        }
      },
      {
        "_index": "nginxlog-2019.11.22",
        "_type": "log",
        "_id": "AW6QrSYLcN5cQJSYWJEM",
        "_score": 1,
        "_source": {
          "statuscode": 200,
          "verb": "POST",
          "upstream_response_time": 0.069,
          "type": "log"
        }
      }
    ]
  },
  "aggregations": {
    "@timestamp": {
      "doc_count": 0
    }
  }
}

## 同上，以下不做详细的说明，只简单解析相应的用法，具体规范细则，请参考官方文档；
时间区域查询：
##写法①
GET /nginxlog-2019.11.22/_search
{   
    "query":
      { "match" :
        { "statuscode" : "200" }
      },
     "aggs":{
      "@timestamp": {
         "filter": {
          "range" : {
            "@timestamp" : {
                "gte" : "now-1m",
                "lt" :  "now"
              }
            }
         }
      }
    },
        "size": 100,
        "from": 0,
        "_source": [ "log_timestamp","statuscode", "@timestamp"]
}
##写法②
GET /nginxlog-2019.11.22/_search
{
    "query": {
        "range" : {
            "@timestamp" : {
                "gte" : "now-1m",
                "lt" :  "now"
            }
        },
     "match" :
        { "statuscode" : "200" }
    },
    "size": 100,
    "_source": [ "first_name", "last_name","log_timestamp","@timestamp","statuscode"]
}

说明：
eq　　　　 　 相等
ne、neq　　  不相等
gt　　　　　　大于
lt　　　　　　小于 
gte、ge 　　 大于等于
lte、le  　　小于等于 

##写法③
组合查询：
GET /nginxlog-2019.01.24/_search
{
  "query": {
    "bool": {
      "must": { "match": { "statuscode" : "200"  }},
      "must": {"range" : {"@timestamp" : {"gte" : "now-1m","lt" :  "now"}}
        }
    }
  },
    "size": 100,
    "_source": [ "first_name", "last_name","log_timestamp","@timestamp","statuscode"]
}

 # -*- coding: utf-8 -*-
 """
 Created on Thu Jun  7 10:08:02 2018
 @author: illusioned
 """
 from elasticsearch import Elasticsearch
 from elasticsearch import helpers
  
 def GetVlue():
     es = Elasticsearch(["192.168.10.121:9200"],timeout=99999) #注意此处timeout，不专门设置，查询百分百超时报错；
　　  ###发现木有，查询语句非常相似；
     query ={
           "query": {
             "bool": {
               "must": [ {"match": { "actaion" : "visit"  }},
                         {"match": { "survey_id" : "471101"}},
                         {"match": { "ref" : "http*"}}
                 ]
             }
           },
             "size": 100,
             "_source": [ "@timestamp","action","survey_id","ref","user_id"]
         }
##是否非常像SQL语句：
##       select  "@timestamp","action","survey_id","ref","user_id"  from jsonlog-2019.11.*
##           where action="visit" and survey_id="471101" and ref="http*"
    scanResp = helpers.scan(client=es, query=query, scroll="3m", index=‘jsonlog-2019.11.*‘, doc_type=‘log‘, timeout="10m") 
    for k in scanResp: 
        yield k 

def write_file(k):
##指向读取需要导出的数据字段，注意编码问题；
     with open(‘China_news.csv‘,‘ab‘) as f:
         k=dict(k)
         f.write(str(k[‘_source‘][‘@timestamp‘]).encode(‘gbk‘))
         f.write(b‘,‘)
         f.write(str(k[‘_source‘][‘action‘]).encode(‘gbk‘))
         f.write(b‘,‘)
         f.write(str(k[‘_source‘][‘survey_id‘]).encode(‘gbk‘))
         f.write(b‘,‘)
         f.write(str(k[‘_source‘][‘ref‘]).encode(‘gbk‘))
         f.write(b‘,‘)
         f.write(str(k[‘_source‘][‘user_id‘]).encode(‘gbk‘))
         f.write(b‘\n‘)
  
 if __name__=="__main__":
     list1 = GetVlue()
     for index,k in enumerate(list1,1):
         write_file(k)
  
         print(‘正在导出‘+str(index)+‘条数据‘)