Python Elasticsearch API操作ES集群

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#minyt 2018.9.1
#获取24小时内出现的模块次数
# 该程序通过elasticsearch python client 获取相关精简数据，可以计算请求数、超时数、错误数、正确率、错误率等等
import MySQLdb
from elasticsearch import Elasticsearch
from elasticsearch import helpers

#定义elasticsearch集群索引名
index_name = "logstash-nginxlog-*"

#实例化Elasticsearch类，并设置超时间为180秒，默认是10秒的，如果数据量很大，时间设置更长一些
es = Elasticsearch(['elasticsearch01','elasticsearch02','elasticsearch03'],timeout=180)

#DSL（领域特定语言）查询语法，查询top50 sname的排列次数
data_sname = {
  "aggs": {
    "2": {
      "terms": {
        "field": "apistatus.sname.keyword",
        "size": 100,
        "order": {
          "_count": "desc"
        }
      }
    }
  },
  "size": 0,
  "_source": {
    "excludes": []
  },
  "stored_fields": [
    "*"
  ],
  "script_fields": {},
  "docvalue_fields": [
    "@timestamp"
  ],
  "query": {
    "bool": {
      "must": [
        {
          "match_all": {}
        },
        {
          "range": {
            "@timestamp": {
              "gte" : "now-24h/h",
              "lt" :  "now/h"
            }
          }
        }
      ],
      "filter": [],
      "should": [],
      "must_not": []
    }
  }
}

#按照DSL（特定领域语言）语法查询获取数据
def get_original_data():
    try:
        #根据上面条件搜索数据
        res = es.search(
            index=index_name,
            size=0,
            body=data_sname
        )
        return res

    except:
        print "get original data failure"

#初始化数据库
def init_mysql():
    # 打开数据库连接
    db = MySQLdb.connect("localhost", "myuser", "mypassword", "mydb", charset='utf8' )

    # 使用cursor()方法获取操作游标 
    cursor = db.cursor()

    # SQL 更新语句
    sql = "update appname set count=0"
    try:
        # 执行SQL语句
        cursor.execute(sql)
        # 提交到数据库执行
        db.commit()
    except:
        # 发生错误时回滚
        db.rollback()

    # 关闭数据库连接
    db.close()

def updata_mysql(sname_count,sname_list):
    # 打开数据库连接
       db = MySQLdb.connect("localhost", "myuser", "mypassword", "mydb", charset='utf8' )

    # 使用cursor()方法获取操作游标 
    cursor = db.cursor()

    # SQL 更新语句
    sql = "update appname set count=%d where sname = '%s'" % (sname_count,sname_list)
    try:
        # 执行SQL语句
        cursor.execute(sql)
        # 提交到数据库执行
        db.commit()
    except:
        # 发生错误时回滚
        db.rollback()

    # 关闭数据库连接
    db.close()

#根据Index数据结构通过Elasticsearch Python Client上传数据到新的Index
def import_process_data():
    try:
        #列表形式显示结果
        res = get_original_data()
        #print res
        res_list = res.get('aggregations').get('2').get('buckets')
        #print res_list

        #初始化数据库
        init_mysql()

        #获取24小时内出现的SNAME 
        for value in res_list:
            sname_list = value.get('key')
            sname_count = value.get('doc_count')
            print sname_list,sname_count
            #更新sname_status值
            updata_mysql(sname_count,sname_list)

    except Exception, e:
        print repr(e)

if __name__ == "__main__":
    import_process_data()