elasticsearch基础查询

Es基础数据类型

string
字符串类型,es中最常用的类型,官方文档

比较重要的参数:

index分析
analyzed(默认)
not_analyzed
no
store存储
true 独立存储
false(默认)不存储,从_source中解析
Numeric
数值类型,注意numeric并不是一个类型,它包括多种类型,比如:long,integer,short,byte,double,float,每种的存储空间都是不一样的,一般默认推荐integer和float。官方文档参考

重要的参数:

index分析
not_analyzed(默认) ,设置为该值可以保证该字段能通过检索查询到
no
store存储
true 独立存储
false(默认)不存储,从_source中解析
date
日期类型,该类型可以接受一些常见的日期表达方式,官方文档参考。

重要的参数:

index分析
not_analyzed(默认) ,设置为该值可以保证该字段能通过检索查询到
no
store存储
true 独立存储
false(默认)不存储,从_source中解析
format格式化
strict_date_optional_time||epoch_millis(默认)
你也可以自定义格式化内容,比如
"date": {
  "type":   "date",
  "format": "yyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
}
更多的时间表达式可以参考这里
IP
这个类型可以用来标识IPV4的地址,参考官方文档

常用参数:

index分析
not_analyzed(默认) ,设置为该值可以保证该字段能通过检索查询到
no
store存储
true 独立存储
false(默认)不存储,从_source中解析
boolean
布尔类型,所有的类型都可以标识布尔类型,参考官方文档

False: 表示该值的有:false, "false", "off", "no", "0", "" (empty string), 0, 0.0
True: 所有非False的都是true
重要的参数:

index分析
not_analyzed(默认) ,设置为该值可以保证该字段能通过检索查询到
no
store存储
true 独立存储
false(默认)不存储,从_source中解析
View Code

 

Es的head插件使用

   1.查看集群中的索引信息和查看索引中定义的列的类型

  2.查看es是如何对某个字符串进行切分的

    

 

Es对Date类型的处理

   es如何存储Date类型,它最终的输出方式都是以字符串输出,只是默认的格式是:1970-01-01T00:00:00Z ,也就是默认的 UTC 格式

   所以我们在查询和添加时间类型数据的时候需要把格式手动转换成UTC格式 否则会出现时间格式转换异常

异常查询示例:

正常查询示例:

 

Es查询条件设置

        body = {
            "query": {
                "filtered": {
                    "filter": {
                        "bool":{
                            "must":
                             [
                               //must数组中的三个条件必须同时满足
                               {"term":{"jylsh": jylsh}},
                               {
                                  "range": {
                                     "@timestamp":
                                      {
                                       "gte": tools.strtime_to_timestamp(startTime),
                                       "lte": tools.strtime_to_timestamp(endTime)
                                      }
                                  }
                               },
                               {
                                 "bool": {
                                     "should": [
                                             //should数组中的条件至少需要满足一个
                                             {"match": {"message": "SERVICE_LOG"}},
                                             {"match": {"message": "ENTRANCE_LOG"}}
                                     ]
                                 }
                               }
                             ]
                        }
                    }
                }
            },
            "sort": sort_dict
        }
并且和或者判断

 

Es查询代码示例

   1.需要把时间转换成unix格式的13位数的时间戳字符  精确到毫秒级

    #格式化日期字符串
    def formatDate(self,timestr):
        timeStruct = time.strptime(timestr, "%Y-%m-%d %H:%M:%S.%f")
        strTime = time.strftime("%Y-%m-%d %H:%M:%S", timeStruct)
        return strTime


import time 
t = "2017-11-24 17:30:00"
#将其转换为时间数组 
timeStruct = time.strptime(t, "%Y-%m-%d %H:%M:%S") 
#转换为时间戳: 
timeStamp = int(time.mktime(timeStruct)) 
print(timeStamp)
日期字符串不同格式转换
#!/usr/bin/env python
# -*- coding: utf-8 -*-

from elasticsearch import Elasticsearch
import time,datetime

####动态修改配置项目############
es = Elasticsearch("http://127.0.0.1:9200")
appname="dzgzpt-wsys"
userChoiceTime_start="2019-04-05 09:27:27.820"
userChoiceTime_end="2019-06-27 09:27:41.986"

#东八区时间
nowtime=datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3]

#计算15分钟前的时间
fifteenminAgo=(datetime.datetime.now()+datetime.timedelta(minutes=-15)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]

#计算1个小时前的时间
hourAgo=(datetime.datetime.now()+datetime.timedelta(hours=-1)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]

#计算1天前的时间
dayAgo=(datetime.datetime.now()+datetime.timedelta(days=-1)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]


def strtime_to_datetime(timestr):
    """将字符串格式的时间 (含毫秒) 转为 datetime 格式
    :param timestr: {str}'2016-02-25 20:21:04.242'
    :return: {datetime}2016-02-25 20:21:04.242000
    """
    local_datetime = datetime.datetime.strptime(timestr, "%Y-%m-%d %H:%M:%S.%f")
    return local_datetime

def datetime_to_timestamp(datetime_obj):
    """将本地(local) datetime 格式的时间 (含毫秒) 转为毫秒时间戳
    :param datetime_obj: {datetime}2016-02-25 20:21:04.242000
    :return: 13 位的毫秒时间戳  1456402864242
    """
    local_timestamp = int(time.mktime(datetime_obj.timetuple()) * 1000.0 + datetime_obj.microsecond / 1000.0)
    return local_timestamp

def strtime_to_timestamp(local_timestr):
    """将本地时间 (字符串格式,含毫秒) 转为 13 位整数的毫秒时间戳
    :param local_timestr: {str}'2016-02-25 20:21:04.242'
    :return: 1456402864242
    """
    local_datetime = strtime_to_datetime(local_timestr)
    timestamp = datetime_to_timestamp(local_datetime)
    return timestamp

def set_interval(startTime,endTime):
    d1 = datetime.datetime.strptime(startTime, "%Y-%m-%d %H:%M:%S.%f")
    d2 = datetime.datetime.strptime(endTime, "%Y-%m-%d %H:%M:%S.%f")
    n_days = d2 - d1

    days = n_days.days
    year = days // 365
    month = days % 365 // 30

    seconds = n_days.seconds
    mins = seconds // 60
    hours = mins // 60

    if year >=1:
        return "1M"
    elif month == 1:
        return "12h"
    elif month > 1:
        return "1d"
    elif days == 1:
        return "30m"
    elif days >=2 and days <=4:
        return "1h"
    elif days >= 5 and days <=12:
        return "3h"
    elif days >=13 and days <= 30:
        return "12h"
    elif hours == 1 or hours ==2:
        return "1m"
    elif hours >=3 and hours<5:
        return "3m"
    elif hours >=5 and hours<10:
        return "5m"
    elif hours >=10 and hours<=60:
        return "10m"
    elif mins>=1 and mins<=30:
        return "30s"
    elif mins>30 and mins <=60:
        return "1m"

def search_qps(startTime,endTime):
    interval=set_interval(startTime,endTime)
    print("interval设置为 %s" %(interval))
    print("开始qps时间%s" %(startTime))
    print("结束qps时间%s " %(endTime))
    body={
     "size": 0,
     "query": {
    "filtered": {
      "query": {
        "query_string": {
          "analyze_wildcard": True,
          "query": "appname:"+appname
        }
      },
      "filter": {
        "bool": {
          "must": [
            {
              "range": {
                "@timestamp": {
                  "gte": strtime_to_timestamp(startTime),
                  "lte": strtime_to_timestamp(endTime)
                }
              }
            }
          ]
        }
      }
    }
  },
     "aggs": {
       "res": {
        "date_histogram": {
        "field": "@timestamp",
        "interval": "%s" %(interval),
        "time_zone": "Asia/Shanghai",
        "min_doc_count": 0,
        "extended_bounds": {
          "min": strtime_to_timestamp(startTime),
          "max": strtime_to_timestamp(endTime)
        }
       }
      }
     }
   }

    res=es.search(body=body)
    print(res)
    print("查询到qps总条数: %s" %(len(res["aggregations"]["res"]["buckets"])))

def search_wastetime(startTime,endTime):
    print("开始延迟时间%s" % (startTime))
    print("结束延迟时间%s " % (endTime))
    body = {
        "size": 0,
        "query": {
            "filtered": {
                "query": {
                    "query_string": {
                        "analyze_wildcard": True,
                        "query": "appname:" + appname
                    }
                },
                "filter": {
                    "bool": {
                        "must": [
                            {
                                "range": {
                                    "@timestamp": {
                                        "gte": strtime_to_timestamp(startTime),
                                        "lte": strtime_to_timestamp(endTime)
                                    }
                                }
                            }
                        ]
                    }
                }
            }
        },
        "aggs": {
            "avg_wastetime": {
                "avg": {
                    "field": "waste_time"
                }
            }
        }
    }
    res=es.search(body=body)
    print(res)

def search_abnormal(startTime,endTime):
    print("开始异常统计时间%s" % (startTime))
    print("结束异常统计时间%s " % (endTime))
    body = {
        "size": 0,
        "query": {
            "filtered": {
                "query": {
                    "query_string": {
                        "analyze_wildcard": True,
                        "query": "appname:" + appname
                    }
                },
                "filter": {
                    "bool": {
                        "must": [
                            {
                                "range": {
                                    "@timestamp": {
                                        "gte": strtime_to_timestamp(startTime),
                                        "lte": strtime_to_timestamp(endTime)
                                    }
                                }
                            }
                        ]
                    }
                }
            }
        },
        "aggs": {
            "res": {
                "terms": {
                    "field": "success"
                }
            }
        }
    }
    res=es.search(body=body)
    reslist=res["aggregations"]["res"]["buckets"]
    for re in reslist:
        if re["key"] == "false":
            print("统计到的异常数 %s" %(re["doc_count"]))


print("---------------------15分钟内的qps总数-------------------")
search_qps(fifteenminAgo,nowtime)
print("-------------------用户设置时间段的qps总数------------------------")
search_qps(userChoiceTime_start,userChoiceTime_end)
print("*******************************************************************")
print("---------------------15分钟内的延迟平均值-------------------")
search_wastetime(fifteenminAgo,nowtime)
print("-------------------用户设置时间段的延迟平均值------------------------")
search_wastetime(userChoiceTime_start,userChoiceTime_end)
print("*******************************************************************")
print("---------------------15分钟内的异常数-------------------")
search_abnormal(fifteenminAgo,nowtime)
print("-------------------用户设置时间段的异常数------------------------")
search_abnormal(userChoiceTime_start,userChoiceTime_end)
统计数据实例
def search_test():
    body={
      "query" : {
         "constant_score" : {
            "filter" : {
                "range" : {
                    "@timestamp":{
                        "gt": "now-3m"
                     }
                 }
             }
          }
       }
    }
    res=es.search(body=body)
    print(res)

import time, datetime
def timeToZtime(time):
    myTime = datetime.datetime.strptime(time, "%Y-%m-%d %H:%M:%S")
    return myTime.strftime("%Y-%m-%dT%H:%M:%S.%fZ")

def search_test2():
    body={
      "query" : {
         "constant_score" : {
            "filter" : {
                "range" : {
                    "@timestamp":{
                        "gt": timeToZtime("2019-01-13 12:10:30"),
                        "lt": timeToZtime("2019-01-13 12:10:30")+"||+1M"
                     }
                 }
             }
          }
       }
    }
    res=es.search(body=body)
    print(res)

search_test2()
时间范围查询
import time, datetime

def strtime_to_datetime(timestr):
    """将字符串格式的时间 (含毫秒) 转为 datetime 格式
    :param timestr: {str}'2016-02-25 20:21:04.242'
    :return: {datetime}2016-02-25 20:21:04.242000
    """
    local_datetime = datetime.datetime.strptime(timestr, "%Y-%m-%d %H:%M:%S.%f")
    return local_datetime

def datetime_to_timestamp(datetime_obj):
    """将本地(local) datetime 格式的时间 (含毫秒) 转为毫秒时间戳
    :param datetime_obj: {datetime}2016-02-25 20:21:04.242000
    :return: 13 位的毫秒时间戳  1456402864242
    """
    local_timestamp = int(time.mktime(datetime_obj.timetuple()) * 1000.0 + datetime_obj.microsecond / 1000.0)
    return local_timestamp

def strtime_to_timestamp(local_timestr):
    """将本地时间 (字符串格式,含毫秒) 转为 13 位整数的毫秒时间戳
    :param local_timestr: {str}'2016-02-25 20:21:04.242'
    :return: 1456402864242
    """
    local_datetime = strtime_to_datetime(local_timestr)
    timestamp = datetime_to_timestamp(local_datetime)
    return timestamp



#调用api处理时间
def search_qps_avg():

    body2={
     "size": 0,
     "query": {
    "filtered": {
      "query": {
        "query_string": {
          "analyze_wildcard": True,
          "query": "appname:dzgzpt-wsys"
        }
      },
      "filter": {
        "bool": {
          "must": [
            {
              "range": {
                "@timestamp": {
                  "gte": strtime_to_timestamp("2019-04-05 09:27:27.820"),
                  "lte": strtime_to_timestamp("2019-04-18 09:34:41.986")
                }
              }
            }
          ]
        }
      }
    }
  },
     "aggs": {
       "2": {
      "date_histogram": {
        "field": "@timestamp",
        "interval": "12h",
        "time_zone": "Asia/Shanghai",
        "min_doc_count": 1,
        "extended_bounds": {
          "min": strtime_to_timestamp("2019-04-05 09:27:27.820"),
          "max": strtime_to_timestamp("2019-04-18 09:34:41.986")
        }
      }
    }
     }
   }

    body1 = {
  "size": 0,
  "query": {
    "filtered": {
      "query": {
        "query_string": {
          "analyze_wildcard": 'true',
          "query": "appname:dzgzpt-wsys"
        }
      },
      "filter": {
        "bool": {
          "must": [
            {
              "range": {
                "@timestamp": {
                  "gte": 1554427647820,
                  "lte": 1555551281986,
                  "format": "epoch_millis"
                }
              }
            }
          ],
          "must_not": []
        }
      }
    }
  },
  "aggs": {
    "2": {
      "date_histogram": {
        "field": "@timestamp",
        "interval": "12h",
        "time_zone": "Asia/Shanghai",
        "min_doc_count": 1,
        "extended_bounds": {
          "min": 1554427647820,
          "max": 1555551281986
        }
      }
    }
  }
}
    res=es.search(body=body2)
    print(res)


search_qps_avg()
python处理时间和es一致
#unix的utc标准时间
print(datetime.datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
#东八区时间
print(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
#计算15分钟后的时间
print((datetime.datetime.now()+datetime.timedelta(minutes=15)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3])
#计算15分钟前的时间
print((datetime.datetime.now()+datetime.timedelta(minutes=-15)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3])
#计算一天后的时间
print((datetime.datetime.now()+datetime.timedelta(days=1)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3])
#计算1个小时后的时间
print((datetime.datetime.now()+datetime.timedelta(hours=1)).strftime("%Y-%m-%d %H:%M:%S.%f")[:-3])


2019-06-04 05:37:41.564
2019-06-04 13:37:41.564
2019-06-04 13:52:41.564
2019-06-04 13:22:41.564
2019-06-05 13:37:41.564
2019-06-04 14:37:41.564
python时间计算
import datetime
d1 = datetime.datetime.strptime("2019-06-27 09:27:27.820", "%Y-%m-%d %H:%M:%S.%f")
d2 = datetime.datetime.strptime("2021-07-29 15:43:41.986", "%Y-%m-%d %H:%M:%S.%f")
n_days = d2 - d1

print("------------计算时分秒-----------------")
seconds = n_days.seconds
print("相差秒数: %s" %(seconds))

mins = seconds // 60
print("相差分钟数: %s" %(mins))

hours = mins // 60
print("相差小时数: %s" %(hours))

print("-------------计算年月日---------------------")
days=n_days.days
print("相差天数: %s" %(days))

month= days%365//30
print("相差月数: %s" %(month))

year = days // 365
print("相差年数: %s" %(year))
计算两个时间差
posted @ 2019-06-04 19:26  不懂123  阅读(1776)  评论(0编辑  收藏  举报