python批量从es取数据的方法(文档数超过10000)

如下所示：

"""
提取文档数超过10000的数据
按照某个字段的值具有唯一性进行升序，
按照@timestamp进行降序，
第一次查询，先将10000条数据取出，
取出最后一个时间戳，
在第二次查询中，设定@timestamp小于将第一次得到的最后一个时间戳，
同时设定某个字段的值具有唯一性进行升序，
按照@timestamp进行降序，
"""

from elasticsearch import Elasticsearch
import os

write_path = "E:\公司\案例数据采集\olt告警案例分析\10000_data.txt"
es = Elasticsearch(hosts="", timeout=1500)
write_file = open(write_path, "a+")


def _first_query():
  index_ = "gather-010"
  _source = ["TWICE_BOOK_TIME", "@timestamp"]
  try:
    rs = es.search(index=index_, body={
      "size": 10000,
      "query": {
 "match_all": {}
      },
      "sort": [
 {
   "@timestamp": {
     "order": "desc"
   }
 },
 {
   "TASK_RECEIVE_ID.keyword": {
     "order": "asc"
   }
 }
      ],
      "_source": _source
    })
    return rs
  except:
    raise Exception("{0} search error".format(index_))


def _get_first_data(first_rs):
  i = 0
  if first_rs:
    for hit in first_rs['hits']['hits']:
      IptvAccount = hit['_source']['TWICE_BOOK_TIME']
      timestamp = hit['_source']['@timestamp']
      if IptvAccount is None:
 IptvAccount = ""
      write_file.write(IptvAccount + "," + timestamp + "n")
      i += 1
      if i == 10000:
 return timestamp


def _second_query(timestamp):
  index_ = "gather-010"
  _source = ["TWICE_BOOK_TIME", "@timestamp"]
  try:
    rs = es.search(index=index_, body={
      "size": 10000,
      "query": {
 "bool": {
   "filter": {
     "range": {
"@timestamp": {
  "lt": timestamp
}
     }
   }
 }
      },
      "sort": [
 {
   "@timestamp": {
     "order": "desc"
   }
 },
 {
   "TASK_RECEIVE_ID.keyword": {
     "order": "asc"
   }
 }
      ],
      "_source": _source
    })
    return rs
  except:
    raise Exception("{0} search error".format(index_))


if __name__ == "__main__":
  first_rs = _first_query()
  first_timestamp = _get_first_data(first_rs)
  print(first_timestamp)
  while True:
    second_rs = _second_query(first_timestamp)
    first_timestamp = _get_first_data(second_rs)
    if first_timestamp is None:
      break
    print(first_timestamp)

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