python分页爬取es日志，获取数据

 这里是分页爬取数据，判断msgId重复的数据，并写入文件。这里重点参考分页的方式

此处是根据下面的代码判断数据是否读取完成的：

# 检查是否有更多结果需要滚动
    scroll_id = query.get('_scroll_id')
    if scroll_id is None or len(query['hits']['hits']) == 0:
        break
    # 使用滚动ID进行下一次滚动查询
    query = es.scroll(scroll_id=scroll_id, scroll='25m')

完整代码 

from elasticsearch import Elasticsearch


es = Elasticsearch(hosts="http://XXXX:9200/", http_auth=('elastic', '密码'))
scroll_id = None
fileName = "order-info-repeat" + ".txt"
msgIdList = []
msgIdListRepeat = []
total=0
repeatTotal=0
query_json = {
    "_source": ["message", "logger_name", "@timestamp"],
    "query": {
        "bool": {
            "filter":
                [
                    {
                        "bool":
                            {
                                "filter":
                                    [
                                        {
                                            "multi_match":
                                                {
                                                    "lenient": True,
                                                    "query": "rocketMQ syncPassengerOrderCnosumer topicList",
                                                    "type": "phrase"
                                                }
                                        }
                                    ]
                            }
                    },
                    {
                        "range":
                            {
                                "@timestamp":
                                    {
                                        "format": "strict_date_optional_time",
                                        "gte": "2023-07-27T02:30:00.000Z",
                                        "lte": "2023-07-27T04:00:00.000Z"
                                    }
                            }
                    }
                ],
            "must":
                [
                ],
            "must_not":
                [
                ],
            "should":
                [
                ]
        }
    }
}
query = es.search(index='indexName索引名称', body=query_json, scroll='25m', size=5000,request_timeout=2000000)
while True:
    for k in query['hits']['hits']:
        timestr = k['_source']['@timestamp']
        result = k['_source']['message']
        orderIdStart = result.find('order_id') + 11
        orderIdEnd = orderIdStart + 19
        orderId = result[orderIdStart:orderIdEnd]
        msgIdStart = result.find('msgId:') + 7
        msgIdEnd = msgIdStart + 32
        msgId = result[msgIdStart:msgIdEnd]
        if msgId in msgIdList:
            msgIdListRepeat.append(msgId)
            repeatTotal=repeatTotal+1
            print("repeat,msgId:"+msgId+",orderId:"+orderId)
            with open(fileName, 'a+', encoding='utf-8') as f2:
                f2.writelines("repeat,msgId:"+msgId+",orderId:"+orderId + "\n")
                f2.close()
        msgIdList.append(msgId)
    total=total+len(query['hits']['hits'])
    print("total:"+str(total)+",repeatTotal:"+str(repeatTotal)+",len:"+str(len(query['hits']['hits'])))
    # 检查是否有更多结果需要滚动
    scroll_id = query.get('_scroll_id')
    if scroll_id is None or len(query['hits']['hits']) == 0:
        break
    # 使用滚动ID进行下一次滚动查询
    query = es.scroll(scroll_id=scroll_id, scroll='25m')