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名师互学网 > IT > 前沿技术 > 大数据 > 大数据系统

通过python将mongodb的数据库批量导入elasticsearch

通过python将mongodb的数据库批量导入elasticsearch

from threading import Thread
from queue import Queue
from pymongo import MongoClient, collection
from elasticsearch import Elasticsearch, client
from hashlib import md5  #哈希函数  
import time
class Putdata(Thread):
    def __init__(self,queue:Queue,config:dict):
        super(Putdata, self).__init__()
        self.queue = queue
        self.config = config

    def run(self):
        while True:
            try:
                title,content = self.queue.get()
                self.put_document(title,content)            
            finally:
                self.queue.task_done()
    @staticmethod
    def get_hash(title):
        return md5(title.encode('utf-8')).hexdigest()
    def put_document(self,title,content):
        doc = {
            'title': title,
            'content': content,
        }
        _id = self.get_hash(title)
        self.config['es'].index(index = self.config['index'],document=doc,id=_id,ignore=[400,409,500])
def read_data(table: collection.Collection,queue: Queue):
    article = table.find({},{'_id':0,'title':1,'content':1})
    for item in article:
        queue.put((item['title'],item['content']))


if __name__ =="__main__":
    article_queue = Queue()
    client = MongoClient()
    db = client['yikaowang']
    es = Elasticsearch(hosts='http://127.0.0.1:9200/')
    put_config = {
        'es':es,
        'index':'wenzhang',
    }
    rd = Thread(target=read_data,args=(db['wenzhang'],article_queue))
    rd.daemon = True
    rd.start()
    time.sleep(2)
    for _ in range(50):
        pd = Putdata(article_queue,put_config)
        pd.daemon = True
        pd.start()
    article_queue.join()
    print('成功入es')
    
        


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