mongo批量插入问题(insert_many,bulk_write)，spark df转json传入mongo

https://blog.csdn.net/nihaoxiaocui/article/details/95060906

https://xuexiyuan.cn/article/detail/173.html

from etlsdk.lib.datasources.datasource_factory import DatasourceFactory
from data_pipeline.df_transform.transform import DataframeTransform
from data_pipeline.utils.utils import get_extractor_cls
import json
import math
from pymongo import MongoClient, ReplaceOne, InsertOne


class CommonMongodbPlugin(object):
    """
    提供dataframe 转化为新的dataframe 并写入mongodb数据库,
    """

    def write2mongo(self, iterator):
        result_list = []
        for x in iterator:
            if self.id:
                result_list.append(ReplaceOne({'_id': x.asDict()[self.id]}, x.asDict(), upsert=True))
            else:
                result_list.append(InsertOne(x.asDict()))
        if len(result_list) > 0:
            client = MongoClient(self.mongo_url)
            collection = client.get_database(self.mongo_db)[self.mongo_collection]
            collection.bulk_write(result_list, ordered=False, bypass_document_validation=True)

    def run(self, inputs, outputs, args):
        """
        根据tdate删除es中的数据
        python3 -m etlsdk.main data_pipeline.plugins.bluebook.common_parsed2mongodb.CommonMongodbPlugin.run\
         --input input_table:name=OSS_default:amazoncrawl:Jingji21/\
        --partition "2019-11-07 10:00:00"\
        --args keys:'["item_id","article_id","content","title","site","news_url","summary","create_time"]'\
        --args mongo:'{"mongo_url": "mongodb://用户名:密码@ip:端口号/连接库名字","mongo_db":"库名","mongo_collection":"表名"}'\
        --args extractor:data_pipeline.extractors.blue_book.jingji21.Jingji21Extractor\
        --args _id:"item_id"
        """
        input_df = inputs['input_table']['df']
        #  获取Extractor "data_pipeline.extractors.blue_book.jingji21.Jingji21Extractor"
        ExtractorCls = get_extractor_cls(args["extractor"])  # get_extractor_cls() 获取Extractor处理类

        keys = args["keys"] if isinstance(args["keys"], list) else json.loads(args["keys"])  # 列名输出的df的字段列表
        self.id = args.get("_id")
        class Extractor(ExtractorCls):  # 继承ExtractorCls
            namespace = args.get("namespace", 'production')
        columns_selected = None
        df = DataframeTransform.struct2struct(input_df, Extractor, keys, columns_selected)
        mymongo = args["mongo"] if isinstance(args["mongo"], dict) else json.loads(args["mongo"])
        self.mongo_url = mymongo["mongo_url"]
        self.mongo_db = mymongo["mongo_db"]
        self.mongo_collection = mymongo["mongo_collection"]
        df_count = df.count()
        partition_number = math.ceil(df_count / 500)
        if partition_number != 1:
            df = df.repartition(partition_number)
        df.foreachPartition(self.write2mongo)  # 遍历 partition