pyspark操作MongoDB的方法步骤

#!/usr/bin/env python# -*- coding: utf-8 -*-"""@author: zhangslob@file: spark_count.py @time: 2019/01/03@desc:  不要安装最新的pyspark版本  `pip3 install pyspark==2.3.2`  更多pyspark操作MongoDB请看https://docs.mongodb.com/spark-connector/master/python-api/"""import osfrom pyspark.sql import SparkSession# set PYSPARK_PYTHON to python36os.environ['PYSPARK_PYTHON'] = '/usr/bin/python36'# load mongodb data# 格式是："mongodb://127.0.0.1:database.collection"input_uri = "mongodb://127.0.0.1:27017/spark.spark_test"output_uri = "mongodb://127.0.0.1:27017/spark.spark_test"# 创建spark，默认使用本地环境，或者"spark://master:7077"spark = SparkSession /  .builder /  .master("local") /  .appName("MyApp") /  .config("spark.mongodb.input.uri", input_uri) /  .config("spark.mongodb.output.uri", output_uri) /  .config('spark.jars.packages', 'org.mongodb.spark:mongo-spark-connector_2.11:2.2.0') /  .getOrCreate()def except_id(collection_1, collection_2, output_collection, pipeline):  """  计算表1与表2中不同的数据  :param collection_1: 导入表1  :param collection_2: 导入表2  :param output_collection: 保存的表  :param pipeline: MongoDB查询语句 str  :return:  """  # 可以在这里指定想要导入的数据库，将会覆盖上面配置中的input_uri。下面保存数据也一样  # .option("collection", "mongodb://127.0.0.1:27017/spark.spark_test")  # .option("database", "people").option("collection", "contacts")  df_1 = spark.read.format('com.mongodb.spark.sql.DefaultSource').option("collection", collection_1) /    .option("pipeline", pipeline).load()  df_2 = spark.read.format('com.mongodb.spark.sql.DefaultSource').option("collection", collection_2) /    .option("pipeline", pipeline).load()  # df_1有但是不在 df_2，同理可以计算df_2有，df_1没有  df = df_1.subtract(df_2)  df.show()  # mode 参数可选范围  # * `append`: Append contents of this :class:`DataFrame` to existing data.  # * `overwrite`: Overwrite existing data.  # * `error` or `errorifexists`: Throw an exception if data already exists.  # * `ignore`: Silently ignore this operation if data already exists.  df.write.format("com.mongodb.spark.sql.DefaultSource").option("collection", output_collection).mode("append").save()  spark.stop()if __name__ == '__main__':  # mongodb query, MongoDB查询语句，可以减少导入数据量  pipeline = "[{'$project': {'uid': 1, '_id': 0}}]"  collection_1 = "spark_1"  collection_2 = "spark_2"  output_collection = 'diff_uid'  except_id(collection_1, collection_2, output_collection, pipeline)  print('success')