#!/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 os 
from pyspark.sql import SparkSession 
 
# set PYSPARK_PYTHON to python36 
os.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')