spark_count_diff_uid.py

#!/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')