pyspark操作MongoDB的方法步驟

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@author: zhangslob
@file: spark_count.py 
@time: 2019/01/03
@desc:
  不要安裝最新的pyspark版本
  `pip3 install pyspark==2.3.2`
  更多pyspark操作MongoDB請看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"

# 創(chuàng)建spark，默認(rèn)使用本地環(huán)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):
  """
  計(jì)算表1與表2中不同的數(shù)據(jù)
  :param collection_1: 導(dǎo)入表1
  :param collection_2: 導(dǎo)入表2
  :param output_collection: 保存的表
  :param pipeline: MongoDB查詢語句 str
  :return:
  """
  # 可以在這里指定想要導(dǎo)入的數(shù)據(jù)庫，將會覆蓋上面配置中的input_uri。下面保存數(shù)據(jù)也一樣
  # .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，同理可以計(jì)算df_2有，df_1沒有
  df = df_1.subtract(df_2)
  df.show()

  # mode 參數(shù)可選范圍
  # * `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查詢語句，可以減少導(dǎo)入數(shù)據(jù)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')