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Spark 2.X MongoDB
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| from pyspark.sql import SparkSession | |
| spark = SparkSession \ | |
| .builder \ | |
| .appName("demography mapper") \ | |
| .getOrCreate() | |
| df_user = spark.read.format("com.mongodb.spark.sql.DefaultSource")\ | |
| .option("spark.mongodb.input.uri", "mongodb://localhost:27017/raw.user").load() | |
| print(df_user.printSchema()) | |
| df_user = df_user.repartition(2) | |
| print(df_user.count()) | |
| df_demography = spark.read.format("com.mongodb.spark.sql.DefaultSource")\ | |
| .option("spark.mongodb.input.uri", "mongodb://localhost:27017/raw.demography").load() | |
| print(df_demography.printSchema()) | |
| df_demography = df_demography.repartition(2) | |
| print(df_demography.count()) | |
| df_result = df_user.join(df_demography, on="user", how="left_outer").cache() | |
| print(df_result.printSchema()) | |
| print(df_result.count()) | |
| df_result.write.format("com.mongodb.spark.sql.DefaultSource")\ | |
| .option("spark.mongodb.output.uri", "mongodb://localhost:27017/raw.user_demography")\ | |
| .save() |
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