如何将pyspark数据帧写入HDFS，然后如何将其读回数据帧? [英] How to write pyspark dataframe to HDFS and then how to read it back into dataframe?

问题描述

我有一个很大的pyspark数据框.因此，我想对其子集执行预处理，然后将其存储到hdfs.稍后，我想阅读所有内容并合并在一起.谢谢.

I have a very big pyspark dataframe. So I want to perform pre processing on subsets of it and then store them to hdfs. Later I want to read all of them and merge together. Thanks.

推荐答案

• 将DataFrame写入HDFS(Spark 1.6).

  • writing DataFrame to HDFS (Spark 1.6).

    df.write.save('/target/path/', format='parquet', mode='append') ## df is an existing DataFrame object.
    

  一些格式选项包括csv，parquet，json等.

  some of the format options are csv, parquet, json etc.

  • 从HDFS(Spark 1.6)读取DataFrame.

  • reading DataFrame from HDFS (Spark 1.6).

  from pyspark.sql import SQLContext
  sqlContext = SQLContext(sc)
  sqlContext.read.format('parquet').load('/path/to/file') 
  

  format方法采用诸如parquet，csv，json等的参数.

  the format method takes argument such as parquet, csv, json etc.

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