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apache-spark - Pyspark（Dataframes）逐行读取文件（将行转换为字符串）

问题描述

我需要逐行读取文件并将每一行拆分为单词并对单词执行操作。

我怎么做？

我写了下面的代码：

logFile = "/home/hadoop/spark-2.3.1-bin-hadoop2.7/README.md"  # Should be 
some file on your system
spark = SparkSession.builder.appName("SimpleApp1").getOrCreate()
logData = spark.read.text(logFile).cache()
logData.printSchema()
logDataLines = logData.collect()

#The line variable below seems to be of type row. How I perform similar operations 
on row or how do I convert row to a string.

for line in logDataLines:
    words = line.select(explode(split(line,"\s+")))
    for word in words:
        print(word)
    print("----------------------------------")

标签： apache-sparkpysparkpyspark-sql

解决方案

我认为你应该map对你的行应用一个函数。您可以在自创函数中应用任何内容：

data = spark.read.text("/home/spark/test_it.txt").cache()

def someFunction(row):
    wordlist = row[0].split(" ")
    result = list()
    for word in wordlist:
        result.append(word.upper())
    return result

data.rdd.map(someFunction).collect()

输出： 

[[u'THIS', u'IS', u'JUST', u'A', u'TEST'], [u'TO', u'UNDERSTAND'], [u'THE', u'PROCESSING']]

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