从单个字符串创建 Spark DataFrame

本文介绍了从单个字符串创建 Spark DataFrame的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我正在尝试采用硬编码的字符串并将其转换为 1 行 Spark DataFrame(具有 StringType 类型的单列)，这样:

I'm trying to take a hardcoded String and turn it into a 1-row Spark DataFrame (with a single column of type StringType) such that:

String fizz = "buzz"

会产生一个数据帧，它的 .show() 方法看起来像:

Would result with a DataFrame whose .show() method looks like:

+-----+
| fizz|
+-----+
| buzz|
+-----+

迄今为止我最好的尝试是:

My best attempt thus far has been:

val rawData = List("fizz")
val df = sqlContext.sparkContext.parallelize(Seq(rawData)).toDF()

df.show()

但我收到以下编译器错误:

But I get the following compiler error:

java.lang.ClassCastException: org.apache.spark.sql.types.ArrayType cannot be cast to org.apache.spark.sql.types.StructType
    at org.apache.spark.sql.SQLContext.createDataFrame(SQLContext.scala:413)
    at org.apache.spark.sql.SQLImplicits.rddToDataFrameHolder(SQLImplicits.scala:155)

关于我要去哪里的任何想法?另外，如何将 "buzz" 设置为 fizz 列的行值?

Any ideas as to where I'm going awry? Also, how do I set "buzz" as the row value for the fizz column?

尝试:

sqlContext.sparkContext.parallelize(rawData).toDF()

我得到的 DF 如下所示:

I get a DF that looks like:

+----+
|  _1|
+----+
|buzz|
+----+

推荐答案

尝试:

sqlContext.sparkContext.parallelize(rawData).toDF()

在 2.0 中，您可以:

In 2.0 you can:

import spark.implicits._

rawData.toDF

可选择为 toDF 提供一系列名称:

Optionally provide a sequence of names for toDF:

sqlContext.sparkContext.parallelize(rawData).toDF("fizz")

这篇关于从单个字符串创建 Spark DataFrame的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！

Buzz