Spark 1.6:过滤由describe()生成的DataFrame [英] Spark 1.6: filtering DataFrames generated by describe()

问题描述

当我在DataFrame上调用describe函数时会出现问题:

The problem arises when I call describe function on a DataFrame:

val statsDF = myDataFrame.describe()

调用describe函数将产生以下输出:

Calling describe function yields the following output:

statsDF: org.apache.spark.sql.DataFrame = [summary: string, count: string]

我可以通过调用statsDF.show()

+-------+------------------+
|summary|             count|
+-------+------------------+
|  count|             53173|
|   mean|104.76128862392568|
| stddev|3577.8184333911513|
|    min|                 1|
|    max|            558407|
+-------+------------------+

我现在想从statsDF获取标准偏差和均值，但是当我尝试通过以下操作来收集值时:

I would like now to get the standard deviation and the mean from statsDF, but when I am trying to collect the values by doing something like:

val temp = statsDF.where($"summary" === "stddev").collect()

我遇到了Task not serializable异常.

当我打电话时，我也面临着同样的异常

I am also facing the same exception when I call:

statsDF.where($"summary" === "stddev").show()

我们似乎无法过滤由describe()函数生成的DataFrame?

It looks like we cannot filter DataFrames generated by describe() function?

推荐答案

我考虑过一个玩具数据集，其中包含一些健康疾病数据

I have considered a toy dataset I had containing some health disease data

val stddev_tobacco = rawData.describe().rdd.map{ 
    case r : Row => (r.getAs[String]("summary"),r.get(1))
}.filter(_._1 == "stddev").map(_._2).collect

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