Apache Spark 如何将列表/数组中的新列附加到 Spark 数据帧 [英] Apache Spark how to append new column from list/array to Spark dataframe

问题描述

我正在使用 Apache Spark 2.0 数据帧/数据集 API我想从值列表向我的数据框中添加一个新列.我的列表具有与给定数据框相同数量的值.

I am using Apache Spark 2.0 Dataframe/Dataset API I want to add a new column to my dataframe from List of values. My list has same number of values like given dataframe.

val list = List(4,5,10,7,2)
val df   = List("a","b","c","d","e").toDF("row1")

我想做类似的事情:

val appendedDF = df.withColumn("row2",somefunc(list))
df.show()
// +----+------+
// |row1 |row2 |
// +----+------+
// |a    |4    |
// |b    |5    |
// |c    |10   |
// |d    |7    |
// |e    |2    |
// +----+------+

对于任何我会很高兴的想法，我的数据框实际上包含更多列.

For any ideas I would be greatful, my dataframe in reality contains more columns.

推荐答案

你可以这样做:

import org.apache.spark.sql.Row
import org.apache.spark.sql.types._    

// create rdd from the list
val rdd = sc.parallelize(List(4,5,10,7,2))
// rdd: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[31] at parallelize at <console>:28

// zip the data frame with rdd
val rdd_new = df.rdd.zip(rdd).map(r => Row.fromSeq(r._1.toSeq ++ Seq(r._2)))
// rdd_new: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] = MapPartitionsRDD[33] at map at <console>:32

// create a new data frame from the rdd_new with modified schema
spark.createDataFrame(rdd_new, df.schema.add("new_col", IntegerType)).show
+----+-------+
|row1|new_col|
+----+-------+
|   a|      4|
|   b|      5|
|   c|     10|
|   d|      7|
|   e|      2|
+----+-------+

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