如何使用withColumn创建新的Column以将两个数字列集中为String?

时间:2018-11-16 04:44:35

标签: scala apache-spark apache-spark-sql

我的数据框如下

val employees = sc.parallelize(Array[(String, Int, BigInt)](
  ("Rafferty", 31, 222222222), ("Jones", 33, 111111111), ("Heisenberg", 33, 222222222), ("Robinson", 34, 111111111), ("Smith", 34, 333333333), ("Williams", 15, 222222222)
)).toDF("LastName", "DepartmentID", "Code")

employees.show()

 +----------+------------+---------+
|  LastName|DepartmentID|     Code|
+----------+------------+---------+
|  Rafferty|          31|222222222|
|     Jones|          33|111111111|
|Heisenberg|          33|222222222|
|  Robinson|          34|111111111|
|     Smith|          34|333333333|
|  Williams|          15|222222222|
+----------+------------+---------+

我想创建另一个列作为personal_id作为集中DepartmentId和Code。例如:拉弗蒂=> 31222222222

所以我写如下代码:

val anotherdf = employees.withColumn("personal_id", $"DepartmentID".cast("String") + $"Code".cast("String"))


 +----------+------------+---------+------------+
|  LastName|DepartmentID|     Code| personal_id|
+----------+------------+---------+------------+
|  Rafferty|          31|222222222|2.22222253E8|
|     Jones|          33|111111111|1.11111144E8|
|Heisenberg|          33|222222222|2.22222255E8|
|  Robinson|          34|111111111|1.11111145E8|
|     Smith|          34|333333333|3.33333367E8|
|  Williams|          15|222222222|2.22222237E8|
+----------+------------+---------+------------+

但是我得到了personal_id两倍。

anotherdf.printSchema

root
 |-- LastName: string (nullable = true)
 |-- DepartmentID: integer (nullable = false)
 |-- Code: decimal(38,0) (nullable = true)
 |-- personal_id: double (nullable = true) 

1 个答案:

答案 0 :(得分:2)

我应该使用concat

import org.apache.spark.sql.functions.concat
val anotherdf2 = employees.withColumn("personal_id", concat($"DepartmentID".cast("String"), $"Code".cast("String")))


 +----------+------------+---------+-----------+
|  LastName|DepartmentID|     Code|personal_id|
+----------+------------+---------+-----------+
|  Rafferty|          31|222222222|31222222222|
|     Jones|          33|111111111|33111111111|
|Heisenberg|          33|222222222|33222222222|
|  Robinson|          34|111111111|34111111111|
|     Smith|          34|333333333|34333333333|
|  Williams|          15|222222222|15222222222|
+----------+------------+---------+-----------+