Spark dataFrame 将列数据类型从字符串转换为日期

Question

我有以下数据，架构

scala> df2.printSchema()
root
 |-- RowID: integer (nullable = true)
 |-- Order Date: string (nullable = true)

scala> df2.show(5)
+-----+----------+
|RowID|Order Date|
+-----+----------+
|    1|   4/10/15|
|   49|   4/10/15|
|   50|   4/10/15|
|   80|   4/10/15|
|   85|   4/10/15|
+-----+----------+

我想将 "Order Date" String 列转换为 Date 数据类型，并尝试以下但没有成功，有人可以建议更好的方法吗？

scala> df2.select(df2.col("RowID"), df2.col("Order Date"), date_format(df2.col("Order Date"), "M/dd/yy")).show(5)
+-----+----------+-------------------------------+
|RowID|Order Date|date_format(Order Date,M/dd/yy)|
+-----+----------+-------------------------------+
|    1|   4/10/15|                           null|
|   49|   4/10/15|                           null|
|   50|   4/10/15|                           null|
|   80|   4/10/15|                           null|
|   85|   4/10/15|                           null|
+-----+----------+-------------------------------+

Answer 1

设法转换为 unix 纪元时间戳，我认为从这里开始很简单

scala> df.select(df.col("RowID"), df.col("Order Date"), unix_timestamp(df.col("Order Date"), "M/d/yy")).show(5)
+-----+----------+--------------------------------+
|RowID|Order Date|unixtimestamp(Order Date,M/d/yy)|
+-----+----------+--------------------------------+
|    1|   4/10/15|                      1428604200|
|   49|   4/10/15|                      1428604200|
|   50|   4/10/15|                      1428604200|
|   80|   4/10/15|                      1428604200|
|   85|   4/10/15|                      1428604200|
+-----+----------+--------------------------------+

Spark dataFrame 将列数据类型从字符串转换为日期

Spark dataFrame convert columns Datatype from String to Date

scala

apache-spark

spark-dataframe