在Pyspark数据框中为时间戳列添加额外的小时数

Question

我有一个数据框Pyspark.在这个数据框中,我有一个timestamp数据类型的列.现在,我想为timestamp列的每一行添加额外的2小时,而不创建任何新列.

例如:这是样本数据

df

id  testing_time            test_name

1   2017-03-12 03:19:58     Raising
2   2017-03-12 03:21:30     sleeping
3   2017-03-12 03:29:40     walking
4   2017-03-12 03:31:23     talking
5   2017-03-12 04:19:47     eating  
6   2017-03-12 04:33:51     working

我想要有类似下面的东西.

df1

id  testing_time            test_name

1   2017-03-12 05:19:58     Raising
2   2017-03-12 05:21:30     sleeping
3   2017-03-12 05:29:40     walking
4   2017-03-12 05:31:23     talking
5   2017-03-12 06:19:47     eating  
6   2017-03-12 06:33:51     working 

我怎样才能做到这一点？

Answer 1

您可以使用函数在几秒钟内将testing_time列转换为bigint,添加2小时(7200秒),然后将结果转换回时间戳:unix_timestamp

import pyspark.sql.functions as F

df.withColumn("testing_time", (F.unix_timestamp("testing_time") + 7200).cast('timestamp')).show()
+---+-------------------+---------+
| id|       testing_time|test_name|
+---+-------------------+---------+
|  1|2017-03-12 05:19:58|  Raising|
|  2|2017-03-12 05:21:30| sleeping|
|  3|2017-03-12 05:29:40|  walking|
|  4|2017-03-12 05:31:23|  talking|
|  5|2017-03-12 06:19:47|   eating|
|  6|2017-03-12 06:33:51|  working|
+---+-------------------+---------+

Answer 2

一种不需要显式强制转换并使用Spark间隔文字的方法（具有可争议的可读性优点）：

df = df.withColumn('testing_time', df.testing_time + F.expr('INTERVAL 2 HOURS'))
df.show()
+---+-------------------+---------+
| id|       testing_time|test_name|
+---+-------------------+---------+
|  1|2017-03-12 05:19:58|  Raising|
|  2|2017-03-12 05:21:30| sleeping|
|  3|2017-03-12 05:29:40|  walking|
|  4|2017-03-12 05:31:23|  talking|
|  5|2017-03-12 06:19:47|   eating|
|  6|2017-03-12 06:33:51|  working|
+---+-------------------+---------+

或全部：

import pyspark.sql.functions as F
from datetime import datetime

data = [
  (1, datetime(2017, 3, 12, 3, 19, 58), 'Raising'),
  (2, datetime(2017, 3, 12, 3, 21, 30), 'sleeping'),
  (3, datetime(2017, 3, 12, 3, 29, 40), 'walking'),
  (4, datetime(2017, 3, 12, 3, 31, 23), 'talking'),
  (5, datetime(2017, 3, 12, 4, 19, 47), 'eating'),
  (6, datetime(2017, 3, 12, 4, 33, 51), 'working'),
]

df = sqlContext.createDataFrame(data, ['id', 'testing_time', 'test_name'])
df = df.withColumn('testing_time', df.testing_time + F.expr('INTERVAL 2 HOURS'))
df.show()
+---+-------------------+---------+
| id|       testing_time|test_name|
+---+-------------------+---------+
|  1|2017-03-12 05:19:58|  Raising|
|  2|2017-03-12 05:21:30| sleeping|
|  3|2017-03-12 05:29:40|  walking|
|  4|2017-03-12 05:31:23|  talking|
|  5|2017-03-12 06:19:47|   eating|
|  6|2017-03-12 06:33:51|  working|
+---+-------------------+---------+