Python Pyspark：如何从时间戳中提取小时

我有一张像下面这样的桌子

    df

 +------------------------------------+-----------------------+
|identifier                          |timestamp              |
+------------------------------------+-----------------------+
|86311425-0890-40a5-8950-54cbaaa60815|2020-03-18 14:41:55 UTC|
|38e121a8-f21f-4d10-bb69-26eb045175b5|2020-03-13 15:19:21 UTC|
|1a69c9b0-283b-4b6d-89ac-66f987280c66|2020-03-16 12:59:51 UTC|
|c7b5c53f-bf40-498f-8302-4b3329322bc9|2020-03-18 22:05:06 UTC|
|0d3d807b-9b3a-466e-907c-c22402240730|2020-03-17 18:40:03 UTC|
+------------------------------------+-----------------------+

tmp.printSchema()
root
 |-- identifier: string (nullable = true)
 |-- timestamp: string (nullable = true)

+--------------------+--------------------+----+
|          identifier|           timestamp|hour|
+--------------------+--------------------+----+
|321869c3-71e5-41d...|2020-03-19 03:34:...|null|
|226b8d50-2c6a-471...|2020-03-19 02:59:...|null|
|47818b7c-34b5-43c...|2020-03-19 01:41:...|null|
|f5ca5599-7252-49d...|2020-03-19 04:25:...|null|
|add2ae24-aa7b-4d3...|2020-03-19 01:50:...|null|
+--------------------+--------------------+----+

我想有一个专栏，只采取从时间戳的天和小时

我正在尝试以下方法：

from pyspark.sql.functions import hour
df = df.withColumn("hour", hour(col("timestamp")))

但我得到了以下信息

    df

 +------------------------------------+-----------------------+
|identifier                          |timestamp              |
+------------------------------------+-----------------------+
|86311425-0890-40a5-8950-54cbaaa60815|2020-03-18 14:41:55 UTC|
|38e121a8-f21f-4d10-bb69-26eb045175b5|2020-03-13 15:19:21 UTC|
|1a69c9b0-283b-4b6d-89ac-66f987280c66|2020-03-16 12:59:51 UTC|
|c7b5c53f-bf40-498f-8302-4b3329322bc9|2020-03-18 22:05:06 UTC|
|0d3d807b-9b3a-466e-907c-c22402240730|2020-03-17 18:40:03 UTC|
+------------------------------------+-----------------------+

tmp.printSchema()
root
 |-- identifier: string (nullable = true)
 |-- timestamp: string (nullable = true)

+--------------------+--------------------+----+
|          identifier|           timestamp|hour|
+--------------------+--------------------+----+
|321869c3-71e5-41d...|2020-03-19 03:34:...|null|
|226b8d50-2c6a-471...|2020-03-19 02:59:...|null|
|47818b7c-34b5-43c...|2020-03-19 01:41:...|null|
|f5ca5599-7252-49d...|2020-03-19 04:25:...|null|
|add2ae24-aa7b-4d3...|2020-03-19 01:50:...|null|
+--------------------+--------------------+----+

虽然我想

+--------------------+--------------------+-------------------+
|          identifier|           timestamp|hour               |
+--------------------+--------------------+-------------------+
|321869c3-71e5-41d...|2020-03-19 03:00:...|2020-03-19 03:00:00|
|226b8d50-2c6a-471...|2020-03-19 02:59:...|2020-03-19 02:00:00|
|47818b7c-34b5-43c...|2020-03-19 01:41:...|2020-03-19 01:00:00|
|f5ca5599-7252-49d...|2020-03-19 04:25:...|2020-03-19 04:00:00|
|add2ae24-aa7b-4d3...|2020-03-19 01:50:...|2020-03-19 01:00:00|
+--------------------+--------------------+-------------------+

---

使用来自unixtime和unix的

时间戳

函数，因为

小时

用于从

时间戳

（或）

字符串（yyyy-MM-dd HH:MM:ss）提取小时值

类型

from pyspark.sql.functions import *
#sample data
df.show(truncate=False)
#+----------+-----------------------+
#|identifier|timestamp              |
#+----------+-----------------------+
#|1         |2020-03-18 14:41:55 UTC|
#+----------+-----------------------+
#DataFrame[identifier: string, timestamp: string]

df.withColumn("hour", from_unixtime(unix_timestamp(col("timestamp"),"yyyy-MM-dd hh:mm:ss"),"yyyy-MM-dd hh:00:00")).show()
#+----------+--------------------+-------------------+
#|identifier|           timestamp|               hour|
#+----------+--------------------+-------------------+
#|         1|2020-03-18 14:41:...|2020-03-18 14:00:00|
#+----------+--------------------+-------------------+

---

小时功能的使用：

#on string type 
spark.sql("select hour('2020-03-04 12:34:34')").show()
#on timestamp type
spark.sql("select hour(timestamp('2020-03-04 12:34:34'))").show()
#+---+
#|_c0|
#+---+
#| 12|
#+---+

---

您应该使用pyspark内置函数

date\u trunc

将时间截断为

hour

。您还可以截断为天/月/年等

from pyspark.sql import functions as F
df.withColumn("hour", F.date_trunc('hour',F.to_timestamp("timestamp","yyyy-MM-dd HH:mm:ss 'UTC'")))\
  .show(truncate=False)


+------------------------------------+-----------------------+-------------------+
|identifier                          |timestamp              |hour               |
+------------------------------------+-----------------------+-------------------+
|86311425-0890-40a5-8950-54cbaaa60815|2020-03-18 14:41:55 UTC|2020-03-18 14:00:00|
|38e121a8-f21f-4d10-bb69-26eb045175b5|2020-03-13 15:19:21 UTC|2020-03-13 15:00:00|
|1a69c9b0-283b-4b6d-89ac-66f987280c66|2020-03-16 12:59:51 UTC|2020-03-16 12:00:00|
|c7b5c53f-bf40-498f-8302-4b3329322bc9|2020-03-18 22:05:06 UTC|2020-03-18 22:00:00|
|0d3d807b-9b3a-466e-907c-c22402240730|2020-03-17 18:40:03 UTC|2020-03-17 18:00:00|
+------------------------------------+-----------------------+-------------------+

---

为什么不仅仅是自定义自定义自定义项

import pyspark.sql.functions as F
from pyspark.sql.types import IntegerType

hour = F.udf(lambda x: x.hour, IntegerType())
hours = df.withColumn("hour", hour("datetime"))

hours.limit(5).toPandas()

我会给你这个：

---

包含模式（

df.printSchema（）

）并用

truncate=False显示数据帧的问题。还请指定您要执行的输出expecting@pault刚刚修改了答案你如何得到实际的小时数？@RaminMelikov F.Hourca我能得到这个的scala版本吗？