Question

我正在执行一个在Spark 3.0.0上流式传输Spark结构的示例，为此，我正在使用Twitter数据。我已经在Kafka中推送了Twitter数据，单条记录看起来像这样

2020-07-21 10：48：19 | 1265200268284588034 | RT @narendramodi：与@IBM首席执行官@ArvindKrishna先生进行了广泛的互动。我们讨论了与技术有关的几个主题，…|印度海德拉巴

此处每个字段均以'|'分隔字段是

约会时间
用户ID
推文
位置

现在在Spark中阅读此消息，我得到了这样的数据帧

 key |   value 
-----+-------------------------
     |  2020-07-21 10:48:19|1265200268284588034|RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,…|Hyderabad, India

根据this的答案，我在我的应用程序中添加了以下代码块。

split_col =  pyspark.sql.functions.split(df['value'], '|')


df = df.withColumn("Tweet Time", split_col.getItem(0))
df = df.withColumn("User ID", split_col.getItem(1))
df = df.withColumn("Tweet Text", split_col.getItem(2))
df = df.withColumn("Location", split_col.getItem(3))
df = df.drop("key")

但是它给了我这样的输出，

                            A                                                                                                                                                                         |  B   |   C     |   D    |  E  |
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------+---------+--------+-----+
  2020-07-21 10:48:19|1265200268284588034|RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,…|Hyderabad, India|2     |    0    |    2   |  0  |

但是我想要这样的输出

       Tweet Time      |       User ID           |                            Tweet text                                                                                                        |   Location        |
-----------------------+-------------------------+----------------------------------------------------------------------------------------------------------------------------------------------+-------------------+
  2020-07-21 10:48:19  |   1265200268284588034   |  RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,… |  Hyderabad, India |

Answer 1

因为它接受 模式：代表正则表达式的字符串。正则表达式字符串应为 Java正则表达式。

使用"\\|"按管道或'[|]'

进行拆分

split_col =  split(df.value, '\\|',)

df = df.withColumn("Tweet Time", split_col.getItem(0))\
    .withColumn("User ID", split_col.getItem(1))\
    .withColumn("Tweet Text", split_col.getItem(2))\
    .withColumn("Location", split_col.getItem(3))\
    .drop("key")

输出：

+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------+----------------+
|value                                                                                                                                                                                               |Tweet Time         |User ID            |Tweet Text                                                                                                                                 |Location        |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------+----------------+
|2020-07-21 10:48:19|1265200268284588034|RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,…|Hyderabad, India|2020-07-21 10:48:19|1265200268284588034|RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,…|Hyderabad, India|
|2020-07-21 10:48:19|1265200268284588034|RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,…|Hyderabad, India|2020-07-21 10:48:19|1265200268284588034|RT @narendramodi: Had an extensive interaction with CEO of @IBM, Mr. @ArvindKrishna. We discussed several subjects relating to technology,…|Hyderabad, India|
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------------+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------+----------------+

Pyspark将Dataframe字符串列拆分为多个列

1 个答案: