Pyspark 将 Dataframe 字符串列拆分为多列

Question

我正在 spark 3.0.0 上执行 Spark Structure 流式传输的示例，为此，我正在使用 Twitter 数据。我在 Kafka 中推送了 twitter 数据，单个记录看起来像这样

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

这里每个字段都用'|'分隔字段是

日期时间
用户 ID
推文
位置

现在在 Spark 中阅读这条消息，我得到了这样的数据框

 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 的回答，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")

但它给我这样的输出，

                            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：表示正则表达式的字符串。正则表达式字符串应该是一个 Java 正则表达式。

使用"\|"按管道拆分或'[|]'

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 字符串列拆分为多列

Pyspark Split Dataframe string column into multiple columns

apache-spark

spark-streaming

apache-spark-sql

spark-structured-streaming