K.A*_*Ali 5 python dataframe apache-spark apache-spark-sql pyspark
我有这个代码:
from pyspark import SparkContext
from pyspark.sql import SQLContext, Row
sc = SparkContext()
sqlContext = SQLContext(sc)
documents = sqlContext.createDataFrame([
Row(id=1, title=[Row(value=u'cars', max_dist=1000)]),
Row(id=2, title=[Row(value=u'horse bus',max_dist=50), Row(value=u'normal bus',max_dist=100)]),
Row(id=3, title=[Row(value=u'Airplane', max_dist=5000)]),
Row(id=4, title=[Row(value=u'Bicycles', max_dist=20),Row(value=u'Motorbikes', max_dist=80)]),
Row(id=5, title=[Row(value=u'Trams', max_dist=15)])])
documents.show(truncate=False)
#+---+----------------------------------+
#|id |title |
#+---+----------------------------------+
#|1 |[[1000,cars]] |
#|2 |[[50,horse bus], [100,normal bus]]|
#|3 |[[5000,Airplane]] |
#|4 |[[20,Bicycles], [80,Motorbikes]] |
#|5 |[[15,Trams]] |
#+---+----------------------------------+
Run Code Online (Sandbox Code Playgroud)
我需要将所有复合行(例如2和4)拆分为多行,同时保留'id',以获得如下结果:
#+---+----------------------------------+
#|id |title |
#+---+----------------------------------+
#|1 |[1000,cars] |
#|2 |[50,horse bus] |
#|2 |[100,normal bus] |
#|3 |[5000,Airplane] |
#|4 |[20,Bicycles] |
#|4 |[80,Motorbikes] |
#|5 |[15,Trams] |
#+---+----------------------------------+
Run Code Online (Sandbox Code Playgroud)
zer*_*323 16
就是explode这样:
from pyspark.sql.functions import explode
documents.withColumn("title", explode("title"))
## +---+----------------+
## | id| title|
## +---+----------------+
## | 1| [1000,cars]|
## | 2| [50,horse bus]|
## | 2|[100,normal bus]|
## | 3| [5000,Airplane]|
## | 4| [20,Bicycles]|
## | 4| [80,Motorbikes]|
## | 5| [15,Trams]|
## +---+----------------+
Run Code Online (Sandbox Code Playgroud)