相关疑难解决方法(0)

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]]                      |
#+---+----------------------------------+

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 …

我有一个数据框（具有更多行和列），如下所示。

示例 DF：

from pyspark import Row
from pyspark.sql import SQLContext
from pyspark.sql.functions import explode

sqlc = SQLContext(sc)

df = sqlc.createDataFrame([Row(col1 = 'z1', col2 = '[a1, b2, c3]', col3 = 'foo')])
# +------+-------------+------+
# |  col1|         col2|  col3|
# +------+-------------+------+
# |    z1| [a1, b2, c3]|   foo|
# +------+-------------+------+

df
# DataFrame[col1: string, col2: string, col3: string]

我想要的是：

+-----+-----+-----+
| col1| col2| col3|
+-----+-----+-----+
|   z1|   a1|  foo|
|   z1|   b2|  foo|
|   z1|   c3|  foo|
+-----+-----+-----+

我试图复制RDD这里提供的解决方案： …