问题
I have a dataframe "df" with the columns ['name', 'age']
I saved the dataframe using df.rdd.saveAsTextFile("..")
to save it as an rdd. I loaded the saved file and then collect() gives me the following result.
a = sc.textFile("\mee\sample")
a.collect()
Output:
[u"Row(name=u'Alice', age=1)",
u"Row(name=u'Alice', age=2)",
u"Row(name=u'Joe', age=3)"]
This is not an rdd of Rows.
a.map(lambda g:g.age).collect()
AttributeError: 'unicode' object has no attribute 'age'
Is there any way to save the dataframe as a normal rdd without column names and Row keywords? I want to save the dataframe so that on loading the file and collect should give me as follows:
a.collect()
[(Alice,1),(Alice,2),(Joe,3)]
回答1:
It is a normal RDD[Row]
. Problem is you that when you saveAsTextFile
and load with textFile
what you get is a bunch of strings. If you want to save objects you should use some form of serialization. For example pickleFile
:
from pyspark.sql import Row
df = sqlContext.createDataFrame(
[('Alice', 1), ('Alice', 2), ('Joe', 3)],
("name", "age")
)
df.rdd.map(tuple).saveAsPickleFile("foo")
sc.pickleFile("foo").collect()
## [('Joe', 3), ('Alice', 1), ('Alice', 2)]
来源:https://stackoverflow.com/questions/34083871/how-to-save-a-spark-dataframe-as-a-text-file-without-rows-in-pyspark