问题
I work on a dataframe with two column, mvv and count.
+---+-----+
|mvv|count|
+---+-----+
| 1 | 5 |
| 2 | 9 |
| 3 | 3 |
| 4 | 1 |
i would like to obtain two list containing mvv values and count value. Something like
mvv = [1,2,3,4]
count = [5,9,3,1]
So, I tried the following code: The first line should return a python list of row. I wanted to see the first value:
mvv_list = mvv_count_df.select('mvv').collect()
firstvalue = mvv_list[0].getInt(0)
But I get an error message with the second line:
AttributeError: getInt
回答1:
See, why this way that you are doing is not working. First, you are trying to get integer from a Row Type, the output of your collect is like this:
>>> mvv_list = mvv_count_df.select('mvv').collect()
>>> mvv_list[0]
Out: Row(mvv=1)
If you take something like this:
>>> firstvalue = mvv_list[0].mvv
Out: 1
You will get the mvv value. If you want all the information of the array you can take something like this:
>>> mvv_array = [int(row.mvv) for row in mvv_list.collect()]
>>> mvv_array
Out: [1,2,3,4]
But if you try the same for the other column, you get:
>>> mvv_count = [int(row.count) for row in mvv_list.collect()]
Out: TypeError: int() argument must be a string or a number, not 'builtin_function_or_method'
This happens because count is a built-in method. And the column has the same name as count. A workaround to do this is change the column name of count to _count:
>>> mvv_list = mvv_list.selectExpr("mvv as mvv", "count as _count")
>>> mvv_count = [int(row._count) for row in mvv_list.collect()]
But this workaround is not needed, as you can access the column using the dictionary syntax:
>>> mvv_array = [int(row['mvv']) for row in mvv_list.collect()]
>>> mvv_count = [int(row['count']) for row in mvv_list.collect()]
And it will finally work!
回答2:
Following one liner gives the list you want.
mvv = mvv_count_df.select("mvv").rdd.flatMap(lambda x: x).collect()
回答3:
This will give you all the elements as a list.
mvv_list = list(
mvv_count_df.select('mvv').toPandas()['mvv']
)
回答4:
The following code will help you
mvv_count_df.select('mvv').rdd.map(lambda row : row[0]).collect()
回答5:
On my data I got these benchmarks:
>>> data.select(col).rdd.flatMap(lambda x: x).collect()
0.52 sec
>>> [row[col] for row in data.collect()]
0.271 sec
>>> list(data.select(col).toPandas()[col])
0.427 sec
The result is the same
回答6:
If you get the error below :
AttributeError: 'list' object has no attribute 'collect'
This code will solve your issues :
mvv_list = mvv_count_df.select('mvv').collect()
mvv_array = [int(i.mvv) for i in mvv_list]
来源：https://stackoverflow.com/questions/38610559/convert-spark-dataframe-column-to-python-list