Xiang Gao created SPARK-16542:
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Summary: bugs about types that result an array of null when
creating dataframe using python
Key: SPARK-16542
URL: https://issues.apache.org/jira/browse/SPARK-16542
Project: Spark
Issue Type: Bug
Components: PySpark, SQL
Reporter: Xiang Gao
This is a bugs about types that result an array of null when creating dataframe
using python.
Python's array.array have richer type than python itself, e.g. we can have
array('f',[1,2,3]) and array('d',[1,2,3]). Codes in spark-sql didn't take this
into consideration which might cause a problem that you get an array of null
values when you have array('f') in your rows.
A simple code to reproduce this is:
from pyspark import SparkContext
from pyspark.sql import SQLContext,Row,DataFrame
from array import array
sc = SparkContext()
sqlContext = SQLContext(sc)
row1 = Row(floatarray=array('f',[1,2,3]), doublearray=array('d',[1,2,3]))
rows = sc.parallelize([ row1 ])
df = sqlContext.createDataFrame(rows)
df.show()
which have output
+---------------+------------------+
| doublearray| floatarray|
+---------------+------------------+
|[1.0, 2.0, 3.0]|[null, null, null]|
+---------------+------------------+
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