Josh Rosen created SPARK-4561:
---------------------------------
Summary: PySparkSQL's Row.asDict() should convert nested rows to
dictionaries
Key: SPARK-4561
URL: https://issues.apache.org/jira/browse/SPARK-4561
Project: Spark
Issue Type: Improvement
Components: PySpark, SQL
Affects Versions: 1.2.0
Reporter: Josh Rosen
In PySpark, you can call {{.asDict
()}} on a SparkSQL {{Row}} to convert it to a dictionary. Unfortunately,
though, this does not convert nested rows to dictionaries. For example:
{code}
>>> sqlContext.sql("select results from results").first()
Row(results=[Row(time=3.762), Row(time=3.47), Row(time=3.559), Row(time=3.458),
Row(time=3.229), Row(time=3.21), Row(time=3.166), Row(time=3.276),
Row(time=3.239), Row(time=3.149)])
>>> sqlContext.sql("select results from results").first().asDict()
{u'results': [(3.762,),
(3.47,),
(3.559,),
(3.458,),
(3.229,),
(3.21,),
(3.166,),
(3.276,),
(3.239,),
(3.149,)]}
{code}
I ran into this issue when trying to use Pandas dataframes to display nested
data that I queried from Spark SQL.
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