rdd = sc.parallelize([3,2,1,4])
rdd.toDF().show()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/spark/python/pyspark/sql/session.py", line 66, in toDF
return sparkSession.createDataFrame(self, schema, sampleRatio)
File "/opt/spark/python/pyspark/sql/session.py", line 675, in
createDataFrame
return self._create_dataframe(data, schema, samplingRatio,
verifySchema)
File "/opt/spark/python/pyspark/sql/session.py", line 698, in
_create_dataframe
rdd, schema = self._createFromRDD(data.map(prepare), schema,
samplingRatio)
File "/opt/spark/python/pyspark/sql/session.py", line 486, in
_createFromRDD
struct = self._inferSchema(rdd, samplingRatio, names=schema)
File "/opt/spark/python/pyspark/sql/session.py", line 466, in
_inferSchema
schema = _infer_schema(first, names=names)
File "/opt/spark/python/pyspark/sql/types.py", line 1067, in
_infer_schema
raise TypeError("Can not infer schema for type: %s" % type(row))
TypeError: Can not infer schema for type: <class 'int'>
In my pyspark why this fails? I didnt get the way.
Thanks for helps.
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