pyspark ibmdpy giving ValueError: ('ordinal must be >= 1 - apache-spark

Question

I am loading data from netezza into a dataframe and then trying to write to dashdb. I am using ibmdpy to try to load the data into dashdb on bluemix. Ibmdpy requires a pandas dataframe so I convert the spark dataframe to pandas to load into dashdb.
all_disputes_df = sqlContext.read.format('jdbc').options(url='jdbc:netezza://pda1-wall.pok.ibm.com:5480/BACC_PRD_ISCNZ_GAPNZ', user=user, password=password, dbtable='METRICS.AR_EM_D2_02_AGG', driver='org.netezza.Driver').load()
from ibmdbpy import IdaDataBase
idadb = IdaDataBase(dsn='BLUDB', uid='dash107474', pwd='k5TY24AbzFjE')
print("current_schema is %s" % idadb.current_schema)
print("tables %s" % idadb.show_tables())
idadb.as_idadataframe(all_disputes_df.toPandas(), "all_disputes")
I am getting the following traceback.
ValueError Traceback (most recent call last)
<ipython-input-4-63dde713c67b> in <module>()
----> 1 idadb.as_idadataframe(all_disputes_df.toPandas(), "all_disputes")
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/sql/dataframe.pyc in toPandas(self)
1379 """
1380 import pandas as pd
-> 1381 return pd.DataFrame.from_records(self.collect(), columns=self.columns)
1382
1383 ##########################################################################################
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/sql/dataframe.pyc in collect(self)
279 with SCCallSiteSync(self._sc) as css:
280 port = self._jdf.collectToPython()
--> 281 return list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
282
283 #ignore_unicode_prefix
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/rdd.pyc in _load_from_socket(port, serializer)
140 try:
141 rf = sock.makefile("rb", 65536)
--> 142 for item in serializer.load_stream(rf):
143 yield item
144 finally:
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/serializers.pyc in load_stream(self, stream)
137 while True:
138 try:
--> 139 yield self._read_with_length(stream)
140 except EOFError:
141 return
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/serializers.pyc in _read_with_length(self, stream)
162 if len(obj) < length:
163 raise EOFError
--> 164 return self.loads(obj)
165
166 def dumps(self, obj):
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/serializers.pyc in loads(self, obj, encoding)
420 else:
421 def loads(self, obj, encoding=None):
--> 422 return pickle.loads(obj)
423
424
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/sql/types.pyc in <lambda>(*a)
1157 # This is used to unpickle a Row from JVM
1158 def _create_row_inbound_converter(dataType):
-> 1159 return lambda *a: dataType.fromInternal(a)
1160
1161
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/sql/types.pyc in fromInternal(self, obj)
563 return obj
564 if self._needSerializeAnyField:
--> 565 values = [f.fromInternal(v) for f, v in zip(self.fields, obj)]
566 else:
567 values = obj
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/sql/types.pyc in fromInternal(self, obj)
436
437 def fromInternal(self, obj):
--> 438 return self.dataType.fromInternal(obj)
439
440
/home/brente/spark/spark-1.6.1-bin-hadoop2.6/python/pyspark/sql/types.pyc in fromInternal(self, v)
174 def fromInternal(self, v):
175 if v is not None:
--> 176 return datetime.date.fromordinal(v + self.EPOCH_ORDINAL)
177
178
ValueError: ('ordinal must be >= 1', <function <lambda> at 0x7f97c0be76e0>, (u'788', u'10', u'00620000 ', u'0129101548 ', 1, u'000028628 ', 16520, Decimal('2124.76'), Decimal('2124.76'), 16525, 16525, u'000611099
Any ideas on what the problem is?

Answer 1

Reading your data from Netezza into dataframes fails. Everything beyond that is speculation from my side:
Could there be invalid data stored in Netezza, that throws off the deserialization into dataframes?
Maybe try some other queries, to make sure that there is no connectivity problem, no typo in the database name, things like that.