programming with pyspark on a Spark cluster,
the data is large and in pieces so can not be loaded into the memory or check the sanity of the data easily

basically it looks like

```
af.b Current%20events 1 996
af.b Kategorie:Musiek 1 4468
af.b Spesiaal:RecentChangesLinked/Gebruikerbespreking:Freakazoid 1 5209
af.b Spesiaal:RecentChangesLinked/Sir_Arthur_Conan_Doyle 1 5214

```

wikipedia data:

I read it from aws S3 and then try to construct spark Dataframe with the following python code in pyspark intepreter:

```
parts = data.map(lambda l: l.split())
wikis = parts.map(lambda p: (p[0], p[1],p[2],p[3]))

fields = [StructField("project", StringType(), True),
StructField("title", StringType(), True),
StructField("count", IntegerType(), True),
StructField("byte_size", StringType(), True)] 

schema = StructType(fields) 

df = sqlContext.createDataFrame(wikis, schema)

```

all look fine, only createDataFrame gives me error

```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/spark/python/pyspark/sql/context.py", line 404, in   createDataFrame
rdd, schema = self._createFromRDD(data, schema, samplingRatio)
File "/usr/lib/spark/python/pyspark/sql/context.py", line 298, in _createFromRDD
_verify_type(row, schema)
File "/usr/lib/spark/python/pyspark/sql/types.py", line 1152, in _verify_type
_verify_type(v, f.dataType)
File "/usr/lib/spark/python/pyspark/sql/types.py", line 1136, in _verify_type
raise TypeError("%s can not accept object in type %s" % (dataType, type(obj)))
TypeError: IntegerType can not accept object in type <type 'unicode'>

```

why I can not set the third column which should be count to IntegerType ?
How can I solve this ?