Which version of Spark are you using? inferSchema() is improved to
support empty dict in 1.2+, could you try the 1.2-RC1?
Also, you can use applySchema():
from pyspark.sql import *
fields = [StructField('field1', IntegerType(), True),
StructField('field2', StringType(), True),
StructField('field3', MapType(StringType(), IntegerType(), True))]
schema = StructType(fields)
rdd2 = rdd.map(lambda x: (x['field1'], x['field2'], x['field3']))
sqlContext.applySchema(rdd2, schema)
PS: the above code is not testsed.
Davies
On Thu, Dec 4, 2014 at 4:22 AM, sahanbull <sa...@skimlinks.com> wrote:
> Hi Davies,
>
> Thanks for the reply
>
> The problem is I have empty dictionaries in my field3 as well. It gives me
> an error :
>
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/root/spark/python/pyspark/sql.py", line 1042, in inferSchema
> schema = _infer_schema(first)
> File "/root/spark/python/pyspark/sql.py", line 495, in _infer_schema
> fields = [StructField(k, _infer_type(v), True) for k, v in items]
> File "/root/spark/python/pyspark/sql.py", line 460, in _infer_type
> raise ValueError("Can not infer type for empty dict")
> ValueError: Can not infer type for empty dict
>
> When I remove the empty dictionary items from each record. That is, when
> mapping to the main dictionary, if field3 is an empty ditc, i do not include
> that hence the record converts from
>
> {
> field1:5,
> field2: 'string',
> field3: {}
> }
>
> to >
>
> {
> field1:5,
> field2: 'string',
> }
>
> At this point, I get :
>
> ERROR TaskSetManager: Task 0 in stage 14.0 failed 4 times; aborting job
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/root/spark/python/pyspark/sql.py", line 1044, in inferSchema
> return self.applySchema(rdd, schema)
> File "/root/spark/python/pyspark/sql.py", line 1117, in applySchema
> rows = rdd.take(10)
> File "/root/spark/python/pyspark/rdd.py", line 1153, in take
> res = self.context.runJob(self, takeUpToNumLeft, p, True)
> File "/root/spark/python/pyspark/context.py", line 770, in runJob
> it = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd,
> javaPartitions, allowLocal)
> File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
> line 538, in __call__
> File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line
> 300, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling
> z:org.apache.spark.api.python.PythonRDD.runJob.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
> in stage 14.0 failed 4 times, most recent failure: Lost task 0.3 in stage
> 14.0 (TID 22628, ip-172-31-30-89.ec2.internal):
> org.apache.spark.api.python.PythonException: Traceback (most recent call
> last):
> File "/root/spark/python/pyspark/worker.py", line 79, in main
> serializer.dump_stream(func(split_index, iterator), outfile)
> File "/root/spark/python/pyspark/serializers.py", line 196, in dump_stream
> self.serializer.dump_stream(self._batched(iterator), stream)
> File "/root/spark/python/pyspark/serializers.py", line 127, in dump_stream
> for obj in iterator:
> File "/root/spark/python/pyspark/serializers.py", line 185, in _batched
> for item in iterator:
> File "/root/spark/python/pyspark/rdd.py", line 1148, in takeUpToNumLeft
> yield next(iterator)
> File "/root/spark/python/pyspark/sql.py", line 552, in _drop_schema
> yield converter(i)
> File "/root/spark/python/pyspark/sql.py", line 540, in nested_conv
> return tuple(f(v) for f, v in zip(convs, conv(row)))
> File "/root/spark/python/pyspark/sql.py", line 540, in <genexpr>
> return tuple(f(v) for f, v in zip(convs, conv(row)))
> File "/root/spark/python/pyspark/sql.py", line 508, in <lambda>
> return lambda row: dict((k, conv(v)) for k, v in row.iteritems())
> AttributeError: 'int' object has no attribute 'iteritems'
>
> I am clueless what to do about this. Hope you can help :)
>
> Many thanks
> SahanB
>
>
>
> --
> View this message in context:
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