Oh great, thank you for clearing that up.
On Fri, Apr 22, 2016 at 5:15 PM, Davies Liu <dav...@databricks.com> wrote:
> This exception is already handled well, just noisy, should be muted.
>
> On Wed, Apr 13, 2016 at 4:52 PM, Pete Werner <pwer...@freelancer.com>
> wrote:
>
>> Hi
>>
>> I am new to spark & pyspark.
>>
>> I am reading a small csv file (~40k rows) into a dataframe.
>>
>> from pyspark.sql import functions as F
>> df =
>> sqlContext.read.format('com.databricks.spark.csv').options(header='true',
>> inferschema='true').load('/tmp/sm.csv')
>> df = df.withColumn('verified', F.when(df['verified'] == 'Y',
>> 1).otherwise(0))
>> df2 = df.map(lambda x: Row(label=float(x[0]),
>> features=Vectors.dense(x[1:]))).toDF()
>>
>> I get some weird error that does not occur every single time, but does
>> happen pretty regularly
>>
>> >>> df2.show(1)
>> +--------------------+---------+
>> | features| label|
>> +--------------------+---------+
>> |[0.0,0.0,0.0,0.0,...|0.0|
>> +--------------------+---------+
>> only showing top 1 row
>>
>> >>> df2.count()
>> 41999
>>
>> >>> df2.show(1)
>> +--------------------+---------+
>> | features| label|
>> +--------------------+---------+
>> |[0.0,0.0,0.0,0.0,...|0.0|
>> +--------------------+---------+
>> only showing top 1 row
>>
>> >>> df2.count()
>> 41999
>>
>> >>> df2.show(1)
>> Traceback (most recent call last):
>> File "spark-1.6.1/python/lib/pyspark.zip/pyspark/daemon.py", line 157,
>> in manager
>> File "spark-1.6.1/python/lib/pyspark.zip/pyspark/daemon.py", line 61,
>> in worker
>> File "spark-1.6.1/python/lib/pyspark.zip/pyspark/worker.py", line 136,
>> in main
>> if read_int(infile) == SpecialLengths.END_OF_STREAM:
>> File "spark-1.6.1/python/lib/pyspark.zip/pyspark/serializers.py", line
>> 545, in read_int
>> raise EOFError
>> EOFError
>> +--------------------+---------+
>> | features| label|
>> +--------------------+---------+
>> |[0.0,0.0,0.0,0.0,...|4700734.0|
>> +--------------------+---------+
>> only showing top 1 row
>>
>> Once that EOFError has been raised, I will not see it again until I do
>> something that requires interacting with the spark server
>>
>> When I call df2.count() it shows that [Stage xxx] prompt which is what I
>> mean by it going to the spark server.
>>
>> Anything that triggers that seems to eventually end up giving the
>> EOFError again when I do something with df2.
>>
>> It does not seem to happen with df (vs. df2) so seems like it must be
>> something happening with the df.map() line.
>>
>> --
>>
>> Pete Werner
>> Data Scientist
>> Freelancer.com
>>
>> Level 20
>> 680 George Street
>> Sydney NSW 2000
>>
>> e: pwer...@freelancer.com
>> p: +61 2 8599 2700
>> w: http://www.freelancer.com
>>
>>
>
--
Pete Werner
Data Scientist
Freelancer.com
Level 20
680 George Street
Sydney NSW 2000
e: pwer...@freelancer.com
p: +61 2 8599 2700
w: http://www.freelancer.com
