How can correct data types on Apache Pig be enforced?

I am having trouble SUMming a bag of values, due to a Data type error.

When I load a csv file whose lines look like this:

6   574 false   10.1.72.23  2010-05-16 13:56:19 +0930   fbcdn.net   static.ak.fbcdn.net 304 text/css    1   /rsrc.php/zPTJC/hash/50l7x7eg.css   http    pwong

Using the following:

logs_base = FOREACH raw_logs GENERATE
  FLATTEN(
     EXTRACT(line, '^(\\d+),"(\\d+)","(\\w+)","(\\S+)","(.+?)","(\\S+)","(\\S+)","(\\d+)","(\\S+)","(\\d+)","(\\S+)","(\\S+)","(\\S+)"')
  )
  as (
    account_id: int,
    bytes: long,
    cached: chararray,
    ip: chararray,
    time: chararray,
    domain: chararray,
    host: chararray,
    status: chararray,
    mime_type: chararray,
    page_view: chararray,
    path: chararray,
    protocol: chararray,
    username: chararray
  );

All fields seem to be loaded fine, and with the right type, as shown by the "describe" command:

grunt> describe logs_base
logs_base: {account_id: int,bytes: long,cached: chararray,ip: chararray,time: chararray,domain: chararray,host: chararray,status: chararray,mime_type: chararray,page_view: chararray,path: chararray,protocol: chararray,username: chararray}

Whenever I perform a SUM using:

bytesCount = FOREACH (GROUP logs_base ALL) GENERATE SUM(logs_base.bytes);

and store, or dump the contents, the mapreduce process fails with the following error:

org.apache.pig.backend.executionengine.ExecException: ERROR 2106: Error while computing sum in Initial
    at org.apache.pig.builtin.LongSum$Initial.exec(LongSum.java:87)
    at org.apache.pig.builtin.LongSum$Initial.exec(LongSum.java:65)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:216)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:253)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.getNext(PhysicalOperator.java:334)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POForEach.processPlan(POForEach.java:332)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POForEach.getNext(POForEach.java:284)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.processInput(PhysicalOperator.java:290)
    at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POLocalRearrange.getNext(POLocalRearrange.java:256)
    at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapBase.runPipeline(PigGenericMapBase.java:267)
    at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapBase.map(PigGenericMapBase.java:262)
    at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapBase.map(PigGenericMapBase.java:64)
    at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144)
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:771)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:375)
    at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:212)
Caused by: java.lang.ClassCastException: java.lang.String cannot be cast to java.lang.Long
    at org.apache.pig.builtin.LongSum$Initial.exec(LongSum.java:79)
    ... 15 more

The line that catches my attention is:

Caused by: java.lang.ClassCastException: java.lang.String cannot be cast to java.lang.Long

Which leads me to believe that the extract function is not converting the bytes field to the required data type (long).

Is there a way to enforce the extract function to convert to the correct data types? How can I cast the value, without having to do a FOREACH on all the records? (Same problem happens when converting the time to a unix time stamp, and attempting to find MIN. I definitely would like to find a solution that does not require unnecessary projections).

Any pointers will be appreciated. Thanks a lot for your help.

Regards, Jorge C.

P.S. I am running this in interactive mode on Amazon elastic mapreduce service.

Have you tried to cast the data retrieved from the UDF? Applying the schema here does not perform any casting.

e.g.

logs_base = 
   FOREACH raw_logs
   GENERATE
       FLATTEN(
           (tuple(LONG,LONG,CHARARRAY,....)) EXTRACT(line, '^...')
       )
       AS (account_id: INT, ...);